Outcomes Research in Review

Study Overview

Objective. To assess the prevalence and determinants of patient–oncologist discordance in opinion of prognosis, and evaluate how often patients are aware of this discordance.

Design. Cross-sectional study.

Setting and participants. The study included 236 adult patients with advanced cancer and their 38 oncologists at academic and community oncology practices in Rochester, New York, and Sacramento, California. Inpatients and those already enrolled in hospice were excluded.

Main outcome measures. Patients and their oncologists independently reported their ratings of 2-year survival probability on a postindex visit multiple-choice questionnaire (response options included 100%, about 90%, about 75%, about 50%, about 25%, about 10%, and 0%). Prognostic discordance was defined as a more than 1 category difference between the patient and physician prognostic ratings. All patients were asked to report how they believed their oncologist would rate their 2-year survival probability. Those who correctly perceived their oncologist’s rating of their prognosis (within 1 category) were defined as knowing their oncologist’s opinion, and the rest were defined as not knowing their oncologist’s opinion. This distinction was used to categorize patients whose self-rating of their prognosis was discordant from their oncologist’s rating as either knowingly discordant or unknowingly discordant. Patient characteristics including age, sex, race/ethnicity, education, income, aggressiveness of cancer, self-efficacy with health care communication, recall of prognostic discussion with the oncologist, and end-of-life treatment preferences were evaluated as potential determinants of prognostic discordance.

Main results. 68% of patients rated their 2-year survival probability discordantly from their oncologists. Among these, 96% rated their prognosis more optimistically than their oncologists, and 89% were unaware that their opinions differed from that of their oncologists. Prognostic discordance was more common among nonwhite compared to white patients (95% versus 65%, P = 0.03). The prevalence of prognostic discordance did not significantly differ based on the other patient characteristics studied. Among patients whose prognostic ratings were discordant from their oncologist’s, 99% reported that they wanted to be involved in treatment decision making, and 70% were interested in involving palliative care when the end of life became near.

Conclusion. Patient–oncologist discordance about prognosis was common, particularly among nonwhite patients. In cases of prognostic discordance, patients rarely knew that their opinion differed from that of their oncologist, suggesting a lack of successful communication of prognostic information.

Commentary

Prior studies have noted that patients with advanced cancer perceive prognosis more optimistically than their physicians [1–3]. In a large national prospective observational study, the majority of patients receiving chemotherapy for metastatic (stage IV) lung or colorectal cancer inaccurately believed that chemotherapy was likely to be curative, potentially compromising their ability to make informed treatment decisions [4]. In the present study by Gramling et al, the authors confirm the observation that patients are more optimistic about prognosis than their oncologists, and furthermore demonstrate that most patients are unaware of the discrepancy, suggesting a failure of communication. As in prior studies, racial disparity in prognostic understanding was observed, with nonwhite patients being more likely to have overly optimistic views of their prognosis [4,5].

While the perceived 2-year survival probability is a somewhat arbitrary measure of prognostic opinion, it provides a useful representation of how one views the expected trajectory of disease. A high perceived likelihood of 2-year survival implies a view that long-term disease control can be achieved, whereas a low perceived likelihood of 2-year survival implies acknowledgement of terminal illness. This study effectively contrasts patient and physician opinions of 2-year survival probability, but it does not discriminate among clinically relevant differences in opinions within the 0–2 year prognostic range. For example, a patient whose oncologist believes his prognosis is < 6 months may be an appropriate candidate for hospice, but the patient may be unprepared to make the transition to hospice if he believes his prognosis is closer to a year or more. While the patient and oncologist may agree that 2-year survival is unlikely, they may have differing beliefs about the appropriateness of certain interventions based on their discrepant short-term prognostic views. Additional studies looking at perceived probabilities of short-term survival may be helpful in assessing patients’ readiness to transition to symptom-focused care when medically appropriate.

The authors designate 7 categories of 2-year survival probability (100%, about 90%, about 75%, about 50%, about 25%, about 10%, and 0%). The differences in percentage between prognostic categories are not evenly distributed, and therefore definition of discordance is non-uniform. The smaller percentage difference at the highest and lowest ends of the scale may result in overestimation of discordance at these extremes. For example, a patient rating her 2-year survival probability at 100% would be defined as having a discordant viewpoint from an oncologist rating her 2-year survival at 75% (as would be realistic for a diagnosis such as metastatic colon cancer). Given the imprecise nature of prognostication, the views of the patient and oncologist in this example are arguably similar, and perhaps should not be categorized as discordant.

As noted, patients already enrolled in hospice were excluded from the study, thus omitting a key group of patients whose prognostic views are more likely to be concordant with their physicians’ views. This group may be better captured in a prospective study of prognostic discordance among newly diagnosed advanced cancer patients after initial oncology consultation, allowing for inclusion of those who make an early transition to hospice.

Applications for Clinical Practice

Although clinicians tend to overestimate prognosis, their predictions correlate with outcomes in advanced cancer [6], and may therefore provide a useful framework for patients to understand the likely course of their disease. However, physicians often avoid explicit discussion of prognosis by shrouding prognostic information in discussions of radiographic findings, and quickly transitioning to discussion of treatment options [7]. Patients and families rarely inquire about prognosis, further limiting disclosure of prognostic information [7,8]. Even when prognostic information is explicitly stated, patients may misinterpret the information [4], potentially adversely affecting their ability to participate in shared decision making.

Some useful approaches for successfully communicating prognostic information may include asking patients what information they wish to hear before it is disclosed, providing prognostic data for patients with similar disease states while acknowledging individual variability, clearly defining the intent of proposed therapy (ie, curative versus noncurative), and asking the patient to restate information in order to assess understanding. Early involvement of palliative care specialists may help reinforce understanding about prognosis and goals of therapy, facilitate advance care planning, and reduce aggressive interventions at the end of life [2]. Ongoing research is directed at identifying effective interventions to improve communication between patients with advanced cancer and their oncologists [9].

—Irene M. Hutchins, MD
Scripps Cancer Center, La Jolla, CA

Study Overview

Objective. To assess the prevalence and determinants of patient–oncologist discordance in opinion of prognosis, and evaluate how often patients are aware of this discordance.

Design. Cross-sectional study.

Setting and participants. The study included 236 adult patients with advanced cancer and their 38 oncologists at academic and community oncology practices in Rochester, New York, and Sacramento, California. Inpatients and those already enrolled in hospice were excluded.

Main outcome measures. Patients and their oncologists independently reported their ratings of 2-year survival probability on a postindex visit multiple-choice questionnaire (response options included 100%, about 90%, about 75%, about 50%, about 25%, about 10%, and 0%). Prognostic discordance was defined as a more than 1 category difference between the patient and physician prognostic ratings. All patients were asked to report how they believed their oncologist would rate their 2-year survival probability. Those who correctly perceived their oncologist’s rating of their prognosis (within 1 category) were defined as knowing their oncologist’s opinion, and the rest were defined as not knowing their oncologist’s opinion. This distinction was used to categorize patients whose self-rating of their prognosis was discordant from their oncologist’s rating as either knowingly discordant or unknowingly discordant. Patient characteristics including age, sex, race/ethnicity, education, income, aggressiveness of cancer, self-efficacy with health care communication, recall of prognostic discussion with the oncologist, and end-of-life treatment preferences were evaluated as potential determinants of prognostic discordance.

Main results. 68% of patients rated their 2-year survival probability discordantly from their oncologists. Among these, 96% rated their prognosis more optimistically than their oncologists, and 89% were unaware that their opinions differed from that of their oncologists. Prognostic discordance was more common among nonwhite compared to white patients (95% versus 65%, P = 0.03). The prevalence of prognostic discordance did not significantly differ based on the other patient characteristics studied. Among patients whose prognostic ratings were discordant from their oncologist’s, 99% reported that they wanted to be involved in treatment decision making, and 70% were interested in involving palliative care when the end of life became near.

Conclusion. Patient–oncologist discordance about prognosis was common, particularly among nonwhite patients. In cases of prognostic discordance, patients rarely knew that their opinion differed from that of their oncologist, suggesting a lack of successful communication of prognostic information.

Commentary

Prior studies have noted that patients with advanced cancer perceive prognosis more optimistically than their physicians [1–3]. In a large national prospective observational study, the majority of patients receiving chemotherapy for metastatic (stage IV) lung or colorectal cancer inaccurately believed that chemotherapy was likely to be curative, potentially compromising their ability to make informed treatment decisions [4]. In the present study by Gramling et al, the authors confirm the observation that patients are more optimistic about prognosis than their oncologists, and furthermore demonstrate that most patients are unaware of the discrepancy, suggesting a failure of communication. As in prior studies, racial disparity in prognostic understanding was observed, with nonwhite patients being more likely to have overly optimistic views of their prognosis [4,5].

While the perceived 2-year survival probability is a somewhat arbitrary measure of prognostic opinion, it provides a useful representation of how one views the expected trajectory of disease. A high perceived likelihood of 2-year survival implies a view that long-term disease control can be achieved, whereas a low perceived likelihood of 2-year survival implies acknowledgement of terminal illness. This study effectively contrasts patient and physician opinions of 2-year survival probability, but it does not discriminate among clinically relevant differences in opinions within the 0–2 year prognostic range. For example, a patient whose oncologist believes his prognosis is < 6 months may be an appropriate candidate for hospice, but the patient may be unprepared to make the transition to hospice if he believes his prognosis is closer to a year or more. While the patient and oncologist may agree that 2-year survival is unlikely, they may have differing beliefs about the appropriateness of certain interventions based on their discrepant short-term prognostic views. Additional studies looking at perceived probabilities of short-term survival may be helpful in assessing patients’ readiness to transition to symptom-focused care when medically appropriate.

The authors designate 7 categories of 2-year survival probability (100%, about 90%, about 75%, about 50%, about 25%, about 10%, and 0%). The differences in percentage between prognostic categories are not evenly distributed, and therefore definition of discordance is non-uniform. The smaller percentage difference at the highest and lowest ends of the scale may result in overestimation of discordance at these extremes. For example, a patient rating her 2-year survival probability at 100% would be defined as having a discordant viewpoint from an oncologist rating her 2-year survival at 75% (as would be realistic for a diagnosis such as metastatic colon cancer). Given the imprecise nature of prognostication, the views of the patient and oncologist in this example are arguably similar, and perhaps should not be categorized as discordant.

As noted, patients already enrolled in hospice were excluded from the study, thus omitting a key group of patients whose prognostic views are more likely to be concordant with their physicians’ views. This group may be better captured in a prospective study of prognostic discordance among newly diagnosed advanced cancer patients after initial oncology consultation, allowing for inclusion of those who make an early transition to hospice.

Applications for Clinical Practice

Although clinicians tend to overestimate prognosis, their predictions correlate with outcomes in advanced cancer [6], and may therefore provide a useful framework for patients to understand the likely course of their disease. However, physicians often avoid explicit discussion of prognosis by shrouding prognostic information in discussions of radiographic findings, and quickly transitioning to discussion of treatment options [7]. Patients and families rarely inquire about prognosis, further limiting disclosure of prognostic information [7,8]. Even when prognostic information is explicitly stated, patients may misinterpret the information [4], potentially adversely affecting their ability to participate in shared decision making.

Some useful approaches for successfully communicating prognostic information may include asking patients what information they wish to hear before it is disclosed, providing prognostic data for patients with similar disease states while acknowledging individual variability, clearly defining the intent of proposed therapy (ie, curative versus noncurative), and asking the patient to restate information in order to assess understanding. Early involvement of palliative care specialists may help reinforce understanding about prognosis and goals of therapy, facilitate advance care planning, and reduce aggressive interventions at the end of life [2]. Ongoing research is directed at identifying effective interventions to improve communication between patients with advanced cancer and their oncologists [9].

—Irene M. Hutchins, MD
Scripps Cancer Center, La Jolla, CA

Study Overview

Objective. To assess the prevalence and determinants of patient–oncologist discordance in opinion of prognosis, and evaluate how often patients are aware of this discordance.

Design. Cross-sectional study.

Setting and participants. The study included 236 adult patients with advanced cancer and their 38 oncologists at academic and community oncology practices in Rochester, New York, and Sacramento, California. Inpatients and those already enrolled in hospice were excluded.

Main outcome measures. Patients and their oncologists independently reported their ratings of 2-year survival probability on a postindex visit multiple-choice questionnaire (response options included 100%, about 90%, about 75%, about 50%, about 25%, about 10%, and 0%). Prognostic discordance was defined as a more than 1 category difference between the patient and physician prognostic ratings. All patients were asked to report how they believed their oncologist would rate their 2-year survival probability. Those who correctly perceived their oncologist’s rating of their prognosis (within 1 category) were defined as knowing their oncologist’s opinion, and the rest were defined as not knowing their oncologist’s opinion. This distinction was used to categorize patients whose self-rating of their prognosis was discordant from their oncologist’s rating as either knowingly discordant or unknowingly discordant. Patient characteristics including age, sex, race/ethnicity, education, income, aggressiveness of cancer, self-efficacy with health care communication, recall of prognostic discussion with the oncologist, and end-of-life treatment preferences were evaluated as potential determinants of prognostic discordance.

Main results. 68% of patients rated their 2-year survival probability discordantly from their oncologists. Among these, 96% rated their prognosis more optimistically than their oncologists, and 89% were unaware that their opinions differed from that of their oncologists. Prognostic discordance was more common among nonwhite compared to white patients (95% versus 65%, P = 0.03). The prevalence of prognostic discordance did not significantly differ based on the other patient characteristics studied. Among patients whose prognostic ratings were discordant from their oncologist’s, 99% reported that they wanted to be involved in treatment decision making, and 70% were interested in involving palliative care when the end of life became near.

Conclusion. Patient–oncologist discordance about prognosis was common, particularly among nonwhite patients. In cases of prognostic discordance, patients rarely knew that their opinion differed from that of their oncologist, suggesting a lack of successful communication of prognostic information.

Commentary

Prior studies have noted that patients with advanced cancer perceive prognosis more optimistically than their physicians [1–3]. In a large national prospective observational study, the majority of patients receiving chemotherapy for metastatic (stage IV) lung or colorectal cancer inaccurately believed that chemotherapy was likely to be curative, potentially compromising their ability to make informed treatment decisions [4]. In the present study by Gramling et al, the authors confirm the observation that patients are more optimistic about prognosis than their oncologists, and furthermore demonstrate that most patients are unaware of the discrepancy, suggesting a failure of communication. As in prior studies, racial disparity in prognostic understanding was observed, with nonwhite patients being more likely to have overly optimistic views of their prognosis [4,5].

While the perceived 2-year survival probability is a somewhat arbitrary measure of prognostic opinion, it provides a useful representation of how one views the expected trajectory of disease. A high perceived likelihood of 2-year survival implies a view that long-term disease control can be achieved, whereas a low perceived likelihood of 2-year survival implies acknowledgement of terminal illness. This study effectively contrasts patient and physician opinions of 2-year survival probability, but it does not discriminate among clinically relevant differences in opinions within the 0–2 year prognostic range. For example, a patient whose oncologist believes his prognosis is < 6 months may be an appropriate candidate for hospice, but the patient may be unprepared to make the transition to hospice if he believes his prognosis is closer to a year or more. While the patient and oncologist may agree that 2-year survival is unlikely, they may have differing beliefs about the appropriateness of certain interventions based on their discrepant short-term prognostic views. Additional studies looking at perceived probabilities of short-term survival may be helpful in assessing patients’ readiness to transition to symptom-focused care when medically appropriate.

The authors designate 7 categories of 2-year survival probability (100%, about 90%, about 75%, about 50%, about 25%, about 10%, and 0%). The differences in percentage between prognostic categories are not evenly distributed, and therefore definition of discordance is non-uniform. The smaller percentage difference at the highest and lowest ends of the scale may result in overestimation of discordance at these extremes. For example, a patient rating her 2-year survival probability at 100% would be defined as having a discordant viewpoint from an oncologist rating her 2-year survival at 75% (as would be realistic for a diagnosis such as metastatic colon cancer). Given the imprecise nature of prognostication, the views of the patient and oncologist in this example are arguably similar, and perhaps should not be categorized as discordant.

As noted, patients already enrolled in hospice were excluded from the study, thus omitting a key group of patients whose prognostic views are more likely to be concordant with their physicians’ views. This group may be better captured in a prospective study of prognostic discordance among newly diagnosed advanced cancer patients after initial oncology consultation, allowing for inclusion of those who make an early transition to hospice.

Applications for Clinical Practice

Although clinicians tend to overestimate prognosis, their predictions correlate with outcomes in advanced cancer [6], and may therefore provide a useful framework for patients to understand the likely course of their disease. However, physicians often avoid explicit discussion of prognosis by shrouding prognostic information in discussions of radiographic findings, and quickly transitioning to discussion of treatment options [7]. Patients and families rarely inquire about prognosis, further limiting disclosure of prognostic information [7,8]. Even when prognostic information is explicitly stated, patients may misinterpret the information [4], potentially adversely affecting their ability to participate in shared decision making.

Some useful approaches for successfully communicating prognostic information may include asking patients what information they wish to hear before it is disclosed, providing prognostic data for patients with similar disease states while acknowledging individual variability, clearly defining the intent of proposed therapy (ie, curative versus noncurative), and asking the patient to restate information in order to assess understanding. Early involvement of palliative care specialists may help reinforce understanding about prognosis and goals of therapy, facilitate advance care planning, and reduce aggressive interventions at the end of life [2]. Ongoing research is directed at identifying effective interventions to improve communication between patients with advanced cancer and their oncologists [9].

—Irene M. Hutchins, MD
Scripps Cancer Center, La Jolla, CA

Study Overview

Objective. To evaluate the impact on overall survival of adding antiandrogen (bicalutamide) therapy to radiation in patients with prostate cancer who have an elevated prostate-specific antigen (PSA) after radical prostatectomy (either as persistence or as a relapse) and no evidence of metastatic disease.

Design. Phase III, randomized, double-blind, placebo-controlled trial.

Setting and participants. The trial was designed by NRG Oncology (Philadelphia, PA), sponsored by the National Cancer Institute, and conducted at NRG Oncology member sites, which included community-based hospitals. Eligible patients had undergone radical prostatectomy and had disease that was originally assessed, on the basis of pathological testing, as tumor stage T2 (confined to the prostate but with a positive surgical margin) or T3 (with histologic extension of tumor beyond the prostatic capsule) without nodal involvement. Patients also had to have a detectable PSA level between 0.2 and 4.0 ng/mL at least 8 weeks after surgery.  All the patients underwent abdominal and pelvic computed tomography (CT) and bone scans to rule out metastatic disease. Patients who received prior chemotherapy or radiation therapy for prostate cancer were excluded. Most patients had not received prior hormonal therapy for prostate cancer.

Intervention. All eligible patients received salvage radiation therapy within 12 weeks after randomization. Radiation was directed to the original prostatic site, the tumor resection bed, and the membranous urethra at a total dose of 64.8 Gy given in 36 daily fractions. In addition to the radiation therapy, patients were randomly assigned to receive either 150 mg of bicalutamide or 1 placebo tablet daily, beginning at the initiation of radiation therapy and continuing for 24 months.  Tablets were administered in a double blind fashion. Follow-up evaluations occurred every 3 months for 2 years, then every 6 months for 3 years, and then yearly. Bone and CT scans were performed either at biochemical recurrence or as indicated clinically. If metastatic disease was detected on follow up or if the serum PSA level rose to more than 4.0 ng/mL, maximum androgen blockade was recommended.

Main outcome measure. The main outcome was overall survival rate at 12 years. Secondary end points were disease-specific death, distant metastases, local disease progression, non–disease-specific death, any prostate cancer progression including a second biochemical recurrence, and adverse events.

Main results. 840 patients were randomized between March 1998 and March 2003, with 760 patients eligible for evaluation (384 patients in bicalutamide group and 376 in placebo group). Demographic and tumor-related characteristics of the 2 groups were similar. In both groups the majority of  patients were white (89.6% in bicalutamide arm; 86.2 in placebo), had Karnofsky performance status score of 100% (77.1 % in bicalutamide arm; 74.5% in placebo), and had positive surgical margin (75% in bicalutamide arm; 74.7% in placebo). Median age was 65 years, and median PSA level at trial entry was 0.6 ng/mL.  The median follow-up among the surviving patients was 13 years.

A total of 21 patients in the bicalutamide group and 46 patients in the placebo group died from prostate cancer. The actuarial rate of overall survival at 12 years was 76.3% in the bicalutamide group and 71.3% in the placebo group (hazard ratio [HR] for death 0.77 [95% confidence interval {CI} 0.59 to 0.99; P = 0.04), resulting in a 23% relative reduction in the risk of death in patients who received bicalutamide. The 12-year incidence of death from prostate cancer was 5.8% in the bicalutamide group versus 13.4% in the placebo group (HR 0.49 [95% CI 0.32 to 0.74]; P < 0.001), resulting in a 51% lower rate of death from prostate cancer in bicalutamide patients. Post hoc subgroup analyses showed that the greatest overall survival benefit was seen in subgroups of patients with more aggressive prostate cancer, such as those with high PSA level at trial entry (1.5 to 4.0 ng/mL) or Gleason score of 7.  There were too few patients with Gleason scores of 8, 9, or 10 to draw meaningful conclusions about this subgroup. There appeared to be a larger benefit in patients with positive surgical margins than in those with negative surgical margins.

Adherence to radiation therapy was similar between the 2 trial groups, and addition of bicalutamide to radiation therapy did not result in an increase in adverse events associated with radiation therapy, such as cystitis, colitis, or sexual dysfunction. The rates of hot flashes and cardiovascular deaths were not significantly higher in the bicalutamide group than in the placebo group. However, gynecomastia was reported significantly more frequently in the bicalutamide group (69.7%) than  in the placebo group (10.9%, P < 0.001).

Conclusion. The addition of 24 months of antiandrogen therapy with daily bicalutamide to salvage radiation therapy resulted in significantly higher rates of long-term overall survival and lower incidence of death from prostate cancer as compared to the addition of placebo. This benefit appeared to be without a significant cost in terms of toxicity.

Commentary

Prostate cancer is the second most common cancer in men worldwide, with an estimated 1,618,000 cases and 366,000 deaths in 2015 [1]. The current lifetime risk of developing prostate cancer for men living in the United States is estimated to be 1 in 6 [2]. Most prostate cancers are diagnosed in the localized stage, which is often treated with radical prostatectomy. All prostate tissue is removed during a successful radical prostatectomy. Postoperatively, detectable serum PSA is indicative of residual prostatic tissue, which presumably represents disease recurrence. This elevation in PSA after surgery in the absence of systemic metastatic disease is termed bio-chemical recurrence. The current standard of care for patients who develop biochemical recurrence is salvage radiation therapy. The prognosis for these patients is related to initial tumor characteristics—grade, volume and local stage. However, approximately 50% of the patients who are treated with salvage radiation therapy for biochemical recurrence will have further disease progression and may ultimately die from prostate cancer [3,4]. This is especially true when aggressive disease features are present. Radiation therapy combined with androgen-deprivation therapy using GnRH agonists or antiandrogen therapy (bicalutamide, flutamide) prolongs survival among some men with an intact prostate. This combination represents a rationale approach to prolong survival among men who develop non-metastatic biochemical relapse after radical prostatectomy.

The study by Shipley and colleagues reports the long-term outcomes of a randomized trial comparing salvage radiation plus 2 years of antiandrogen therapy to salvage radiation and placebo. Starting daily bicalutamide 150 mg orally with salvage radiation and continuing for 2 years was associated with a 23% improvement in overall survival and a 51% lower rate of death from prostate cancer, as compared to the placebo group. The number needed to treat (NNT) with bicalutamide to prevent one death from prostate cancer over 12 years was 20. By comparison, standard treatment of prostate cancer with surgery or radiation has an NNT of 27, which demonstrates the magnitude of the benefit of addition of antiandrogen therapy to salvage radiation. The benefit appears to be greatest in patients with poor prognostic factors such as higher Gleason scores (8 to 10), a higher PSA level at entry (0.7 to 4.0 ng/mL), or positive surgical margins. In contrast, patients with lower Gleason score or negative margins seemed to benefit less from the addition of antiandrogen therapy to salvage radiation. Two years of bicalutamide was not associated with increased incidence of radiation-related toxicities or cardiovascular death. As expected, the primary adverse effect of bicalutamide was gynecomastia, which was seen in 70% of the men treated. This adverse effect can be distressing but can be mitigated by prophylactic radiation of the breast or by the administration of tamoxifen, which were not done as preventative measures in this trial.

While the addition of bicalutamide to radiation did show a clear benefit to overall survival, questions remain about whether bicalutamide is the best drug to use. As the authors note, at present GnRH agonists such as leuprolide are considered first-line hormonal therapy with radiation for most patients with prostate cancer, and bicalutamide at the dose used in this study (150 mg) is not approved. We do not know how GnRH agonists will perform either as a single agent or in combination with antiandrogen for patients who develop biochemical relapse, as the use of GnRH agonists with radiation therapy has not been evaluated in patients who develop biochemical relapse in randomized clinical trials. Two trials exploring the use of androgen deprivation therapy with salvage radiation therapy in patients with biochemical recurrence (Radiotherapy and Androgen Deprivation in Combination After Local Surgery–Hormone Duration [RADICALS-HD] and the Groupe d’Etude des Tumeurs Uro-Génitales [GETUG]-16 trial) have finished enrollment; however, we will have to wait until the overall survival data matures before drawing any meaningful conclusions from them [5,6]. We know that patients with certain aggressive disease features based on tumor stage, grade, and volume are more likely to develop biochemical recurrence. As such, it is logical to consider evaluating the role of androgen deprivation therapy with adjuvant radiation therapy in patients who are at high risk of biochemical relapse with the goal of prolonging survival and reducing the risk of metastases. The RADICALS (Radiation Therapy and Androgen Deprivation Therapy in Treating Patients Who Have Undergone Surgery for Prostate Cancer) trial, which is evaluating the role of androgen deprivation therapy after adjuvant radiation therapy in patients who are at high risk of developing biochemical relapse, will help to address this issue.

Applications for Clinical Practice

Adding an antiandrogen agent (bicalutamide) to salvage radiation therapy in this randomized, double-blind, placebo-controlled trial resulted in higher rates of overall survival, disease-specific survival, and metastasis-free interval than radiation therapy alone for patients who developed biochemical relapse after radical prostatectomy for pathological T2/T3 and node-negative prostate cancer. We eagerly await the results of clinical trials evaluating the role of GnRH agonists in combination with salvage radiation therapy in patients in this setting. Given the long natural history of prostate cancer and the relatively low event rate, such studies can take over a decade to show differences in overall survival. Thus, until such data is available, 24 months of bicalutamide in combination with salvage radiation should be considered the new standard of care for patients (especially those at high risk) who develop non-metastatic biochemical relapse after prostatectomy.

—Devalkumar Rajyaguru, MD, and Lori Rosenstein, MD,
Gundersen Health System, La Crosse, WI

Study Overview

Objective. To evaluate the impact on overall survival of adding antiandrogen (bicalutamide) therapy to radiation in patients with prostate cancer who have an elevated prostate-specific antigen (PSA) after radical prostatectomy (either as persistence or as a relapse) and no evidence of metastatic disease.

Design. Phase III, randomized, double-blind, placebo-controlled trial.

Setting and participants. The trial was designed by NRG Oncology (Philadelphia, PA), sponsored by the National Cancer Institute, and conducted at NRG Oncology member sites, which included community-based hospitals. Eligible patients had undergone radical prostatectomy and had disease that was originally assessed, on the basis of pathological testing, as tumor stage T2 (confined to the prostate but with a positive surgical margin) or T3 (with histologic extension of tumor beyond the prostatic capsule) without nodal involvement. Patients also had to have a detectable PSA level between 0.2 and 4.0 ng/mL at least 8 weeks after surgery.  All the patients underwent abdominal and pelvic computed tomography (CT) and bone scans to rule out metastatic disease. Patients who received prior chemotherapy or radiation therapy for prostate cancer were excluded. Most patients had not received prior hormonal therapy for prostate cancer.

Intervention. All eligible patients received salvage radiation therapy within 12 weeks after randomization. Radiation was directed to the original prostatic site, the tumor resection bed, and the membranous urethra at a total dose of 64.8 Gy given in 36 daily fractions. In addition to the radiation therapy, patients were randomly assigned to receive either 150 mg of bicalutamide or 1 placebo tablet daily, beginning at the initiation of radiation therapy and continuing for 24 months.  Tablets were administered in a double blind fashion. Follow-up evaluations occurred every 3 months for 2 years, then every 6 months for 3 years, and then yearly. Bone and CT scans were performed either at biochemical recurrence or as indicated clinically. If metastatic disease was detected on follow up or if the serum PSA level rose to more than 4.0 ng/mL, maximum androgen blockade was recommended.

Main outcome measure. The main outcome was overall survival rate at 12 years. Secondary end points were disease-specific death, distant metastases, local disease progression, non–disease-specific death, any prostate cancer progression including a second biochemical recurrence, and adverse events.

Main results. 840 patients were randomized between March 1998 and March 2003, with 760 patients eligible for evaluation (384 patients in bicalutamide group and 376 in placebo group). Demographic and tumor-related characteristics of the 2 groups were similar. In both groups the majority of  patients were white (89.6% in bicalutamide arm; 86.2 in placebo), had Karnofsky performance status score of 100% (77.1 % in bicalutamide arm; 74.5% in placebo), and had positive surgical margin (75% in bicalutamide arm; 74.7% in placebo). Median age was 65 years, and median PSA level at trial entry was 0.6 ng/mL.  The median follow-up among the surviving patients was 13 years.

A total of 21 patients in the bicalutamide group and 46 patients in the placebo group died from prostate cancer. The actuarial rate of overall survival at 12 years was 76.3% in the bicalutamide group and 71.3% in the placebo group (hazard ratio [HR] for death 0.77 [95% confidence interval {CI} 0.59 to 0.99; P = 0.04), resulting in a 23% relative reduction in the risk of death in patients who received bicalutamide. The 12-year incidence of death from prostate cancer was 5.8% in the bicalutamide group versus 13.4% in the placebo group (HR 0.49 [95% CI 0.32 to 0.74]; P < 0.001), resulting in a 51% lower rate of death from prostate cancer in bicalutamide patients. Post hoc subgroup analyses showed that the greatest overall survival benefit was seen in subgroups of patients with more aggressive prostate cancer, such as those with high PSA level at trial entry (1.5 to 4.0 ng/mL) or Gleason score of 7.  There were too few patients with Gleason scores of 8, 9, or 10 to draw meaningful conclusions about this subgroup. There appeared to be a larger benefit in patients with positive surgical margins than in those with negative surgical margins.

Adherence to radiation therapy was similar between the 2 trial groups, and addition of bicalutamide to radiation therapy did not result in an increase in adverse events associated with radiation therapy, such as cystitis, colitis, or sexual dysfunction. The rates of hot flashes and cardiovascular deaths were not significantly higher in the bicalutamide group than in the placebo group. However, gynecomastia was reported significantly more frequently in the bicalutamide group (69.7%) than  in the placebo group (10.9%, P < 0.001).

Conclusion. The addition of 24 months of antiandrogen therapy with daily bicalutamide to salvage radiation therapy resulted in significantly higher rates of long-term overall survival and lower incidence of death from prostate cancer as compared to the addition of placebo. This benefit appeared to be without a significant cost in terms of toxicity.

