Outcomes Research in Review

Study Overview

Objective. To assess the effect of extending adjuvant therapy with an aromatase inhibitor beyond 5 years in postmenopausal women with breast cancer.

Design. Phase 3, randomized, double-blind, placebo-controlled trial.

Setting and participants. This was a North American Breast Cancer Group trial, coordinated by the Canadian Cancer Trials Group. The trial was originally designed as an extension of the MA.17 trial evaluating the role for 5 years of letrozole versus placebo after 5 years of tamoxifen, with re-randomization of letrozole-assigned patients to an additional 5 years of letrozole versus placebo. The trial was then extended to include additional postmenopausal women with stage I-III breast cancer who had been treated with 4.5 to 6 years of adjuvant therapy with any aromatase inhibitor with or without prior tamoxifen.

Most patients had received adjuvant treatment with tamoxifen before the aromatase inhibitor. Patients were randomized within 2 years after completing treatment with the aromatase inhibitor to either letrozole 2.5 mg or placebo orally once a day, for another 5 years. The criteria for stratification included lymph node status, prior receipt of adjuvant chemotherapy, the interval between the last dose of aromatase inhibitor and randomization, and the duration of prior use of tamoxifen. Eligibility criteria included patients who were disease-free after 4.5 to 6 years of aromatase inhibitor, hormone-positive tumors (and unknown receptor status for participants in the MA.17 trial), ECOG performance status of 0 to 2, and life expectancy of 5 or more years.

Main outcome measures. The primary endpoint was disease-free survival, defined as the time from randomization to recurrence or the development of new primary breast cancer. Secondary endpoints included overall survival, incidence of contralateral breast cancer, quality of life using the Medical Outcomes Study 36-Item Short-Form Heath Survey (SF-36) and the Menopause-Specific Quality of Life (MENQOL) questionnaire, and long-term safety. The investigators calculated that 196 events were required for the study to have 80% power to detect a 33% lower hazard of recurrence with letrozole as compared with placebo. At the 6-year point, only 176 events had been observed, and the study design was amended to have a time-based analysis instead of event-based. On 13 Nov 2015 the final database had 165 events, with 80% power to detect a hazard ratio for disease-free survival of 0.655. The analysis of time-to-event outcomes was performed utilizing a log-rank test with adjustment for stratification factors. Fisher’s exact test was used to assess binary outcomes, and Wilcoxon test, to assess continuous outcomes. Comparisons between the letrozole and the placebo groups were made using a 2-sided test with an alpha level of 5%.

Main results. A total of 1918 patients were randomized to receive either letrozole (n = 959) or placebo (n = 959). The rate of adherence to the study regimen was approximately 62% for both arms. The median duration of prior treatment with tamoxifen was 5 years; 20.7% of patients did not receive tamoxifen. The median duration of prior treatment with aromatase inhibitor was 5 years, and the median time interval between the last dose of aromatase inhibitor and randomization was less than 6 months. The median duration of the study regimen (letrozole or placebo) was 5 years, and the median follow-up was 6.3 years. Approximately 90% of patients had stage T1 or T2 tumors at diagnosis, and 94% of nodal stage were N0 or N1. Estrogen receptor, progesterone receptor or both were known to be positive in 98.8% of patients.

Disease recurrence or contralateral breast cancer occurred in 67 patients (7%) in the letrozole group and 98 patients (10.2%) in the placebo group. The hazard ratio for recurrence or occurrence of contralateral breast cancer was 0.66 (95% confidence interval [CI], 0.48–0.91, P = 0.01). In the letrozole group, 55 patients had disease recurrence and 13 patients had contralateral breast cancer. Among the patients in the placebo group, 68 had recurrence of disease and 31 had contralateral breast cancer. Both disease recurrence and contralateral breast cancer occurred in one patient in each group. Distant disease recurrence was 5.5% in the placebo group and 4.4% in the letrozole group.

Five-year disease-free survival, the primary endpoint of this study, was 95% in the letrozole group (95% CI, 93–96) and 91% in the placebo group (95% CI, 89–93). The rate of 5-year disease free-survival was higher in the letrozole group in all subgroups. A total of 200 deaths were observed, 100 in each group. The rate of 5-year overall survival was not statistically different between the 2 groups (93% in the letrozole group and 94% in the placebo group, HR 0.97, P = 0.83). The annual incidence rate of contralateral breast cancer favored the letrozole group, with a rate of 0.21% in comparison with 0.49% in the placebo group (HR 0.42, P = 0.007).

Discontinuation of treatment occurred in 5.4% of patients in the letrozole group and 3.7% in the placebo group. The majority of toxic effects had a similar incidence in both groups, however bone-related side effects were more common in the letrozole group. Bone fractures occurred in 14% of patients in the letrozole group and 9% in the placebo group (P = 0.001). New-onset osteoporosis was also more common in the letrozole group (11% versus 6%, P < 0.001). Of note, 5 patients developed a hip fracture after discontinuation of letrozole. In regards to quality of life, patients receiving letrozole had a greater reduction in scores in the role-physical subscale of the SF-36 survey, indicating worse quality of life, but the difference was less than the minimum clinically important difference. There were no differences in the MENQOL questionnaire subscales.

Conclusion. Treatment with an aromatase inhibitor for additional 4.5 to 6 years was beneficial in preventing disease recurrence. There was no difference in overall survival.

Commentary

Adjuvant endocrine therapy reduces the risk of recurrence and increases survival in women with hormone receptor–positive breast cancer. The use of tamoxifen as adjuvant therapy for women with early stage breast cancer has been extensively studied. A metanalysis performed by the Early Breast Cancer Trialists’ Collaborative Group (EBCTG) demonstrated that tamoxifen reduces breast cancer mortality by a third when given as adjuvant therapy for women with hormone positive breast cancer [1].