Commentary

Prostate cancer is the second most common cancer in men worldwide, with an estimated 1,618,000 cases and 366,000 deaths in 2015 [1]. The current lifetime risk of developing prostate cancer for men living in the United States is estimated to be 1 in 6 [2]. Most prostate cancers are diagnosed in the localized stage, which is often treated with radical prostatectomy. All prostate tissue is removed during a successful radical prostatectomy. Postoperatively, detectable serum PSA is indicative of residual prostatic tissue, which presumably represents disease recurrence. This elevation in PSA after surgery in the absence of systemic metastatic disease is termed bio-chemical recurrence. The current standard of care for patients who develop biochemical recurrence is salvage radiation therapy. The prognosis for these patients is related to initial tumor characteristics—grade, volume and local stage. However, approximately 50% of the patients who are treated with salvage radiation therapy for biochemical recurrence will have further disease progression and may ultimately die from prostate cancer [3,4]. This is especially true when aggressive disease features are present. Radiation therapy combined with androgen-deprivation therapy using GnRH agonists or antiandrogen therapy (bicalutamide, flutamide) prolongs survival among some men with an intact prostate. This combination represents a rationale approach to prolong survival among men who develop non-metastatic biochemical relapse after radical prostatectomy.

The study by Shipley and colleagues reports the long-term outcomes of a randomized trial comparing salvage radiation plus 2 years of antiandrogen therapy to salvage radiation and placebo. Starting daily bicalutamide 150 mg orally with salvage radiation and continuing for 2 years was associated with a 23% improvement in overall survival and a 51% lower rate of death from prostate cancer, as compared to the placebo group. The number needed to treat (NNT) with bicalutamide to prevent one death from prostate cancer over 12 years was 20. By comparison, standard treatment of prostate cancer with surgery or radiation has an NNT of 27, which demonstrates the magnitude of the benefit of addition of antiandrogen therapy to salvage radiation. The benefit appears to be greatest in patients with poor prognostic factors such as higher Gleason scores (8 to 10), a higher PSA level at entry (0.7 to 4.0 ng/mL), or positive surgical margins. In contrast, patients with lower Gleason score or negative margins seemed to benefit less from the addition of antiandrogen therapy to salvage radiation. Two years of bicalutamide was not associated with increased incidence of radiation-related toxicities or cardiovascular death. As expected, the primary adverse effect of bicalutamide was gynecomastia, which was seen in 70% of the men treated. This adverse effect can be distressing but can be mitigated by prophylactic radiation of the breast or by the administration of tamoxifen, which were not done as preventative measures in this trial.

While the addition of bicalutamide to radiation did show a clear benefit to overall survival, questions remain about whether bicalutamide is the best drug to use. As the authors note, at present GnRH agonists such as leuprolide are considered first-line hormonal therapy with radiation for most patients with prostate cancer, and bicalutamide at the dose used in this study (150 mg) is not approved. We do not know how GnRH agonists will perform either as a single agent or in combination with antiandrogen for patients who develop biochemical relapse, as the use of GnRH agonists with radiation therapy has not been evaluated in patients who develop biochemical relapse in randomized clinical trials. Two trials exploring the use of androgen deprivation therapy with salvage radiation therapy in patients with biochemical recurrence (Radiotherapy and Androgen Deprivation in Combination After Local Surgery–Hormone Duration [RADICALS-HD] and the Groupe d’Etude des Tumeurs Uro-Génitales [GETUG]-16 trial) have finished enrollment; however, we will have to wait until the overall survival data matures before drawing any meaningful conclusions from them [5,6]. We know that patients with certain aggressive disease features based on tumor stage, grade, and volume are more likely to develop biochemical recurrence. As such, it is logical to consider evaluating the role of androgen deprivation therapy with adjuvant radiation therapy in patients who are at high risk of biochemical relapse with the goal of prolonging survival and reducing the risk of metastases. The RADICALS (Radiation Therapy and Androgen Deprivation Therapy in Treating Patients Who Have Undergone Surgery for Prostate Cancer) trial, which is evaluating the role of androgen deprivation therapy after adjuvant radiation therapy in patients who are at high risk of developing biochemical relapse, will help to address this issue.

Applications for Clinical Practice

Adding an antiandrogen agent (bicalutamide) to salvage radiation therapy in this randomized, double-blind, placebo-controlled trial resulted in higher rates of overall survival, disease-specific survival, and metastasis-free interval than radiation therapy alone for patients who developed biochemical relapse after radical prostatectomy for pathological T2/T3 and node-negative prostate cancer. We eagerly await the results of clinical trials evaluating the role of GnRH agonists in combination with salvage radiation therapy in patients in this setting. Given the long natural history of prostate cancer and the relatively low event rate, such studies can take over a decade to show differences in overall survival. Thus, until such data is available, 24 months of bicalutamide in combination with salvage radiation should be considered the new standard of care for patients (especially those at high risk) who develop non-metastatic biochemical relapse after prostatectomy.

—Devalkumar Rajyaguru, MD, and Lori Rosenstein, MD,
Gundersen Health System, La Crosse, WI

Study Overview

Objective. To evaluate the impact on overall survival of adding antiandrogen (bicalutamide) therapy to radiation in patients with prostate cancer who have an elevated prostate-specific antigen (PSA) after radical prostatectomy (either as persistence or as a relapse) and no evidence of metastatic disease.

Design. Phase III, randomized, double-blind, placebo-controlled trial.

Setting and participants. The trial was designed by NRG Oncology (Philadelphia, PA), sponsored by the National Cancer Institute, and conducted at NRG Oncology member sites, which included community-based hospitals. Eligible patients had undergone radical prostatectomy and had disease that was originally assessed, on the basis of pathological testing, as tumor stage T2 (confined to the prostate but with a positive surgical margin) or T3 (with histologic extension of tumor beyond the prostatic capsule) without nodal involvement. Patients also had to have a detectable PSA level between 0.2 and 4.0 ng/mL at least 8 weeks after surgery.  All the patients underwent abdominal and pelvic computed tomography (CT) and bone scans to rule out metastatic disease. Patients who received prior chemotherapy or radiation therapy for prostate cancer were excluded. Most patients had not received prior hormonal therapy for prostate cancer.

Intervention. All eligible patients received salvage radiation therapy within 12 weeks after randomization. Radiation was directed to the original prostatic site, the tumor resection bed, and the membranous urethra at a total dose of 64.8 Gy given in 36 daily fractions. In addition to the radiation therapy, patients were randomly assigned to receive either 150 mg of bicalutamide or 1 placebo tablet daily, beginning at the initiation of radiation therapy and continuing for 24 months.  Tablets were administered in a double blind fashion. Follow-up evaluations occurred every 3 months for 2 years, then every 6 months for 3 years, and then yearly. Bone and CT scans were performed either at biochemical recurrence or as indicated clinically. If metastatic disease was detected on follow up or if the serum PSA level rose to more than 4.0 ng/mL, maximum androgen blockade was recommended.

Main outcome measure. The main outcome was overall survival rate at 12 years. Secondary end points were disease-specific death, distant metastases, local disease progression, non–disease-specific death, any prostate cancer progression including a second biochemical recurrence, and adverse events.

Main results. 840 patients were randomized between March 1998 and March 2003, with 760 patients eligible for evaluation (384 patients in bicalutamide group and 376 in placebo group). Demographic and tumor-related characteristics of the 2 groups were similar. In both groups the majority of  patients were white (89.6% in bicalutamide arm; 86.2 in placebo), had Karnofsky performance status score of 100% (77.1 % in bicalutamide arm; 74.5% in placebo), and had positive surgical margin (75% in bicalutamide arm; 74.7% in placebo). Median age was 65 years, and median PSA level at trial entry was 0.6 ng/mL.  The median follow-up among the surviving patients was 13 years.

A total of 21 patients in the bicalutamide group and 46 patients in the placebo group died from prostate cancer. The actuarial rate of overall survival at 12 years was 76.3% in the bicalutamide group and 71.3% in the placebo group (hazard ratio [HR] for death 0.77 [95% confidence interval {CI} 0.59 to 0.99; P = 0.04), resulting in a 23% relative reduction in the risk of death in patients who received bicalutamide. The 12-year incidence of death from prostate cancer was 5.8% in the bicalutamide group versus 13.4% in the placebo group (HR 0.49 [95% CI 0.32 to 0.74]; P < 0.001), resulting in a 51% lower rate of death from prostate cancer in bicalutamide patients. Post hoc subgroup analyses showed that the greatest overall survival benefit was seen in subgroups of patients with more aggressive prostate cancer, such as those with high PSA level at trial entry (1.5 to 4.0 ng/mL) or Gleason score of 7.  There were too few patients with Gleason scores of 8, 9, or 10 to draw meaningful conclusions about this subgroup. There appeared to be a larger benefit in patients with positive surgical margins than in those with negative surgical margins.

Adherence to radiation therapy was similar between the 2 trial groups, and addition of bicalutamide to radiation therapy did not result in an increase in adverse events associated with radiation therapy, such as cystitis, colitis, or sexual dysfunction. The rates of hot flashes and cardiovascular deaths were not significantly higher in the bicalutamide group than in the placebo group. However, gynecomastia was reported significantly more frequently in the bicalutamide group (69.7%) than  in the placebo group (10.9%, P < 0.001).

Conclusion. The addition of 24 months of antiandrogen therapy with daily bicalutamide to salvage radiation therapy resulted in significantly higher rates of long-term overall survival and lower incidence of death from prostate cancer as compared to the addition of placebo. This benefit appeared to be without a significant cost in terms of toxicity.

Commentary

Prostate cancer is the second most common cancer in men worldwide, with an estimated 1,618,000 cases and 366,000 deaths in 2015 [1]. The current lifetime risk of developing prostate cancer for men living in the United States is estimated to be 1 in 6 [2]. Most prostate cancers are diagnosed in the localized stage, which is often treated with radical prostatectomy. All prostate tissue is removed during a successful radical prostatectomy. Postoperatively, detectable serum PSA is indicative of residual prostatic tissue, which presumably represents disease recurrence. This elevation in PSA after surgery in the absence of systemic metastatic disease is termed bio-chemical recurrence. The current standard of care for patients who develop biochemical recurrence is salvage radiation therapy. The prognosis for these patients is related to initial tumor characteristics—grade, volume and local stage. However, approximately 50% of the patients who are treated with salvage radiation therapy for biochemical recurrence will have further disease progression and may ultimately die from prostate cancer [3,4]. This is especially true when aggressive disease features are present. Radiation therapy combined with androgen-deprivation therapy using GnRH agonists or antiandrogen therapy (bicalutamide, flutamide) prolongs survival among some men with an intact prostate. This combination represents a rationale approach to prolong survival among men who develop non-metastatic biochemical relapse after radical prostatectomy.

The study by Shipley and colleagues reports the long-term outcomes of a randomized trial comparing salvage radiation plus 2 years of antiandrogen therapy to salvage radiation and placebo. Starting daily bicalutamide 150 mg orally with salvage radiation and continuing for 2 years was associated with a 23% improvement in overall survival and a 51% lower rate of death from prostate cancer, as compared to the placebo group. The number needed to treat (NNT) with bicalutamide to prevent one death from prostate cancer over 12 years was 20. By comparison, standard treatment of prostate cancer with surgery or radiation has an NNT of 27, which demonstrates the magnitude of the benefit of addition of antiandrogen therapy to salvage radiation. The benefit appears to be greatest in patients with poor prognostic factors such as higher Gleason scores (8 to 10), a higher PSA level at entry (0.7 to 4.0 ng/mL), or positive surgical margins. In contrast, patients with lower Gleason score or negative margins seemed to benefit less from the addition of antiandrogen therapy to salvage radiation. Two years of bicalutamide was not associated with increased incidence of radiation-related toxicities or cardiovascular death. As expected, the primary adverse effect of bicalutamide was gynecomastia, which was seen in 70% of the men treated. This adverse effect can be distressing but can be mitigated by prophylactic radiation of the breast or by the administration of tamoxifen, which were not done as preventative measures in this trial.

While the addition of bicalutamide to radiation did show a clear benefit to overall survival, questions remain about whether bicalutamide is the best drug to use. As the authors note, at present GnRH agonists such as leuprolide are considered first-line hormonal therapy with radiation for most patients with prostate cancer, and bicalutamide at the dose used in this study (150 mg) is not approved. We do not know how GnRH agonists will perform either as a single agent or in combination with antiandrogen for patients who develop biochemical relapse, as the use of GnRH agonists with radiation therapy has not been evaluated in patients who develop biochemical relapse in randomized clinical trials. Two trials exploring the use of androgen deprivation therapy with salvage radiation therapy in patients with biochemical recurrence (Radiotherapy and Androgen Deprivation in Combination After Local Surgery–Hormone Duration [RADICALS-HD] and the Groupe d’Etude des Tumeurs Uro-Génitales [GETUG]-16 trial) have finished enrollment; however, we will have to wait until the overall survival data matures before drawing any meaningful conclusions from them [5,6]. We know that patients with certain aggressive disease features based on tumor stage, grade, and volume are more likely to develop biochemical recurrence. As such, it is logical to consider evaluating the role of androgen deprivation therapy with adjuvant radiation therapy in patients who are at high risk of biochemical relapse with the goal of prolonging survival and reducing the risk of metastases. The RADICALS (Radiation Therapy and Androgen Deprivation Therapy in Treating Patients Who Have Undergone Surgery for Prostate Cancer) trial, which is evaluating the role of androgen deprivation therapy after adjuvant radiation therapy in patients who are at high risk of developing biochemical relapse, will help to address this issue.

Applications for Clinical Practice

Adding an antiandrogen agent (bicalutamide) to salvage radiation therapy in this randomized, double-blind, placebo-controlled trial resulted in higher rates of overall survival, disease-specific survival, and metastasis-free interval than radiation therapy alone for patients who developed biochemical relapse after radical prostatectomy for pathological T2/T3 and node-negative prostate cancer. We eagerly await the results of clinical trials evaluating the role of GnRH agonists in combination with salvage radiation therapy in patients in this setting. Given the long natural history of prostate cancer and the relatively low event rate, such studies can take over a decade to show differences in overall survival. Thus, until such data is available, 24 months of bicalutamide in combination with salvage radiation should be considered the new standard of care for patients (especially those at high risk) who develop non-metastatic biochemical relapse after prostatectomy.

—Devalkumar Rajyaguru, MD, and Lori Rosenstein, MD,
Gundersen Health System, La Crosse, WI

Study Overview

Objective. To compare the safety and efficacy of basal–bolus insulin therapy with sitagliptin plus insulin glargine in type 2 diabetes patients admitted to general medicine and surgical wards.

Design. Multicenter, prospective, open-label, noninferiority randomized clinical trial.

Setting and participants. Type 2 diabetes patients aged 18 to 80 years admitted to the general medicine and surgery services at one of 5 academic-based US hospitals were recruited. Eligible participants presented with a random blood glucose concentration between 140 and 400 mg/dL and were treated at home with diet, oral agents, or oral agents plus insulin at a maximum daily dose of 0.6 units/kg. Among those excluded were patients recently treated with a dipeptidyl peptidase-4 (DPP-4) inhibitor or glucagon-like peptide-1 (GLP-1) agonist, patients with clinically relevant hepatic disease, patients who were not eating for more than 48 hours, and those with an estimated glomerular filtration rate (eGFR) < 30 mL/min.

Intervention. Participants were randomly assigned to receive basal–bolus insulin therapy (BBI) with glargine once daily plus rapid-acting insulin before meals or sitagliptin plus glargine (SPG) once daily. Those in the SPG group received sitagliptin 100 mg/day if their eGFR was > 50 mL/min and sitagliptin 50 mg/day if their eGFR was 30 to 50 mL/min. If the eGFR fell below 30 mL/min during the hospitalization, sitagliptin was reduced to 25 mg/day. Glargine doses for those in the SPG group were started at 0.2 units/kg if randomization blood glucose was 140–200 mg/dL and 0.25 units/kg if randomization glucose was 201–400 mg/dL. Patients aged 70 or older or with an eGFR < 50 mL/min started with a daily glargine dose of 0.15 units/kg. For the BBI group, a total daily insulin dose of 0.4 units/kg was initiated for those with blood glucose levels between 140 and 200 mg/dL, and 0.5 units/kg for those with randomization glucose between 201 and 400 mg/dL. Half of this daily dose was given as glargine and the other half was distributed evenly across 3 pre-meal doses. Both the BBI and SPG groups received pre-meal and bedtime correction doses of rapid-acting insulin for glucose levels above 140 mg/dL. Blood glucose concentrations were measured fasting, before meals, and at bedtime or every 6 hours for patients who were not eating. Target fasting and pre-meal blood glucose levels were 100 to 140 mg/dL. Investigators and participants were not blinded to group assignment and glucose control was managed by the primary medical or surgical team.

Main outcomes measure. The primary outcome for this trial was noninferiority for differences between the SPG and BBI groups in glycemic control. Secondary endpoints included differences in the number of hypoglycemic and hyperglycemic events, the number of blood glucose values between 70 and 140 mg/dL and between 70 and 180 mg/dL, and the number of treatment failures (defined as 2 consecutive blood glucose values > 240 mg/dL or mean daily glucose > 240 mg/dL), length of hospital stay, total daily dose of insulin, number of insulin injections per day, transfer to the intensive care unit, and hospital complications and mortality.

Main results. A total of 138 patients in the SPG group and 139 patients in the BBI group completed the study and were included in this analysis. Of these 277 patients, 84% were admitted to a medicine ward and 16% were admitted to a surgical ward. The average age of participants was approximately 57 years, the average BMI was approximately 35 kg/m², and the average duration of diabetes was approximately 10 years. These baseline characteristics as well as ethnic origin, sex, and baseline A1c (approximately 40% of patients in both groups had a baseline A1c between 7% and 9%) did not differ between groups. Prior to admission, approximately 40% of patients in both groups were managed with oral drugs alone, approximately 25% were managed with insulin alone, and about 22% were managed with insulin and oral therapy.

With respect to the primary outcome, both groups had similar mean daily blood glucose concentrations (171 mg/dL in SPG and 169 mg/dL in BBI) throughout the hospitalization, meeting the noninferiority threshold for glycemic control between groups. As for secondary outcomes, the mean proportion of blood glucose readings between 70 and 140 mg/dL, 70 and 180 mg/dL, and 100 and 140 mg/dL did not differ between groups. Pre-meal and bedtime blood glucose concentrations were also similar in both groups. There was a significant difference between groups in average daily insulin dose (24 units in SPG versus 34 units in BBI), total units of insulin per kg per day (0.2 units/kg in SPG versus 0.3 units/kg in BBI), and number of insulin injections per day (2.2 in SPG versus 2.9 in BBI). There was no difference in the number of hypoglycemic or hyperglycemic events, length of hospital stay (approximately 4 days in both groups), and rates of complications (including acute respiratory failure, acute kidney injury, and myocardial infarction) between groups.

Conclusion. Inpatient treatment with sitagliptin plus glargine was noninferior to basal–bolus insulin therapy in measurements of glycemic control.

Commentary

Approximately 25% to 30% of adult patients admitted to general medical and surgical wards and critical care units have type 2 diabetes [1]. Maintaining adequate blood sugar control is important, as both hyperglycemia and hypoglycemia have been associated with adverse outcomes. Although group consensus statements differ slightly with respect to recommended target glucose levels, generally the recommended range in a noncritical inpatient setting is 140 to 180 mg/dL [2,3]. Establishing and maintaining these levels can often be very challenging. Barriers to achieving adequate glucose control in the inpatient setting include changes in a patients’ nutrition status, renal function, pain level, the use of glucocorticoids, and the development of infections. In addition, a significant gap in knowledge can exist from provider to provider in terms of how to appropriately initiate and titrate insulin regimens. To circumvent this, many hospitals have created built-in order sets and protocols in the electronic medical record for basal–bolus correction insulin regimens. While these protocols may have improved many parameters of inpatient diabetes management at several institutions, improper initiation and execution of these protocols still occur. Also, at times the priorities of the medical team can shift so that titration of the insulin regimen may not occur frequently enough. Overall, simplification of inpatient glucose management would certainly be a welcomed change.

Unfortunately, there is a dearth of studies that investigate the role of oral therapy in the inpatient setting. In general, oral medications are discontinued upon admission and insulin is the recommended standard of care. In this study, Pasquel and colleagues investigated the use of the DPP-4 inhibitor sitagliptin in the inpatient setting. Unlike some of the other classes of oral agents used in the outpatient setting, DPP-4 inhibitors are generally well tolerated. A major advantage of DPP-4 inhibitors is that, with dose titration, they can also be used in mild to moderate renal failure. However, because DPP-4 inhibitors work in the prandial setting, they are not effective in the NPO patient. In this study, both the SPG group and BBI group had similar average daily blood glucose levels after the first day of therapy and throughout the hospitalization (171 mg/dL in SPG versus 169 mg/dL in BBI). Since the key finding here was noninferiority for blood sugar control between the treatments, the major differences between SPG and BBI therapy should be highlighted.

One benefit of SPG versus BBI therapy is that replacement of bolus insulin injections with a once-daily pill reduces the need for frequent bolus insulin dose titration. Nonetheless, renal function should be monitored frequently, as sitagliptin dose adjustments may be required, and the importance of bedside glucose checks should not be diminished, as some patients may not maintain adequate control on this regimen and will need to betransitioned to BBI therapy. Both treatment groups received correctional insulin doses in the prandial setting if their pre-meal glucose levels met a specific threshold. Overall, the SPG group required significantly fewer total insulin injections per day (2.2 injections in SPG versus 2.9 injections in BBI, P < 0.001). Though this difference is rather small, the need to administer fewer insulin injections would certainly be beneficial to nursing staff, who often care for several type 2 diabetes patients at once. It would have been interesting to know how many patients in each group were free of any correctional insulin doses or how many were adequately controlled with just 1 prandial injection per day. Although it cannot be concluded from this study, it could be expected that the reduced need for bolus insulin dose titration and fewer total insulin injections associated with oral therapy would result in less insulin dosing error and perhaps greater patient satisfaction.

It is important to keep in mind that initiating a DPP-4 inhibitor with basal insulin may not be an appropriate option for all admitted type 2 diabetes patients. It can be a beneficial alternative to insulin for the select group of patients included in this study: those treated at home with diet alone, oral therapy alone, or oral therapy plus insulin.

While the potential for implementation of SPG therapy in an inpatient setting does exist, there are some limitations to this study that make further investigation necessary. Though the patent on Januvia (sitagliptin’s trade name) expires in 2017, sitagliptin is currently a very expensive drug. Therefore, a cost-benefit analysis of SPG therapy versus insulin therapy alone should be undertaken. Also, this was an unblinded study, which may have resulted in more attentive, prioritized blood sugar management than what would typically occur in an inpatient setting. Also, the providers’ level of expertise on insulin management in this study may not be generalized to all inpatient medical and surgical providers. Despite these limitations, this study may have a profound impact on inpatient diabetes management, since a less labor-intensive alternative to basal–bolus insulin therapy may present a more attractive option for many inpatient providers.

Applications for Clinical Practice

This study could pave the way for a practice-changing method of inpatient glucose management for a select group of patients who do not have severely uncontrolled type 2 diabetes. One should keep in mind that cost could be a barrier to implementation of sitagliptin in hospitals, and that while the bolus dose of insulin can be replaced with sitagliptin, patients may still need correctional doses of insulin to maintain target ranges. Also, a daily assess-ment of glucose control is still necessary in order to determine if a change in management is needed. Therefore, the sitagliptin plus glargine option should not be viewed as a “shortcut” therapy, but rather as a potentially less labor-intensive option that may increase the ability to prioritize blood sugar management in the inpatient setting.

— Lisa Parikh, MD, Yale School of Medicine,
New Haven, CT

Study Overview

Objective. To compare the safety and efficacy of basal–bolus insulin therapy with sitagliptin plus insulin glargine in type 2 diabetes patients admitted to general medicine and surgical wards.

Design. Multicenter, prospective, open-label, noninferiority randomized clinical trial.

Setting and participants. Type 2 diabetes patients aged 18 to 80 years admitted to the general medicine and surgery services at one of 5 academic-based US hospitals were recruited. Eligible participants presented with a random blood glucose concentration between 140 and 400 mg/dL and were treated at home with diet, oral agents, or oral agents plus insulin at a maximum daily dose of 0.6 units/kg. Among those excluded were patients recently treated with a dipeptidyl peptidase-4 (DPP-4) inhibitor or glucagon-like peptide-1 (GLP-1) agonist, patients with clinically relevant hepatic disease, patients who were not eating for more than 48 hours, and those with an estimated glomerular filtration rate (eGFR) < 30 mL/min.

Intervention. Participants were randomly assigned to receive basal–bolus insulin therapy (BBI) with glargine once daily plus rapid-acting insulin before meals or sitagliptin plus glargine (SPG) once daily. Those in the SPG group received sitagliptin 100 mg/day if their eGFR was > 50 mL/min and sitagliptin 50 mg/day if their eGFR was 30 to 50 mL/min. If the eGFR fell below 30 mL/min during the hospitalization, sitagliptin was reduced to 25 mg/day. Glargine doses for those in the SPG group were started at 0.2 units/kg if randomization blood glucose was 140–200 mg/dL and 0.25 units/kg if randomization glucose was 201–400 mg/dL. Patients aged 70 or older or with an eGFR < 50 mL/min started with a daily glargine dose of 0.15 units/kg. For the BBI group, a total daily insulin dose of 0.4 units/kg was initiated for those with blood glucose levels between 140 and 200 mg/dL, and 0.5 units/kg for those with randomization glucose between 201 and 400 mg/dL. Half of this daily dose was given as glargine and the other half was distributed evenly across 3 pre-meal doses. Both the BBI and SPG groups received pre-meal and bedtime correction doses of rapid-acting insulin for glucose levels above 140 mg/dL. Blood glucose concentrations were measured fasting, before meals, and at bedtime or every 6 hours for patients who were not eating. Target fasting and pre-meal blood glucose levels were 100 to 140 mg/dL. Investigators and participants were not blinded to group assignment and glucose control was managed by the primary medical or surgical team.

Main outcomes measure. The primary outcome for this trial was noninferiority for differences between the SPG and BBI groups in glycemic control. Secondary endpoints included differences in the number of hypoglycemic and hyperglycemic events, the number of blood glucose values between 70 and 140 mg/dL and between 70 and 180 mg/dL, and the number of treatment failures (defined as 2 consecutive blood glucose values > 240 mg/dL or mean daily glucose > 240 mg/dL), length of hospital stay, total daily dose of insulin, number of insulin injections per day, transfer to the intensive care unit, and hospital complications and mortality.

Main results. A total of 138 patients in the SPG group and 139 patients in the BBI group completed the study and were included in this analysis. Of these 277 patients, 84% were admitted to a medicine ward and 16% were admitted to a surgical ward. The average age of participants was approximately 57 years, the average BMI was approximately 35 kg/m², and the average duration of diabetes was approximately 10 years. These baseline characteristics as well as ethnic origin, sex, and baseline A1c (approximately 40% of patients in both groups had a baseline A1c between 7% and 9%) did not differ between groups. Prior to admission, approximately 40% of patients in both groups were managed with oral drugs alone, approximately 25% were managed with insulin alone, and about 22% were managed with insulin and oral therapy.

With respect to the primary outcome, both groups had similar mean daily blood glucose concentrations (171 mg/dL in SPG and 169 mg/dL in BBI) throughout the hospitalization, meeting the noninferiority threshold for glycemic control between groups. As for secondary outcomes, the mean proportion of blood glucose readings between 70 and 140 mg/dL, 70 and 180 mg/dL, and 100 and 140 mg/dL did not differ between groups. Pre-meal and bedtime blood glucose concentrations were also similar in both groups. There was a significant difference between groups in average daily insulin dose (24 units in SPG versus 34 units in BBI), total units of insulin per kg per day (0.2 units/kg in SPG versus 0.3 units/kg in BBI), and number of insulin injections per day (2.2 in SPG versus 2.9 in BBI). There was no difference in the number of hypoglycemic or hyperglycemic events, length of hospital stay (approximately 4 days in both groups), and rates of complications (including acute respiratory failure, acute kidney injury, and myocardial infarction) between groups.

Conclusion. Inpatient treatment with sitagliptin plus glargine was noninferior to basal–bolus insulin therapy in measurements of glycemic control.

Commentary

Approximately 25% to 30% of adult patients admitted to general medical and surgical wards and critical care units have type 2 diabetes [1]. Maintaining adequate blood sugar control is important, as both hyperglycemia and hypoglycemia have been associated with adverse outcomes. Although group consensus statements differ slightly with respect to recommended target glucose levels, generally the recommended range in a noncritical inpatient setting is 140 to 180 mg/dL [2,3]. Establishing and maintaining these levels can often be very challenging. Barriers to achieving adequate glucose control in the inpatient setting include changes in a patients’ nutrition status, renal function, pain level, the use of glucocorticoids, and the development of infections. In addition, a significant gap in knowledge can exist from provider to provider in terms of how to appropriately initiate and titrate insulin regimens. To circumvent this, many hospitals have created built-in order sets and protocols in the electronic medical record for basal–bolus correction insulin regimens. While these protocols may have improved many parameters of inpatient diabetes management at several institutions, improper initiation and execution of these protocols still occur. Also, at times the priorities of the medical team can shift so that titration of the insulin regimen may not occur frequently enough. Overall, simplification of inpatient glucose management would certainly be a welcomed change.

Unfortunately, there is a dearth of studies that investigate the role of oral therapy in the inpatient setting. In general, oral medications are discontinued upon admission and insulin is the recommended standard of care. In this study, Pasquel and colleagues investigated the use of the DPP-4 inhibitor sitagliptin in the inpatient setting. Unlike some of the other classes of oral agents used in the outpatient setting, DPP-4 inhibitors are generally well tolerated. A major advantage of DPP-4 inhibitors is that, with dose titration, they can also be used in mild to moderate renal failure. However, because DPP-4 inhibitors work in the prandial setting, they are not effective in the NPO patient. In this study, both the SPG group and BBI group had similar average daily blood glucose levels after the first day of therapy and throughout the hospitalization (171 mg/dL in SPG versus 169 mg/dL in BBI). Since the key finding here was noninferiority for blood sugar control between the treatments, the major differences between SPG and BBI therapy should be highlighted.

One benefit of SPG versus BBI therapy is that replacement of bolus insulin injections with a once-daily pill reduces the need for frequent bolus insulin dose titration. Nonetheless, renal function should be monitored frequently, as sitagliptin dose adjustments may be required, and the importance of bedside glucose checks should not be diminished, as some patients may not maintain adequate control on this regimen and will need to betransitioned to BBI therapy. Both treatment groups received correctional insulin doses in the prandial setting if their pre-meal glucose levels met a specific threshold. Overall, the SPG group required significantly fewer total insulin injections per day (2.2 injections in SPG versus 2.9 injections in BBI, P < 0.001). Though this difference is rather small, the need to administer fewer insulin injections would certainly be beneficial to nursing staff, who often care for several type 2 diabetes patients at once. It would have been interesting to know how many patients in each group were free of any correctional insulin doses or how many were adequately controlled with just 1 prandial injection per day. Although it cannot be concluded from this study, it could be expected that the reduced need for bolus insulin dose titration and fewer total insulin injections associated with oral therapy would result in less insulin dosing error and perhaps greater patient satisfaction.

It is important to keep in mind that initiating a DPP-4 inhibitor with basal insulin may not be an appropriate option for all admitted type 2 diabetes patients. It can be a beneficial alternative to insulin for the select group of patients included in this study: those treated at home with diet alone, oral therapy alone, or oral therapy plus insulin.

While the potential for implementation of SPG therapy in an inpatient setting does exist, there are some limitations to this study that make further investigation necessary. Though the patent on Januvia (sitagliptin’s trade name) expires in 2017, sitagliptin is currently a very expensive drug. Therefore, a cost-benefit analysis of SPG therapy versus insulin therapy alone should be undertaken. Also, this was an unblinded study, which may have resulted in more attentive, prioritized blood sugar management than what would typically occur in an inpatient setting. Also, the providers’ level of expertise on insulin management in this study may not be generalized to all inpatient medical and surgical providers. Despite these limitations, this study may have a profound impact on inpatient diabetes management, since a less labor-intensive alternative to basal–bolus insulin therapy may present a more attractive option for many inpatient providers.

Applications for Clinical Practice

This study could pave the way for a practice-changing method of inpatient glucose management for a select group of patients who do not have severely uncontrolled type 2 diabetes. One should keep in mind that cost could be a barrier to implementation of sitagliptin in hospitals, and that while the bolus dose of insulin can be replaced with sitagliptin, patients may still need correctional doses of insulin to maintain target ranges. Also, a daily assess-ment of glucose control is still necessary in order to determine if a change in management is needed. Therefore, the sitagliptin plus glargine option should not be viewed as a “shortcut” therapy, but rather as a potentially less labor-intensive option that may increase the ability to prioritize blood sugar management in the inpatient setting.

— Lisa Parikh, MD, Yale School of Medicine,
New Haven, CT

Study Overview

Objective. To compare the safety and efficacy of basal–bolus insulin therapy with sitagliptin plus insulin glargine in type 2 diabetes patients admitted to general medicine and surgical wards.

Design. Multicenter, prospective, open-label, noninferiority randomized clinical trial.

Setting and participants. Type 2 diabetes patients aged 18 to 80 years admitted to the general medicine and surgery services at one of 5 academic-based US hospitals were recruited. Eligible participants presented with a random blood glucose concentration between 140 and 400 mg/dL and were treated at home with diet, oral agents, or oral agents plus insulin at a maximum daily dose of 0.6 units/kg. Among those excluded were patients recently treated with a dipeptidyl peptidase-4 (DPP-4) inhibitor or glucagon-like peptide-1 (GLP-1) agonist, patients with clinically relevant hepatic disease, patients who were not eating for more than 48 hours, and those with an estimated glomerular filtration rate (eGFR) < 30 mL/min.

Intervention. Participants were randomly assigned to receive basal–bolus insulin therapy (BBI) with glargine once daily plus rapid-acting insulin before meals or sitagliptin plus glargine (SPG) once daily. Those in the SPG group received sitagliptin 100 mg/day if their eGFR was > 50 mL/min and sitagliptin 50 mg/day if their eGFR was 30 to 50 mL/min. If the eGFR fell below 30 mL/min during the hospitalization, sitagliptin was reduced to 25 mg/day. Glargine doses for those in the SPG group were started at 0.2 units/kg if randomization blood glucose was 140–200 mg/dL and 0.25 units/kg if randomization glucose was 201–400 mg/dL. Patients aged 70 or older or with an eGFR < 50 mL/min started with a daily glargine dose of 0.15 units/kg. For the BBI group, a total daily insulin dose of 0.4 units/kg was initiated for those with blood glucose levels between 140 and 200 mg/dL, and 0.5 units/kg for those with randomization glucose between 201 and 400 mg/dL. Half of this daily dose was given as glargine and the other half was distributed evenly across 3 pre-meal doses. Both the BBI and SPG groups received pre-meal and bedtime correction doses of rapid-acting insulin for glucose levels above 140 mg/dL. Blood glucose concentrations were measured fasting, before meals, and at bedtime or every 6 hours for patients who were not eating. Target fasting and pre-meal blood glucose levels were 100 to 140 mg/dL. Investigators and participants were not blinded to group assignment and glucose control was managed by the primary medical or surgical team.

Main outcomes measure. The primary outcome for this trial was noninferiority for differences between the SPG and BBI groups in glycemic control. Secondary endpoints included differences in the number of hypoglycemic and hyperglycemic events, the number of blood glucose values between 70 and 140 mg/dL and between 70 and 180 mg/dL, and the number of treatment failures (defined as 2 consecutive blood glucose values > 240 mg/dL or mean daily glucose > 240 mg/dL), length of hospital stay, total daily dose of insulin, number of insulin injections per day, transfer to the intensive care unit, and hospital complications and mortality.

Main results. A total of 138 patients in the SPG group and 139 patients in the BBI group completed the study and were included in this analysis. Of these 277 patients, 84% were admitted to a medicine ward and 16% were admitted to a surgical ward. The average age of participants was approximately 57 years, the average BMI was approximately 35 kg/m², and the average duration of diabetes was approximately 10 years. These baseline characteristics as well as ethnic origin, sex, and baseline A1c (approximately 40% of patients in both groups had a baseline A1c between 7% and 9%) did not differ between groups. Prior to admission, approximately 40% of patients in both groups were managed with oral drugs alone, approximately 25% were managed with insulin alone, and about 22% were managed with insulin and oral therapy.

With respect to the primary outcome, both groups had similar mean daily blood glucose concentrations (171 mg/dL in SPG and 169 mg/dL in BBI) throughout the hospitalization, meeting the noninferiority threshold for glycemic control between groups. As for secondary outcomes, the mean proportion of blood glucose readings between 70 and 140 mg/dL, 70 and 180 mg/dL, and 100 and 140 mg/dL did not differ between groups. Pre-meal and bedtime blood glucose concentrations were also similar in both groups. There was a significant difference between groups in average daily insulin dose (24 units in SPG versus 34 units in BBI), total units of insulin per kg per day (0.2 units/kg in SPG versus 0.3 units/kg in BBI), and number of insulin injections per day (2.2 in SPG versus 2.9 in BBI). There was no difference in the number of hypoglycemic or hyperglycemic events, length of hospital stay (approximately 4 days in both groups), and rates of complications (including acute respiratory failure, acute kidney injury, and myocardial infarction) between groups.

Conclusion. Inpatient treatment with sitagliptin plus glargine was noninferior to basal–bolus insulin therapy in measurements of glycemic control.

Commentary

Approximately 25% to 30% of adult patients admitted to general medical and surgical wards and critical care units have type 2 diabetes [1]. Maintaining adequate blood sugar control is important, as both hyperglycemia and hypoglycemia have been associated with adverse outcomes. Although group consensus statements differ slightly with respect to recommended target glucose levels, generally the recommended range in a noncritical inpatient setting is 140 to 180 mg/dL [2,3]. Establishing and maintaining these levels can often be very challenging. Barriers to achieving adequate glucose control in the inpatient setting include changes in a patients’ nutrition status, renal function, pain level, the use of glucocorticoids, and the development of infections. In addition, a significant gap in knowledge can exist from provider to provider in terms of how to appropriately initiate and titrate insulin regimens. To circumvent this, many hospitals have created built-in order sets and protocols in the electronic medical record for basal–bolus correction insulin regimens. While these protocols may have improved many parameters of inpatient diabetes management at several institutions, improper initiation and execution of these protocols still occur. Also, at times the priorities of the medical team can shift so that titration of the insulin regimen may not occur frequently enough. Overall, simplification of inpatient glucose management would certainly be a welcomed change.

Unfortunately, there is a dearth of studies that investigate the role of oral therapy in the inpatient setting. In general, oral medications are discontinued upon admission and insulin is the recommended standard of care. In this study, Pasquel and colleagues investigated the use of the DPP-4 inhibitor sitagliptin in the inpatient setting. Unlike some of the other classes of oral agents used in the outpatient setting, DPP-4 inhibitors are generally well tolerated. A major advantage of DPP-4 inhibitors is that, with dose titration, they can also be used in mild to moderate renal failure. However, because DPP-4 inhibitors work in the prandial setting, they are not effective in the NPO patient. In this study, both the SPG group and BBI group had similar average daily blood glucose levels after the first day of therapy and throughout the hospitalization (171 mg/dL in SPG versus 169 mg/dL in BBI). Since the key finding here was noninferiority for blood sugar control between the treatments, the major differences between SPG and BBI therapy should be highlighted.

One benefit of SPG versus BBI therapy is that replacement of bolus insulin injections with a once-daily pill reduces the need for frequent bolus insulin dose titration. Nonetheless, renal function should be monitored frequently, as sitagliptin dose adjustments may be required, and the importance of bedside glucose checks should not be diminished, as some patients may not maintain adequate control on this regimen and will need to betransitioned to BBI therapy. Both treatment groups received correctional insulin doses in the prandial setting if their pre-meal glucose levels met a specific threshold. Overall, the SPG group required significantly fewer total insulin injections per day (2.2 injections in SPG versus 2.9 injections in BBI, P < 0.001). Though this difference is rather small, the need to administer fewer insulin injections would certainly be beneficial to nursing staff, who often care for several type 2 diabetes patients at once. It would have been interesting to know how many patients in each group were free of any correctional insulin doses or how many were adequately controlled with just 1 prandial injection per day. Although it cannot be concluded from this study, it could be expected that the reduced need for bolus insulin dose titration and fewer total insulin injections associated with oral therapy would result in less insulin dosing error and perhaps greater patient satisfaction.

It is important to keep in mind that initiating a DPP-4 inhibitor with basal insulin may not be an appropriate option for all admitted type 2 diabetes patients. It can be a beneficial alternative to insulin for the select group of patients included in this study: those treated at home with diet alone, oral therapy alone, or oral therapy plus insulin.

While the potential for implementation of SPG therapy in an inpatient setting does exist, there are some limitations to this study that make further investigation necessary. Though the patent on Januvia (sitagliptin’s trade name) expires in 2017, sitagliptin is currently a very expensive drug. Therefore, a cost-benefit analysis of SPG therapy versus insulin therapy alone should be undertaken. Also, this was an unblinded study, which may have resulted in more attentive, prioritized blood sugar management than what would typically occur in an inpatient setting. Also, the providers’ level of expertise on insulin management in this study may not be generalized to all inpatient medical and surgical providers. Despite these limitations, this study may have a profound impact on inpatient diabetes management, since a less labor-intensive alternative to basal–bolus insulin therapy may present a more attractive option for many inpatient providers.

Applications for Clinical Practice

This study could pave the way for a practice-changing method of inpatient glucose management for a select group of patients who do not have severely uncontrolled type 2 diabetes. One should keep in mind that cost could be a barrier to implementation of sitagliptin in hospitals, and that while the bolus dose of insulin can be replaced with sitagliptin, patients may still need correctional doses of insulin to maintain target ranges. Also, a daily assess-ment of glucose control is still necessary in order to determine if a change in management is needed. Therefore, the sitagliptin plus glargine option should not be viewed as a “shortcut” therapy, but rather as a potentially less labor-intensive option that may increase the ability to prioritize blood sugar management in the inpatient setting.

— Lisa Parikh, MD, Yale School of Medicine,
New Haven, CT

Nicolls SJ, Puri S, Anderson, T, et al. Effect of evolocumab on progression of coronary disease in statin-treated patients. The GLAGOV randomized clinical trial. JAMA 2016;316:2372–84.

To Download a PDF of the Full Article:

Click Here

Study Overview

Objective. To determine if evolocumab, a PCSK9 inhibitor, affects the progression of coronary artery disease in patients treated with statins.

Design. Multicenter, international, double-blind, placebo-controlled, randomized clinical trial.

Setting and participants. 197 community and academic hospitals worldwide enrolled 978 participants who underwent serial intravascular ultrasounds (IVUS) to measure their burden of coronary atherosclerosis. A total of 2628 patients were screened. Patients were considered for inclusion if they were 18 years of age or older and had at least 1 coronary artery stenosis of at least 20% on a clinically indicated catheterization. Additionally, the target vessel had to meet IVUS imaging quality and visibility standards. Participants were required to have been on stable statin therapy for at least 4 weeks with an LDL level of > 80 mg/dL or between 60–80 mg/dL with either 1 major or 3 minor cardiovascular risk factors. Major risk factors were noncoronary atherosclerotic disease, myocardial infarction (MI) or hospitalization for unstable angina within the past 2 years, or type 2 diabetes. Minor risk factors included current tobacco use, hypertension, low HDL-C levels, family history of early coronary disease, hsCRP level of 2 mg/L or greater, and age older than 50 years for men and 55 years for women. Patients with uncontrolled hypertension, uncontrolled diabetes, heart failure, renal insufficiency, or liver disease were excluded.

Intervention. Patients were randomized to either treatment with monthly subcutaneous injections of 420 mg evolocumab or placebo injections for 76 weeks. Participants attended 7 follow-up visits during the study period and then underwent repeat IVUS imaging at the 78th week. Research staff, who were blinded to both treatment status and imaging sequence, collected and assessed target vessel measurements, including the vessel lumen and external elastic membrane dimensions. IVUS imaging has been used in numerous clinical studies and has been shown to be accurate and reliable [1].

Main outcome measures. The primary outcome was the target artery change in percent atheroma volume (PAV) from baseline to week 78. PAV was calculated from IVUS measurements. Nominal change in PAV was then determined by calculating the difference of the PAV at baseline and at week 78.

The secondary measure was the normalized total atheroma volume (TAV). TAV addresses variability in the length of vessel segments and the number of images collected during IVUS catheter pullback. The nominal change in TAV was then determined by the difference at baseline and at week 78.

Additional secondary efficacy endpoints included number of patients with regression of plaque and change in lipid parameters. Safety outcomes were investigated through evaluation of the incidence of adjudicated clinical events, including all-cause mortality, cardiovascular death, MI, unstable angina requiring hospitalization, coronary revascularization, stroke, transient ischemic attack, and heart failure requiring hospitalization. Post-hoc analysis compared baseline LDL-C level and change in PAV and regression of PAV. The association between LDL lowering and plaque progression was also assessed post hoc.

IVUS measurements were evaluated as least squares means. Comparison of treatment groups was conducted using analysis of covariance on rank transformed data that accounted for baseline value and geographic location. Investigators used a step-down statistical procedure to evaluate primary and secondary endpoints. The statistical model accounted for confounders such as baseline LDL-C, baseline PAV, intensity of statin therapy, geographic region, age, and sex.

Main results. 484 participants were randomized to the evolocumab group and 484 to the placebo group, and 423 participants in both groups completed both baseline and follow-up IVUS imaging. Treatment and control groups contained participants matched for age, gender, ethnicity, cardiovascular risk factors, and baseline medication use, including lipid-lowering agents, ACE inhibitors, ARBs, beta-blockers, and antiplatelet therapies. Both groups consisted of a majority of white (93.4% in placebo and 94.2% in treatment) males (72.3% in placebo and 72.1% in treatment). Approximately 80% of participants had hypertension (83.7% in placebo and 82.2% in treatment), about 35% had prior MIs (35.3% in placebo and 34.9% in treatment), and roughly a fifth of participants had diabetes (21.5% in placebo and 20.2% in treatment). At baseline 98.6% of participants were treated with statins, with 58.9% on high-intensity therapy and 39.4% on moderate-intensity. Mean LDL-C level at baseline was 92.5 (SD, 27.2) mg/dL.

After 76 weeks of treatment, mean LDL-C level in the placebo group was 93.0 mg/dL and 36.6 mg/dL in the treatment group, which corresponds to a 0.2 mg/dL increase in the placebo group and a 56.3 mg/dL reduction in the treatment group. The change in LDL-C level was statistically significant (P < 0.001).

Placebo group participants had no significant change in PAV (0.05%, P = 0.78), but the evolocumab group experienced a 0.95% decrease from baseline (P < 0.001). Similarly, the placebo group had no change in TAV from baseline (–0.9 mm³, P = 0.45), but the treatment group had a 5.8 mm³ reduction in TAV from baseline (P < 0.001). The treatment group had a greater proportion of patients who experienced PAV regression (64.3% vs. 47.3%, P < 0.001) and TAV regression (61.5% vs. 48.9%, P < 0.001).

Subgroup analysis did not demonstrate a significant association between change in PAV and specific study participant characteristics (eg, age, gender, ethnicity).

Post-hoc analysis using local regression (LOESS) curve revealed a linear relationship between achieved LDL-C level and change in PAV for LDL-C levels from 110 mg/dL to 20 mg/dL.

The treatment group did not exhibit a significant increase in adverse drug events, which included injection site reactions, myalgias, neurocognitive events, and incidence of diabetes. There was no significant difference in adverse cardiovascular outcomes between groups; however, there were numerically fewer nonfatal MIs and coronary revascularizations in the treatment group.

Conclusion. The use of evolocumab in statin-treated patients resulted in greater reduction of PAV than use of statins alone.

Commentary

Evolocumab is a monoclonal antibody that inhibits pro-protein convertase subtilisin-kexin type 9 (PCSK9), which is involved in LDL-C receptor recycling. By reducing removal of LDL-C receptors, evolocumab amplifies LDL-C clearance and has been shown to reduce LDL-C levels by approximately 61% from baseline with 12 weeks oftreatment [2]. Studies have shown that the lipid-lowering potential of evolocumab is superior to statins alone and to combination therapy with statins and ezetimibe [2]. Furthermore, PCSK9 inhibitors have been effective at LDL-lowering in patients who failed or could not tolerate standard of care therapy with statins and ezetimibe [3,4]. PCSK9 inhibitors hold great promise for reducing morbidity and mortality of cardiovascular disease; however, LDL-lowering is not equivalent to improved clinical outcomes.

The GLAGOV study moves toward demonstration of the clinical benefit of evolocumab. The study shows that combined therapy with statins and evolocumab, versus statins alone, not only achieves better stability of atherosclerotic plaque dimensions but actually results in regression of plaque size. In the study, plaque burden is extrapolated from vessel measurements obtained through IVUS, and nominal changes in PAV and TAV serve as markers for atherosclerosis, but these surrogates cannot be equated to a reduction in cardiovascular events. The GLAGOV trial does explore clinical outcomes such as MI, stroke, unstable angina, coronary revascularization, and death; however, the study is not powered to evaluate the statistical significance of these events. We await sufficiently powered phase 3 clinical trials to determine the clinical benefits of PCSK9 inhibitors on cardiovascular disease.

The GLAGOV trial has several strengths, including its design as an international, double-blind, placebo-controlled, randomized clinical trial. The intervention is simple and the outcomes are clearly defined. The statistical assessment yields significant results. Nonetheless, there are multiple limitations to the study. The lead author has received research support from Amgen, the maker of evolocumab. Amgen also participated in study design and maintenance of trial databases; however, data analysis was conducted by an independent statistician. Additionally, the majority of study participants were white males with very few minority patients despite inclusion of study sites around the globe. The homogeneity of the study cohort makes the data difficult to generalize to a larger population. Similarly, patients who lacked a clinical indication for coronary catheterization and those with uncontrolled diabetes, hypertension, and heart failure were excluded, which further limits application of this study to many patients with atherosclerosis. Another limitation is study attrition; only 87% of participants completed the 78-week IVUS and were included in the data analysis, and results may have differed if those lost to follow-up had completed the trial. Furthermore, study duration was limited to 76 weeks and the magnitude and durability of study outcomes after this time point remain unknown.

Applications for Clinical Practice

Reduction in PAV and TAV are surrogate endpoints and are not indicative of a clinical benefit. Nonetheless, the GLAGOV study demonstrates that evolocumab, when used in conjunction with statins, can promote regression of atherosclerosis greater than treatment with statins alone. More studies are needed to evaluate a clinical benefit of adding evolocumab to the regularly used arsenal of lipid-lowering therapies for the treatment of atherosclerosis. Furthermore, cost-effectiveness of evolocumab has not been shown. In 2015 the yearly wholesale price of evolcumab was $14,350. A cost-effectiveness analysis based on this price estimates that treatment of atherosclerotic coronary vascular disease with evolocumab has a cost of $414,000 per quality-adjusted life year [5]. Evolocumab is well tolerated, but additional studies for cardiovascular and mortality outcomes are needed before it can be considered part of the standard of treatment for coronary artery disease.

—Lauren Brooks, MD, University of Maryland School of Medicine, Baltimore, MD

References

1. Nicholls SJ, Hsu A, Wolski K, et al. Intravascular ultrasound-derived measures of coronary atherosclerotic plaque burden and clinical outcome. J Am Coll Cardiol 2010;55:2399–407.

2. Sabatine MS, Giugliano RP, Wiviolt SD, et al. Efficacy and safety of evolocumab in reducing lipids and cardiovascular events. N Engl J Med 2015;372:1500–9.

3. Giugliano RP, Sabatine MS. Are PCSK9 inhibitors the next breakthrough in the cardiovascular field. J Am Coll Cardiol 2015;65:2639–51.

4. Stroes E, Colquhoun D, Sullivan D, et al. Anti-PCSK9 antibody effectively lowers cholesterol in patients with statin intolerance: the GAUSS-2 randomized, placebo-controlled phase 3 clinical trial of evolocumab. J Am Coll Cardiol 2014;63:2541–8.

5. Dhruv KS, Moran AE, Coxson PG, et al. Cost-effectiveness of PCSK9 inhibitor therapy in patients with heterozygous familial hypercholesterolemia or atherosclerotic coronary artery disease. JAMA 2016;316:743–53.

Nicolls SJ, Puri S, Anderson, T, et al. Effect of evolocumab on progression of coronary disease in statin-treated patients. The GLAGOV randomized clinical trial. JAMA 2016;316:2372–84.

To Download a PDF of the Full Article:

Click Here

Study Overview

Objective. To determine if evolocumab, a PCSK9 inhibitor, affects the progression of coronary artery disease in patients treated with statins.

Design. Multicenter, international, double-blind, placebo-controlled, randomized clinical trial.

Setting and participants. 197 community and academic hospitals worldwide enrolled 978 participants who underwent serial intravascular ultrasounds (IVUS) to measure their burden of coronary atherosclerosis. A total of 2628 patients were screened. Patients were considered for inclusion if they were 18 years of age or older and had at least 1 coronary artery stenosis of at least 20% on a clinically indicated catheterization. Additionally, the target vessel had to meet IVUS imaging quality and visibility standards. Participants were required to have been on stable statin therapy for at least 4 weeks with an LDL level of > 80 mg/dL or between 60–80 mg/dL with either 1 major or 3 minor cardiovascular risk factors. Major risk factors were noncoronary atherosclerotic disease, myocardial infarction (MI) or hospitalization for unstable angina within the past 2 years, or type 2 diabetes. Minor risk factors included current tobacco use, hypertension, low HDL-C levels, family history of early coronary disease, hsCRP level of 2 mg/L or greater, and age older than 50 years for men and 55 years for women. Patients with uncontrolled hypertension, uncontrolled diabetes, heart failure, renal insufficiency, or liver disease were excluded.

Intervention. Patients were randomized to either treatment with monthly subcutaneous injections of 420 mg evolocumab or placebo injections for 76 weeks. Participants attended 7 follow-up visits during the study period and then underwent repeat IVUS imaging at the 78th week. Research staff, who were blinded to both treatment status and imaging sequence, collected and assessed target vessel measurements, including the vessel lumen and external elastic membrane dimensions. IVUS imaging has been used in numerous clinical studies and has been shown to be accurate and reliable [1].

Main outcome measures. The primary outcome was the target artery change in percent atheroma volume (PAV) from baseline to week 78. PAV was calculated from IVUS measurements. Nominal change in PAV was then determined by calculating the difference of the PAV at baseline and at week 78.

The secondary measure was the normalized total atheroma volume (TAV). TAV addresses variability in the length of vessel segments and the number of images collected during IVUS catheter pullback. The nominal change in TAV was then determined by the difference at baseline and at week 78.

Additional secondary efficacy endpoints included number of patients with regression of plaque and change in lipid parameters. Safety outcomes were investigated through evaluation of the incidence of adjudicated clinical events, including all-cause mortality, cardiovascular death, MI, unstable angina requiring hospitalization, coronary revascularization, stroke, transient ischemic attack, and heart failure requiring hospitalization. Post-hoc analysis compared baseline LDL-C level and change in PAV and regression of PAV. The association between LDL lowering and plaque progression was also assessed post hoc.

IVUS measurements were evaluated as least squares means. Comparison of treatment groups was conducted using analysis of covariance on rank transformed data that accounted for baseline value and geographic location. Investigators used a step-down statistical procedure to evaluate primary and secondary endpoints. The statistical model accounted for confounders such as baseline LDL-C, baseline PAV, intensity of statin therapy, geographic region, age, and sex.

Main results. 484 participants were randomized to the evolocumab group and 484 to the placebo group, and 423 participants in both groups completed both baseline and follow-up IVUS imaging. Treatment and control groups contained participants matched for age, gender, ethnicity, cardiovascular risk factors, and baseline medication use, including lipid-lowering agents, ACE inhibitors, ARBs, beta-blockers, and antiplatelet therapies. Both groups consisted of a majority of white (93.4% in placebo and 94.2% in treatment) males (72.3% in placebo and 72.1% in treatment). Approximately 80% of participants had hypertension (83.7% in placebo and 82.2% in treatment), about 35% had prior MIs (35.3% in placebo and 34.9% in treatment), and roughly a fifth of participants had diabetes (21.5% in placebo and 20.2% in treatment). At baseline 98.6% of participants were treated with statins, with 58.9% on high-intensity therapy and 39.4% on moderate-intensity. Mean LDL-C level at baseline was 92.5 (SD, 27.2) mg/dL.

After 76 weeks of treatment, mean LDL-C level in the placebo group was 93.0 mg/dL and 36.6 mg/dL in the treatment group, which corresponds to a 0.2 mg/dL increase in the placebo group and a 56.3 mg/dL reduction in the treatment group. The change in LDL-C level was statistically significant (P < 0.001).

Placebo group participants had no significant change in PAV (0.05%, P = 0.78), but the evolocumab group experienced a 0.95% decrease from baseline (P < 0.001). Similarly, the placebo group had no change in TAV from baseline (–0.9 mm³, P = 0.45), but the treatment group had a 5.8 mm³ reduction in TAV from baseline (P < 0.001). The treatment group had a greater proportion of patients who experienced PAV regression (64.3% vs. 47.3%, P < 0.001) and TAV regression (61.5% vs. 48.9%, P < 0.001).

Subgroup analysis did not demonstrate a significant association between change in PAV and specific study participant characteristics (eg, age, gender, ethnicity).

Post-hoc analysis using local regression (LOESS) curve revealed a linear relationship between achieved LDL-C level and change in PAV for LDL-C levels from 110 mg/dL to 20 mg/dL.

The treatment group did not exhibit a significant increase in adverse drug events, which included injection site reactions, myalgias, neurocognitive events, and incidence of diabetes. There was no significant difference in adverse cardiovascular outcomes between groups; however, there were numerically fewer nonfatal MIs and coronary revascularizations in the treatment group.

Conclusion. The use of evolocumab in statin-treated patients resulted in greater reduction of PAV than use of statins alone.

Commentary

Evolocumab is a monoclonal antibody that inhibits pro-protein convertase subtilisin-kexin type 9 (PCSK9), which is involved in LDL-C receptor recycling. By reducing removal of LDL-C receptors, evolocumab amplifies LDL-C clearance and has been shown to reduce LDL-C levels by approximately 61% from baseline with 12 weeks oftreatment [2]. Studies have shown that the lipid-lowering potential of evolocumab is superior to statins alone and to combination therapy with statins and ezetimibe [2]. Furthermore, PCSK9 inhibitors have been effective at LDL-lowering in patients who failed or could not tolerate standard of care therapy with statins and ezetimibe [3,4]. PCSK9 inhibitors hold great promise for reducing morbidity and mortality of cardiovascular disease; however, LDL-lowering is not equivalent to improved clinical outcomes.

The GLAGOV study moves toward demonstration of the clinical benefit of evolocumab. The study shows that combined therapy with statins and evolocumab, versus statins alone, not only achieves better stability of atherosclerotic plaque dimensions but actually results in regression of plaque size. In the study, plaque burden is extrapolated from vessel measurements obtained through IVUS, and nominal changes in PAV and TAV serve as markers for atherosclerosis, but these surrogates cannot be equated to a reduction in cardiovascular events. The GLAGOV trial does explore clinical outcomes such as MI, stroke, unstable angina, coronary revascularization, and death; however, the study is not powered to evaluate the statistical significance of these events. We await sufficiently powered phase 3 clinical trials to determine the clinical benefits of PCSK9 inhibitors on cardiovascular disease.

The GLAGOV trial has several strengths, including its design as an international, double-blind, placebo-controlled, randomized clinical trial. The intervention is simple and the outcomes are clearly defined. The statistical assessment yields significant results. Nonetheless, there are multiple limitations to the study. The lead author has received research support from Amgen, the maker of evolocumab. Amgen also participated in study design and maintenance of trial databases; however, data analysis was conducted by an independent statistician. Additionally, the majority of study participants were white males with very few minority patients despite inclusion of study sites around the globe. The homogeneity of the study cohort makes the data difficult to generalize to a larger population. Similarly, patients who lacked a clinical indication for coronary catheterization and those with uncontrolled diabetes, hypertension, and heart failure were excluded, which further limits application of this study to many patients with atherosclerosis. Another limitation is study attrition; only 87% of participants completed the 78-week IVUS and were included in the data analysis, and results may have differed if those lost to follow-up had completed the trial. Furthermore, study duration was limited to 76 weeks and the magnitude and durability of study outcomes after this time point remain unknown.

Applications for Clinical Practice

Reduction in PAV and TAV are surrogate endpoints and are not indicative of a clinical benefit. Nonetheless, the GLAGOV study demonstrates that evolocumab, when used in conjunction with statins, can promote regression of atherosclerosis greater than treatment with statins alone. More studies are needed to evaluate a clinical benefit of adding evolocumab to the regularly used arsenal of lipid-lowering therapies for the treatment of atherosclerosis. Furthermore, cost-effectiveness of evolocumab has not been shown. In 2015 the yearly wholesale price of evolcumab was $14,350. A cost-effectiveness analysis based on this price estimates that treatment of atherosclerotic coronary vascular disease with evolocumab has a cost of $414,000 per quality-adjusted life year [5]. Evolocumab is well tolerated, but additional studies for cardiovascular and mortality outcomes are needed before it can be considered part of the standard of treatment for coronary artery disease.

—Lauren Brooks, MD, University of Maryland School of Medicine, Baltimore, MD

References

1. Nicholls SJ, Hsu A, Wolski K, et al. Intravascular ultrasound-derived measures of coronary atherosclerotic plaque burden and clinical outcome. J Am Coll Cardiol 2010;55:2399–407.

2. Sabatine MS, Giugliano RP, Wiviolt SD, et al. Efficacy and safety of evolocumab in reducing lipids and cardiovascular events. N Engl J Med 2015;372:1500–9.

3. Giugliano RP, Sabatine MS. Are PCSK9 inhibitors the next breakthrough in the cardiovascular field. J Am Coll Cardiol 2015;65:2639–51.

4. Stroes E, Colquhoun D, Sullivan D, et al. Anti-PCSK9 antibody effectively lowers cholesterol in patients with statin intolerance: the GAUSS-2 randomized, placebo-controlled phase 3 clinical trial of evolocumab. J Am Coll Cardiol 2014;63:2541–8.

5. Dhruv KS, Moran AE, Coxson PG, et al. Cost-effectiveness of PCSK9 inhibitor therapy in patients with heterozygous familial hypercholesterolemia or atherosclerotic coronary artery disease. JAMA 2016;316:743–53.

Nicolls SJ, Puri S, Anderson, T, et al. Effect of evolocumab on progression of coronary disease in statin-treated patients. The GLAGOV randomized clinical trial. JAMA 2016;316:2372–84.

To Download a PDF of the Full Article:

Click Here

Study Overview

Objective. To determine if evolocumab, a PCSK9 inhibitor, affects the progression of coronary artery disease in patients treated with statins.

Design. Multicenter, international, double-blind, placebo-controlled, randomized clinical trial.

Setting and participants. 197 community and academic hospitals worldwide enrolled 978 participants who underwent serial intravascular ultrasounds (IVUS) to measure their burden of coronary atherosclerosis. A total of 2628 patients were screened. Patients were considered for inclusion if they were 18 years of age or older and had at least 1 coronary artery stenosis of at least 20% on a clinically indicated catheterization. Additionally, the target vessel had to meet IVUS imaging quality and visibility standards. Participants were required to have been on stable statin therapy for at least 4 weeks with an LDL level of > 80 mg/dL or between 60–80 mg/dL with either 1 major or 3 minor cardiovascular risk factors. Major risk factors were noncoronary atherosclerotic disease, myocardial infarction (MI) or hospitalization for unstable angina within the past 2 years, or type 2 diabetes. Minor risk factors included current tobacco use, hypertension, low HDL-C levels, family history of early coronary disease, hsCRP level of 2 mg/L or greater, and age older than 50 years for men and 55 years for women. Patients with uncontrolled hypertension, uncontrolled diabetes, heart failure, renal insufficiency, or liver disease were excluded.