Two important studies published in the last decade demonstrated that extending therapy with tamoxifen beyond 5 years reduces the chance of recurrence and improves survival. In the ATLAS (Adjuvant Tamoxifen: Longer Against Shorter) trial, women with early stage breast cancer who had completed 5 years of adjuvant tamoxifen were randomized to stop therapy or to continue tamoxifen for 5 additional years. Among patients with estrogen receptor (ER)–positive disease, the results demonstrated an absolute recurrence reduction of 3.7% and an absolute mortality reduction of 2.8% in 15 years after diagnosis [2].The aTTom trial randomized 6953 women with ER-positive breast cancer to discontinue tamoxifen after 5 years or to continue to complete 10 years of treatment and confirmed a benefit in recurrence rates and breast cancer mortality with 10 years of adjuvant tamoxifen [3].

Although tamoxifen is active in both pre- and postmenopausal patients, therapy with an aromatase inhibitor either as first-line or following treatment with tamoxifen has been demonstrated to be superior to tamoxifen alone in hormone receptor–positive postmenopausal women. In the ATAC (The Arimidex, Tamoxifen, Alone or in Combination) trial, postmenopausal patients were randomized to receive 5 years of either tamoxifen or anastrozole as adjuvant therapy. The anastrozole group had higher disease-free survival, time to recurrence and time to distant recurrence [4].In the Breast Intergroup (BIG) 1-98 trial, postmenopausal women were assigned to 4 different arms: 5 years of letrozole, 5 years of tamoxifen, letrozole for 2 years followed by tamoxifen for 3 years, or tamoxifen for 2 years followed by letrozole for 3 years. The 2 groups assigned to receive letrozole initially were compared to the 2 groups assigned to receive tamoxifen initially. Compared with tamoxifen, letrozole significantly decrease the risk of recurrence [5].The MA-17 trial demonstrated a disease-free survival advantage with 5 years of letrozole compared with placebo in women who had been treated with tamoxifen for 5 years [6].  Based on these data, current guidelines for adjuvant endocrine therapy for postmenopausal women recommend an aromatase inhibitor for 5 years as primary therapy or after 2 to 3 years of tamoxifen [7].  

Results from studies with extended endocrine therapy, either 10 years of tamoxifen or 5 years of aromatase inhibitor after up to 5 years of tamoxifen, provide rationale to study the effect of therapy with aromatase inhibitor beyond 5 years. The current study by Goss et al (the MA 17.R trial) addresses the relevant question of whether extended adjuvant therapy with an aromatase inhibitor in post-menopausal women beyond 5 years provides additional benefit. The design of this study has several strengths including being randomized, phase 3, placebo-controlled and double-blind. Another strength was the large number of patients enrolled. The choice of disease-free survival as the primary endpoint is in accordance with the natural course of ER-positive breast cancer, which has a prolonged rate of recurrence. The study results showed that patients who received 10 years of letrozole had a 34% lower risk of recurrence, with an absolute improvement of 4% in disease-free survival. However, no overall survival benefit was demonstrated at a median follow-up of 6.3 years. This might be a result of the fact that the highest proportional benefit was reduction in incidence of contralateral breast cancer. It is also possible that an overall survival benefit would be observed with a longer follow-up.

As highlighted by the authors, the benefit of extended adjuvant therapy is higher in the first years. Given that the majority of patients enrolled in this study had received prior tamoxifen, it is possible that patients who receive only an aromatase inhibitor for 5 years without prior tamoxifen would benefit even more from extended aromatase inhibitor therapy. On the other hand, the 1.1% numerical advantage observed in reducing distant recurrence is quite modest, with the majority of the disease-free survival advantage seen with extended aromatase inhibition being due to a reduction in local recurrence and contralateral new concerns.

The quality of life assessment enhanced this trial, since adherence to adjuvant endocrine therapy remains a challenge. It should be noted, however, that patients willing to participate in a trial of extended therapy are likely to be those who have tolerated therapy reasonably well. The increase in body pain and differences in the role-emotional subscale in the letrozole reflect side effects of aromatase inhibitors that are seen in clinical practice. The higher rates of new-onset osteoporosis and bone fractures underscore the need to balance potential benefits and risks with extended aromatase inhibitor therapy.

Results from other trials evaluating extended adjuvant therapy will be helpful. The NSABP B-42 study randomized ER-positive postmenopausal patients to receive 5 years of letrozole or placebo after completing 5 years of hormonal therapy with an aromatase inhibitor for 5 years or ≤ 3 years of tamoxifen followed by an aromatase inhibitor. This study has completed enrollment and should provide additional insight regarding duration of therapy with aromatase inhibitors.

Applications for Clinical Practice

These trial results showed a benefit with extended aromatase inhibitor therapy; however, the magnitude of benefit was relatively small, particularly with respect to impacting distant recurrence risk. Given that extended therapy has potential side effects, it is appropriate to have a detailed discussion with patients regarding potential benefits and risks. A reasonable clinical strategy is to discuss extended therapy with patients who have a higher chance of relapse and those who are motivated to continue therapy to reduce new breast cancer events.

—Leticia Varella, MD, and Halle Moore, MD,
Cleveland Clinic Taussig Cancer Institute, Cleveland, OH

Study Overview

Objective. To assess the effect of extending adjuvant therapy with an aromatase inhibitor beyond 5 years in postmenopausal women with breast cancer.

Design. Phase 3, randomized, double-blind, placebo-controlled trial.

Setting and participants. This was a North American Breast Cancer Group trial, coordinated by the Canadian Cancer Trials Group. The trial was originally designed as an extension of the MA.17 trial evaluating the role for 5 years of letrozole versus placebo after 5 years of tamoxifen, with re-randomization of letrozole-assigned patients to an additional 5 years of letrozole versus placebo. The trial was then extended to include additional postmenopausal women with stage I-III breast cancer who had been treated with 4.5 to 6 years of adjuvant therapy with any aromatase inhibitor with or without prior tamoxifen.

Most patients had received adjuvant treatment with tamoxifen before the aromatase inhibitor. Patients were randomized within 2 years after completing treatment with the aromatase inhibitor to either letrozole 2.5 mg or placebo orally once a day, for another 5 years. The criteria for stratification included lymph node status, prior receipt of adjuvant chemotherapy, the interval between the last dose of aromatase inhibitor and randomization, and the duration of prior use of tamoxifen. Eligibility criteria included patients who were disease-free after 4.5 to 6 years of aromatase inhibitor, hormone-positive tumors (and unknown receptor status for participants in the MA.17 trial), ECOG performance status of 0 to 2, and life expectancy of 5 or more years.