Intervention. Patients were randomized to either treatment with monthly subcutaneous injections of 420 mg evolocumab or placebo injections for 76 weeks. Participants attended 7 follow-up visits during the study period and then underwent repeat IVUS imaging at the 78th week. Research staff, who were blinded to both treatment status and imaging sequence, collected and assessed target vessel measurements, including the vessel lumen and external elastic membrane dimensions. IVUS imaging has been used in numerous clinical studies and has been shown to be accurate and reliable [1].

Main outcome measures. The primary outcome was the target artery change in percent atheroma volume (PAV) from baseline to week 78. PAV was calculated from IVUS measurements. Nominal change in PAV was then determined by calculating the difference of the PAV at baseline and at week 78.

The secondary measure was the normalized total atheroma volume (TAV). TAV addresses variability in the length of vessel segments and the number of images collected during IVUS catheter pullback. The nominal change in TAV was then determined by the difference at baseline and at week 78.

Additional secondary efficacy endpoints included number of patients with regression of plaque and change in lipid parameters. Safety outcomes were investigated through evaluation of the incidence of adjudicated clinical events, including all-cause mortality, cardiovascular death, MI, unstable angina requiring hospitalization, coronary revascularization, stroke, transient ischemic attack, and heart failure requiring hospitalization. Post-hoc analysis compared baseline LDL-C level and change in PAV and regression of PAV. The association between LDL lowering and plaque progression was also assessed post hoc.

IVUS measurements were evaluated as least squares means. Comparison of treatment groups was conducted using analysis of covariance on rank transformed data that accounted for baseline value and geographic location. Investigators used a step-down statistical procedure to evaluate primary and secondary endpoints. The statistical model accounted for confounders such as baseline LDL-C, baseline PAV, intensity of statin therapy, geographic region, age, and sex.

Main results. 484 participants were randomized to the evolocumab group and 484 to the placebo group, and 423 participants in both groups completed both baseline and follow-up IVUS imaging. Treatment and control groups contained participants matched for age, gender, ethnicity, cardiovascular risk factors, and baseline medication use, including lipid-lowering agents, ACE inhibitors, ARBs, beta-blockers, and antiplatelet therapies. Both groups consisted of a majority of white (93.4% in placebo and 94.2% in treatment) males (72.3% in placebo and 72.1% in treatment). Approximately 80% of participants had hypertension (83.7% in placebo and 82.2% in treatment), about 35% had prior MIs (35.3% in placebo and 34.9% in treatment), and roughly a fifth of participants had diabetes (21.5% in placebo and 20.2% in treatment). At baseline 98.6% of participants were treated with statins, with 58.9% on high-intensity therapy and 39.4% on moderate-intensity. Mean LDL-C level at baseline was 92.5 (SD, 27.2) mg/dL.

After 76 weeks of treatment, mean LDL-C level in the placebo group was 93.0 mg/dL and 36.6 mg/dL in the treatment group, which corresponds to a 0.2 mg/dL increase in the placebo group and a 56.3 mg/dL reduction in the treatment group. The change in LDL-C level was statistically significant (P < 0.001).

Placebo group participants had no significant change in PAV (0.05%, P = 0.78), but the evolocumab group experienced a 0.95% decrease from baseline (P < 0.001). Similarly, the placebo group had no change in TAV from baseline (–0.9 mm³, P = 0.45), but the treatment group had a 5.8 mm³ reduction in TAV from baseline (P < 0.001). The treatment group had a greater proportion of patients who experienced PAV regression (64.3% vs. 47.3%, P < 0.001) and TAV regression (61.5% vs. 48.9%, P < 0.001).

Subgroup analysis did not demonstrate a significant association between change in PAV and specific study participant characteristics (eg, age, gender, ethnicity).

Post-hoc analysis using local regression (LOESS) curve revealed a linear relationship between achieved LDL-C level and change in PAV for LDL-C levels from 110 mg/dL to 20 mg/dL.

The treatment group did not exhibit a significant increase in adverse drug events, which included injection site reactions, myalgias, neurocognitive events, and incidence of diabetes. There was no significant difference in adverse cardiovascular outcomes between groups; however, there were numerically fewer nonfatal MIs and coronary revascularizations in the treatment group.

Conclusion. The use of evolocumab in statin-treated patients resulted in greater reduction of PAV than use of statins alone.

Commentary

Evolocumab is a monoclonal antibody that inhibits pro-protein convertase subtilisin-kexin type 9 (PCSK9), which is involved in LDL-C receptor recycling. By reducing removal of LDL-C receptors, evolocumab amplifies LDL-C clearance and has been shown to reduce LDL-C levels by approximately 61% from baseline with 12 weeks oftreatment [2]. Studies have shown that the lipid-lowering potential of evolocumab is superior to statins alone and to combination therapy with statins and ezetimibe [2]. Furthermore, PCSK9 inhibitors have been effective at LDL-lowering in patients who failed or could not tolerate standard of care therapy with statins and ezetimibe [3,4]. PCSK9 inhibitors hold great promise for reducing morbidity and mortality of cardiovascular disease; however, LDL-lowering is not equivalent to improved clinical outcomes.

The GLAGOV study moves toward demonstration of the clinical benefit of evolocumab. The study shows that combined therapy with statins and evolocumab, versus statins alone, not only achieves better stability of atherosclerotic plaque dimensions but actually results in regression of plaque size. In the study, plaque burden is extrapolated from vessel measurements obtained through IVUS, and nominal changes in PAV and TAV serve as markers for atherosclerosis, but these surrogates cannot be equated to a reduction in cardiovascular events. The GLAGOV trial does explore clinical outcomes such as MI, stroke, unstable angina, coronary revascularization, and death; however, the study is not powered to evaluate the statistical significance of these events. We await sufficiently powered phase 3 clinical trials to determine the clinical benefits of PCSK9 inhibitors on cardiovascular disease.

The GLAGOV trial has several strengths, including its design as an international, double-blind, placebo-controlled, randomized clinical trial. The intervention is simple and the outcomes are clearly defined. The statistical assessment yields significant results. Nonetheless, there are multiple limitations to the study. The lead author has received research support from Amgen, the maker of evolocumab. Amgen also participated in study design and maintenance of trial databases; however, data analysis was conducted by an independent statistician. Additionally, the majority of study participants were white males with very few minority patients despite inclusion of study sites around the globe. The homogeneity of the study cohort makes the data difficult to generalize to a larger population. Similarly, patients who lacked a clinical indication for coronary catheterization and those with uncontrolled diabetes, hypertension, and heart failure were excluded, which further limits application of this study to many patients with atherosclerosis. Another limitation is study attrition; only 87% of participants completed the 78-week IVUS and were included in the data analysis, and results may have differed if those lost to follow-up had completed the trial. Furthermore, study duration was limited to 76 weeks and the magnitude and durability of study outcomes after this time point remain unknown.

Applications for Clinical Practice

Reduction in PAV and TAV are surrogate endpoints and are not indicative of a clinical benefit. Nonetheless, the GLAGOV study demonstrates that evolocumab, when used in conjunction with statins, can promote regression of atherosclerosis greater than treatment with statins alone. More studies are needed to evaluate a clinical benefit of adding evolocumab to the regularly used arsenal of lipid-lowering therapies for the treatment of atherosclerosis. Furthermore, cost-effectiveness of evolocumab has not been shown. In 2015 the yearly wholesale price of evolcumab was $14,350. A cost-effectiveness analysis based on this price estimates that treatment of atherosclerotic coronary vascular disease with evolocumab has a cost of $414,000 per quality-adjusted life year [5]. Evolocumab is well tolerated, but additional studies for cardiovascular and mortality outcomes are needed before it can be considered part of the standard of treatment for coronary artery disease.

—Lauren Brooks, MD, University of Maryland School of Medicine, Baltimore, MD

References

1. Nicholls SJ, Hsu A, Wolski K, et al. Intravascular ultrasound-derived measures of coronary atherosclerotic plaque burden and clinical outcome. J Am Coll Cardiol 2010;55:2399–407.

2. Sabatine MS, Giugliano RP, Wiviolt SD, et al. Efficacy and safety of evolocumab in reducing lipids and cardiovascular events. N Engl J Med 2015;372:1500–9.

3. Giugliano RP, Sabatine MS. Are PCSK9 inhibitors the next breakthrough in the cardiovascular field. J Am Coll Cardiol 2015;65:2639–51.

4. Stroes E, Colquhoun D, Sullivan D, et al. Anti-PCSK9 antibody effectively lowers cholesterol in patients with statin intolerance: the GAUSS-2 randomized, placebo-controlled phase 3 clinical trial of evolocumab. J Am Coll Cardiol 2014;63:2541–8.

5. Dhruv KS, Moran AE, Coxson PG, et al. Cost-effectiveness of PCSK9 inhibitor therapy in patients with heterozygous familial hypercholesterolemia or atherosclerotic coronary artery disease. JAMA 2016;316:743–53.

Study Overview

Objective. To determine if evolocumab, a PCSK9 inhibitor, affects the progression of coronary artery disease in patients treated with statins.

Design. Multicenter, international, double-blind, placebo-controlled, randomized clinical trial.

Setting and participants. 197 community and academic hospitals worldwide enrolled 978 participants who underwent serial intravascular ultrasounds (IVUS) to measure their burden of coronary atherosclerosis. A total of 2628 patients were screened. Patients were considered for inclusion if they were 18 years of age or older and had at least 1 coronary artery stenosis of at least 20% on a clinically indicated catheterization. Additionally, the target vessel had to meet IVUS imaging quality and visibility standards. Participants were required to have been on stable statin therapy for at least 4 weeks with an LDL level of > 80 mg/dL or between 60–80 mg/dL with either 1 major or 3 minor cardiovascular risk factors. Major risk factors were noncoronary atherosclerotic disease, myocardial infarction (MI) or hospitalization for unstable angina within the past 2 years, or type 2 diabetes. Minor risk factors included current tobacco use, hypertension, low HDL-C levels, family history of early coronary disease, hsCRP level of 2 mg/L or greater, and age older than 50 years for men and 55 years for women. Patients with uncontrolled hypertension, uncontrolled diabetes, heart failure, renal insufficiency, or liver disease were excluded.

Intervention. Patients were randomized to either treatment with monthly subcutaneous injections of 420 mg evolocumab or placebo injections for 76 weeks. Participants attended 7 follow-up visits during the study period and then underwent repeat IVUS imaging at the 78th week. Research staff, who were blinded to both treatment status and imaging sequence, collected and assessed target vessel measurements, including the vessel lumen and external elastic membrane dimensions. IVUS imaging has been used in numerous clinical studies and has been shown to be accurate and reliable [1].

Main outcome measures. The primary outcome was the target artery change in percent atheroma volume (PAV) from baseline to week 78. PAV was calculated from IVUS measurements. Nominal change in PAV was then determined by calculating the difference of the PAV at baseline and at week 78.

The secondary measure was the normalized total atheroma volume (TAV). TAV addresses variability in the length of vessel segments and the number of images collected during IVUS catheter pullback. The nominal change in TAV was then determined by the difference at baseline and at week 78.

Additional secondary efficacy endpoints included number of patients with regression of plaque and change in lipid parameters. Safety outcomes were investigated through evaluation of the incidence of adjudicated clinical events, including all-cause mortality, cardiovascular death, MI, unstable angina requiring hospitalization, coronary revascularization, stroke, transient ischemic attack, and heart failure requiring hospitalization. Post-hoc analysis compared baseline LDL-C level and change in PAV and regression of PAV. The association between LDL lowering and plaque progression was also assessed post hoc.

IVUS measurements were evaluated as least squares means. Comparison of treatment groups was conducted using analysis of covariance on rank transformed data that accounted for baseline value and geographic location. Investigators used a step-down statistical procedure to evaluate primary and secondary endpoints. The statistical model accounted for confounders such as baseline LDL-C, baseline PAV, intensity of statin therapy, geographic region, age, and sex.

Main results. 484 participants were randomized to the evolocumab group and 484 to the placebo group, and 423 participants in both groups completed both baseline and follow-up IVUS imaging. Treatment and control groups contained participants matched for age, gender, ethnicity, cardiovascular risk factors, and baseline medication use, including lipid-lowering agents, ACE inhibitors, ARBs, beta-blockers, and antiplatelet therapies. Both groups consisted of a majority of white (93.4% in placebo and 94.2% in treatment) males (72.3% in placebo and 72.1% in treatment). Approximately 80% of participants had hypertension (83.7% in placebo and 82.2% in treatment), about 35% had prior MIs (35.3% in placebo and 34.9% in treatment), and roughly a fifth of participants had diabetes (21.5% in placebo and 20.2% in treatment). At baseline 98.6% of participants were treated with statins, with 58.9% on high-intensity therapy and 39.4% on moderate-intensity. Mean LDL-C level at baseline was 92.5 (SD, 27.2) mg/dL.

After 76 weeks of treatment, mean LDL-C level in the placebo group was 93.0 mg/dL and 36.6 mg/dL in the treatment group, which corresponds to a 0.2 mg/dL increase in the placebo group and a 56.3 mg/dL reduction in the treatment group. The change in LDL-C level was statistically significant (P < 0.001).

Placebo group participants had no significant change in PAV (0.05%, P = 0.78), but the evolocumab group experienced a 0.95% decrease from baseline (P < 0.001). Similarly, the placebo group had no change in TAV from baseline (–0.9 mm³, P = 0.45), but the treatment group had a 5.8 mm³ reduction in TAV from baseline (P < 0.001). The treatment group had a greater proportion of patients who experienced PAV regression (64.3% vs. 47.3%, P < 0.001) and TAV regression (61.5% vs. 48.9%, P < 0.001).

Subgroup analysis did not demonstrate a significant association between change in PAV and specific study participant characteristics (eg, age, gender, ethnicity).

Post-hoc analysis using local regression (LOESS) curve revealed a linear relationship between achieved LDL-C level and change in PAV for LDL-C levels from 110 mg/dL to 20 mg/dL.

The treatment group did not exhibit a significant increase in adverse drug events, which included injection site reactions, myalgias, neurocognitive events, and incidence of diabetes. There was no significant difference in adverse cardiovascular outcomes between groups; however, there were numerically fewer nonfatal MIs and coronary revascularizations in the treatment group.

Conclusion. The use of evolocumab in statin-treated patients resulted in greater reduction of PAV than use of statins alone.

Commentary

Evolocumab is a monoclonal antibody that inhibits pro-protein convertase subtilisin-kexin type 9 (PCSK9), which is involved in LDL-C receptor recycling. By reducing removal of LDL-C receptors, evolocumab amplifies LDL-C clearance and has been shown to reduce LDL-C levels by approximately 61% from baseline with 12 weeks oftreatment [2]. Studies have shown that the lipid-lowering potential of evolocumab is superior to statins alone and to combination therapy with statins and ezetimibe [2]. Furthermore, PCSK9 inhibitors have been effective at LDL-lowering in patients who failed or could not tolerate standard of care therapy with statins and ezetimibe [3,4]. PCSK9 inhibitors hold great promise for reducing morbidity and mortality of cardiovascular disease; however, LDL-lowering is not equivalent to improved clinical outcomes.

The GLAGOV study moves toward demonstration of the clinical benefit of evolocumab. The study shows that combined therapy with statins and evolocumab, versus statins alone, not only achieves better stability of atherosclerotic plaque dimensions but actually results in regression of plaque size. In the study, plaque burden is extrapolated from vessel measurements obtained through IVUS, and nominal changes in PAV and TAV serve as markers for atherosclerosis, but these surrogates cannot be equated to a reduction in cardiovascular events. The GLAGOV trial does explore clinical outcomes such as MI, stroke, unstable angina, coronary revascularization, and death; however, the study is not powered to evaluate the statistical significance of these events. We await sufficiently powered phase 3 clinical trials to determine the clinical benefits of PCSK9 inhibitors on cardiovascular disease.

The GLAGOV trial has several strengths, including its design as an international, double-blind, placebo-controlled, randomized clinical trial. The intervention is simple and the outcomes are clearly defined. The statistical assessment yields significant results. Nonetheless, there are multiple limitations to the study. The lead author has received research support from Amgen, the maker of evolocumab. Amgen also participated in study design and maintenance of trial databases; however, data analysis was conducted by an independent statistician. Additionally, the majority of study participants were white males with very few minority patients despite inclusion of study sites around the globe. The homogeneity of the study cohort makes the data difficult to generalize to a larger population. Similarly, patients who lacked a clinical indication for coronary catheterization and those with uncontrolled diabetes, hypertension, and heart failure were excluded, which further limits application of this study to many patients with atherosclerosis. Another limitation is study attrition; only 87% of participants completed the 78-week IVUS and were included in the data analysis, and results may have differed if those lost to follow-up had completed the trial. Furthermore, study duration was limited to 76 weeks and the magnitude and durability of study outcomes after this time point remain unknown.

Applications for Clinical Practice

Reduction in PAV and TAV are surrogate endpoints and are not indicative of a clinical benefit. Nonetheless, the GLAGOV study demonstrates that evolocumab, when used in conjunction with statins, can promote regression of atherosclerosis greater than treatment with statins alone. More studies are needed to evaluate a clinical benefit of adding evolocumab to the regularly used arsenal of lipid-lowering therapies for the treatment of atherosclerosis. Furthermore, cost-effectiveness of evolocumab has not been shown. In 2015 the yearly wholesale price of evolcumab was $14,350. A cost-effectiveness analysis based on this price estimates that treatment of atherosclerotic coronary vascular disease with evolocumab has a cost of $414,000 per quality-adjusted life year [5]. Evolocumab is well tolerated, but additional studies for cardiovascular and mortality outcomes are needed before it can be considered part of the standard of treatment for coronary artery disease.

—Lauren Brooks, MD, University of Maryland School of Medicine, Baltimore, MD

Study Overview

Objective. To determine if evolocumab, a PCSK9 inhibitor, affects the progression of coronary artery disease in patients treated with statins.

Design. Multicenter, international, double-blind, placebo-controlled, randomized clinical trial.

Setting and participants. 197 community and academic hospitals worldwide enrolled 978 participants who underwent serial intravascular ultrasounds (IVUS) to measure their burden of coronary atherosclerosis. A total of 2628 patients were screened. Patients were considered for inclusion if they were 18 years of age or older and had at least 1 coronary artery stenosis of at least 20% on a clinically indicated catheterization. Additionally, the target vessel had to meet IVUS imaging quality and visibility standards. Participants were required to have been on stable statin therapy for at least 4 weeks with an LDL level of > 80 mg/dL or between 60–80 mg/dL with either 1 major or 3 minor cardiovascular risk factors. Major risk factors were noncoronary atherosclerotic disease, myocardial infarction (MI) or hospitalization for unstable angina within the past 2 years, or type 2 diabetes. Minor risk factors included current tobacco use, hypertension, low HDL-C levels, family history of early coronary disease, hsCRP level of 2 mg/L or greater, and age older than 50 years for men and 55 years for women. Patients with uncontrolled hypertension, uncontrolled diabetes, heart failure, renal insufficiency, or liver disease were excluded.

Intervention. Patients were randomized to either treatment with monthly subcutaneous injections of 420 mg evolocumab or placebo injections for 76 weeks. Participants attended 7 follow-up visits during the study period and then underwent repeat IVUS imaging at the 78th week. Research staff, who were blinded to both treatment status and imaging sequence, collected and assessed target vessel measurements, including the vessel lumen and external elastic membrane dimensions. IVUS imaging has been used in numerous clinical studies and has been shown to be accurate and reliable [1].

Main outcome measures. The primary outcome was the target artery change in percent atheroma volume (PAV) from baseline to week 78. PAV was calculated from IVUS measurements. Nominal change in PAV was then determined by calculating the difference of the PAV at baseline and at week 78.

The secondary measure was the normalized total atheroma volume (TAV). TAV addresses variability in the length of vessel segments and the number of images collected during IVUS catheter pullback. The nominal change in TAV was then determined by the difference at baseline and at week 78.

Additional secondary efficacy endpoints included number of patients with regression of plaque and change in lipid parameters. Safety outcomes were investigated through evaluation of the incidence of adjudicated clinical events, including all-cause mortality, cardiovascular death, MI, unstable angina requiring hospitalization, coronary revascularization, stroke, transient ischemic attack, and heart failure requiring hospitalization. Post-hoc analysis compared baseline LDL-C level and change in PAV and regression of PAV. The association between LDL lowering and plaque progression was also assessed post hoc.

IVUS measurements were evaluated as least squares means. Comparison of treatment groups was conducted using analysis of covariance on rank transformed data that accounted for baseline value and geographic location. Investigators used a step-down statistical procedure to evaluate primary and secondary endpoints. The statistical model accounted for confounders such as baseline LDL-C, baseline PAV, intensity of statin therapy, geographic region, age, and sex.

Main results. 484 participants were randomized to the evolocumab group and 484 to the placebo group, and 423 participants in both groups completed both baseline and follow-up IVUS imaging. Treatment and control groups contained participants matched for age, gender, ethnicity, cardiovascular risk factors, and baseline medication use, including lipid-lowering agents, ACE inhibitors, ARBs, beta-blockers, and antiplatelet therapies. Both groups consisted of a majority of white (93.4% in placebo and 94.2% in treatment) males (72.3% in placebo and 72.1% in treatment). Approximately 80% of participants had hypertension (83.7% in placebo and 82.2% in treatment), about 35% had prior MIs (35.3% in placebo and 34.9% in treatment), and roughly a fifth of participants had diabetes (21.5% in placebo and 20.2% in treatment). At baseline 98.6% of participants were treated with statins, with 58.9% on high-intensity therapy and 39.4% on moderate-intensity. Mean LDL-C level at baseline was 92.5 (SD, 27.2) mg/dL.

After 76 weeks of treatment, mean LDL-C level in the placebo group was 93.0 mg/dL and 36.6 mg/dL in the treatment group, which corresponds to a 0.2 mg/dL increase in the placebo group and a 56.3 mg/dL reduction in the treatment group. The change in LDL-C level was statistically significant (P < 0.001).

Placebo group participants had no significant change in PAV (0.05%, P = 0.78), but the evolocumab group experienced a 0.95% decrease from baseline (P < 0.001). Similarly, the placebo group had no change in TAV from baseline (–0.9 mm³, P = 0.45), but the treatment group had a 5.8 mm³ reduction in TAV from baseline (P < 0.001). The treatment group had a greater proportion of patients who experienced PAV regression (64.3% vs. 47.3%, P < 0.001) and TAV regression (61.5% vs. 48.9%, P < 0.001).

Subgroup analysis did not demonstrate a significant association between change in PAV and specific study participant characteristics (eg, age, gender, ethnicity).

Post-hoc analysis using local regression (LOESS) curve revealed a linear relationship between achieved LDL-C level and change in PAV for LDL-C levels from 110 mg/dL to 20 mg/dL.

The treatment group did not exhibit a significant increase in adverse drug events, which included injection site reactions, myalgias, neurocognitive events, and incidence of diabetes. There was no significant difference in adverse cardiovascular outcomes between groups; however, there were numerically fewer nonfatal MIs and coronary revascularizations in the treatment group.

Conclusion. The use of evolocumab in statin-treated patients resulted in greater reduction of PAV than use of statins alone.

Commentary

Evolocumab is a monoclonal antibody that inhibits pro-protein convertase subtilisin-kexin type 9 (PCSK9), which is involved in LDL-C receptor recycling. By reducing removal of LDL-C receptors, evolocumab amplifies LDL-C clearance and has been shown to reduce LDL-C levels by approximately 61% from baseline with 12 weeks oftreatment [2]. Studies have shown that the lipid-lowering potential of evolocumab is superior to statins alone and to combination therapy with statins and ezetimibe [2]. Furthermore, PCSK9 inhibitors have been effective at LDL-lowering in patients who failed or could not tolerate standard of care therapy with statins and ezetimibe [3,4]. PCSK9 inhibitors hold great promise for reducing morbidity and mortality of cardiovascular disease; however, LDL-lowering is not equivalent to improved clinical outcomes.

The GLAGOV study moves toward demonstration of the clinical benefit of evolocumab. The study shows that combined therapy with statins and evolocumab, versus statins alone, not only achieves better stability of atherosclerotic plaque dimensions but actually results in regression of plaque size. In the study, plaque burden is extrapolated from vessel measurements obtained through IVUS, and nominal changes in PAV and TAV serve as markers for atherosclerosis, but these surrogates cannot be equated to a reduction in cardiovascular events. The GLAGOV trial does explore clinical outcomes such as MI, stroke, unstable angina, coronary revascularization, and death; however, the study is not powered to evaluate the statistical significance of these events. We await sufficiently powered phase 3 clinical trials to determine the clinical benefits of PCSK9 inhibitors on cardiovascular disease.

The GLAGOV trial has several strengths, including its design as an international, double-blind, placebo-controlled, randomized clinical trial. The intervention is simple and the outcomes are clearly defined. The statistical assessment yields significant results. Nonetheless, there are multiple limitations to the study. The lead author has received research support from Amgen, the maker of evolocumab. Amgen also participated in study design and maintenance of trial databases; however, data analysis was conducted by an independent statistician. Additionally, the majority of study participants were white males with very few minority patients despite inclusion of study sites around the globe. The homogeneity of the study cohort makes the data difficult to generalize to a larger population. Similarly, patients who lacked a clinical indication for coronary catheterization and those with uncontrolled diabetes, hypertension, and heart failure were excluded, which further limits application of this study to many patients with atherosclerosis. Another limitation is study attrition; only 87% of participants completed the 78-week IVUS and were included in the data analysis, and results may have differed if those lost to follow-up had completed the trial. Furthermore, study duration was limited to 76 weeks and the magnitude and durability of study outcomes after this time point remain unknown.

Applications for Clinical Practice

Reduction in PAV and TAV are surrogate endpoints and are not indicative of a clinical benefit. Nonetheless, the GLAGOV study demonstrates that evolocumab, when used in conjunction with statins, can promote regression of atherosclerosis greater than treatment with statins alone. More studies are needed to evaluate a clinical benefit of adding evolocumab to the regularly used arsenal of lipid-lowering therapies for the treatment of atherosclerosis. Furthermore, cost-effectiveness of evolocumab has not been shown. In 2015 the yearly wholesale price of evolcumab was $14,350. A cost-effectiveness analysis based on this price estimates that treatment of atherosclerotic coronary vascular disease with evolocumab has a cost of $414,000 per quality-adjusted life year [5]. Evolocumab is well tolerated, but additional studies for cardiovascular and mortality outcomes are needed before it can be considered part of the standard of treatment for coronary artery disease.

—Lauren Brooks, MD, University of Maryland School of Medicine, Baltimore, MD

Study Overview

Objective. To determine if evolocumab, a PCSK9 inhibitor, affects the progression of coronary artery disease in patients treated with statins.

Design. Multicenter, international, double-blind, placebo-controlled, randomized clinical trial.

Setting and participants. 197 community and academic hospitals worldwide enrolled 978 participants who underwent serial intravascular ultrasounds (IVUS) to measure their burden of coronary atherosclerosis. A total of 2628 patients were screened. Patients were considered for inclusion if they were 18 years of age or older and had at least 1 coronary artery stenosis of at least 20% on a clinically indicated catheterization. Additionally, the target vessel had to meet IVUS imaging quality and visibility standards. Participants were required to have been on stable statin therapy for at least 4 weeks with an LDL level of > 80 mg/dL or between 60–80 mg/dL with either 1 major or 3 minor cardiovascular risk factors. Major risk factors were noncoronary atherosclerotic disease, myocardial infarction (MI) or hospitalization for unstable angina within the past 2 years, or type 2 diabetes. Minor risk factors included current tobacco use, hypertension, low HDL-C levels, family history of early coronary disease, hsCRP level of 2 mg/L or greater, and age older than 50 years for men and 55 years for women. Patients with uncontrolled hypertension, uncontrolled diabetes, heart failure, renal insufficiency, or liver disease were excluded.

Intervention. Patients were randomized to either treatment with monthly subcutaneous injections of 420 mg evolocumab or placebo injections for 76 weeks. Participants attended 7 follow-up visits during the study period and then underwent repeat IVUS imaging at the 78th week. Research staff, who were blinded to both treatment status and imaging sequence, collected and assessed target vessel measurements, including the vessel lumen and external elastic membrane dimensions. IVUS imaging has been used in numerous clinical studies and has been shown to be accurate and reliable [1].

Main outcome measures. The primary outcome was the target artery change in percent atheroma volume (PAV) from baseline to week 78. PAV was calculated from IVUS measurements. Nominal change in PAV was then determined by calculating the difference of the PAV at baseline and at week 78.

The secondary measure was the normalized total atheroma volume (TAV). TAV addresses variability in the length of vessel segments and the number of images collected during IVUS catheter pullback. The nominal change in TAV was then determined by the difference at baseline and at week 78.

Additional secondary efficacy endpoints included number of patients with regression of plaque and change in lipid parameters. Safety outcomes were investigated through evaluation of the incidence of adjudicated clinical events, including all-cause mortality, cardiovascular death, MI, unstable angina requiring hospitalization, coronary revascularization, stroke, transient ischemic attack, and heart failure requiring hospitalization. Post-hoc analysis compared baseline LDL-C level and change in PAV and regression of PAV. The association between LDL lowering and plaque progression was also assessed post hoc.

IVUS measurements were evaluated as least squares means. Comparison of treatment groups was conducted using analysis of covariance on rank transformed data that accounted for baseline value and geographic location. Investigators used a step-down statistical procedure to evaluate primary and secondary endpoints. The statistical model accounted for confounders such as baseline LDL-C, baseline PAV, intensity of statin therapy, geographic region, age, and sex.

Main results. 484 participants were randomized to the evolocumab group and 484 to the placebo group, and 423 participants in both groups completed both baseline and follow-up IVUS imaging. Treatment and control groups contained participants matched for age, gender, ethnicity, cardiovascular risk factors, and baseline medication use, including lipid-lowering agents, ACE inhibitors, ARBs, beta-blockers, and antiplatelet therapies. Both groups consisted of a majority of white (93.4% in placebo and 94.2% in treatment) males (72.3% in placebo and 72.1% in treatment). Approximately 80% of participants had hypertension (83.7% in placebo and 82.2% in treatment), about 35% had prior MIs (35.3% in placebo and 34.9% in treatment), and roughly a fifth of participants had diabetes (21.5% in placebo and 20.2% in treatment). At baseline 98.6% of participants were treated with statins, with 58.9% on high-intensity therapy and 39.4% on moderate-intensity. Mean LDL-C level at baseline was 92.5 (SD, 27.2) mg/dL.

After 76 weeks of treatment, mean LDL-C level in the placebo group was 93.0 mg/dL and 36.6 mg/dL in the treatment group, which corresponds to a 0.2 mg/dL increase in the placebo group and a 56.3 mg/dL reduction in the treatment group. The change in LDL-C level was statistically significant (P < 0.001).

Placebo group participants had no significant change in PAV (0.05%, P = 0.78), but the evolocumab group experienced a 0.95% decrease from baseline (P < 0.001). Similarly, the placebo group had no change in TAV from baseline (–0.9 mm³, P = 0.45), but the treatment group had a 5.8 mm³ reduction in TAV from baseline (P < 0.001). The treatment group had a greater proportion of patients who experienced PAV regression (64.3% vs. 47.3%, P < 0.001) and TAV regression (61.5% vs. 48.9%, P < 0.001).

Subgroup analysis did not demonstrate a significant association between change in PAV and specific study participant characteristics (eg, age, gender, ethnicity).

Post-hoc analysis using local regression (LOESS) curve revealed a linear relationship between achieved LDL-C level and change in PAV for LDL-C levels from 110 mg/dL to 20 mg/dL.

The treatment group did not exhibit a significant increase in adverse drug events, which included injection site reactions, myalgias, neurocognitive events, and incidence of diabetes. There was no significant difference in adverse cardiovascular outcomes between groups; however, there were numerically fewer nonfatal MIs and coronary revascularizations in the treatment group.

Conclusion. The use of evolocumab in statin-treated patients resulted in greater reduction of PAV than use of statins alone.