Main outcome measures. The primary endpoint was disease-free survival, defined as the time from randomization to recurrence or the development of new primary breast cancer. Secondary endpoints included overall survival, incidence of contralateral breast cancer, quality of life using the Medical Outcomes Study 36-Item Short-Form Heath Survey (SF-36) and the Menopause-Specific Quality of Life (MENQOL) questionnaire, and long-term safety. The investigators calculated that 196 events were required for the study to have 80% power to detect a 33% lower hazard of recurrence with letrozole as compared with placebo. At the 6-year point, only 176 events had been observed, and the study design was amended to have a time-based analysis instead of event-based. On 13 Nov 2015 the final database had 165 events, with 80% power to detect a hazard ratio for disease-free survival of 0.655. The analysis of time-to-event outcomes was performed utilizing a log-rank test with adjustment for stratification factors. Fisher’s exact test was used to assess binary outcomes, and Wilcoxon test, to assess continuous outcomes. Comparisons between the letrozole and the placebo groups were made using a 2-sided test with an alpha level of 5%.

Main results. A total of 1918 patients were randomized to receive either letrozole (n = 959) or placebo (n = 959). The rate of adherence to the study regimen was approximately 62% for both arms. The median duration of prior treatment with tamoxifen was 5 years; 20.7% of patients did not receive tamoxifen. The median duration of prior treatment with aromatase inhibitor was 5 years, and the median time interval between the last dose of aromatase inhibitor and randomization was less than 6 months. The median duration of the study regimen (letrozole or placebo) was 5 years, and the median follow-up was 6.3 years. Approximately 90% of patients had stage T1 or T2 tumors at diagnosis, and 94% of nodal stage were N0 or N1. Estrogen receptor, progesterone receptor or both were known to be positive in 98.8% of patients.

Disease recurrence or contralateral breast cancer occurred in 67 patients (7%) in the letrozole group and 98 patients (10.2%) in the placebo group. The hazard ratio for recurrence or occurrence of contralateral breast cancer was 0.66 (95% confidence interval [CI], 0.48–0.91, P = 0.01). In the letrozole group, 55 patients had disease recurrence and 13 patients had contralateral breast cancer. Among the patients in the placebo group, 68 had recurrence of disease and 31 had contralateral breast cancer. Both disease recurrence and contralateral breast cancer occurred in one patient in each group. Distant disease recurrence was 5.5% in the placebo group and 4.4% in the letrozole group.

Five-year disease-free survival, the primary endpoint of this study, was 95% in the letrozole group (95% CI, 93–96) and 91% in the placebo group (95% CI, 89–93). The rate of 5-year disease free-survival was higher in the letrozole group in all subgroups. A total of 200 deaths were observed, 100 in each group. The rate of 5-year overall survival was not statistically different between the 2 groups (93% in the letrozole group and 94% in the placebo group, HR 0.97, P = 0.83). The annual incidence rate of contralateral breast cancer favored the letrozole group, with a rate of 0.21% in comparison with 0.49% in the placebo group (HR 0.42, P = 0.007).

Discontinuation of treatment occurred in 5.4% of patients in the letrozole group and 3.7% in the placebo group. The majority of toxic effects had a similar incidence in both groups, however bone-related side effects were more common in the letrozole group. Bone fractures occurred in 14% of patients in the letrozole group and 9% in the placebo group (P = 0.001). New-onset osteoporosis was also more common in the letrozole group (11% versus 6%, P < 0.001). Of note, 5 patients developed a hip fracture after discontinuation of letrozole. In regards to quality of life, patients receiving letrozole had a greater reduction in scores in the role-physical subscale of the SF-36 survey, indicating worse quality of life, but the difference was less than the minimum clinically important difference. There were no differences in the MENQOL questionnaire subscales.

Conclusion. Treatment with an aromatase inhibitor for additional 4.5 to 6 years was beneficial in preventing disease recurrence. There was no difference in overall survival.

Commentary

Adjuvant endocrine therapy reduces the risk of recurrence and increases survival in women with hormone receptor–positive breast cancer. The use of tamoxifen as adjuvant therapy for women with early stage breast cancer has been extensively studied. A metanalysis performed by the Early Breast Cancer Trialists’ Collaborative Group (EBCTG) demonstrated that tamoxifen reduces breast cancer mortality by a third when given as adjuvant therapy for women with hormone positive breast cancer [1].

Two important studies published in the last decade demonstrated that extending therapy with tamoxifen beyond 5 years reduces the chance of recurrence and improves survival. In the ATLAS (Adjuvant Tamoxifen: Longer Against Shorter) trial, women with early stage breast cancer who had completed 5 years of adjuvant tamoxifen were randomized to stop therapy or to continue tamoxifen for 5 additional years. Among patients with estrogen receptor (ER)–positive disease, the results demonstrated an absolute recurrence reduction of 3.7% and an absolute mortality reduction of 2.8% in 15 years after diagnosis [2].The aTTom trial randomized 6953 women with ER-positive breast cancer to discontinue tamoxifen after 5 years or to continue to complete 10 years of treatment and confirmed a benefit in recurrence rates and breast cancer mortality with 10 years of adjuvant tamoxifen [3].

Although tamoxifen is active in both pre- and postmenopausal patients, therapy with an aromatase inhibitor either as first-line or following treatment with tamoxifen has been demonstrated to be superior to tamoxifen alone in hormone receptor–positive postmenopausal women. In the ATAC (The Arimidex, Tamoxifen, Alone or in Combination) trial, postmenopausal patients were randomized to receive 5 years of either tamoxifen or anastrozole as adjuvant therapy. The anastrozole group had higher disease-free survival, time to recurrence and time to distant recurrence [4].In the Breast Intergroup (BIG) 1-98 trial, postmenopausal women were assigned to 4 different arms: 5 years of letrozole, 5 years of tamoxifen, letrozole for 2 years followed by tamoxifen for 3 years, or tamoxifen for 2 years followed by letrozole for 3 years. The 2 groups assigned to receive letrozole initially were compared to the 2 groups assigned to receive tamoxifen initially. Compared with tamoxifen, letrozole significantly decrease the risk of recurrence [5].The MA-17 trial demonstrated a disease-free survival advantage with 5 years of letrozole compared with placebo in women who had been treated with tamoxifen for 5 years [6].  Based on these data, current guidelines for adjuvant endocrine therapy for postmenopausal women recommend an aromatase inhibitor for 5 years as primary therapy or after 2 to 3 years of tamoxifen [7].  