Commentary

Evolocumab is a monoclonal antibody that inhibits pro-protein convertase subtilisin-kexin type 9 (PCSK9), which is involved in LDL-C receptor recycling. By reducing removal of LDL-C receptors, evolocumab amplifies LDL-C clearance and has been shown to reduce LDL-C levels by approximately 61% from baseline with 12 weeks oftreatment [2]. Studies have shown that the lipid-lowering potential of evolocumab is superior to statins alone and to combination therapy with statins and ezetimibe [2]. Furthermore, PCSK9 inhibitors have been effective at LDL-lowering in patients who failed or could not tolerate standard of care therapy with statins and ezetimibe [3,4]. PCSK9 inhibitors hold great promise for reducing morbidity and mortality of cardiovascular disease; however, LDL-lowering is not equivalent to improved clinical outcomes.

The GLAGOV study moves toward demonstration of the clinical benefit of evolocumab. The study shows that combined therapy with statins and evolocumab, versus statins alone, not only achieves better stability of atherosclerotic plaque dimensions but actually results in regression of plaque size. In the study, plaque burden is extrapolated from vessel measurements obtained through IVUS, and nominal changes in PAV and TAV serve as markers for atherosclerosis, but these surrogates cannot be equated to a reduction in cardiovascular events. The GLAGOV trial does explore clinical outcomes such as MI, stroke, unstable angina, coronary revascularization, and death; however, the study is not powered to evaluate the statistical significance of these events. We await sufficiently powered phase 3 clinical trials to determine the clinical benefits of PCSK9 inhibitors on cardiovascular disease.

The GLAGOV trial has several strengths, including its design as an international, double-blind, placebo-controlled, randomized clinical trial. The intervention is simple and the outcomes are clearly defined. The statistical assessment yields significant results. Nonetheless, there are multiple limitations to the study. The lead author has received research support from Amgen, the maker of evolocumab. Amgen also participated in study design and maintenance of trial databases; however, data analysis was conducted by an independent statistician. Additionally, the majority of study participants were white males with very few minority patients despite inclusion of study sites around the globe. The homogeneity of the study cohort makes the data difficult to generalize to a larger population. Similarly, patients who lacked a clinical indication for coronary catheterization and those with uncontrolled diabetes, hypertension, and heart failure were excluded, which further limits application of this study to many patients with atherosclerosis. Another limitation is study attrition; only 87% of participants completed the 78-week IVUS and were included in the data analysis, and results may have differed if those lost to follow-up had completed the trial. Furthermore, study duration was limited to 76 weeks and the magnitude and durability of study outcomes after this time point remain unknown.

Applications for Clinical Practice

Reduction in PAV and TAV are surrogate endpoints and are not indicative of a clinical benefit. Nonetheless, the GLAGOV study demonstrates that evolocumab, when used in conjunction with statins, can promote regression of atherosclerosis greater than treatment with statins alone. More studies are needed to evaluate a clinical benefit of adding evolocumab to the regularly used arsenal of lipid-lowering therapies for the treatment of atherosclerosis. Furthermore, cost-effectiveness of evolocumab has not been shown. In 2015 the yearly wholesale price of evolcumab was $14,350. A cost-effectiveness analysis based on this price estimates that treatment of atherosclerotic coronary vascular disease with evolocumab has a cost of $414,000 per quality-adjusted life year [5]. Evolocumab is well tolerated, but additional studies for cardiovascular and mortality outcomes are needed before it can be considered part of the standard of treatment for coronary artery disease.

—Lauren Brooks, MD, University of Maryland School of Medicine, Baltimore, MD

Study Overview

Objective. To compare patients’ health care experiences related to their weight across racial and ethnic groups.

Design. Cross-sectional survey-based study.

Setting and participants. Between March and July 2015, 5400 individuals were randomly sampled from the Patient Outcomes to Advance Learning (PORTAL) obesity cohort, which includes over 5 million adults. The PORTAL network is a clinical data research network funded by the Patient Centered Outcomes Research Institute to promote collaboration across several large health systems with electronic medical records (EMRs), including all the Kaiser Permanente regions, Group Health Cooperative, Health Partners, and Denver Health. The selected 5400 cohort members were equally distributed across 3 geographically diverse Kaiser Permanente regions (Southwest, Northern and Southern California, Hawaii, Colorado, and Northwest) and Denver sites. Selected individuals were non-pregnant English or Spanish speakers with a body mass index (BMI) ≥ 25 kg/m² (per their EMR) who were members of a participating health plan and had at least 1 outpatient visit in the last 12 months. Patients with BMI ≥ 40 kg/m² were oversampled. Individuals were mailed a written 10-minute survey (offered in English or Spanish based on a patient’s written language preference noted in their EMR), consisting of 36 multiple-choice and fill-in-the-blank items. Telephone contact for verbal administration was attempted if a mailed response was not received within 4 weeks.

Main measures and analysis. The primary independent variable was a respondent’s racial/ethnic group, categorized as (1) non-Hispanic white (White), 2) non-Hispanic black (Black), 3) Hispanic, 4) Asian, or 5) Native Hawaiian/Other Pacific Islanders/American Indian/Native Alaskan (NA/PI).

Dependent variables focused on patients’ perceptions of the health care experience (based on services received at their usual place of care from their primary care providers) related to being overweight or obese using items based on the Rudd Center’s Patient Survey of Weight-Sensitive Healthcare Practices. Respondents described (1) whether and how often they avoid coming to their provider because they do not want to be weighed or have a discussion about their weight; (2) how often does their provider ask their permission before discussion their weight; (3) how often has their provider been supportive of their weight concerns and efforts to be healthy; (4) whether they think that their provider understands the physical and emotional challenges faced by individuals who are overweight or obese; (5) how often has their provider brought up their weight during a clinic visit; (6) whether their provider has ever given or discussed resources on healthy eating and weight loss; and (7) what types of weight loss resources were discussed with their provider and which types did they want more information about (ie, dietary changes, physical activity, classes, medications, meal replacements, and bariatric surgery). Covariate variables derived from EMR data included sex, age category, diabetes, hypertension, Charlson Index score (overall measures of morbidity), Medicaid enrollment, language preferences, site, and BMI. Survey-derived covariate variables included emotional well-being, perceived weight status, and educational attainment.

Descriptive statistics were generated and compared across racial/ethnic groups using Kruskal-Wallis and chi-square testing, as appropriate. To evaluate the association between a patient’s race/ethnicity and their perceived weight management experience, multinomial logistic regression adjusted for covariates was used to estimate odds ratios (OR).

Main results. From the original sample (n = 5400), 1569 individuals (29%) did not respond, 925 (17%) refused, and 114 (2%) were ineligible, leaving an eligible sample pool of 5286 individuals. The overall response rate was 53% (2197 written; 614 phone, n = 2811). Those with missing data were excluded (6 with missing race/ethnicity; 80 missing other covariates), leaving a final group of 2725 respondents for analysis. Mean age was 52.7 years (SD 15), almost 62% of participants were female, 51.7% identified as White, 21.1% identified as Black, 14.6% identified as Hispanic, 5.8% identified as Asian, and 6.7% identified as NA/PI. About a quarter (24.4%) had diabetes, less than half (43.5%) had hypertension, and most (86.2%) perceived themselves to be overweight. There were significant differences in measured baseline covariates by racial/ethnic groups including mean BMI, diabetes, and being a Medicaid beneficiary.

In response to the 7 key areas assessed regarding patients’ perceptions of the health care experience related to being overweight or obese:

• Black respondents were less likely than Whites to report that they frequently avoided care from their provider because they did not want to be weighed or discuss their weight (OR 0.49 [95% confidence interval, 0.26–0.90]), with a trend toward all groups being less likely to report frequent avoidance compared to Whites.
• While just over half of respondents (59.3%) indicated that their providers never asked for their permission before discussing their weight, Asians and NA/PI were more likely to report that their providers either frequently (Asians: OR 2.7 [1.3–5.6]; NA/PI: OR 2.3 [1.1–5.0]) or sometimes (Asians: OR 2.3 [1.2–4.3]; NA/PI: OR 2.1 [1.1–4.1]) asked their permission before discussing their weight compared to Whites.
• Over half (61.9%) indicated that their providers were sometimes or frequently supportive of their weight concerns, with no significant differences among racial/ethnic groups.
• Just over half (52.0%) indicated they felt their providers understood the physical and emotional challenges faced by people who are overweight/obese, with Blacks more likely to feel this way (OR 1.8 [1.2–2.8]) compared to Whites.
• Black patients were more likely than Whites (OR 2.0 [1.4–2.8]) to report that their providers discussed their weight with them at a clinic visit.
• While over half (59.7%) indicated that their providers had given or discussed resources with them on healthy eating and weight loss, Black and Asian respondents were more likely than Whites to recall these discussions (Black: OR 1.6 [1.2–2.1]; Asians: OR 1.8 [1.1–2.9]).
• Most weight loss resources or recommendations received were related to lifestyle changes, with very few resources given related to weight loss medications, meal replacement products, or bariatric surgery—few differences across racial/ethnic groups were identified. However, respondents from racial/ethnic minority groups were more likely than Whites to say that they wanted more information about lifestyle changes, classes, and meal replacements. Other than Blacks, all other racial/ethnic groups were also more likely than Whites to indicate that they wanted more information about bariatric surgery.

Conclusions. Most patients across racial/ethnic groups are having positive experiences with weight-related care. However, race/ethnicity correlates with patients’ perception of weight-related care and discussions in clinic encounters.

Commentary

The obesity epidemic in the United States is well-established [1], and recent data from 2014 show that over 37% of adults in the US are obese (defined as having a body mass index greater than 30 kg/m²) [2]. However, while obesity prevalence rates have increased over the past several decades across all genders, ethnicities, income levels, and education levels, important racial/ethnic disparities exist [2,3]. Primary care physicians (PCPs) are ideally situated to promote weight loss via effective obesity counseling since multiple clinic visits over time have the potential to enable rapport building and behavioral change management [4]. In fact, the US Preventive Services Task Force (USPTF) recommends that all patients be screened for obesity and offered intensive lifestyle counseling, as modest weight loss can have significant health benefits [5]. However, some studies have found racial/ethnic differences and disparities in weight-related diagnoses, counseling, and treatment by providers, but also patient perceptions of care and preferred interventions [6–10]. Other studies have described racial/ethnic differences in weight-related concerns and behaviors, body satisfaction, and body image [11–13]. Thus, research is needed to examine these differences.

This cross-sectional study contributes to the limited literature examining the potential for heterogeneity of care according to patient characteristics like race and ethnicity. Key strengths of the design include a large and both geographically and racially/ethnically diverse sample of patients (increased generalizability), the use of mailed brief surveys (reduces non-response rate and reporting bias) and telephone follow-up for verbal administration (reduces non-response rate, though it increases interviewer bias), oversampling of respondents with BMI ≥ 40 kg/m², and the controlling of key covariates including sex, age, Medicaid enrollment, site, and BMI.

However, there are several important limitations, many of which are acknowledged by the authors. While respondents were overall representative of the targeted sample population, the final respondent population was comprised of mostly older females who received managed care, which may have contributed to selection bias and impacted generalizability of findings. Further, Whites were overrepresented, Hispanics were underrepresented, and the small combined sample of NA/PI may have masked important distinctions between these subpopulations. Importantly, this study only provided the survey in English and Spanish and did not include other language translations (eg, Chinese, Japanese, Tagalog), which likely contributed to underrepresented perspectives of immigrants and ESL patients who may struggle with receiving/discussing weight management counseling and resources. The use of a surveys collected subjective and self-reported data on patient encounters as opposed to objective observations. Lastly, the study did not adjust for individual provider factors or assess the potential impact of provider-level differences on care, such as provider-patient concordance on race, ethnicity, language, and/or weight. The incorporation of qualitative interviewers or focus groups with a subsample of each racial/ethnic may have also provided relevant context to understand differences in weight-related care experiences.

Applications for Clinical Practice

As the authors suggest, this study highlights several opportunities to continue improving weight-related care and weight management counseling. PCPs should engage all overweight/obese patients in weight management discussions, and in particular, high-risk minority patients who may desire these conversations and more weight loss advice and resources. However, these discussions require sensitivity and can benefit from the simple practice of asking permission of the patient to talk about their weight in order to reduce care avoidance and improve perceptions of care. Providers should also be mindful of patient priorities and assess patient preferences for all the different weight loss strategies, including lifestyle changes, meal replacements, medications, and surgery.

—Katrina F. Mateo, MPH

Study Overview

Objective. To compare patients’ health care experiences related to their weight across racial and ethnic groups.

Design. Cross-sectional survey-based study.

Setting and participants. Between March and July 2015, 5400 individuals were randomly sampled from the Patient Outcomes to Advance Learning (PORTAL) obesity cohort, which includes over 5 million adults. The PORTAL network is a clinical data research network funded by the Patient Centered Outcomes Research Institute to promote collaboration across several large health systems with electronic medical records (EMRs), including all the Kaiser Permanente regions, Group Health Cooperative, Health Partners, and Denver Health. The selected 5400 cohort members were equally distributed across 3 geographically diverse Kaiser Permanente regions (Southwest, Northern and Southern California, Hawaii, Colorado, and Northwest) and Denver sites. Selected individuals were non-pregnant English or Spanish speakers with a body mass index (BMI) ≥ 25 kg/m² (per their EMR) who were members of a participating health plan and had at least 1 outpatient visit in the last 12 months. Patients with BMI ≥ 40 kg/m² were oversampled. Individuals were mailed a written 10-minute survey (offered in English or Spanish based on a patient’s written language preference noted in their EMR), consisting of 36 multiple-choice and fill-in-the-blank items. Telephone contact for verbal administration was attempted if a mailed response was not received within 4 weeks.

Main measures and analysis. The primary independent variable was a respondent’s racial/ethnic group, categorized as (1) non-Hispanic white (White), 2) non-Hispanic black (Black), 3) Hispanic, 4) Asian, or 5) Native Hawaiian/Other Pacific Islanders/American Indian/Native Alaskan (NA/PI).

Dependent variables focused on patients’ perceptions of the health care experience (based on services received at their usual place of care from their primary care providers) related to being overweight or obese using items based on the Rudd Center’s Patient Survey of Weight-Sensitive Healthcare Practices. Respondents described (1) whether and how often they avoid coming to their provider because they do not want to be weighed or have a discussion about their weight; (2) how often does their provider ask their permission before discussion their weight; (3) how often has their provider been supportive of their weight concerns and efforts to be healthy; (4) whether they think that their provider understands the physical and emotional challenges faced by individuals who are overweight or obese; (5) how often has their provider brought up their weight during a clinic visit; (6) whether their provider has ever given or discussed resources on healthy eating and weight loss; and (7) what types of weight loss resources were discussed with their provider and which types did they want more information about (ie, dietary changes, physical activity, classes, medications, meal replacements, and bariatric surgery). Covariate variables derived from EMR data included sex, age category, diabetes, hypertension, Charlson Index score (overall measures of morbidity), Medicaid enrollment, language preferences, site, and BMI. Survey-derived covariate variables included emotional well-being, perceived weight status, and educational attainment.

Descriptive statistics were generated and compared across racial/ethnic groups using Kruskal-Wallis and chi-square testing, as appropriate. To evaluate the association between a patient’s race/ethnicity and their perceived weight management experience, multinomial logistic regression adjusted for covariates was used to estimate odds ratios (OR).

Main results. From the original sample (n = 5400), 1569 individuals (29%) did not respond, 925 (17%) refused, and 114 (2%) were ineligible, leaving an eligible sample pool of 5286 individuals. The overall response rate was 53% (2197 written; 614 phone, n = 2811). Those with missing data were excluded (6 with missing race/ethnicity; 80 missing other covariates), leaving a final group of 2725 respondents for analysis. Mean age was 52.7 years (SD 15), almost 62% of participants were female, 51.7% identified as White, 21.1% identified as Black, 14.6% identified as Hispanic, 5.8% identified as Asian, and 6.7% identified as NA/PI. About a quarter (24.4%) had diabetes, less than half (43.5%) had hypertension, and most (86.2%) perceived themselves to be overweight. There were significant differences in measured baseline covariates by racial/ethnic groups including mean BMI, diabetes, and being a Medicaid beneficiary.

In response to the 7 key areas assessed regarding patients’ perceptions of the health care experience related to being overweight or obese:

• Black respondents were less likely than Whites to report that they frequently avoided care from their provider because they did not want to be weighed or discuss their weight (OR 0.49 [95% confidence interval, 0.26–0.90]), with a trend toward all groups being less likely to report frequent avoidance compared to Whites.
• While just over half of respondents (59.3%) indicated that their providers never asked for their permission before discussing their weight, Asians and NA/PI were more likely to report that their providers either frequently (Asians: OR 2.7 [1.3–5.6]; NA/PI: OR 2.3 [1.1–5.0]) or sometimes (Asians: OR 2.3 [1.2–4.3]; NA/PI: OR 2.1 [1.1–4.1]) asked their permission before discussing their weight compared to Whites.
• Over half (61.9%) indicated that their providers were sometimes or frequently supportive of their weight concerns, with no significant differences among racial/ethnic groups.
• Just over half (52.0%) indicated they felt their providers understood the physical and emotional challenges faced by people who are overweight/obese, with Blacks more likely to feel this way (OR 1.8 [1.2–2.8]) compared to Whites.
• Black patients were more likely than Whites (OR 2.0 [1.4–2.8]) to report that their providers discussed their weight with them at a clinic visit.
• While over half (59.7%) indicated that their providers had given or discussed resources with them on healthy eating and weight loss, Black and Asian respondents were more likely than Whites to recall these discussions (Black: OR 1.6 [1.2–2.1]; Asians: OR 1.8 [1.1–2.9]).
• Most weight loss resources or recommendations received were related to lifestyle changes, with very few resources given related to weight loss medications, meal replacement products, or bariatric surgery—few differences across racial/ethnic groups were identified. However, respondents from racial/ethnic minority groups were more likely than Whites to say that they wanted more information about lifestyle changes, classes, and meal replacements. Other than Blacks, all other racial/ethnic groups were also more likely than Whites to indicate that they wanted more information about bariatric surgery.

Conclusions. Most patients across racial/ethnic groups are having positive experiences with weight-related care. However, race/ethnicity correlates with patients’ perception of weight-related care and discussions in clinic encounters.

Commentary

The obesity epidemic in the United States is well-established [1], and recent data from 2014 show that over 37% of adults in the US are obese (defined as having a body mass index greater than 30 kg/m²) [2]. However, while obesity prevalence rates have increased over the past several decades across all genders, ethnicities, income levels, and education levels, important racial/ethnic disparities exist [2,3]. Primary care physicians (PCPs) are ideally situated to promote weight loss via effective obesity counseling since multiple clinic visits over time have the potential to enable rapport building and behavioral change management [4]. In fact, the US Preventive Services Task Force (USPTF) recommends that all patients be screened for obesity and offered intensive lifestyle counseling, as modest weight loss can have significant health benefits [5]. However, some studies have found racial/ethnic differences and disparities in weight-related diagnoses, counseling, and treatment by providers, but also patient perceptions of care and preferred interventions [6–10]. Other studies have described racial/ethnic differences in weight-related concerns and behaviors, body satisfaction, and body image [11–13]. Thus, research is needed to examine these differences.

This cross-sectional study contributes to the limited literature examining the potential for heterogeneity of care according to patient characteristics like race and ethnicity. Key strengths of the design include a large and both geographically and racially/ethnically diverse sample of patients (increased generalizability), the use of mailed brief surveys (reduces non-response rate and reporting bias) and telephone follow-up for verbal administration (reduces non-response rate, though it increases interviewer bias), oversampling of respondents with BMI ≥ 40 kg/m², and the controlling of key covariates including sex, age, Medicaid enrollment, site, and BMI.

However, there are several important limitations, many of which are acknowledged by the authors. While respondents were overall representative of the targeted sample population, the final respondent population was comprised of mostly older females who received managed care, which may have contributed to selection bias and impacted generalizability of findings. Further, Whites were overrepresented, Hispanics were underrepresented, and the small combined sample of NA/PI may have masked important distinctions between these subpopulations. Importantly, this study only provided the survey in English and Spanish and did not include other language translations (eg, Chinese, Japanese, Tagalog), which likely contributed to underrepresented perspectives of immigrants and ESL patients who may struggle with receiving/discussing weight management counseling and resources. The use of a surveys collected subjective and self-reported data on patient encounters as opposed to objective observations. Lastly, the study did not adjust for individual provider factors or assess the potential impact of provider-level differences on care, such as provider-patient concordance on race, ethnicity, language, and/or weight. The incorporation of qualitative interviewers or focus groups with a subsample of each racial/ethnic may have also provided relevant context to understand differences in weight-related care experiences.

Applications for Clinical Practice

As the authors suggest, this study highlights several opportunities to continue improving weight-related care and weight management counseling. PCPs should engage all overweight/obese patients in weight management discussions, and in particular, high-risk minority patients who may desire these conversations and more weight loss advice and resources. However, these discussions require sensitivity and can benefit from the simple practice of asking permission of the patient to talk about their weight in order to reduce care avoidance and improve perceptions of care. Providers should also be mindful of patient priorities and assess patient preferences for all the different weight loss strategies, including lifestyle changes, meal replacements, medications, and surgery.

—Katrina F. Mateo, MPH

Study Overview

Objective. To compare patients’ health care experiences related to their weight across racial and ethnic groups.

Design. Cross-sectional survey-based study.

Setting and participants. Between March and July 2015, 5400 individuals were randomly sampled from the Patient Outcomes to Advance Learning (PORTAL) obesity cohort, which includes over 5 million adults. The PORTAL network is a clinical data research network funded by the Patient Centered Outcomes Research Institute to promote collaboration across several large health systems with electronic medical records (EMRs), including all the Kaiser Permanente regions, Group Health Cooperative, Health Partners, and Denver Health. The selected 5400 cohort members were equally distributed across 3 geographically diverse Kaiser Permanente regions (Southwest, Northern and Southern California, Hawaii, Colorado, and Northwest) and Denver sites. Selected individuals were non-pregnant English or Spanish speakers with a body mass index (BMI) ≥ 25 kg/m² (per their EMR) who were members of a participating health plan and had at least 1 outpatient visit in the last 12 months. Patients with BMI ≥ 40 kg/m² were oversampled. Individuals were mailed a written 10-minute survey (offered in English or Spanish based on a patient’s written language preference noted in their EMR), consisting of 36 multiple-choice and fill-in-the-blank items. Telephone contact for verbal administration was attempted if a mailed response was not received within 4 weeks.

Main measures and analysis. The primary independent variable was a respondent’s racial/ethnic group, categorized as (1) non-Hispanic white (White), 2) non-Hispanic black (Black), 3) Hispanic, 4) Asian, or 5) Native Hawaiian/Other Pacific Islanders/American Indian/Native Alaskan (NA/PI).

Dependent variables focused on patients’ perceptions of the health care experience (based on services received at their usual place of care from their primary care providers) related to being overweight or obese using items based on the Rudd Center’s Patient Survey of Weight-Sensitive Healthcare Practices. Respondents described (1) whether and how often they avoid coming to their provider because they do not want to be weighed or have a discussion about their weight; (2) how often does their provider ask their permission before discussion their weight; (3) how often has their provider been supportive of their weight concerns and efforts to be healthy; (4) whether they think that their provider understands the physical and emotional challenges faced by individuals who are overweight or obese; (5) how often has their provider brought up their weight during a clinic visit; (6) whether their provider has ever given or discussed resources on healthy eating and weight loss; and (7) what types of weight loss resources were discussed with their provider and which types did they want more information about (ie, dietary changes, physical activity, classes, medications, meal replacements, and bariatric surgery). Covariate variables derived from EMR data included sex, age category, diabetes, hypertension, Charlson Index score (overall measures of morbidity), Medicaid enrollment, language preferences, site, and BMI. Survey-derived covariate variables included emotional well-being, perceived weight status, and educational attainment.

Descriptive statistics were generated and compared across racial/ethnic groups using Kruskal-Wallis and chi-square testing, as appropriate. To evaluate the association between a patient’s race/ethnicity and their perceived weight management experience, multinomial logistic regression adjusted for covariates was used to estimate odds ratios (OR).

Main results. From the original sample (n = 5400), 1569 individuals (29%) did not respond, 925 (17%) refused, and 114 (2%) were ineligible, leaving an eligible sample pool of 5286 individuals. The overall response rate was 53% (2197 written; 614 phone, n = 2811). Those with missing data were excluded (6 with missing race/ethnicity; 80 missing other covariates), leaving a final group of 2725 respondents for analysis. Mean age was 52.7 years (SD 15), almost 62% of participants were female, 51.7% identified as White, 21.1% identified as Black, 14.6% identified as Hispanic, 5.8% identified as Asian, and 6.7% identified as NA/PI. About a quarter (24.4%) had diabetes, less than half (43.5%) had hypertension, and most (86.2%) perceived themselves to be overweight. There were significant differences in measured baseline covariates by racial/ethnic groups including mean BMI, diabetes, and being a Medicaid beneficiary.

In response to the 7 key areas assessed regarding patients’ perceptions of the health care experience related to being overweight or obese:

• Black respondents were less likely than Whites to report that they frequently avoided care from their provider because they did not want to be weighed or discuss their weight (OR 0.49 [95% confidence interval, 0.26–0.90]), with a trend toward all groups being less likely to report frequent avoidance compared to Whites.
• While just over half of respondents (59.3%) indicated that their providers never asked for their permission before discussing their weight, Asians and NA/PI were more likely to report that their providers either frequently (Asians: OR 2.7 [1.3–5.6]; NA/PI: OR 2.3 [1.1–5.0]) or sometimes (Asians: OR 2.3 [1.2–4.3]; NA/PI: OR 2.1 [1.1–4.1]) asked their permission before discussing their weight compared to Whites.
• Over half (61.9%) indicated that their providers were sometimes or frequently supportive of their weight concerns, with no significant differences among racial/ethnic groups.
• Just over half (52.0%) indicated they felt their providers understood the physical and emotional challenges faced by people who are overweight/obese, with Blacks more likely to feel this way (OR 1.8 [1.2–2.8]) compared to Whites.
• Black patients were more likely than Whites (OR 2.0 [1.4–2.8]) to report that their providers discussed their weight with them at a clinic visit.
• While over half (59.7%) indicated that their providers had given or discussed resources with them on healthy eating and weight loss, Black and Asian respondents were more likely than Whites to recall these discussions (Black: OR 1.6 [1.2–2.1]; Asians: OR 1.8 [1.1–2.9]).
• Most weight loss resources or recommendations received were related to lifestyle changes, with very few resources given related to weight loss medications, meal replacement products, or bariatric surgery—few differences across racial/ethnic groups were identified. However, respondents from racial/ethnic minority groups were more likely than Whites to say that they wanted more information about lifestyle changes, classes, and meal replacements. Other than Blacks, all other racial/ethnic groups were also more likely than Whites to indicate that they wanted more information about bariatric surgery.

Conclusions. Most patients across racial/ethnic groups are having positive experiences with weight-related care. However, race/ethnicity correlates with patients’ perception of weight-related care and discussions in clinic encounters.

Commentary

The obesity epidemic in the United States is well-established [1], and recent data from 2014 show that over 37% of adults in the US are obese (defined as having a body mass index greater than 30 kg/m²) [2]. However, while obesity prevalence rates have increased over the past several decades across all genders, ethnicities, income levels, and education levels, important racial/ethnic disparities exist [2,3]. Primary care physicians (PCPs) are ideally situated to promote weight loss via effective obesity counseling since multiple clinic visits over time have the potential to enable rapport building and behavioral change management [4]. In fact, the US Preventive Services Task Force (USPTF) recommends that all patients be screened for obesity and offered intensive lifestyle counseling, as modest weight loss can have significant health benefits [5]. However, some studies have found racial/ethnic differences and disparities in weight-related diagnoses, counseling, and treatment by providers, but also patient perceptions of care and preferred interventions [6–10]. Other studies have described racial/ethnic differences in weight-related concerns and behaviors, body satisfaction, and body image [11–13]. Thus, research is needed to examine these differences.

This cross-sectional study contributes to the limited literature examining the potential for heterogeneity of care according to patient characteristics like race and ethnicity. Key strengths of the design include a large and both geographically and racially/ethnically diverse sample of patients (increased generalizability), the use of mailed brief surveys (reduces non-response rate and reporting bias) and telephone follow-up for verbal administration (reduces non-response rate, though it increases interviewer bias), oversampling of respondents with BMI ≥ 40 kg/m², and the controlling of key covariates including sex, age, Medicaid enrollment, site, and BMI.

However, there are several important limitations, many of which are acknowledged by the authors. While respondents were overall representative of the targeted sample population, the final respondent population was comprised of mostly older females who received managed care, which may have contributed to selection bias and impacted generalizability of findings. Further, Whites were overrepresented, Hispanics were underrepresented, and the small combined sample of NA/PI may have masked important distinctions between these subpopulations. Importantly, this study only provided the survey in English and Spanish and did not include other language translations (eg, Chinese, Japanese, Tagalog), which likely contributed to underrepresented perspectives of immigrants and ESL patients who may struggle with receiving/discussing weight management counseling and resources. The use of a surveys collected subjective and self-reported data on patient encounters as opposed to objective observations. Lastly, the study did not adjust for individual provider factors or assess the potential impact of provider-level differences on care, such as provider-patient concordance on race, ethnicity, language, and/or weight. The incorporation of qualitative interviewers or focus groups with a subsample of each racial/ethnic may have also provided relevant context to understand differences in weight-related care experiences.

Applications for Clinical Practice

As the authors suggest, this study highlights several opportunities to continue improving weight-related care and weight management counseling. PCPs should engage all overweight/obese patients in weight management discussions, and in particular, high-risk minority patients who may desire these conversations and more weight loss advice and resources. However, these discussions require sensitivity and can benefit from the simple practice of asking permission of the patient to talk about their weight in order to reduce care avoidance and improve perceptions of care. Providers should also be mindful of patient priorities and assess patient preferences for all the different weight loss strategies, including lifestyle changes, meal replacements, medications, and surgery.

—Katrina F. Mateo, MPH

Study Overview

Objective. To determine if the Dietary Approaches to Stop Hypertension (DASH) diet is effective for lowering serum uric acid (SUA) levels, and if lower sodium intake as part of the diet would have an effect on SUA.

Design. Ancillary study of a randomized, crossover feeding trial.

Setting and participants. The original DASH study was an National Institute of Health (NIH)–funded, investigator-initiated trial conducted at 4 university centers in the United States from 1997 to 1999. Participants aged 22 years or older who did not have preexisting renal insufficiency, heart disease, uncontrolled dyslipidemia, or diabetes were recruited. Those on antihypertensives, insulin, or with alcohol intake exceeding daily recommended limits for men (> 14 drinks per week) were excluded. For the current secondary analysis, only subjects from 1 center, where SUA was measured, were studied. Participants were randomized to a consume a diet consistent with the typical American diet (control diet) or a diet in line with the principles of the DASH diet. For the first 2 weeks, all groups ate the high-sodium control diet. After this 2-week run-in period, the patients in the study then ate the diet they were assigned to for 30 days. After this 30-day period, participants ate their usual home diet for 5 days. The groups were then crossed over.

Intervention. The DASH diet emphasizes fruits, vegetables, and low-fat dairy foods; includes whole grains, poultry, fish, and nuts; and contains smaller amounts of red meat, sweets, and sugar-containing beverages than the typical US diet. It also contains smaller amounts of total and saturated fat and cholesterol and larger amounts of potassium, calcium, magnesium, dietary fiber, and protein than the typical diet. Both diets contained the same number of calories overall. The diets were similar in mg/day of sodium, however, each arm was subdivided to intake either a high (4400 mg/day), intermediate (3000 mg/day), or low (1400 mg/day) level of sodium. During the study period, all food was provided for participants, including meals and snacks, and was donated by various food vendors in the United States.