Results from studies with extended endocrine therapy, either 10 years of tamoxifen or 5 years of aromatase inhibitor after up to 5 years of tamoxifen, provide rationale to study the effect of therapy with aromatase inhibitor beyond 5 years. The current study by Goss et al (the MA 17.R trial) addresses the relevant question of whether extended adjuvant therapy with an aromatase inhibitor in post-menopausal women beyond 5 years provides additional benefit. The design of this study has several strengths including being randomized, phase 3, placebo-controlled and double-blind. Another strength was the large number of patients enrolled. The choice of disease-free survival as the primary endpoint is in accordance with the natural course of ER-positive breast cancer, which has a prolonged rate of recurrence. The study results showed that patients who received 10 years of letrozole had a 34% lower risk of recurrence, with an absolute improvement of 4% in disease-free survival. However, no overall survival benefit was demonstrated at a median follow-up of 6.3 years. This might be a result of the fact that the highest proportional benefit was reduction in incidence of contralateral breast cancer. It is also possible that an overall survival benefit would be observed with a longer follow-up.

As highlighted by the authors, the benefit of extended adjuvant therapy is higher in the first years. Given that the majority of patients enrolled in this study had received prior tamoxifen, it is possible that patients who receive only an aromatase inhibitor for 5 years without prior tamoxifen would benefit even more from extended aromatase inhibitor therapy. On the other hand, the 1.1% numerical advantage observed in reducing distant recurrence is quite modest, with the majority of the disease-free survival advantage seen with extended aromatase inhibition being due to a reduction in local recurrence and contralateral new concerns.

The quality of life assessment enhanced this trial, since adherence to adjuvant endocrine therapy remains a challenge. It should be noted, however, that patients willing to participate in a trial of extended therapy are likely to be those who have tolerated therapy reasonably well. The increase in body pain and differences in the role-emotional subscale in the letrozole reflect side effects of aromatase inhibitors that are seen in clinical practice. The higher rates of new-onset osteoporosis and bone fractures underscore the need to balance potential benefits and risks with extended aromatase inhibitor therapy.

Results from other trials evaluating extended adjuvant therapy will be helpful. The NSABP B-42 study randomized ER-positive postmenopausal patients to receive 5 years of letrozole or placebo after completing 5 years of hormonal therapy with an aromatase inhibitor for 5 years or ≤ 3 years of tamoxifen followed by an aromatase inhibitor. This study has completed enrollment and should provide additional insight regarding duration of therapy with aromatase inhibitors.

Applications for Clinical Practice

These trial results showed a benefit with extended aromatase inhibitor therapy; however, the magnitude of benefit was relatively small, particularly with respect to impacting distant recurrence risk. Given that extended therapy has potential side effects, it is appropriate to have a detailed discussion with patients regarding potential benefits and risks. A reasonable clinical strategy is to discuss extended therapy with patients who have a higher chance of relapse and those who are motivated to continue therapy to reduce new breast cancer events.

—Leticia Varella, MD, and Halle Moore, MD,
Cleveland Clinic Taussig Cancer Institute, Cleveland, OH

Study Overview

Objective. To assess the effect of extending adjuvant therapy with an aromatase inhibitor beyond 5 years in postmenopausal women with breast cancer.

Design. Phase 3, randomized, double-blind, placebo-controlled trial.

Setting and participants. This was a North American Breast Cancer Group trial, coordinated by the Canadian Cancer Trials Group. The trial was originally designed as an extension of the MA.17 trial evaluating the role for 5 years of letrozole versus placebo after 5 years of tamoxifen, with re-randomization of letrozole-assigned patients to an additional 5 years of letrozole versus placebo. The trial was then extended to include additional postmenopausal women with stage I-III breast cancer who had been treated with 4.5 to 6 years of adjuvant therapy with any aromatase inhibitor with or without prior tamoxifen.

Most patients had received adjuvant treatment with tamoxifen before the aromatase inhibitor. Patients were randomized within 2 years after completing treatment with the aromatase inhibitor to either letrozole 2.5 mg or placebo orally once a day, for another 5 years. The criteria for stratification included lymph node status, prior receipt of adjuvant chemotherapy, the interval between the last dose of aromatase inhibitor and randomization, and the duration of prior use of tamoxifen. Eligibility criteria included patients who were disease-free after 4.5 to 6 years of aromatase inhibitor, hormone-positive tumors (and unknown receptor status for participants in the MA.17 trial), ECOG performance status of 0 to 2, and life expectancy of 5 or more years.

Main outcome measures. The primary endpoint was disease-free survival, defined as the time from randomization to recurrence or the development of new primary breast cancer. Secondary endpoints included overall survival, incidence of contralateral breast cancer, quality of life using the Medical Outcomes Study 36-Item Short-Form Heath Survey (SF-36) and the Menopause-Specific Quality of Life (MENQOL) questionnaire, and long-term safety. The investigators calculated that 196 events were required for the study to have 80% power to detect a 33% lower hazard of recurrence with letrozole as compared with placebo. At the 6-year point, only 176 events had been observed, and the study design was amended to have a time-based analysis instead of event-based. On 13 Nov 2015 the final database had 165 events, with 80% power to detect a hazard ratio for disease-free survival of 0.655. The analysis of time-to-event outcomes was performed utilizing a log-rank test with adjustment for stratification factors. Fisher’s exact test was used to assess binary outcomes, and Wilcoxon test, to assess continuous outcomes. Comparisons between the letrozole and the placebo groups were made using a 2-sided test with an alpha level of 5%.

Main results. A total of 1918 patients were randomized to receive either letrozole (n = 959) or placebo (n = 959). The rate of adherence to the study regimen was approximately 62% for both arms. The median duration of prior treatment with tamoxifen was 5 years; 20.7% of patients did not receive tamoxifen. The median duration of prior treatment with aromatase inhibitor was 5 years, and the median time interval between the last dose of aromatase inhibitor and randomization was less than 6 months. The median duration of the study regimen (letrozole or placebo) was 5 years, and the median follow-up was 6.3 years. Approximately 90% of patients had stage T1 or T2 tumors at diagnosis, and 94% of nodal stage were N0 or N1. Estrogen receptor, progesterone receptor or both were known to be positive in 98.8% of patients.

Disease recurrence or contralateral breast cancer occurred in 67 patients (7%) in the letrozole group and 98 patients (10.2%) in the placebo group. The hazard ratio for recurrence or occurrence of contralateral breast cancer was 0.66 (95% confidence interval [CI], 0.48–0.91, P = 0.01). In the letrozole group, 55 patients had disease recurrence and 13 patients had contralateral breast cancer. Among the patients in the placebo group, 68 had recurrence of disease and 31 had contralateral breast cancer. Both disease recurrence and contralateral breast cancer occurred in one patient in each group. Distant disease recurrence was 5.5% in the placebo group and 4.4% in the letrozole group.

Five-year disease-free survival, the primary endpoint of this study, was 95% in the letrozole group (95% CI, 93–96) and 91% in the placebo group (95% CI, 89–93). The rate of 5-year disease free-survival was higher in the letrozole group in all subgroups. A total of 200 deaths were observed, 100 in each group. The rate of 5-year overall survival was not statistically different between the 2 groups (93% in the letrozole group and 94% in the placebo group, HR 0.97, P = 0.83). The annual incidence rate of contralateral breast cancer favored the letrozole group, with a rate of 0.21% in comparison with 0.49% in the placebo group (HR 0.42, P = 0.007).

Discontinuation of treatment occurred in 5.4% of patients in the letrozole group and 3.7% in the placebo group. The majority of toxic effects had a similar incidence in both groups, however bone-related side effects were more common in the letrozole group. Bone fractures occurred in 14% of patients in the letrozole group and 9% in the placebo group (P = 0.001). New-onset osteoporosis was also more common in the letrozole group (11% versus 6%, P < 0.001). Of note, 5 patients developed a hip fracture after discontinuation of letrozole. In regards to quality of life, patients receiving letrozole had a greater reduction in scores in the role-physical subscale of the SF-36 survey, indicating worse quality of life, but the difference was less than the minimum clinically important difference. There were no differences in the MENQOL questionnaire subscales.

Conclusion. Treatment with an aromatase inhibitor for additional 4.5 to 6 years was beneficial in preventing disease recurrence. There was no difference in overall survival.

Commentary

Adjuvant endocrine therapy reduces the risk of recurrence and increases survival in women with hormone receptor–positive breast cancer. The use of tamoxifen as adjuvant therapy for women with early stage breast cancer has been extensively studied. A metanalysis performed by the Early Breast Cancer Trialists’ Collaborative Group (EBCTG) demonstrated that tamoxifen reduces breast cancer mortality by a third when given as adjuvant therapy for women with hormone positive breast cancer [1].

Two important studies published in the last decade demonstrated that extending therapy with tamoxifen beyond 5 years reduces the chance of recurrence and improves survival. In the ATLAS (Adjuvant Tamoxifen: Longer Against Shorter) trial, women with early stage breast cancer who had completed 5 years of adjuvant tamoxifen were randomized to stop therapy or to continue tamoxifen for 5 additional years. Among patients with estrogen receptor (ER)–positive disease, the results demonstrated an absolute recurrence reduction of 3.7% and an absolute mortality reduction of 2.8% in 15 years after diagnosis [2].The aTTom trial randomized 6953 women with ER-positive breast cancer to discontinue tamoxifen after 5 years or to continue to complete 10 years of treatment and confirmed a benefit in recurrence rates and breast cancer mortality with 10 years of adjuvant tamoxifen [3].

Although tamoxifen is active in both pre- and postmenopausal patients, therapy with an aromatase inhibitor either as first-line or following treatment with tamoxifen has been demonstrated to be superior to tamoxifen alone in hormone receptor–positive postmenopausal women. In the ATAC (The Arimidex, Tamoxifen, Alone or in Combination) trial, postmenopausal patients were randomized to receive 5 years of either tamoxifen or anastrozole as adjuvant therapy. The anastrozole group had higher disease-free survival, time to recurrence and time to distant recurrence [4].In the Breast Intergroup (BIG) 1-98 trial, postmenopausal women were assigned to 4 different arms: 5 years of letrozole, 5 years of tamoxifen, letrozole for 2 years followed by tamoxifen for 3 years, or tamoxifen for 2 years followed by letrozole for 3 years. The 2 groups assigned to receive letrozole initially were compared to the 2 groups assigned to receive tamoxifen initially. Compared with tamoxifen, letrozole significantly decrease the risk of recurrence [5].The MA-17 trial demonstrated a disease-free survival advantage with 5 years of letrozole compared with placebo in women who had been treated with tamoxifen for 5 years [6].  Based on these data, current guidelines for adjuvant endocrine therapy for postmenopausal women recommend an aromatase inhibitor for 5 years as primary therapy or after 2 to 3 years of tamoxifen [7].  

Results from studies with extended endocrine therapy, either 10 years of tamoxifen or 5 years of aromatase inhibitor after up to 5 years of tamoxifen, provide rationale to study the effect of therapy with aromatase inhibitor beyond 5 years. The current study by Goss et al (the MA 17.R trial) addresses the relevant question of whether extended adjuvant therapy with an aromatase inhibitor in post-menopausal women beyond 5 years provides additional benefit. The design of this study has several strengths including being randomized, phase 3, placebo-controlled and double-blind. Another strength was the large number of patients enrolled. The choice of disease-free survival as the primary endpoint is in accordance with the natural course of ER-positive breast cancer, which has a prolonged rate of recurrence. The study results showed that patients who received 10 years of letrozole had a 34% lower risk of recurrence, with an absolute improvement of 4% in disease-free survival. However, no overall survival benefit was demonstrated at a median follow-up of 6.3 years. This might be a result of the fact that the highest proportional benefit was reduction in incidence of contralateral breast cancer. It is also possible that an overall survival benefit would be observed with a longer follow-up.