Main outcome measure. SUA levels, which were measured after each change in diet and at baseline. Other measures were blood pressure, body mass index, renal function, and fasting glucose and lipids.

Main results. There were 103 participants with an average blood pressure of 139/87 mm Hg at baseline. Mean age was 51 years and about half of the patients were women. The majority of patients were overweight (mean BMI, 29.5 kg/m²) and African American (74.8%), with an average SUA level of 5.0 mg/dL. There were 8 participants with a SUA level > 7 mg/dL at baseline. Daily alcohol intake, fasting glucose and triglycerides, renal function, and blood pressure did not differ significantly between the groups. The DASH diet was effective in lowering SUA levels overall by an average of 0.35 mg/dL (P = 0.02). The sodium content had an effect on SUA levels regardless of the diet. The intermediate sodium subset of both the DASH and the control diets resulted in an overall decrease in SUA by 0.34 mg/dL, P < 0.001 (0.35 mg/dL for the DASH diet, P = 0.04; 0.33 mg/dL for the control diet, P < 0.001). There was no difference in SUA between the low- and high-sodium groups. Those participants with the highest SUA at the start of the study had the greatest reduction in SUA. For those with levels > 7 mg/dL, there was a decrease in SUA by 1.29 mg/dL. If the SUA at the start of the trial was lower, reductions were more modest. SUA was reduced by 0.76 mg/dL when the starting level was between 6 and 7 mg/dL. When the participants had a SUA between 4 and 5 mg/dL, the effect of the diet was nonexistent. Other variables such as hypertension and obesity were found not to be confounders.

Conclusion. For participants with SUA levels > 7, an average reduction in serum uric acid of 1.29 mg/dL can reasonably be expected from implementation of a DASH-type diet.

Commentary

SUA is considered an important etiologic factor in gout, but there has been little evidence for success in controlling uric acid with diet. Dietary recommendations for gout patients from the American College of Rheumatology include avoiding organ meats, high-fructose corn syrup, and alcohol in excess, and suggest that beef, lamb, pork, shellfish and sugary beverages should be limited while vegetables and nonfat dairy be encouraged [1].

The DASH diet, promoted by the National Heart, Lung, and Blood Institute to prevent and control hypertension, has been widely disseminated in the popular press and is well known to many Americans. Clinical evidence supporting DASH as first-line nonpharmacologic treatment for high blood pressure is based mainly on the results of 3 trials: DASH Trial[2], DASH-Sodium Trial [3], and PREMIER clinical trial [4]. The DASH diet, while it overlaps with the ACR recommendations of encouraging intake of vegetables and non-fat dairy and discouraging added sugars, recommends as a primary calorie source whole grains, followed by vegetables, fruits, and lean meats, poultry, or fish. One to 2 servings of nuts, seeds, or legumes is also encouraged as well as healthful fats and oils.

The authors’ hypothesis, that the DASH diet would lower uric acid levels as compared with the control diet, was affirmed, with the greater effect seen in patients with higher SUA at baseline. The authors also hypothesized that reducing sodium intake would lower uric acid levels, given its association with high blood pressure. In this study, higher levels of sodium were found to be associated with a decrease in uric acid. The reason for this is unclear and the authors speculate as to why this could be physiologically. The relationship between sodium intake and SUA level is controversial and the authors do not recommend advising anincrease in sodium in the diet to lower SUA levels based on their findings.

Long-term dietary change is not easy. It is encouraging that, according to the authors, most of the participants in the study found the DASH diet to be preferable to the typical Western control diet provided and expressed a desire to maintain the DASH style of eating. This is important to consider, as any lifestyle change must be sustained to see continued benefit. The study participants maintained a constant weight, which eliminates this potentially confounding variable as weight reduction alone leads to a reduction in SUA.

While this study showed a positive effect of implementing the DASH diet in those with elevated SUA levels, it excluded those with comorbidities often found in patients with gout, such as cardiovascular disease, diabetes, and renal impairment. This limits generalizability, as does excluding those who consume alcohol beyond the daily recommended quantities—a known risk factor for hyperuricemia. As with any dietary study, it is difficult to know for certain that participants did not eat any foods outside of the study protocol even when the food was provided.

Patients with gout and hyperuricemia are at an increased risk for cardiovascular disease and the metabolic syndrome, making lifestyle interventions and dietary counselling crucial to the global wellbeing of the patient. Overall, this randomized crossover study provides compelling evidence that the DASH diet should be recommended to patients with hyperuricemia.

Applications for Clinical Practice

For patients with borderline-high SUA (between 6–7 mg/dL), it is reasonable to encourage implementation of the DASH diet with the expectation that SUA will be lowered by about 1.29 mg/dL, getting the patient to goal SUA. As a greater benefit was seen in patients with higher levels of SUA at baseline, it is also reasonable to attempt to lower SUA with a DASH-style diet prior to pharmacologic intervention for higher SUA level if the patient is amenable to trying this tactic.

—Christina Downey, MD, Geisinger Medical Center, Danville, PA

Study Overview

Objective. To determine if the Dietary Approaches to Stop Hypertension (DASH) diet is effective for lowering serum uric acid (SUA) levels, and if lower sodium intake as part of the diet would have an effect on SUA.

Design. Ancillary study of a randomized, crossover feeding trial.

Setting and participants. The original DASH study was an National Institute of Health (NIH)–funded, investigator-initiated trial conducted at 4 university centers in the United States from 1997 to 1999. Participants aged 22 years or older who did not have preexisting renal insufficiency, heart disease, uncontrolled dyslipidemia, or diabetes were recruited. Those on antihypertensives, insulin, or with alcohol intake exceeding daily recommended limits for men (> 14 drinks per week) were excluded. For the current secondary analysis, only subjects from 1 center, where SUA was measured, were studied. Participants were randomized to a consume a diet consistent with the typical American diet (control diet) or a diet in line with the principles of the DASH diet. For the first 2 weeks, all groups ate the high-sodium control diet. After this 2-week run-in period, the patients in the study then ate the diet they were assigned to for 30 days. After this 30-day period, participants ate their usual home diet for 5 days. The groups were then crossed over.

Intervention. The DASH diet emphasizes fruits, vegetables, and low-fat dairy foods; includes whole grains, poultry, fish, and nuts; and contains smaller amounts of red meat, sweets, and sugar-containing beverages than the typical US diet. It also contains smaller amounts of total and saturated fat and cholesterol and larger amounts of potassium, calcium, magnesium, dietary fiber, and protein than the typical diet. Both diets contained the same number of calories overall. The diets were similar in mg/day of sodium, however, each arm was subdivided to intake either a high (4400 mg/day), intermediate (3000 mg/day), or low (1400 mg/day) level of sodium. During the study period, all food was provided for participants, including meals and snacks, and was donated by various food vendors in the United States.

Main outcome measure. SUA levels, which were measured after each change in diet and at baseline. Other measures were blood pressure, body mass index, renal function, and fasting glucose and lipids.

Main results. There were 103 participants with an average blood pressure of 139/87 mm Hg at baseline. Mean age was 51 years and about half of the patients were women. The majority of patients were overweight (mean BMI, 29.5 kg/m²) and African American (74.8%), with an average SUA level of 5.0 mg/dL. There were 8 participants with a SUA level > 7 mg/dL at baseline. Daily alcohol intake, fasting glucose and triglycerides, renal function, and blood pressure did not differ significantly between the groups. The DASH diet was effective in lowering SUA levels overall by an average of 0.35 mg/dL (P = 0.02). The sodium content had an effect on SUA levels regardless of the diet. The intermediate sodium subset of both the DASH and the control diets resulted in an overall decrease in SUA by 0.34 mg/dL, P < 0.001 (0.35 mg/dL for the DASH diet, P = 0.04; 0.33 mg/dL for the control diet, P < 0.001). There was no difference in SUA between the low- and high-sodium groups. Those participants with the highest SUA at the start of the study had the greatest reduction in SUA. For those with levels > 7 mg/dL, there was a decrease in SUA by 1.29 mg/dL. If the SUA at the start of the trial was lower, reductions were more modest. SUA was reduced by 0.76 mg/dL when the starting level was between 6 and 7 mg/dL. When the participants had a SUA between 4 and 5 mg/dL, the effect of the diet was nonexistent. Other variables such as hypertension and obesity were found not to be confounders.

Conclusion. For participants with SUA levels > 7, an average reduction in serum uric acid of 1.29 mg/dL can reasonably be expected from implementation of a DASH-type diet.

Commentary

SUA is considered an important etiologic factor in gout, but there has been little evidence for success in controlling uric acid with diet. Dietary recommendations for gout patients from the American College of Rheumatology include avoiding organ meats, high-fructose corn syrup, and alcohol in excess, and suggest that beef, lamb, pork, shellfish and sugary beverages should be limited while vegetables and nonfat dairy be encouraged [1].

The DASH diet, promoted by the National Heart, Lung, and Blood Institute to prevent and control hypertension, has been widely disseminated in the popular press and is well known to many Americans. Clinical evidence supporting DASH as first-line nonpharmacologic treatment for high blood pressure is based mainly on the results of 3 trials: DASH Trial[2], DASH-Sodium Trial [3], and PREMIER clinical trial [4]. The DASH diet, while it overlaps with the ACR recommendations of encouraging intake of vegetables and non-fat dairy and discouraging added sugars, recommends as a primary calorie source whole grains, followed by vegetables, fruits, and lean meats, poultry, or fish. One to 2 servings of nuts, seeds, or legumes is also encouraged as well as healthful fats and oils.

The authors’ hypothesis, that the DASH diet would lower uric acid levels as compared with the control diet, was affirmed, with the greater effect seen in patients with higher SUA at baseline. The authors also hypothesized that reducing sodium intake would lower uric acid levels, given its association with high blood pressure. In this study, higher levels of sodium were found to be associated with a decrease in uric acid. The reason for this is unclear and the authors speculate as to why this could be physiologically. The relationship between sodium intake and SUA level is controversial and the authors do not recommend advising anincrease in sodium in the diet to lower SUA levels based on their findings.

Long-term dietary change is not easy. It is encouraging that, according to the authors, most of the participants in the study found the DASH diet to be preferable to the typical Western control diet provided and expressed a desire to maintain the DASH style of eating. This is important to consider, as any lifestyle change must be sustained to see continued benefit. The study participants maintained a constant weight, which eliminates this potentially confounding variable as weight reduction alone leads to a reduction in SUA.

While this study showed a positive effect of implementing the DASH diet in those with elevated SUA levels, it excluded those with comorbidities often found in patients with gout, such as cardiovascular disease, diabetes, and renal impairment. This limits generalizability, as does excluding those who consume alcohol beyond the daily recommended quantities—a known risk factor for hyperuricemia. As with any dietary study, it is difficult to know for certain that participants did not eat any foods outside of the study protocol even when the food was provided.

Patients with gout and hyperuricemia are at an increased risk for cardiovascular disease and the metabolic syndrome, making lifestyle interventions and dietary counselling crucial to the global wellbeing of the patient. Overall, this randomized crossover study provides compelling evidence that the DASH diet should be recommended to patients with hyperuricemia.

Applications for Clinical Practice

For patients with borderline-high SUA (between 6–7 mg/dL), it is reasonable to encourage implementation of the DASH diet with the expectation that SUA will be lowered by about 1.29 mg/dL, getting the patient to goal SUA. As a greater benefit was seen in patients with higher levels of SUA at baseline, it is also reasonable to attempt to lower SUA with a DASH-style diet prior to pharmacologic intervention for higher SUA level if the patient is amenable to trying this tactic.

—Christina Downey, MD, Geisinger Medical Center, Danville, PA

Study Overview

Objective. To determine if the Dietary Approaches to Stop Hypertension (DASH) diet is effective for lowering serum uric acid (SUA) levels, and if lower sodium intake as part of the diet would have an effect on SUA.

Design. Ancillary study of a randomized, crossover feeding trial.

Setting and participants. The original DASH study was an National Institute of Health (NIH)–funded, investigator-initiated trial conducted at 4 university centers in the United States from 1997 to 1999. Participants aged 22 years or older who did not have preexisting renal insufficiency, heart disease, uncontrolled dyslipidemia, or diabetes were recruited. Those on antihypertensives, insulin, or with alcohol intake exceeding daily recommended limits for men (> 14 drinks per week) were excluded. For the current secondary analysis, only subjects from 1 center, where SUA was measured, were studied. Participants were randomized to a consume a diet consistent with the typical American diet (control diet) or a diet in line with the principles of the DASH diet. For the first 2 weeks, all groups ate the high-sodium control diet. After this 2-week run-in period, the patients in the study then ate the diet they were assigned to for 30 days. After this 30-day period, participants ate their usual home diet for 5 days. The groups were then crossed over.

Intervention. The DASH diet emphasizes fruits, vegetables, and low-fat dairy foods; includes whole grains, poultry, fish, and nuts; and contains smaller amounts of red meat, sweets, and sugar-containing beverages than the typical US diet. It also contains smaller amounts of total and saturated fat and cholesterol and larger amounts of potassium, calcium, magnesium, dietary fiber, and protein than the typical diet. Both diets contained the same number of calories overall. The diets were similar in mg/day of sodium, however, each arm was subdivided to intake either a high (4400 mg/day), intermediate (3000 mg/day), or low (1400 mg/day) level of sodium. During the study period, all food was provided for participants, including meals and snacks, and was donated by various food vendors in the United States.

Main outcome measure. SUA levels, which were measured after each change in diet and at baseline. Other measures were blood pressure, body mass index, renal function, and fasting glucose and lipids.

Main results. There were 103 participants with an average blood pressure of 139/87 mm Hg at baseline. Mean age was 51 years and about half of the patients were women. The majority of patients were overweight (mean BMI, 29.5 kg/m²) and African American (74.8%), with an average SUA level of 5.0 mg/dL. There were 8 participants with a SUA level > 7 mg/dL at baseline. Daily alcohol intake, fasting glucose and triglycerides, renal function, and blood pressure did not differ significantly between the groups. The DASH diet was effective in lowering SUA levels overall by an average of 0.35 mg/dL (P = 0.02). The sodium content had an effect on SUA levels regardless of the diet. The intermediate sodium subset of both the DASH and the control diets resulted in an overall decrease in SUA by 0.34 mg/dL, P < 0.001 (0.35 mg/dL for the DASH diet, P = 0.04; 0.33 mg/dL for the control diet, P < 0.001). There was no difference in SUA between the low- and high-sodium groups. Those participants with the highest SUA at the start of the study had the greatest reduction in SUA. For those with levels > 7 mg/dL, there was a decrease in SUA by 1.29 mg/dL. If the SUA at the start of the trial was lower, reductions were more modest. SUA was reduced by 0.76 mg/dL when the starting level was between 6 and 7 mg/dL. When the participants had a SUA between 4 and 5 mg/dL, the effect of the diet was nonexistent. Other variables such as hypertension and obesity were found not to be confounders.

Conclusion. For participants with SUA levels > 7, an average reduction in serum uric acid of 1.29 mg/dL can reasonably be expected from implementation of a DASH-type diet.

Commentary

SUA is considered an important etiologic factor in gout, but there has been little evidence for success in controlling uric acid with diet. Dietary recommendations for gout patients from the American College of Rheumatology include avoiding organ meats, high-fructose corn syrup, and alcohol in excess, and suggest that beef, lamb, pork, shellfish and sugary beverages should be limited while vegetables and nonfat dairy be encouraged [1].

The DASH diet, promoted by the National Heart, Lung, and Blood Institute to prevent and control hypertension, has been widely disseminated in the popular press and is well known to many Americans. Clinical evidence supporting DASH as first-line nonpharmacologic treatment for high blood pressure is based mainly on the results of 3 trials: DASH Trial[2], DASH-Sodium Trial [3], and PREMIER clinical trial [4]. The DASH diet, while it overlaps with the ACR recommendations of encouraging intake of vegetables and non-fat dairy and discouraging added sugars, recommends as a primary calorie source whole grains, followed by vegetables, fruits, and lean meats, poultry, or fish. One to 2 servings of nuts, seeds, or legumes is also encouraged as well as healthful fats and oils.

The authors’ hypothesis, that the DASH diet would lower uric acid levels as compared with the control diet, was affirmed, with the greater effect seen in patients with higher SUA at baseline. The authors also hypothesized that reducing sodium intake would lower uric acid levels, given its association with high blood pressure. In this study, higher levels of sodium were found to be associated with a decrease in uric acid. The reason for this is unclear and the authors speculate as to why this could be physiologically. The relationship between sodium intake and SUA level is controversial and the authors do not recommend advising anincrease in sodium in the diet to lower SUA levels based on their findings.

Long-term dietary change is not easy. It is encouraging that, according to the authors, most of the participants in the study found the DASH diet to be preferable to the typical Western control diet provided and expressed a desire to maintain the DASH style of eating. This is important to consider, as any lifestyle change must be sustained to see continued benefit. The study participants maintained a constant weight, which eliminates this potentially confounding variable as weight reduction alone leads to a reduction in SUA.

While this study showed a positive effect of implementing the DASH diet in those with elevated SUA levels, it excluded those with comorbidities often found in patients with gout, such as cardiovascular disease, diabetes, and renal impairment. This limits generalizability, as does excluding those who consume alcohol beyond the daily recommended quantities—a known risk factor for hyperuricemia. As with any dietary study, it is difficult to know for certain that participants did not eat any foods outside of the study protocol even when the food was provided.

Patients with gout and hyperuricemia are at an increased risk for cardiovascular disease and the metabolic syndrome, making lifestyle interventions and dietary counselling crucial to the global wellbeing of the patient. Overall, this randomized crossover study provides compelling evidence that the DASH diet should be recommended to patients with hyperuricemia.

Applications for Clinical Practice

For patients with borderline-high SUA (between 6–7 mg/dL), it is reasonable to encourage implementation of the DASH diet with the expectation that SUA will be lowered by about 1.29 mg/dL, getting the patient to goal SUA. As a greater benefit was seen in patients with higher levels of SUA at baseline, it is also reasonable to attempt to lower SUA with a DASH-style diet prior to pharmacologic intervention for higher SUA level if the patient is amenable to trying this tactic.

—Christina Downey, MD, Geisinger Medical Center, Danville, PA

Study Overview

Objective. To determine whether a non–tumor necrosis factor (TNF)-targeted drug is more effective than a second anti-TNF drug in rheumatoid arthritis (RA) patients who have had an inadequate response to a first anti-TNF drug.

Design. 52-week pragmatic, multicenter, open-label, parallel-group, randomized clinical trial (the “Rotation or Change” trial).

Setting and participants. 300 patients who were at least 18 years old were recruited from December 2009 to August 2012 from 47 French clinical centers. These patients had to have a diagnosis of RA according to the 1987 American College of Rheumatology criteria, presence of erosions, a DAS28-ESR (a measure of disease burden using patient global health, tender and swollen joint counts, and the erythrocyte sedimentation rate) of 3.2 or more, and insufficient response to an anti-TNF according to the physician (based on 1 or more of: persistent tender and swollen joints, persistent disease activity according to patient global assessment, elevated levels of acute-phase reactants, and dependence on analgesics, nonsteroidal anti-inflammatory drugs, or corticosteroids). In addition, patients had to have a stable dose of oral corticosteroids of 15 mg/d or less of equivalent prednisone within 4 weeks before enrollment, a stable dose of synthetic disease-modifying antirheumatic drugs (DMARDs) within 4 weeks of enrollment, and informed written consent. Exclusion criteria included cessation of the first anti-TNF agent due only to an adverse event, previous treatment with 2 or more anti-TNF agents, previous treatment with abatacept, rituximab, or tocilizumab, a contraindication to all anti-TNF agents and other biologics such as an infection or cancer, pregnancy and breastfeeding.

Intervention. Patients were randomly assigned in equal proportions to receive either a non-TNF biologic (abatacept, rituximab, or tocilizumab) or a second anti-TNF agent (adalimumab, certolizumab, etanercept, infliximab, or golimumab); the choice of agent after randomization was decided by the physician. The starting dose and frequency of treatment was predetermined. Golimumab was not available for use at the time of this study. The choice of future dosing and frequency of the treatment was left up to the treating physician in both groups. The assigned drug treatments continued for 12 months but were allowed to be discontinued for adverse events, patient choice, or inefficacy. Treatment and dose adjustments for oral corticosteroids and glucocorticoid intra-articular injections were allowed for both treatment groups.

Main outcome measures. The primary outcome was the proportion of patients at week 24 with a good or moderate European League Against Rheumatism (EULAR) response. A good EULAR response is defined as a decrease in DAS28-ESR of more than 1.2 points leading to a score of 3.2 or lower while a moderate EULAR response is defined as a decrease of more than 0.6 and resulting in a score of 5.1 points or lower. Secondary end points were EULAR response at weeks 12 and 52, DAS28-ESR at weeks 12, 24, and 52, low disease activity (DAS28-ESR < 3.2) and remission (DAS28-ESR < 2.6) at weeks 12, 24, and 52, mean oral corticosteroid use at weeks 24 and 52, therapeutic maintenance (defined as the proportion of patients who did not discontinue the assigned biologic treatment) at weeks 24 and 52, and health assessment questionnaire (HAQ) score (range, 0–3 with 0 representing the best and 3 the worst outcomes) at weeks 12, 24, and 52. Safety including serious adverse events as well as serious infections was also evaluated throughout the study.

Main results. 300 patients were randomized. The 2 groups were not different with regard to demographic and disease characteristics. In the non-TNF group of 150 patients, 33 of 146 patients (23%) received abatacept, 41 (28%) rituximab, and 70 (48%) tocilizumab; 2 patients (1%) did not receive the intervention as planned, 1 patient received adalimumab and 1 patient received no treatment. For the anti-TNF group, 57 of 146 patients (39%) received adalimumab, 23 (16%) certolizumab, 53 (36%) etanercept, and 8 (5%) infliximab. Five patients (3%) did not receive the intervention assigned as 2 patients received rituximab, 1 patient received tocilizumab, and 2 patients received no treatment. About two-thirds of patients in each group received concomitant methotrexate and about half in each group received oral corticosteroids.

With regard to the primary outcome, at week 24 101 of 146 patients (69%) in the non-TNF group and 76 (52%) in the second anti-TNF group achieved a good or moderate EULAR response, with 39% with a good response and 30% with a moderate response in the non-TNF group and 21% with a good response and 31% with a moderate response in the second anti-TNF group (odds ratio [OR], 2.06; 95% confidence interval [CI], 1.27 to 3.37; P = 0.004, with imputation of missing data; absolute difference, 17.2%; 95% CI, 6.2% to 28.2%). The DAS28-ESR was lower in the non-TNF group (mean difference adjusted for baseline differences, −0.43; 95% CI, −0.72 to −0.14; P = 0.004). More patients in the non-TNF group vs the second anti-TNF group showed low disease activity at week 24 (45% vs 28%; OR, 2.09; 95% CI, 1.27 to 3.43; P = 0.004) and at week 52 (41% vs 23%; OR, 2.26; 95% CI, 1.33 to 3.86; P = 0.003).

The mean DAS28-ESR change from baseline was greater for patients in the non-TNF group than for patients in the second anti-TNF group with a 24-week mean difference of −0.43 (95% CI,−0.72 to −0.14; P = 0.004) and 52-week mean difference of −0.38 (95% CI, −0.69 to −0.08; P = 0.01).

The proportion of EULAR good and moderate responders at week 24 did not significantly differ with abatacept, rituximab, and tocilizumab treatment. The therapeutic maintenance rate, defined as the proportion of patients who continued the biologic treatment, was found to be significantly higher at weeks 24 and 52 in the non-TNF group than in the second anti-TNF group. The mean change from baseline to weeks 24 and 52 in the level of prednisone doses was not significantly different between patients between treatment groups.

With respect to safety, 16 patients (11%) in the non-TNF group experienced 18 serious adverse events and 8 patients (5%) in the second anti-TNF group experienced 13 events (P = 0.10) with 7 patients (5%) in each group developing serious infections.

Conclusion. In patients with RA previously treated with an anti-TNF drug with an inadequate response, the use of a non-TNF biologic agent was found to be more effective in achieving a good or moderate disease activity response at 24 weeks compared with a second anti-TNF medication.

Commentary

In patients with RA who have shown an inadequate response to methotrexate, TNF-α inhibitors have been shown to improve quality of life. However, it has been shown that almost one-third of patients have an insufficient and inadequate response to anti-TNF agents and continue to have persistent disease activity [1–3].Alternative treatments are therefore needed, but there is currently little guidance available for choosing the next treatment.

There are 3 placebo-controlled trials that have shown that switching to a non–TNF-targeted therapy may be appropriate [4–6]. The most commonly used non-TNF agents are abatacept, rituximab, and tocilizumab. However, there is evidence that switching to another anti-TNF agent after failure of a first can also be a good choice, as the molecular structure of TNF-inhibitors and their affinity for membrane and TNF-α vary. There were 2 randomized placebo-controlled trials that reported that approximately half of patients with RA with insufficient response to a TNF-α inhibitor responded to a second anti-TNF drug [7,8].

Although there have been observational studies addressing this question, this is the first randomized controlled trial to evaluate the efficacy of a non-TNF-targeted biologic compared to a second anti-TNF drug to treat RA in patients with an insufficient response to a first anti-TNF drug. Data showed that at week 24, 69% in the non-TNF group and 52% in the anti-TNF group achieved a good or moderate EULAR response. The non-TNF treatment was also associated with a better EULAR response than a second anti-TNF drug at weeks 12 and 52. The DAS28-ESR and the number of patients achieving low disease activity status were found to be greater at months 6 and 12 in the non-TNF group than in the second anti-TNF group. One strength of the study is its pragmatic design—the study evaluated the  effectiveness of interventions under real-life, routine practice conditions where physicians often choose one drug over another for reasons based on the habits or characteristics of the patient. The comparison of strategies and not individual drugs more appropriately addresses the questions that physicians face in daily practice. However, there were some limitations including the lack of blinding by participants, the exclusion of some biologic agents such as golimunab, the lack of assessment of individual drug efficacy, and the fact that approximately 40% of patients in each group did not have concomitant treatment with methotrexate, an agent known to improve the efficacy of most biologic agents.

Applications for Clinical Practice

This is the first randomized controlled trial to evaluate the efficacy of a non-TNF-targeted biologic vs. a second anti-TNF in patients with RA who have an insufficient response to a first anti-TNF drug. Further studies addressing the limitations identified in this study are needed before physicians can employ these findings in clinical practice.

—Anita Laloo, MD

Study Overview

Objective. To determine whether a non–tumor necrosis factor (TNF)-targeted drug is more effective than a second anti-TNF drug in rheumatoid arthritis (RA) patients who have had an inadequate response to a first anti-TNF drug.

Design. 52-week pragmatic, multicenter, open-label, parallel-group, randomized clinical trial (the “Rotation or Change” trial).

Setting and participants. 300 patients who were at least 18 years old were recruited from December 2009 to August 2012 from 47 French clinical centers. These patients had to have a diagnosis of RA according to the 1987 American College of Rheumatology criteria, presence of erosions, a DAS28-ESR (a measure of disease burden using patient global health, tender and swollen joint counts, and the erythrocyte sedimentation rate) of 3.2 or more, and insufficient response to an anti-TNF according to the physician (based on 1 or more of: persistent tender and swollen joints, persistent disease activity according to patient global assessment, elevated levels of acute-phase reactants, and dependence on analgesics, nonsteroidal anti-inflammatory drugs, or corticosteroids). In addition, patients had to have a stable dose of oral corticosteroids of 15 mg/d or less of equivalent prednisone within 4 weeks before enrollment, a stable dose of synthetic disease-modifying antirheumatic drugs (DMARDs) within 4 weeks of enrollment, and informed written consent. Exclusion criteria included cessation of the first anti-TNF agent due only to an adverse event, previous treatment with 2 or more anti-TNF agents, previous treatment with abatacept, rituximab, or tocilizumab, a contraindication to all anti-TNF agents and other biologics such as an infection or cancer, pregnancy and breastfeeding.

Intervention. Patients were randomly assigned in equal proportions to receive either a non-TNF biologic (abatacept, rituximab, or tocilizumab) or a second anti-TNF agent (adalimumab, certolizumab, etanercept, infliximab, or golimumab); the choice of agent after randomization was decided by the physician. The starting dose and frequency of treatment was predetermined. Golimumab was not available for use at the time of this study. The choice of future dosing and frequency of the treatment was left up to the treating physician in both groups. The assigned drug treatments continued for 12 months but were allowed to be discontinued for adverse events, patient choice, or inefficacy. Treatment and dose adjustments for oral corticosteroids and glucocorticoid intra-articular injections were allowed for both treatment groups.

Main outcome measures. The primary outcome was the proportion of patients at week 24 with a good or moderate European League Against Rheumatism (EULAR) response. A good EULAR response is defined as a decrease in DAS28-ESR of more than 1.2 points leading to a score of 3.2 or lower while a moderate EULAR response is defined as a decrease of more than 0.6 and resulting in a score of 5.1 points or lower. Secondary end points were EULAR response at weeks 12 and 52, DAS28-ESR at weeks 12, 24, and 52, low disease activity (DAS28-ESR < 3.2) and remission (DAS28-ESR < 2.6) at weeks 12, 24, and 52, mean oral corticosteroid use at weeks 24 and 52, therapeutic maintenance (defined as the proportion of patients who did not discontinue the assigned biologic treatment) at weeks 24 and 52, and health assessment questionnaire (HAQ) score (range, 0–3 with 0 representing the best and 3 the worst outcomes) at weeks 12, 24, and 52. Safety including serious adverse events as well as serious infections was also evaluated throughout the study.

Main results. 300 patients were randomized. The 2 groups were not different with regard to demographic and disease characteristics. In the non-TNF group of 150 patients, 33 of 146 patients (23%) received abatacept, 41 (28%) rituximab, and 70 (48%) tocilizumab; 2 patients (1%) did not receive the intervention as planned, 1 patient received adalimumab and 1 patient received no treatment. For the anti-TNF group, 57 of 146 patients (39%) received adalimumab, 23 (16%) certolizumab, 53 (36%) etanercept, and 8 (5%) infliximab. Five patients (3%) did not receive the intervention assigned as 2 patients received rituximab, 1 patient received tocilizumab, and 2 patients received no treatment. About two-thirds of patients in each group received concomitant methotrexate and about half in each group received oral corticosteroids.

With regard to the primary outcome, at week 24 101 of 146 patients (69%) in the non-TNF group and 76 (52%) in the second anti-TNF group achieved a good or moderate EULAR response, with 39% with a good response and 30% with a moderate response in the non-TNF group and 21% with a good response and 31% with a moderate response in the second anti-TNF group (odds ratio [OR], 2.06; 95% confidence interval [CI], 1.27 to 3.37; P = 0.004, with imputation of missing data; absolute difference, 17.2%; 95% CI, 6.2% to 28.2%). The DAS28-ESR was lower in the non-TNF group (mean difference adjusted for baseline differences, −0.43; 95% CI, −0.72 to −0.14; P = 0.004). More patients in the non-TNF group vs the second anti-TNF group showed low disease activity at week 24 (45% vs 28%; OR, 2.09; 95% CI, 1.27 to 3.43; P = 0.004) and at week 52 (41% vs 23%; OR, 2.26; 95% CI, 1.33 to 3.86; P = 0.003).

The mean DAS28-ESR change from baseline was greater for patients in the non-TNF group than for patients in the second anti-TNF group with a 24-week mean difference of −0.43 (95% CI,−0.72 to −0.14; P = 0.004) and 52-week mean difference of −0.38 (95% CI, −0.69 to −0.08; P = 0.01).

The proportion of EULAR good and moderate responders at week 24 did not significantly differ with abatacept, rituximab, and tocilizumab treatment. The therapeutic maintenance rate, defined as the proportion of patients who continued the biologic treatment, was found to be significantly higher at weeks 24 and 52 in the non-TNF group than in the second anti-TNF group. The mean change from baseline to weeks 24 and 52 in the level of prednisone doses was not significantly different between patients between treatment groups.