As highlighted by the authors, the benefit of extended adjuvant therapy is higher in the first years. Given that the majority of patients enrolled in this study had received prior tamoxifen, it is possible that patients who receive only an aromatase inhibitor for 5 years without prior tamoxifen would benefit even more from extended aromatase inhibitor therapy. On the other hand, the 1.1% numerical advantage observed in reducing distant recurrence is quite modest, with the majority of the disease-free survival advantage seen with extended aromatase inhibition being due to a reduction in local recurrence and contralateral new concerns.

The quality of life assessment enhanced this trial, since adherence to adjuvant endocrine therapy remains a challenge. It should be noted, however, that patients willing to participate in a trial of extended therapy are likely to be those who have tolerated therapy reasonably well. The increase in body pain and differences in the role-emotional subscale in the letrozole reflect side effects of aromatase inhibitors that are seen in clinical practice. The higher rates of new-onset osteoporosis and bone fractures underscore the need to balance potential benefits and risks with extended aromatase inhibitor therapy.

Results from other trials evaluating extended adjuvant therapy will be helpful. The NSABP B-42 study randomized ER-positive postmenopausal patients to receive 5 years of letrozole or placebo after completing 5 years of hormonal therapy with an aromatase inhibitor for 5 years or ≤ 3 years of tamoxifen followed by an aromatase inhibitor. This study has completed enrollment and should provide additional insight regarding duration of therapy with aromatase inhibitors.

Applications for Clinical Practice

These trial results showed a benefit with extended aromatase inhibitor therapy; however, the magnitude of benefit was relatively small, particularly with respect to impacting distant recurrence risk. Given that extended therapy has potential side effects, it is appropriate to have a detailed discussion with patients regarding potential benefits and risks. A reasonable clinical strategy is to discuss extended therapy with patients who have a higher chance of relapse and those who are motivated to continue therapy to reduce new breast cancer events.

—Leticia Varella, MD, and Halle Moore, MD,
Cleveland Clinic Taussig Cancer Institute, Cleveland, OH

Study Overview

Objective. To understand how the experience of intimate partner violence and non-partner sexual assault (IPV/SA) in women in the military intersects with military service.

Design. Qualitative interviews conducted as part of a larger study focused on experiences of IPV/SA and health care needs and preferences among women veteran patients.

Setting and participants. Participants were 25 women veterans from all branches of the service, ages 22 to 58 years (mean 44.6), who were patients at the Veteran’s Medical Center in Philadelphia, PA. The sample was diverse: 56% self-identified as black or African American, 20% as white or Caucasian, 16% as Hispanic or Latina, and 8% as “other” or multiple race/ethnicity.

Interviews. Researchers conducted face-to-face interviews using a semi-structured interview guide to gather in-depth narratives related to the participants’ lives in the military and their experiences of IPV/SA. The Military Occupational Mental Health Model was used as a framework to understand the experience of IPV/SA within the cultural context of the military and how that context influences health and well-being. The model considers the unique context of the military, including the importance of the values of mission over individual well-being, hierarchy and subordination, leadership, and unit support, as well as what resources are made available.

Data analysis. The authors followed an inductive approach informed by grounded theory, with the goal of identifying themes and a unifying theory empirically grounded in the interview data. First, 2 members of the research team conducted independent, close readings of each transcript and applied open coding, then compared their coding to identify common patterns across transcripts. Through this process, they developed and refined a codebook to define a set of codes and guide application of codes to text. Research team members conducted line-by-line coding of each transcript, based on the codebook definitions. Then the authors read all coded text and met to discuss patterns within and between transcripts, leading to identification of 2 core categories pertaining to the relationship betweenIPV/SA and military service, as well as several subthemes within each core category.

Main results. The 2 core categories identified  had both positive and negative influences. The first was  the “experience of IPV/SA affects participation in military service, including entering and leaving military service,” and included the subthemes of coercion by the perpetrator to enter or leave military service, effects on service and work performance such as physical and mental health problems that interfered with their ability to do their job, and survival strategies that had negative repercussions on the woman’s career. The second was  the “military context shapes responses to, and coping with, experiences of IPV/SA,” and included the subthemes of military sanction for IPV (but not sexual assault) if both partners were in the military, lack of accountability for and protection of service member perpetrators due to the value of unit support, military service as an opportunity to escape through relocation, even preferring a combat zone over home, and resistance to seeking help because of expectations of invulnerability related to the warrior identity.

Conclusion. The military context can provide personal and occupational resources for women who experience IPV/SA, but the institutional (ie, chain of command reporting) and cultural context can constrain women’s ability to access resources and support, negatively affecting outcomes.

Commentary

Intimate partner violence (IPV) is a widespread public health problem in the United States and women in the military are no exception. According to Black and Merrick [1], 36.3% of active duty women experienced sexual violence in their lifetime and 39.7% experienced IPV. Violence has significant health, economic, and social consequences for women in all settings, including serious short- and long-term physical and mental health problems, economic hardship, isolation, and decreased quality of life [2–5]. Women who experience IPV/SA in any setting face challenges in protecting themselves, overcoming violence, and seeking justice, however, the context in which the violence occurs can significantly influence the individual experiences of women. This study used a qualitative approach to understand how it is experienced by service women in the context of the military.

As the authors note, military culture can both facilitate and hamper women’s recovery from the physical, psychological, and economic sequelae of IPV/SA. The rigid hierarchal structure of the military and the expectation that one supports the unit and fellow soldiers above all else makes it very difficult for women to disclose IPV/SA and seek and receive protection and justice. On the other hand, military training and service provides women with the skills and means to be independent and to physically distance themselves from the perpetrator. However, the comment of one woman that facing bombs in Iraq was preferable to facing the violence at home should serve as a reminder of how devastating IPV/SA is and suggests that victims do not think there are effective institutional deterrents or protection available to them.

As the authors note, this was a small convenience sample of women at one VA medical center. This qualitative study provides a beginning understanding that should be expanded on with multisite quantitative research with large samples. Sexual assault in the military has been recognized as a significant problem, particularly for women but also for men. We need to continue to study this problem from many different perspectives to determine how to prevent violence and to ensure all victims get the resources and effective services they need.

Applications for Clinical Practice

This study has implications for all health care providers, as active duty and veteran service women seek care outside as well as within the VA. An important finding that has direct application to practice in all settings is the influence of the warrior identity. The warrior identity has been widely acknowledged as a barrier to seeking help for depression or PTSD in service men returning from combat but not as much in service women and not in the context of IPV/SA. It is important that providers consider warrior identity in assessing and treating women for IPV/SA. Not only can this affect disclosure and prevent a victim from seeking help, but the expectation that they should have been invulnerable and strong may increase feelings of self-blame and worsen psychological distress.

 —Karen Roush, PhD, RN

Study Overview

Objective. To understand how the experience of intimate partner violence and non-partner sexual assault (IPV/SA) in women in the military intersects with military service.

Design. Qualitative interviews conducted as part of a larger study focused on experiences of IPV/SA and health care needs and preferences among women veteran patients.

Setting and participants. Participants were 25 women veterans from all branches of the service, ages 22 to 58 years (mean 44.6), who were patients at the Veteran’s Medical Center in Philadelphia, PA. The sample was diverse: 56% self-identified as black or African American, 20% as white or Caucasian, 16% as Hispanic or Latina, and 8% as “other” or multiple race/ethnicity.

Interviews. Researchers conducted face-to-face interviews using a semi-structured interview guide to gather in-depth narratives related to the participants’ lives in the military and their experiences of IPV/SA. The Military Occupational Mental Health Model was used as a framework to understand the experience of IPV/SA within the cultural context of the military and how that context influences health and well-being. The model considers the unique context of the military, including the importance of the values of mission over individual well-being, hierarchy and subordination, leadership, and unit support, as well as what resources are made available.

Data analysis. The authors followed an inductive approach informed by grounded theory, with the goal of identifying themes and a unifying theory empirically grounded in the interview data. First, 2 members of the research team conducted independent, close readings of each transcript and applied open coding, then compared their coding to identify common patterns across transcripts. Through this process, they developed and refined a codebook to define a set of codes and guide application of codes to text. Research team members conducted line-by-line coding of each transcript, based on the codebook definitions. Then the authors read all coded text and met to discuss patterns within and between transcripts, leading to identification of 2 core categories pertaining to the relationship betweenIPV/SA and military service, as well as several subthemes within each core category.

Main results. The 2 core categories identified  had both positive and negative influences. The first was  the “experience of IPV/SA affects participation in military service, including entering and leaving military service,” and included the subthemes of coercion by the perpetrator to enter or leave military service, effects on service and work performance such as physical and mental health problems that interfered with their ability to do their job, and survival strategies that had negative repercussions on the woman’s career. The second was  the “military context shapes responses to, and coping with, experiences of IPV/SA,” and included the subthemes of military sanction for IPV (but not sexual assault) if both partners were in the military, lack of accountability for and protection of service member perpetrators due to the value of unit support, military service as an opportunity to escape through relocation, even preferring a combat zone over home, and resistance to seeking help because of expectations of invulnerability related to the warrior identity.

Conclusion. The military context can provide personal and occupational resources for women who experience IPV/SA, but the institutional (ie, chain of command reporting) and cultural context can constrain women’s ability to access resources and support, negatively affecting outcomes.

Commentary

Intimate partner violence (IPV) is a widespread public health problem in the United States and women in the military are no exception. According to Black and Merrick [1], 36.3% of active duty women experienced sexual violence in their lifetime and 39.7% experienced IPV. Violence has significant health, economic, and social consequences for women in all settings, including serious short- and long-term physical and mental health problems, economic hardship, isolation, and decreased quality of life [2–5]. Women who experience IPV/SA in any setting face challenges in protecting themselves, overcoming violence, and seeking justice, however, the context in which the violence occurs can significantly influence the individual experiences of women. This study used a qualitative approach to understand how it is experienced by service women in the context of the military.

As the authors note, military culture can both facilitate and hamper women’s recovery from the physical, psychological, and economic sequelae of IPV/SA. The rigid hierarchal structure of the military and the expectation that one supports the unit and fellow soldiers above all else makes it very difficult for women to disclose IPV/SA and seek and receive protection and justice. On the other hand, military training and service provides women with the skills and means to be independent and to physically distance themselves from the perpetrator. However, the comment of one woman that facing bombs in Iraq was preferable to facing the violence at home should serve as a reminder of how devastating IPV/SA is and suggests that victims do not think there are effective institutional deterrents or protection available to them.

As the authors note, this was a small convenience sample of women at one VA medical center. This qualitative study provides a beginning understanding that should be expanded on with multisite quantitative research with large samples. Sexual assault in the military has been recognized as a significant problem, particularly for women but also for men. We need to continue to study this problem from many different perspectives to determine how to prevent violence and to ensure all victims get the resources and effective services they need.

Applications for Clinical Practice

This study has implications for all health care providers, as active duty and veteran service women seek care outside as well as within the VA. An important finding that has direct application to practice in all settings is the influence of the warrior identity. The warrior identity has been widely acknowledged as a barrier to seeking help for depression or PTSD in service men returning from combat but not as much in service women and not in the context of IPV/SA. It is important that providers consider warrior identity in assessing and treating women for IPV/SA. Not only can this affect disclosure and prevent a victim from seeking help, but the expectation that they should have been invulnerable and strong may increase feelings of self-blame and worsen psychological distress.

 —Karen Roush, PhD, RN

Study Overview

Objective. To understand how the experience of intimate partner violence and non-partner sexual assault (IPV/SA) in women in the military intersects with military service.

Design. Qualitative interviews conducted as part of a larger study focused on experiences of IPV/SA and health care needs and preferences among women veteran patients.