With respect to safety, 16 patients (11%) in the non-TNF group experienced 18 serious adverse events and 8 patients (5%) in the second anti-TNF group experienced 13 events (P = 0.10) with 7 patients (5%) in each group developing serious infections.

Conclusion. In patients with RA previously treated with an anti-TNF drug with an inadequate response, the use of a non-TNF biologic agent was found to be more effective in achieving a good or moderate disease activity response at 24 weeks compared with a second anti-TNF medication.

Commentary

In patients with RA who have shown an inadequate response to methotrexate, TNF-α inhibitors have been shown to improve quality of life. However, it has been shown that almost one-third of patients have an insufficient and inadequate response to anti-TNF agents and continue to have persistent disease activity [1–3].Alternative treatments are therefore needed, but there is currently little guidance available for choosing the next treatment.

There are 3 placebo-controlled trials that have shown that switching to a non–TNF-targeted therapy may be appropriate [4–6]. The most commonly used non-TNF agents are abatacept, rituximab, and tocilizumab. However, there is evidence that switching to another anti-TNF agent after failure of a first can also be a good choice, as the molecular structure of TNF-inhibitors and their affinity for membrane and TNF-α vary. There were 2 randomized placebo-controlled trials that reported that approximately half of patients with RA with insufficient response to a TNF-α inhibitor responded to a second anti-TNF drug [7,8].

Although there have been observational studies addressing this question, this is the first randomized controlled trial to evaluate the efficacy of a non-TNF-targeted biologic compared to a second anti-TNF drug to treat RA in patients with an insufficient response to a first anti-TNF drug. Data showed that at week 24, 69% in the non-TNF group and 52% in the anti-TNF group achieved a good or moderate EULAR response. The non-TNF treatment was also associated with a better EULAR response than a second anti-TNF drug at weeks 12 and 52. The DAS28-ESR and the number of patients achieving low disease activity status were found to be greater at months 6 and 12 in the non-TNF group than in the second anti-TNF group. One strength of the study is its pragmatic design—the study evaluated the  effectiveness of interventions under real-life, routine practice conditions where physicians often choose one drug over another for reasons based on the habits or characteristics of the patient. The comparison of strategies and not individual drugs more appropriately addresses the questions that physicians face in daily practice. However, there were some limitations including the lack of blinding by participants, the exclusion of some biologic agents such as golimunab, the lack of assessment of individual drug efficacy, and the fact that approximately 40% of patients in each group did not have concomitant treatment with methotrexate, an agent known to improve the efficacy of most biologic agents.

Applications for Clinical Practice

This is the first randomized controlled trial to evaluate the efficacy of a non-TNF-targeted biologic vs. a second anti-TNF in patients with RA who have an insufficient response to a first anti-TNF drug. Further studies addressing the limitations identified in this study are needed before physicians can employ these findings in clinical practice.

—Anita Laloo, MD

Study Overview

Objective. To determine whether a non–tumor necrosis factor (TNF)-targeted drug is more effective than a second anti-TNF drug in rheumatoid arthritis (RA) patients who have had an inadequate response to a first anti-TNF drug.

Design. 52-week pragmatic, multicenter, open-label, parallel-group, randomized clinical trial (the “Rotation or Change” trial).

Setting and participants. 300 patients who were at least 18 years old were recruited from December 2009 to August 2012 from 47 French clinical centers. These patients had to have a diagnosis of RA according to the 1987 American College of Rheumatology criteria, presence of erosions, a DAS28-ESR (a measure of disease burden using patient global health, tender and swollen joint counts, and the erythrocyte sedimentation rate) of 3.2 or more, and insufficient response to an anti-TNF according to the physician (based on 1 or more of: persistent tender and swollen joints, persistent disease activity according to patient global assessment, elevated levels of acute-phase reactants, and dependence on analgesics, nonsteroidal anti-inflammatory drugs, or corticosteroids). In addition, patients had to have a stable dose of oral corticosteroids of 15 mg/d or less of equivalent prednisone within 4 weeks before enrollment, a stable dose of synthetic disease-modifying antirheumatic drugs (DMARDs) within 4 weeks of enrollment, and informed written consent. Exclusion criteria included cessation of the first anti-TNF agent due only to an adverse event, previous treatment with 2 or more anti-TNF agents, previous treatment with abatacept, rituximab, or tocilizumab, a contraindication to all anti-TNF agents and other biologics such as an infection or cancer, pregnancy and breastfeeding.

Intervention. Patients were randomly assigned in equal proportions to receive either a non-TNF biologic (abatacept, rituximab, or tocilizumab) or a second anti-TNF agent (adalimumab, certolizumab, etanercept, infliximab, or golimumab); the choice of agent after randomization was decided by the physician. The starting dose and frequency of treatment was predetermined. Golimumab was not available for use at the time of this study. The choice of future dosing and frequency of the treatment was left up to the treating physician in both groups. The assigned drug treatments continued for 12 months but were allowed to be discontinued for adverse events, patient choice, or inefficacy. Treatment and dose adjustments for oral corticosteroids and glucocorticoid intra-articular injections were allowed for both treatment groups.

Main outcome measures. The primary outcome was the proportion of patients at week 24 with a good or moderate European League Against Rheumatism (EULAR) response. A good EULAR response is defined as a decrease in DAS28-ESR of more than 1.2 points leading to a score of 3.2 or lower while a moderate EULAR response is defined as a decrease of more than 0.6 and resulting in a score of 5.1 points or lower. Secondary end points were EULAR response at weeks 12 and 52, DAS28-ESR at weeks 12, 24, and 52, low disease activity (DAS28-ESR < 3.2) and remission (DAS28-ESR < 2.6) at weeks 12, 24, and 52, mean oral corticosteroid use at weeks 24 and 52, therapeutic maintenance (defined as the proportion of patients who did not discontinue the assigned biologic treatment) at weeks 24 and 52, and health assessment questionnaire (HAQ) score (range, 0–3 with 0 representing the best and 3 the worst outcomes) at weeks 12, 24, and 52. Safety including serious adverse events as well as serious infections was also evaluated throughout the study.

Main results. 300 patients were randomized. The 2 groups were not different with regard to demographic and disease characteristics. In the non-TNF group of 150 patients, 33 of 146 patients (23%) received abatacept, 41 (28%) rituximab, and 70 (48%) tocilizumab; 2 patients (1%) did not receive the intervention as planned, 1 patient received adalimumab and 1 patient received no treatment. For the anti-TNF group, 57 of 146 patients (39%) received adalimumab, 23 (16%) certolizumab, 53 (36%) etanercept, and 8 (5%) infliximab. Five patients (3%) did not receive the intervention assigned as 2 patients received rituximab, 1 patient received tocilizumab, and 2 patients received no treatment. About two-thirds of patients in each group received concomitant methotrexate and about half in each group received oral corticosteroids.

With regard to the primary outcome, at week 24 101 of 146 patients (69%) in the non-TNF group and 76 (52%) in the second anti-TNF group achieved a good or moderate EULAR response, with 39% with a good response and 30% with a moderate response in the non-TNF group and 21% with a good response and 31% with a moderate response in the second anti-TNF group (odds ratio [OR], 2.06; 95% confidence interval [CI], 1.27 to 3.37; P = 0.004, with imputation of missing data; absolute difference, 17.2%; 95% CI, 6.2% to 28.2%). The DAS28-ESR was lower in the non-TNF group (mean difference adjusted for baseline differences, −0.43; 95% CI, −0.72 to −0.14; P = 0.004). More patients in the non-TNF group vs the second anti-TNF group showed low disease activity at week 24 (45% vs 28%; OR, 2.09; 95% CI, 1.27 to 3.43; P = 0.004) and at week 52 (41% vs 23%; OR, 2.26; 95% CI, 1.33 to 3.86; P = 0.003).

The mean DAS28-ESR change from baseline was greater for patients in the non-TNF group than for patients in the second anti-TNF group with a 24-week mean difference of −0.43 (95% CI,−0.72 to −0.14; P = 0.004) and 52-week mean difference of −0.38 (95% CI, −0.69 to −0.08; P = 0.01).

The proportion of EULAR good and moderate responders at week 24 did not significantly differ with abatacept, rituximab, and tocilizumab treatment. The therapeutic maintenance rate, defined as the proportion of patients who continued the biologic treatment, was found to be significantly higher at weeks 24 and 52 in the non-TNF group than in the second anti-TNF group. The mean change from baseline to weeks 24 and 52 in the level of prednisone doses was not significantly different between patients between treatment groups.

With respect to safety, 16 patients (11%) in the non-TNF group experienced 18 serious adverse events and 8 patients (5%) in the second anti-TNF group experienced 13 events (P = 0.10) with 7 patients (5%) in each group developing serious infections.

Conclusion. In patients with RA previously treated with an anti-TNF drug with an inadequate response, the use of a non-TNF biologic agent was found to be more effective in achieving a good or moderate disease activity response at 24 weeks compared with a second anti-TNF medication.

Commentary

In patients with RA who have shown an inadequate response to methotrexate, TNF-α inhibitors have been shown to improve quality of life. However, it has been shown that almost one-third of patients have an insufficient and inadequate response to anti-TNF agents and continue to have persistent disease activity [1–3].Alternative treatments are therefore needed, but there is currently little guidance available for choosing the next treatment.

There are 3 placebo-controlled trials that have shown that switching to a non–TNF-targeted therapy may be appropriate [4–6]. The most commonly used non-TNF agents are abatacept, rituximab, and tocilizumab. However, there is evidence that switching to another anti-TNF agent after failure of a first can also be a good choice, as the molecular structure of TNF-inhibitors and their affinity for membrane and TNF-α vary. There were 2 randomized placebo-controlled trials that reported that approximately half of patients with RA with insufficient response to a TNF-α inhibitor responded to a second anti-TNF drug [7,8].

Although there have been observational studies addressing this question, this is the first randomized controlled trial to evaluate the efficacy of a non-TNF-targeted biologic compared to a second anti-TNF drug to treat RA in patients with an insufficient response to a first anti-TNF drug. Data showed that at week 24, 69% in the non-TNF group and 52% in the anti-TNF group achieved a good or moderate EULAR response. The non-TNF treatment was also associated with a better EULAR response than a second anti-TNF drug at weeks 12 and 52. The DAS28-ESR and the number of patients achieving low disease activity status were found to be greater at months 6 and 12 in the non-TNF group than in the second anti-TNF group. One strength of the study is its pragmatic design—the study evaluated the  effectiveness of interventions under real-life, routine practice conditions where physicians often choose one drug over another for reasons based on the habits or characteristics of the patient. The comparison of strategies and not individual drugs more appropriately addresses the questions that physicians face in daily practice. However, there were some limitations including the lack of blinding by participants, the exclusion of some biologic agents such as golimunab, the lack of assessment of individual drug efficacy, and the fact that approximately 40% of patients in each group did not have concomitant treatment with methotrexate, an agent known to improve the efficacy of most biologic agents.

Applications for Clinical Practice

This is the first randomized controlled trial to evaluate the efficacy of a non-TNF-targeted biologic vs. a second anti-TNF in patients with RA who have an insufficient response to a first anti-TNF drug. Further studies addressing the limitations identified in this study are needed before physicians can employ these findings in clinical practice.

—Anita Laloo, MD

Study Overview

Objective. To evaluate the efficacy and safety of the CDK4/6 inhibitor ribociclib in combination with letrozole as initial therapy in patients with hormone-receptor (HR)–positive, human epidermal growth factor receptor 2 (HER-2)–negative advanced breast cancer.

Design. Pre-planned interim analysis of a randomized, double-blind, phase 3 clinical trial.

Setting and participants. This study enrolled patients in 29 countries at 223 centers. A total of 668 postmenopausal women underwent randomization, with 334 assigned to receive ribociclib plus letrozole and 334 assigned to receive placebo plus letrozole. All women had HR-positive, HER-2 negative recurrent or metastatic breast cancer and had not received prior systemic therapy. Enrolled patients had either measurable disease on imaging or at least 1 lytic bone lesion. All patients were required to have an Eastern Cooperative Oncology Group performance status of 0 or 1. Patients were excluded if they had received prior therapy with a CDK4/6 inhibitor, previous systemic chemotherapy or endocrine therapy. If a patient received an aromatase inhibitor for neoadjuvant or adjuvant therapy, the disease-free interval needed to be more than 12 months to be included in the study. Patients with inflammatory breast cancer or central nervous system involvement were also excluded. Normal cardiac function (normal QT interval) was required for enrollment. The randomization was stratified by presence of liver or lung metastases.

Intervention. The patients were randomized to oral ribociclib 600 mg per day 3 weeks on, 1 week off in a 28-day treatment cycle plus letrozole 2.5 mg daily or placebo plus letrozole. The dosing of ribociclib was based on a prior phase 1 study [1]. Treatment was continued until disease progression, unacceptable toxicity, discontinuation, or death. Dose reductions of ribociclib were allowed; however, dose reductions of letrozole were not permitted. Crossover between treatment arms was not allowed. Patients were assessed with computed tomo-graphy at the time of randomization, every 8 weeks for the first 18 months and every 12 weeks there-after. Patients were monitored for hematological toxicity each cycle. Electrocardiographic assessment was done at screening, on day 15 of cycle 1 and on day 1 of all subsequent cycles to monitor for QT prolongation.

Main outcome measures. The primary outcome was progression-free survival. The secondary outcomes were overall survival, overall response rate (complete or partial response), clinical benefit rate, and safety. Clinical benefit rate was defined as overall response plus stable disease lasting 24 weeks or more. A prespecified interim analysis was planned after disease progression or death was reported in 211 of 302 patients (70%).

Results. The baseline characteristics were balanced between the 2 groups. Visceral disease was present in 58.8% and bone-only disease in 22% of the patients. The median duration of therapy exposure was 13 months in the ribociclib group and 12.4 months in the placebo group. The median duration of follow-up was 15.3 months. After 18 months, progression-free survival was 63% (95% confidence interval [CI], 54.6 to 70.3) in the ribociclib/letrozole group versus 42.2% (95% CI, 34.8 to 49.5) in the placebo group (P < 0.001). The median progression-free survival was not met in the combination group (95% CI, 19.3 to not reached) versus 14.7 months (95% CI, 13.0 to 16.5) in the placebo group. The improved progression-free survival was seen across all subgroups. The overall response rate was higher in the combination arm (52.7% vs. 37.1%) as was the clinical benefit rate (80.1% vs. 71.8%). Serious adverse events occurred in 21.3% of patients in the ribociclib group and 11.8% in the placebo group. Serious adverse events were attributed to the study drug in 7.5% of the ribociclib group and 1.5% of the placebo group. The most common adverse events were myelosuppression, nausea, fatigue and diarrhea. Grade 3 and 4 neutropenia was noted in 59.3% in the ribociclib group versus < 1% in the placebo arm. The discontinuation rate due to adverse events in the ribociclib and placebo groups was 7.5% versus 2.1%, respectively. The most common reason for discontinuation was disease progression in 26% in the ribociclib group and 43.7% in the placebo group. Three deaths occurred in the ribociclib group and one in the placebo group. Interruptions in ribociclib occurred in 76.9% of patients. Dose reductions occurred in 53.9% of patients in the ribociclib group versus 7% in the placebo group. The most common reason a dose reduction occurred was neutropenia.

Conclusion. First-line treatment with ribociclib plus letrozole in postmenopausal women with HR-positive, HER-2 negative advanced breast cancer was associated with significantly longer progression-free survival compared with letrozole plus placebo. The improved progression-free survival was seen across all subgroups.

Commentary

Nearly 80% of all breast cancers express hormone receptor positivity. Hormonal therapy has been an important component of treatment for women with hormone-positive breast cancer in both the local and metastatic setting. Many tumors will eventually develop resistance to such therapy with the median progression-free survival with first-line endocrine therapy alone being around 9 months [2]. Cyclin dependent kinases 4 and 6 (CDK4/6) play an important role in estrogen-receptor signaling and cell cycle progression. CDK 4/6 mediates progression through the cell cycle from G1 to S phase via phosphorylation and inactivation of the retinoblastoma tumor suppressor protein [3]. Overexpression of CDK 4/6 in hormone receptor positive breast cancer is thought to play an important role in the development of endocrine therapy resistance [4].

The previously published PALOMA-2 trial, which compared treatment with the CDK 4/6 inhibitor palbociclib plus letrozole with letrozole alone, reported a significant improvement in progression-free survival with the addition of palbociclib (24.8 months vs. 14.5 months) in the front-line setting for women with advanced, hormone-positive breast cancer [5]. The improved progression-free survival with palbociclib was seen across all subgroups with a favorable toxicity profile. The current study represents the second randomized trial to show that the addition of CDK4/6 inhibitor to endocrine-based therapy significantly improves progression-free survival. This benefit was also seen across all patient subgroups including those with liver and lung metastases. In addition, the combination of ribociclib and letrozole also show significantly higher rates of overall response compared with placebo. In general, the addition of ribociclib to letrozole was well tolerated with a very low rate (7.5%) of discontinuation of therapy. Although neutropenia was a frequent complication in the ribociclib group febrile neutropenia occurred in only 1.5% of patients.

The incorporation of CDK4/6 inhibitors to endocrine-based therapy in the front-line setting has proven effective with an impressive early separation of the progression-free survival curves. Both the PALOMA-2 trial and the current MONALEESA-2 trial have shown similar results with approximately 40% improvement in progression-free survival. Whether the results seen in these trials will translate into an improvement in overall survival is yet to be determined. The results of these 2 trial suggest that CDK4/6 inhibitors have activity in both patients who have not received previous treatment with endocrine therapy and in those who received adjuvant endocrine therapy with late (> 12 months) relapse. Further determination of the subset of women who would benefit from the addition of CDK4/6 inhibitors remains an important clinical question. There are currently no clinical biomarkers that can be used to predict whether a patient would benefit from the addition of these medications.

Applications for Clinical Practice

The results of the current trial represent an exciting step forward in the treatment of advanced breast cancer. Palbociclib in combination with endocrine therapy is currently incorporated into clinical practice. The cost of these agents remains a concern; however, most insurance policies will cover them. Clinical trials are ongoing in the neoadjuvant and adjuvant setting for early breast cancer.

—Daniel Isaac, DO, MS

Study Overview

Objective. To evaluate the efficacy and safety of the CDK4/6 inhibitor ribociclib in combination with letrozole as initial therapy in patients with hormone-receptor (HR)–positive, human epidermal growth factor receptor 2 (HER-2)–negative advanced breast cancer.

Design. Pre-planned interim analysis of a randomized, double-blind, phase 3 clinical trial.

Setting and participants. This study enrolled patients in 29 countries at 223 centers. A total of 668 postmenopausal women underwent randomization, with 334 assigned to receive ribociclib plus letrozole and 334 assigned to receive placebo plus letrozole. All women had HR-positive, HER-2 negative recurrent or metastatic breast cancer and had not received prior systemic therapy. Enrolled patients had either measurable disease on imaging or at least 1 lytic bone lesion. All patients were required to have an Eastern Cooperative Oncology Group performance status of 0 or 1. Patients were excluded if they had received prior therapy with a CDK4/6 inhibitor, previous systemic chemotherapy or endocrine therapy. If a patient received an aromatase inhibitor for neoadjuvant or adjuvant therapy, the disease-free interval needed to be more than 12 months to be included in the study. Patients with inflammatory breast cancer or central nervous system involvement were also excluded. Normal cardiac function (normal QT interval) was required for enrollment. The randomization was stratified by presence of liver or lung metastases.

Intervention. The patients were randomized to oral ribociclib 600 mg per day 3 weeks on, 1 week off in a 28-day treatment cycle plus letrozole 2.5 mg daily or placebo plus letrozole. The dosing of ribociclib was based on a prior phase 1 study [1]. Treatment was continued until disease progression, unacceptable toxicity, discontinuation, or death. Dose reductions of ribociclib were allowed; however, dose reductions of letrozole were not permitted. Crossover between treatment arms was not allowed. Patients were assessed with computed tomo-graphy at the time of randomization, every 8 weeks for the first 18 months and every 12 weeks there-after. Patients were monitored for hematological toxicity each cycle. Electrocardiographic assessment was done at screening, on day 15 of cycle 1 and on day 1 of all subsequent cycles to monitor for QT prolongation.

Main outcome measures. The primary outcome was progression-free survival. The secondary outcomes were overall survival, overall response rate (complete or partial response), clinical benefit rate, and safety. Clinical benefit rate was defined as overall response plus stable disease lasting 24 weeks or more. A prespecified interim analysis was planned after disease progression or death was reported in 211 of 302 patients (70%).

Results. The baseline characteristics were balanced between the 2 groups. Visceral disease was present in 58.8% and bone-only disease in 22% of the patients. The median duration of therapy exposure was 13 months in the ribociclib group and 12.4 months in the placebo group. The median duration of follow-up was 15.3 months. After 18 months, progression-free survival was 63% (95% confidence interval [CI], 54.6 to 70.3) in the ribociclib/letrozole group versus 42.2% (95% CI, 34.8 to 49.5) in the placebo group (P < 0.001). The median progression-free survival was not met in the combination group (95% CI, 19.3 to not reached) versus 14.7 months (95% CI, 13.0 to 16.5) in the placebo group. The improved progression-free survival was seen across all subgroups. The overall response rate was higher in the combination arm (52.7% vs. 37.1%) as was the clinical benefit rate (80.1% vs. 71.8%). Serious adverse events occurred in 21.3% of patients in the ribociclib group and 11.8% in the placebo group. Serious adverse events were attributed to the study drug in 7.5% of the ribociclib group and 1.5% of the placebo group. The most common adverse events were myelosuppression, nausea, fatigue and diarrhea. Grade 3 and 4 neutropenia was noted in 59.3% in the ribociclib group versus < 1% in the placebo arm. The discontinuation rate due to adverse events in the ribociclib and placebo groups was 7.5% versus 2.1%, respectively. The most common reason for discontinuation was disease progression in 26% in the ribociclib group and 43.7% in the placebo group. Three deaths occurred in the ribociclib group and one in the placebo group. Interruptions in ribociclib occurred in 76.9% of patients. Dose reductions occurred in 53.9% of patients in the ribociclib group versus 7% in the placebo group. The most common reason a dose reduction occurred was neutropenia.

Conclusion. First-line treatment with ribociclib plus letrozole in postmenopausal women with HR-positive, HER-2 negative advanced breast cancer was associated with significantly longer progression-free survival compared with letrozole plus placebo. The improved progression-free survival was seen across all subgroups.

Commentary

Nearly 80% of all breast cancers express hormone receptor positivity. Hormonal therapy has been an important component of treatment for women with hormone-positive breast cancer in both the local and metastatic setting. Many tumors will eventually develop resistance to such therapy with the median progression-free survival with first-line endocrine therapy alone being around 9 months [2]. Cyclin dependent kinases 4 and 6 (CDK4/6) play an important role in estrogen-receptor signaling and cell cycle progression. CDK 4/6 mediates progression through the cell cycle from G1 to S phase via phosphorylation and inactivation of the retinoblastoma tumor suppressor protein [3]. Overexpression of CDK 4/6 in hormone receptor positive breast cancer is thought to play an important role in the development of endocrine therapy resistance [4].

The previously published PALOMA-2 trial, which compared treatment with the CDK 4/6 inhibitor palbociclib plus letrozole with letrozole alone, reported a significant improvement in progression-free survival with the addition of palbociclib (24.8 months vs. 14.5 months) in the front-line setting for women with advanced, hormone-positive breast cancer [5]. The improved progression-free survival with palbociclib was seen across all subgroups with a favorable toxicity profile. The current study represents the second randomized trial to show that the addition of CDK4/6 inhibitor to endocrine-based therapy significantly improves progression-free survival. This benefit was also seen across all patient subgroups including those with liver and lung metastases. In addition, the combination of ribociclib and letrozole also show significantly higher rates of overall response compared with placebo. In general, the addition of ribociclib to letrozole was well tolerated with a very low rate (7.5%) of discontinuation of therapy. Although neutropenia was a frequent complication in the ribociclib group febrile neutropenia occurred in only 1.5% of patients.

The incorporation of CDK4/6 inhibitors to endocrine-based therapy in the front-line setting has proven effective with an impressive early separation of the progression-free survival curves. Both the PALOMA-2 trial and the current MONALEESA-2 trial have shown similar results with approximately 40% improvement in progression-free survival. Whether the results seen in these trials will translate into an improvement in overall survival is yet to be determined. The results of these 2 trial suggest that CDK4/6 inhibitors have activity in both patients who have not received previous treatment with endocrine therapy and in those who received adjuvant endocrine therapy with late (> 12 months) relapse. Further determination of the subset of women who would benefit from the addition of CDK4/6 inhibitors remains an important clinical question. There are currently no clinical biomarkers that can be used to predict whether a patient would benefit from the addition of these medications.

Applications for Clinical Practice

The results of the current trial represent an exciting step forward in the treatment of advanced breast cancer. Palbociclib in combination with endocrine therapy is currently incorporated into clinical practice. The cost of these agents remains a concern; however, most insurance policies will cover them. Clinical trials are ongoing in the neoadjuvant and adjuvant setting for early breast cancer.

—Daniel Isaac, DO, MS

Study Overview

Objective. To evaluate the efficacy and safety of the CDK4/6 inhibitor ribociclib in combination with letrozole as initial therapy in patients with hormone-receptor (HR)–positive, human epidermal growth factor receptor 2 (HER-2)–negative advanced breast cancer.

Design. Pre-planned interim analysis of a randomized, double-blind, phase 3 clinical trial.

Setting and participants. This study enrolled patients in 29 countries at 223 centers. A total of 668 postmenopausal women underwent randomization, with 334 assigned to receive ribociclib plus letrozole and 334 assigned to receive placebo plus letrozole. All women had HR-positive, HER-2 negative recurrent or metastatic breast cancer and had not received prior systemic therapy. Enrolled patients had either measurable disease on imaging or at least 1 lytic bone lesion. All patients were required to have an Eastern Cooperative Oncology Group performance status of 0 or 1. Patients were excluded if they had received prior therapy with a CDK4/6 inhibitor, previous systemic chemotherapy or endocrine therapy. If a patient received an aromatase inhibitor for neoadjuvant or adjuvant therapy, the disease-free interval needed to be more than 12 months to be included in the study. Patients with inflammatory breast cancer or central nervous system involvement were also excluded. Normal cardiac function (normal QT interval) was required for enrollment. The randomization was stratified by presence of liver or lung metastases.

Intervention. The patients were randomized to oral ribociclib 600 mg per day 3 weeks on, 1 week off in a 28-day treatment cycle plus letrozole 2.5 mg daily or placebo plus letrozole. The dosing of ribociclib was based on a prior phase 1 study [1]. Treatment was continued until disease progression, unacceptable toxicity, discontinuation, or death. Dose reductions of ribociclib were allowed; however, dose reductions of letrozole were not permitted. Crossover between treatment arms was not allowed. Patients were assessed with computed tomo-graphy at the time of randomization, every 8 weeks for the first 18 months and every 12 weeks there-after. Patients were monitored for hematological toxicity each cycle. Electrocardiographic assessment was done at screening, on day 15 of cycle 1 and on day 1 of all subsequent cycles to monitor for QT prolongation.

Main outcome measures. The primary outcome was progression-free survival. The secondary outcomes were overall survival, overall response rate (complete or partial response), clinical benefit rate, and safety. Clinical benefit rate was defined as overall response plus stable disease lasting 24 weeks or more. A prespecified interim analysis was planned after disease progression or death was reported in 211 of 302 patients (70%).

Results. The baseline characteristics were balanced between the 2 groups. Visceral disease was present in 58.8% and bone-only disease in 22% of the patients. The median duration of therapy exposure was 13 months in the ribociclib group and 12.4 months in the placebo group. The median duration of follow-up was 15.3 months. After 18 months, progression-free survival was 63% (95% confidence interval [CI], 54.6 to 70.3) in the ribociclib/letrozole group versus 42.2% (95% CI, 34.8 to 49.5) in the placebo group (P < 0.001). The median progression-free survival was not met in the combination group (95% CI, 19.3 to not reached) versus 14.7 months (95% CI, 13.0 to 16.5) in the placebo group. The improved progression-free survival was seen across all subgroups. The overall response rate was higher in the combination arm (52.7% vs. 37.1%) as was the clinical benefit rate (80.1% vs. 71.8%). Serious adverse events occurred in 21.3% of patients in the ribociclib group and 11.8% in the placebo group. Serious adverse events were attributed to the study drug in 7.5% of the ribociclib group and 1.5% of the placebo group. The most common adverse events were myelosuppression, nausea, fatigue and diarrhea. Grade 3 and 4 neutropenia was noted in 59.3% in the ribociclib group versus < 1% in the placebo arm. The discontinuation rate due to adverse events in the ribociclib and placebo groups was 7.5% versus 2.1%, respectively. The most common reason for discontinuation was disease progression in 26% in the ribociclib group and 43.7% in the placebo group. Three deaths occurred in the ribociclib group and one in the placebo group. Interruptions in ribociclib occurred in 76.9% of patients. Dose reductions occurred in 53.9% of patients in the ribociclib group versus 7% in the placebo group. The most common reason a dose reduction occurred was neutropenia.

Conclusion. First-line treatment with ribociclib plus letrozole in postmenopausal women with HR-positive, HER-2 negative advanced breast cancer was associated with significantly longer progression-free survival compared with letrozole plus placebo. The improved progression-free survival was seen across all subgroups.

Commentary

Nearly 80% of all breast cancers express hormone receptor positivity. Hormonal therapy has been an important component of treatment for women with hormone-positive breast cancer in both the local and metastatic setting. Many tumors will eventually develop resistance to such therapy with the median progression-free survival with first-line endocrine therapy alone being around 9 months [2]. Cyclin dependent kinases 4 and 6 (CDK4/6) play an important role in estrogen-receptor signaling and cell cycle progression. CDK 4/6 mediates progression through the cell cycle from G1 to S phase via phosphorylation and inactivation of the retinoblastoma tumor suppressor protein [3]. Overexpression of CDK 4/6 in hormone receptor positive breast cancer is thought to play an important role in the development of endocrine therapy resistance [4].

The previously published PALOMA-2 trial, which compared treatment with the CDK 4/6 inhibitor palbociclib plus letrozole with letrozole alone, reported a significant improvement in progression-free survival with the addition of palbociclib (24.8 months vs. 14.5 months) in the front-line setting for women with advanced, hormone-positive breast cancer [5]. The improved progression-free survival with palbociclib was seen across all subgroups with a favorable toxicity profile. The current study represents the second randomized trial to show that the addition of CDK4/6 inhibitor to endocrine-based therapy significantly improves progression-free survival. This benefit was also seen across all patient subgroups including those with liver and lung metastases. In addition, the combination of ribociclib and letrozole also show significantly higher rates of overall response compared with placebo. In general, the addition of ribociclib to letrozole was well tolerated with a very low rate (7.5%) of discontinuation of therapy. Although neutropenia was a frequent complication in the ribociclib group febrile neutropenia occurred in only 1.5% of patients.

The incorporation of CDK4/6 inhibitors to endocrine-based therapy in the front-line setting has proven effective with an impressive early separation of the progression-free survival curves. Both the PALOMA-2 trial and the current MONALEESA-2 trial have shown similar results with approximately 40% improvement in progression-free survival. Whether the results seen in these trials will translate into an improvement in overall survival is yet to be determined. The results of these 2 trial suggest that CDK4/6 inhibitors have activity in both patients who have not received previous treatment with endocrine therapy and in those who received adjuvant endocrine therapy with late (> 12 months) relapse. Further determination of the subset of women who would benefit from the addition of CDK4/6 inhibitors remains an important clinical question. There are currently no clinical biomarkers that can be used to predict whether a patient would benefit from the addition of these medications.

Applications for Clinical Practice

The results of the current trial represent an exciting step forward in the treatment of advanced breast cancer. Palbociclib in combination with endocrine therapy is currently incorporated into clinical practice. The cost of these agents remains a concern; however, most insurance policies will cover them. Clinical trials are ongoing in the neoadjuvant and adjuvant setting for early breast cancer.

—Daniel Isaac, DO, MS

Study Overview

Objective. To evaluate whether higher BMI alone contributes to risk of cardiovascular disease (CVD) and death.

Study design. Cohort study of weight-discordant monozygotic twin pairs

Setting and participants. This study took place in Sweden, using a subset of data from the Swedish Twin Registry and the Screening Across Lifespan Twin (SALT) study, which aimed to screen Swedish twins born prior to 1958 for the development of “common complex diseases.” From a total of 44,820 individuals, the current study limited to a subset of 4046 monozygotic twin pairs where both twins had self-reported height and weight data, and where calculated body mass index (BMI) was discordant between the twins, defined as a difference > 0.01 kg/m². No other inclusion or exclusion criteria are mentioned. Data for the study were collected from several different sources, including telephone interviews (eg, height and weight, behaviors such as physical activity and smoking), national registries on health conditions (eg, myocardial infarction [MI], stroke, diabetes) or prescriptions (eg, diabetes medications), the national causes of death register, and a nationwide database containing socioeconomic variables (eg, income and education). The primary exposure of interest for this study was weight status, categorized as “leaner” or “heavier,” depending on the relative BMI of each twin in a given pair. “Leaner” twins were assumed to have lower adiposity than their “heavier” counterparts, and yet to have identical genetic makeup, thereby allowing the authors to eliminate the contribution of genetic confounding in evaluating the relationship between weight status and CVD risk. The classification system could mean that one person with a BMI of 26 kg/m² would be placed in the “leaner” category if their twin had a BMI of 28, while someone else in another twin pair but also with a BMI of 26 kg/m² might be classified in the “heavier” category if their twin had a BMI of 22. Twin pairs were followed for up to 15 years to assess for incident outcomes of interest, with baseline data collected between 1998 and 2002, and follow-up through 2013.

Main outcome measures. The primary outcome of interest was the occurrence of incident MI or death from any cause. As above, these outcomes were assessed using national disease and death registries spanning 1987-2013, and ICD-9 or -10 codes of interest. A secondary outcome of incident diabetes was also specified, presumably limited to development of type 2 diabetes mellitus, and identified using the same datasets, as well as the national prescription registry. Kaplan-Meier curves for incident MI and death were constructed comparing all “leaner” twins against all “heavier” twins, and Cox proportional hazards modeling was used to compare the hazard of the primary composite outcome between groups. Logistic regression was used to evaluate the odds of each outcome including diabetes incidence, and several models were built, ranging from an unadjusted model to one adjusting for a number of lifestyle factors (eg, smoking status, physical activity), baseline health conditions, and sociodemographic factors.

The authors separately examined risk of MI/death in the subgroup of twins where the “heavier” twin had a BMI ≤ 24.9 kg/m² at baseline (ie, despite being labeled “heavier” they still had a technically normal BMI), and examined the impact of weight trajectory prior to the defined baseline (eg, they were able to incorporate into models whether someone had been actively gaining or losing weight over time prior to the baseline exposure categorization). The authors also conducted several sensitivity analyses, including running models excluding twins with < 1 year of follow-up in an effort to insure that results of the main analysis were not biased due to differential loss to follow-up between exposure categories.

Results. Of the 4046 twin pairs in this study, 56% (2283 pairs) were female, and mean (SD) age at baseline was 57.6 (9.5) years. Race/ethnicity was not reported but presumably the vast majority, if not all, are non-Hispanic white, based on the country of origin. In comparing the group of “heavier” twins to “leaner” twins, several important baseline differences were found. By design, the “heavier” twins had significantly higher mean (SD) BMI at study baseline (25.9 [3.6] kg/m² vs. 23.9 [3.1] kg/m²) and reported greater increases in BMI over the 15–20 years preceding baseline (change since 1973 was +4.3 [2.9] BMI units for “heavier” twins, vs. +2.6 [2.6] for “leaner” twins). Smoking status differed significantly between groups, with 15% of “heavier” twins reporting they were current smokers versus ~21% of “leaner” twins. “Leaner” twins were also slightly more active than their “heavier” counterparts (50.4% reported getting “rather much or very much” exercise versus 46.5%). The groups were otherwise very similar with respect to marital status, educational level, income, and baseline diagnoses of MI, stroke, diabetes, cancer or alcohol abuse.

In fully adjusted models over a mean (SD) 12.4 (2.5)-year follow-up, “heavier” twins had a significantly lower odds of MI or death (combined) than “leaner” twins (odds ratio [OR] 0.75, 95% CI 0.63–0.91). Because the “heavier” vs. “leaner” dichotomy did not map to clinical definitions of overweight or obesity, the investigators also examined this primary outcome among subgroups with more clinical relevance. Being “heavier” actually had the greatest protective effect against MI/death (OR 0.61, 95% CI 0.46–0.80) among pairs where the so-called “heavier” twin had a normal BMI (< 25.0 kg/m²), and this subgroup appeared to be driving the overall finding of lower odds of MI/death in the “heavier” group as a whole. This pattern was underscored when examining the subgroup of twin pairs where the “heavier” twin had a BMI ≥ 30 kg/m² at baseline – in this group the protective effect of being “heavier” disappeared (OR 0.92, 95% CI 0.60 to 1.42). Besides not always reflecting clinically relevant weight categories, the “heavier” vs. “leaner” twin dichotomy could, in some cases, amount to a very small difference in BMI between twins (anything > 0.01 unit counted as discordant). As such, the investigators sought to examine whether their results held up when looking at pairs with a higher threshold for BMI discordance (1.0 to 7.0 units or more difference between twins), finding that risk of MI or death did not increase among the “heavier” group in these more widely split twin pairs, even when adjusting for smoking status and physical activity.

In contrast to the MI/mortality analyses, “heavier” twins did have significantly greater odds of developing diabetes during follow-up compared to their “leaner” counterparts (OR 1.94, 95% CI 1.51 to 2.48, adjusted for smoking and physical activity). Also unlike the MI/death analyses, this relationship of increased diabetes risk among “heavier” twins was enhanced by increasing BMI dissimilarity between twins, and among twins who had been gaining weight prior to baseline BMI measurement.

Sensitivity analyses excluding twins with less than 1 year of follow-up did not result in changes to the main findings—“heavier” twins still had similar odds of MI/death as “leaner” twins.

Conclusion. The authors conclude that among monozygotic twin pairs, where the possibility for genetic confounding has been eliminated, obesity is not causally associated with increased risk of MI or death, although the results do support an increased risk of developing incident diabetes among individuals with higher BMI.

Commentary

Obesity is a known risk factor for many chronic conditions, including diabetes, osteoarthritis, sleep apnea, and hypertension [1]. However, the relationship between obesity and cardiovascular outcomes, particularly coronary artery disease and death from heart disease, has been more controversial. Some epidemiologic studies have demonstrated reduced mortality risk among patients with obesity and heart failure, and even among those with established coronary artery disease—the so-called “obesity paradox” [2]. Others have observed that overweight older adults may have lower overall mortality compared to their normal weight counterparts [3]. On the other hand, it is known that obesity increases risk for diabetes, which is itself a clear and proven risk factor for CVD and death.

As the authors of the current study point out, genetic confounding may be a potential reason for the conflicting results produced in studies of the obesity–CVD risk relationship. In other words, patients who have genes that promote weight gain may also have genes that promote CVD, through pathways independent of excess adipose tissue, with these hidden pathways acting as confounders of the obesity–CVD relationship. By studying monozygotic twin pairs, who have identical genetic makeup but have developed differential weight status due to different environmental exposures, the investigators designed a study that would eliminate any genetic confounding and allow them to better isolate the relationship between higher BMI and CVD. This is an important topic area because, at a population level, we are faced with an immense number of adults who have obesity. Treatment of this condition is resource intense and it is critical that patients and health care systems understand the potential risk reduction that will be achieved with sustained weight loss.

The strengths of this study include the use of a very unique dataset with longitudinal measures on a large number of monozygotic twin pairs, and the authors’ ability to link this dataset with nationwide comprehensive datasets on health conditions, health care use (pharmacy), sociodemographics, and death. Sweden’s national registries are quite impressive and permit these types of studies in a way that would be very difficult to achieve in the United States, with its innumerable separate health care systems and few data sources that contain information on all citizens. Because of these multiple data sources, the authors were able to adjust for some important lifestyle factors that could easily confound the weight status-MI/death relationship, such as smoking and physical activity. Additionally, their models were able to factor in trajectory of weight on some individuals prior to baseline, rather than viewing baseline weight only as a “snapshot” which could risk missing an important trend of weight gain or loss over time, with important health implications.

There are several limitations of the study that are worth reviewing. First, and most importantly, as pointed out in a commentary associated with the article, the categorization of “leaner” and “heavier” can be somewhat misleading if the true question is whether or not excess adiposity is an independent driver of cardiovascular risk [4]. BMI, at the individual level, is not an ideal measure of adiposity and it does not speak to distribution of fat tissue, which is critically important in evaluating CVD risk [5]. For example, 2 siblings could have identical BMIs, but one might have significantly more lean mass in their legs and buttocks, and the other could have more central adipose tissue, translating to a much higher cardiovascular risk. Measures such as waist circumference are critical factors in addition to BMI to better understand an individual’s adipose tissue volume and distribution.

Although the authors did adjust for some self-reported behaviors that are important predictors of CVD (smoking, exercise), there is still potential for confounding due to unscreened or unreported exposures that differ systematically between “leaner” and “heavier” twins. Of note, smoking status—probably the single most important risk factor for CVD—was missing in 13% of the cohort, and no imputation techniques were used for missing data. Another limitation of this study is that its generalizability to more racial/ethnically diverse populations may be limited. Presumably, the patients in this study were non-Hispanic white Swedes, and whether or not these findings would be replicated in other groups, such as those of African or Asian ancestry, is not known.

Finally, the finding that “heavier” twins had greater odds of developing diabetes during follow-up is certainly consistent with existing literature. However, it is also known that diabetes is a strong risk factor for the development of CVD, including MI, and for death [6]. This raises the question of why the authors observed an increased diabetes risk yet no change in MI/death rates among heavier twins. Most likely the discrepancy is due to inadequate follow-up time of incident diabetes cases. Complications of diabetes can take a number of years to materialize, and, with an average of 12 years’ total follow-up in this study, there simply may not have been time to observe an increased risk of MI/death in heavier twins.

Applications for Clinical Practice

For patients interested in weight loss as a way of reducing CVD risk, this paper does not support the notion that lower body weight alone exerts direct influence on this endpoint. However, it reinforces the link between higher body weight and diabetes, which is a clear risk factor for CVD. Therefore, it still seems reasonable to advise patients who are at risk of diabetes that improving dietary quality, increasing cardiorespiratory fitness, and losing weight can reduce their long-term risk of CVD, even if indirectly so.

—Kristina Lewis, MD, MPH

Study Overview

Objective. To evaluate whether higher BMI alone contributes to risk of cardiovascular disease (CVD) and death.

Study design. Cohort study of weight-discordant monozygotic twin pairs

Setting and participants. This study took place in Sweden, using a subset of data from the Swedish Twin Registry and the Screening Across Lifespan Twin (SALT) study, which aimed to screen Swedish twins born prior to 1958 for the development of “common complex diseases.” From a total of 44,820 individuals, the current study limited to a subset of 4046 monozygotic twin pairs where both twins had self-reported height and weight data, and where calculated body mass index (BMI) was discordant between the twins, defined as a difference > 0.01 kg/m². No other inclusion or exclusion criteria are mentioned. Data for the study were collected from several different sources, including telephone interviews (eg, height and weight, behaviors such as physical activity and smoking), national registries on health conditions (eg, myocardial infarction [MI], stroke, diabetes) or prescriptions (eg, diabetes medications), the national causes of death register, and a nationwide database containing socioeconomic variables (eg, income and education). The primary exposure of interest for this study was weight status, categorized as “leaner” or “heavier,” depending on the relative BMI of each twin in a given pair. “Leaner” twins were assumed to have lower adiposity than their “heavier” counterparts, and yet to have identical genetic makeup, thereby allowing the authors to eliminate the contribution of genetic confounding in evaluating the relationship between weight status and CVD risk. The classification system could mean that one person with a BMI of 26 kg/m² would be placed in the “leaner” category if their twin had a BMI of 28, while someone else in another twin pair but also with a BMI of 26 kg/m² might be classified in the “heavier” category if their twin had a BMI of 22. Twin pairs were followed for up to 15 years to assess for incident outcomes of interest, with baseline data collected between 1998 and 2002, and follow-up through 2013.

Main outcome measures. The primary outcome of interest was the occurrence of incident MI or death from any cause. As above, these outcomes were assessed using national disease and death registries spanning 1987-2013, and ICD-9 or -10 codes of interest. A secondary outcome of incident diabetes was also specified, presumably limited to development of type 2 diabetes mellitus, and identified using the same datasets, as well as the national prescription registry. Kaplan-Meier curves for incident MI and death were constructed comparing all “leaner” twins against all “heavier” twins, and Cox proportional hazards modeling was used to compare the hazard of the primary composite outcome between groups. Logistic regression was used to evaluate the odds of each outcome including diabetes incidence, and several models were built, ranging from an unadjusted model to one adjusting for a number of lifestyle factors (eg, smoking status, physical activity), baseline health conditions, and sociodemographic factors.

The authors separately examined risk of MI/death in the subgroup of twins where the “heavier” twin had a BMI ≤ 24.9 kg/m² at baseline (ie, despite being labeled “heavier” they still had a technically normal BMI), and examined the impact of weight trajectory prior to the defined baseline (eg, they were able to incorporate into models whether someone had been actively gaining or losing weight over time prior to the baseline exposure categorization). The authors also conducted several sensitivity analyses, including running models excluding twins with < 1 year of follow-up in an effort to insure that results of the main analysis were not biased due to differential loss to follow-up between exposure categories.

Results. Of the 4046 twin pairs in this study, 56% (2283 pairs) were female, and mean (SD) age at baseline was 57.6 (9.5) years. Race/ethnicity was not reported but presumably the vast majority, if not all, are non-Hispanic white, based on the country of origin. In comparing the group of “heavier” twins to “leaner” twins, several important baseline differences were found. By design, the “heavier” twins had significantly higher mean (SD) BMI at study baseline (25.9 [3.6] kg/m² vs. 23.9 [3.1] kg/m²) and reported greater increases in BMI over the 15–20 years preceding baseline (change since 1973 was +4.3 [2.9] BMI units for “heavier” twins, vs. +2.6 [2.6] for “leaner” twins). Smoking status differed significantly between groups, with 15% of “heavier” twins reporting they were current smokers versus ~21% of “leaner” twins. “Leaner” twins were also slightly more active than their “heavier” counterparts (50.4% reported getting “rather much or very much” exercise versus 46.5%). The groups were otherwise very similar with respect to marital status, educational level, income, and baseline diagnoses of MI, stroke, diabetes, cancer or alcohol abuse.

In fully adjusted models over a mean (SD) 12.4 (2.5)-year follow-up, “heavier” twins had a significantly lower odds of MI or death (combined) than “leaner” twins (odds ratio [OR] 0.75, 95% CI 0.63–0.91). Because the “heavier” vs. “leaner” dichotomy did not map to clinical definitions of overweight or obesity, the investigators also examined this primary outcome among subgroups with more clinical relevance. Being “heavier” actually had the greatest protective effect against MI/death (OR 0.61, 95% CI 0.46–0.80) among pairs where the so-called “heavier” twin had a normal BMI (< 25.0 kg/m²), and this subgroup appeared to be driving the overall finding of lower odds of MI/death in the “heavier” group as a whole. This pattern was underscored when examining the subgroup of twin pairs where the “heavier” twin had a BMI ≥ 30 kg/m² at baseline – in this group the protective effect of being “heavier” disappeared (OR 0.92, 95% CI 0.60 to 1.42). Besides not always reflecting clinically relevant weight categories, the “heavier” vs. “leaner” twin dichotomy could, in some cases, amount to a very small difference in BMI between twins (anything > 0.01 unit counted as discordant). As such, the investigators sought to examine whether their results held up when looking at pairs with a higher threshold for BMI discordance (1.0 to 7.0 units or more difference between twins), finding that risk of MI or death did not increase among the “heavier” group in these more widely split twin pairs, even when adjusting for smoking status and physical activity.

In contrast to the MI/mortality analyses, “heavier” twins did have significantly greater odds of developing diabetes during follow-up compared to their “leaner” counterparts (OR 1.94, 95% CI 1.51 to 2.48, adjusted for smoking and physical activity). Also unlike the MI/death analyses, this relationship of increased diabetes risk among “heavier” twins was enhanced by increasing BMI dissimilarity between twins, and among twins who had been gaining weight prior to baseline BMI measurement.

Sensitivity analyses excluding twins with less than 1 year of follow-up did not result in changes to the main findings—“heavier” twins still had similar odds of MI/death as “leaner” twins.

Conclusion. The authors conclude that among monozygotic twin pairs, where the possibility for genetic confounding has been eliminated, obesity is not causally associated with increased risk of MI or death, although the results do support an increased risk of developing incident diabetes among individuals with higher BMI.

Commentary

Obesity is a known risk factor for many chronic conditions, including diabetes, osteoarthritis, sleep apnea, and hypertension [1]. However, the relationship between obesity and cardiovascular outcomes, particularly coronary artery disease and death from heart disease, has been more controversial. Some epidemiologic studies have demonstrated reduced mortality risk among patients with obesity and heart failure, and even among those with established coronary artery disease—the so-called “obesity paradox” [2]. Others have observed that overweight older adults may have lower overall mortality compared to their normal weight counterparts [3]. On the other hand, it is known that obesity increases risk for diabetes, which is itself a clear and proven risk factor for CVD and death.

As the authors of the current study point out, genetic confounding may be a potential reason for the conflicting results produced in studies of the obesity–CVD risk relationship. In other words, patients who have genes that promote weight gain may also have genes that promote CVD, through pathways independent of excess adipose tissue, with these hidden pathways acting as confounders of the obesity–CVD relationship. By studying monozygotic twin pairs, who have identical genetic makeup but have developed differential weight status due to different environmental exposures, the investigators designed a study that would eliminate any genetic confounding and allow them to better isolate the relationship between higher BMI and CVD. This is an important topic area because, at a population level, we are faced with an immense number of adults who have obesity. Treatment of this condition is resource intense and it is critical that patients and health care systems understand the potential risk reduction that will be achieved with sustained weight loss.

The strengths of this study include the use of a very unique dataset with longitudinal measures on a large number of monozygotic twin pairs, and the authors’ ability to link this dataset with nationwide comprehensive datasets on health conditions, health care use (pharmacy), sociodemographics, and death. Sweden’s national registries are quite impressive and permit these types of studies in a way that would be very difficult to achieve in the United States, with its innumerable separate health care systems and few data sources that contain information on all citizens. Because of these multiple data sources, the authors were able to adjust for some important lifestyle factors that could easily confound the weight status-MI/death relationship, such as smoking and physical activity. Additionally, their models were able to factor in trajectory of weight on some individuals prior to baseline, rather than viewing baseline weight only as a “snapshot” which could risk missing an important trend of weight gain or loss over time, with important health implications.

There are several limitations of the study that are worth reviewing. First, and most importantly, as pointed out in a commentary associated with the article, the categorization of “leaner” and “heavier” can be somewhat misleading if the true question is whether or not excess adiposity is an independent driver of cardiovascular risk [4]. BMI, at the individual level, is not an ideal measure of adiposity and it does not speak to distribution of fat tissue, which is critically important in evaluating CVD risk [5]. For example, 2 siblings could have identical BMIs, but one might have significantly more lean mass in their legs and buttocks, and the other could have more central adipose tissue, translating to a much higher cardiovascular risk. Measures such as waist circumference are critical factors in addition to BMI to better understand an individual’s adipose tissue volume and distribution.

Although the authors did adjust for some self-reported behaviors that are important predictors of CVD (smoking, exercise), there is still potential for confounding due to unscreened or unreported exposures that differ systematically between “leaner” and “heavier” twins. Of note, smoking status—probably the single most important risk factor for CVD—was missing in 13% of the cohort, and no imputation techniques were used for missing data. Another limitation of this study is that its generalizability to more racial/ethnically diverse populations may be limited. Presumably, the patients in this study were non-Hispanic white Swedes, and whether or not these findings would be replicated in other groups, such as those of African or Asian ancestry, is not known.

Finally, the finding that “heavier” twins had greater odds of developing diabetes during follow-up is certainly consistent with existing literature. However, it is also known that diabetes is a strong risk factor for the development of CVD, including MI, and for death [6]. This raises the question of why the authors observed an increased diabetes risk yet no change in MI/death rates among heavier twins. Most likely the discrepancy is due to inadequate follow-up time of incident diabetes cases. Complications of diabetes can take a number of years to materialize, and, with an average of 12 years’ total follow-up in this study, there simply may not have been time to observe an increased risk of MI/death in heavier twins.

Applications for Clinical Practice

For patients interested in weight loss as a way of reducing CVD risk, this paper does not support the notion that lower body weight alone exerts direct influence on this endpoint. However, it reinforces the link between higher body weight and diabetes, which is a clear risk factor for CVD. Therefore, it still seems reasonable to advise patients who are at risk of diabetes that improving dietary quality, increasing cardiorespiratory fitness, and losing weight can reduce their long-term risk of CVD, even if indirectly so.

—Kristina Lewis, MD, MPH

Study Overview

Objective. To evaluate whether higher BMI alone contributes to risk of cardiovascular disease (CVD) and death.

Study design. Cohort study of weight-discordant monozygotic twin pairs

Setting and participants. This study took place in Sweden, using a subset of data from the Swedish Twin Registry and the Screening Across Lifespan Twin (SALT) study, which aimed to screen Swedish twins born prior to 1958 for the development of “common complex diseases.” From a total of 44,820 individuals, the current study limited to a subset of 4046 monozygotic twin pairs where both twins had self-reported height and weight data, and where calculated body mass index (BMI) was discordant between the twins, defined as a difference > 0.01 kg/m². No other inclusion or exclusion criteria are mentioned. Data for the study were collected from several different sources, including telephone interviews (eg, height and weight, behaviors such as physical activity and smoking), national registries on health conditions (eg, myocardial infarction [MI], stroke, diabetes) or prescriptions (eg, diabetes medications), the national causes of death register, and a nationwide database containing socioeconomic variables (eg, income and education). The primary exposure of interest for this study was weight status, categorized as “leaner” or “heavier,” depending on the relative BMI of each twin in a given pair. “Leaner” twins were assumed to have lower adiposity than their “heavier” counterparts, and yet to have identical genetic makeup, thereby allowing the authors to eliminate the contribution of genetic confounding in evaluating the relationship between weight status and CVD risk. The classification system could mean that one person with a BMI of 26 kg/m² would be placed in the “leaner” category if their twin had a BMI of 28, while someone else in another twin pair but also with a BMI of 26 kg/m² might be classified in the “heavier” category if their twin had a BMI of 22. Twin pairs were followed for up to 15 years to assess for incident outcomes of interest, with baseline data collected between 1998 and 2002, and follow-up through 2013.

Main outcome measures. The primary outcome of interest was the occurrence of incident MI or death from any cause. As above, these outcomes were assessed using national disease and death registries spanning 1987-2013, and ICD-9 or -10 codes of interest. A secondary outcome of incident diabetes was also specified, presumably limited to development of type 2 diabetes mellitus, and identified using the same datasets, as well as the national prescription registry. Kaplan-Meier curves for incident MI and death were constructed comparing all “leaner” twins against all “heavier” twins, and Cox proportional hazards modeling was used to compare the hazard of the primary composite outcome between groups. Logistic regression was used to evaluate the odds of each outcome including diabetes incidence, and several models were built, ranging from an unadjusted model to one adjusting for a number of lifestyle factors (eg, smoking status, physical activity), baseline health conditions, and sociodemographic factors.

The authors separately examined risk of MI/death in the subgroup of twins where the “heavier” twin had a BMI ≤ 24.9 kg/m² at baseline (ie, despite being labeled “heavier” they still had a technically normal BMI), and examined the impact of weight trajectory prior to the defined baseline (eg, they were able to incorporate into models whether someone had been actively gaining or losing weight over time prior to the baseline exposure categorization). The authors also conducted several sensitivity analyses, including running models excluding twins with < 1 year of follow-up in an effort to insure that results of the main analysis were not biased due to differential loss to follow-up between exposure categories.

Results. Of the 4046 twin pairs in this study, 56% (2283 pairs) were female, and mean (SD) age at baseline was 57.6 (9.5) years. Race/ethnicity was not reported but presumably the vast majority, if not all, are non-Hispanic white, based on the country of origin. In comparing the group of “heavier” twins to “leaner” twins, several important baseline differences were found. By design, the “heavier” twins had significantly higher mean (SD) BMI at study baseline (25.9 [3.6] kg/m² vs. 23.9 [3.1] kg/m²) and reported greater increases in BMI over the 15–20 years preceding baseline (change since 1973 was +4.3 [2.9] BMI units for “heavier” twins, vs. +2.6 [2.6] for “leaner” twins). Smoking status differed significantly between groups, with 15% of “heavier” twins reporting they were current smokers versus ~21% of “leaner” twins. “Leaner” twins were also slightly more active than their “heavier” counterparts (50.4% reported getting “rather much or very much” exercise versus 46.5%). The groups were otherwise very similar with respect to marital status, educational level, income, and baseline diagnoses of MI, stroke, diabetes, cancer or alcohol abuse.

In fully adjusted models over a mean (SD) 12.4 (2.5)-year follow-up, “heavier” twins had a significantly lower odds of MI or death (combined) than “leaner” twins (odds ratio [OR] 0.75, 95% CI 0.63–0.91). Because the “heavier” vs. “leaner” dichotomy did not map to clinical definitions of overweight or obesity, the investigators also examined this primary outcome among subgroups with more clinical relevance. Being “heavier” actually had the greatest protective effect against MI/death (OR 0.61, 95% CI 0.46–0.80) among pairs where the so-called “heavier” twin had a normal BMI (< 25.0 kg/m²), and this subgroup appeared to be driving the overall finding of lower odds of MI/death in the “heavier” group as a whole. This pattern was underscored when examining the subgroup of twin pairs where the “heavier” twin had a BMI ≥ 30 kg/m² at baseline – in this group the protective effect of being “heavier” disappeared (OR 0.92, 95% CI 0.60 to 1.42). Besides not always reflecting clinically relevant weight categories, the “heavier” vs. “leaner” twin dichotomy could, in some cases, amount to a very small difference in BMI between twins (anything > 0.01 unit counted as discordant). As such, the investigators sought to examine whether their results held up when looking at pairs with a higher threshold for BMI discordance (1.0 to 7.0 units or more difference between twins), finding that risk of MI or death did not increase among the “heavier” group in these more widely split twin pairs, even when adjusting for smoking status and physical activity.

In contrast to the MI/mortality analyses, “heavier” twins did have significantly greater odds of developing diabetes during follow-up compared to their “leaner” counterparts (OR 1.94, 95% CI 1.51 to 2.48, adjusted for smoking and physical activity). Also unlike the MI/death analyses, this relationship of increased diabetes risk among “heavier” twins was enhanced by increasing BMI dissimilarity between twins, and among twins who had been gaining weight prior to baseline BMI measurement.

Sensitivity analyses excluding twins with less than 1 year of follow-up did not result in changes to the main findings—“heavier” twins still had similar odds of MI/death as “leaner” twins.

Conclusion. The authors conclude that among monozygotic twin pairs, where the possibility for genetic confounding has been eliminated, obesity is not causally associated with increased risk of MI or death, although the results do support an increased risk of developing incident diabetes among individuals with higher BMI.

Commentary

Obesity is a known risk factor for many chronic conditions, including diabetes, osteoarthritis, sleep apnea, and hypertension [1]. However, the relationship between obesity and cardiovascular outcomes, particularly coronary artery disease and death from heart disease, has been more controversial. Some epidemiologic studies have demonstrated reduced mortality risk among patients with obesity and heart failure, and even among those with established coronary artery disease—the so-called “obesity paradox” [2]. Others have observed that overweight older adults may have lower overall mortality compared to their normal weight counterparts [3]. On the other hand, it is known that obesity increases risk for diabetes, which is itself a clear and proven risk factor for CVD and death.

As the authors of the current study point out, genetic confounding may be a potential reason for the conflicting results produced in studies of the obesity–CVD risk relationship. In other words, patients who have genes that promote weight gain may also have genes that promote CVD, through pathways independent of excess adipose tissue, with these hidden pathways acting as confounders of the obesity–CVD relationship. By studying monozygotic twin pairs, who have identical genetic makeup but have developed differential weight status due to different environmental exposures, the investigators designed a study that would eliminate any genetic confounding and allow them to better isolate the relationship between higher BMI and CVD. This is an important topic area because, at a population level, we are faced with an immense number of adults who have obesity. Treatment of this condition is resource intense and it is critical that patients and health care systems understand the potential risk reduction that will be achieved with sustained weight loss.

The strengths of this study include the use of a very unique dataset with longitudinal measures on a large number of monozygotic twin pairs, and the authors’ ability to link this dataset with nationwide comprehensive datasets on health conditions, health care use (pharmacy), sociodemographics, and death. Sweden’s national registries are quite impressive and permit these types of studies in a way that would be very difficult to achieve in the United States, with its innumerable separate health care systems and few data sources that contain information on all citizens. Because of these multiple data sources, the authors were able to adjust for some important lifestyle factors that could easily confound the weight status-MI/death relationship, such as smoking and physical activity. Additionally, their models were able to factor in trajectory of weight on some individuals prior to baseline, rather than viewing baseline weight only as a “snapshot” which could risk missing an important trend of weight gain or loss over time, with important health implications.

There are several limitations of the study that are worth reviewing. First, and most importantly, as pointed out in a commentary associated with the article, the categorization of “leaner” and “heavier” can be somewhat misleading if the true question is whether or not excess adiposity is an independent driver of cardiovascular risk [4]. BMI, at the individual level, is not an ideal measure of adiposity and it does not speak to distribution of fat tissue, which is critically important in evaluating CVD risk [5]. For example, 2 siblings could have identical BMIs, but one might have significantly more lean mass in their legs and buttocks, and the other could have more central adipose tissue, translating to a much higher cardiovascular risk. Measures such as waist circumference are critical factors in addition to BMI to better understand an individual’s adipose tissue volume and distribution.

Although the authors did adjust for some self-reported behaviors that are important predictors of CVD (smoking, exercise), there is still potential for confounding due to unscreened or unreported exposures that differ systematically between “leaner” and “heavier” twins. Of note, smoking status—probably the single most important risk factor for CVD—was missing in 13% of the cohort, and no imputation techniques were used for missing data. Another limitation of this study is that its generalizability to more racial/ethnically diverse populations may be limited. Presumably, the patients in this study were non-Hispanic white Swedes, and whether or not these findings would be replicated in other groups, such as those of African or Asian ancestry, is not known.

Finally, the finding that “heavier” twins had greater odds of developing diabetes during follow-up is certainly consistent with existing literature. However, it is also known that diabetes is a strong risk factor for the development of CVD, including MI, and for death [6]. This raises the question of why the authors observed an increased diabetes risk yet no change in MI/death rates among heavier twins. Most likely the discrepancy is due to inadequate follow-up time of incident diabetes cases. Complications of diabetes can take a number of years to materialize, and, with an average of 12 years’ total follow-up in this study, there simply may not have been time to observe an increased risk of MI/death in heavier twins.

Applications for Clinical Practice

For patients interested in weight loss as a way of reducing CVD risk, this paper does not support the notion that lower body weight alone exerts direct influence on this endpoint. However, it reinforces the link between higher body weight and diabetes, which is a clear risk factor for CVD. Therefore, it still seems reasonable to advise patients who are at risk of diabetes that improving dietary quality, increasing cardiorespiratory fitness, and losing weight can reduce their long-term risk of CVD, even if indirectly so.

—Kristina Lewis, MD, MPH