Setting and participants. Participants were 25 women veterans from all branches of the service, ages 22 to 58 years (mean 44.6), who were patients at the Veteran’s Medical Center in Philadelphia, PA. The sample was diverse: 56% self-identified as black or African American, 20% as white or Caucasian, 16% as Hispanic or Latina, and 8% as “other” or multiple race/ethnicity.

Interviews. Researchers conducted face-to-face interviews using a semi-structured interview guide to gather in-depth narratives related to the participants’ lives in the military and their experiences of IPV/SA. The Military Occupational Mental Health Model was used as a framework to understand the experience of IPV/SA within the cultural context of the military and how that context influences health and well-being. The model considers the unique context of the military, including the importance of the values of mission over individual well-being, hierarchy and subordination, leadership, and unit support, as well as what resources are made available.

Data analysis. The authors followed an inductive approach informed by grounded theory, with the goal of identifying themes and a unifying theory empirically grounded in the interview data. First, 2 members of the research team conducted independent, close readings of each transcript and applied open coding, then compared their coding to identify common patterns across transcripts. Through this process, they developed and refined a codebook to define a set of codes and guide application of codes to text. Research team members conducted line-by-line coding of each transcript, based on the codebook definitions. Then the authors read all coded text and met to discuss patterns within and between transcripts, leading to identification of 2 core categories pertaining to the relationship betweenIPV/SA and military service, as well as several subthemes within each core category.

Main results. The 2 core categories identified  had both positive and negative influences. The first was  the “experience of IPV/SA affects participation in military service, including entering and leaving military service,” and included the subthemes of coercion by the perpetrator to enter or leave military service, effects on service and work performance such as physical and mental health problems that interfered with their ability to do their job, and survival strategies that had negative repercussions on the woman’s career. The second was  the “military context shapes responses to, and coping with, experiences of IPV/SA,” and included the subthemes of military sanction for IPV (but not sexual assault) if both partners were in the military, lack of accountability for and protection of service member perpetrators due to the value of unit support, military service as an opportunity to escape through relocation, even preferring a combat zone over home, and resistance to seeking help because of expectations of invulnerability related to the warrior identity.

Conclusion. The military context can provide personal and occupational resources for women who experience IPV/SA, but the institutional (ie, chain of command reporting) and cultural context can constrain women’s ability to access resources and support, negatively affecting outcomes.

Commentary

Intimate partner violence (IPV) is a widespread public health problem in the United States and women in the military are no exception. According to Black and Merrick [1], 36.3% of active duty women experienced sexual violence in their lifetime and 39.7% experienced IPV. Violence has significant health, economic, and social consequences for women in all settings, including serious short- and long-term physical and mental health problems, economic hardship, isolation, and decreased quality of life [2–5]. Women who experience IPV/SA in any setting face challenges in protecting themselves, overcoming violence, and seeking justice, however, the context in which the violence occurs can significantly influence the individual experiences of women. This study used a qualitative approach to understand how it is experienced by service women in the context of the military.

As the authors note, military culture can both facilitate and hamper women’s recovery from the physical, psychological, and economic sequelae of IPV/SA. The rigid hierarchal structure of the military and the expectation that one supports the unit and fellow soldiers above all else makes it very difficult for women to disclose IPV/SA and seek and receive protection and justice. On the other hand, military training and service provides women with the skills and means to be independent and to physically distance themselves from the perpetrator. However, the comment of one woman that facing bombs in Iraq was preferable to facing the violence at home should serve as a reminder of how devastating IPV/SA is and suggests that victims do not think there are effective institutional deterrents or protection available to them.

As the authors note, this was a small convenience sample of women at one VA medical center. This qualitative study provides a beginning understanding that should be expanded on with multisite quantitative research with large samples. Sexual assault in the military has been recognized as a significant problem, particularly for women but also for men. We need to continue to study this problem from many different perspectives to determine how to prevent violence and to ensure all victims get the resources and effective services they need.

Applications for Clinical Practice

This study has implications for all health care providers, as active duty and veteran service women seek care outside as well as within the VA. An important finding that has direct application to practice in all settings is the influence of the warrior identity. The warrior identity has been widely acknowledged as a barrier to seeking help for depression or PTSD in service men returning from combat but not as much in service women and not in the context of IPV/SA. It is important that providers consider warrior identity in assessing and treating women for IPV/SA. Not only can this affect disclosure and prevent a victim from seeking help, but the expectation that they should have been invulnerable and strong may increase feelings of self-blame and worsen psychological distress.

 —Karen Roush, PhD, RN

Study Overview

Objective. To test the efficacy of a weight loss app with incorporated social support and self-monitoring of diet, physical activity, and weight compared to a commercially available diet and PA tracking app.

Design. 2-group, randomized controlled trial.

Setting and participants. From October 2014 to January 2015, potential study participants were recruited via university/worksite listserv announcements, flyers, electronic newsletters, newspaper advertisements, social media posts, and a local research fair in 2 cities in South Carolina. Exclusion criteria included body mass index (BMI) outside the range of 25.0 to 49.9 kg/m², unable to attend required measurement sessions, unable to access a computer or internet for completing assessments, having a psychiatric illness, receiving treatment for drug or alcohol dependency, having an eating disorder, participating in another weight loss program, reporting weight loss of 10+ pounds in the past 6 months, being pregnant or planning on becoming pregnant during study, or breastfeeding, or endorsing items on the Physical Activity Readiness Questionnaire (PAR-Q) regarding having a heart condition, feeling chest pain during physical activity, experiencing chest pain, becoming dizzy/ever losing balance or consciousness, and not having a physician give consent to participate despite reporting joint problems or taking blood pressure medication. Those who were eligible were invited to an orientation to the study, signed consent, and completed baseline assessments.

Intervention. Participants were randomized to either the experimental group (theory-based podcasts plus the Social POD app) or the comparison group (theory-based podcasts plus a standard app [“Fat Secret” app]). Both groups attended a training session on how to access the podcasts and download and use their app, and also had their baseline height and weight taken by study staff. Both groups received 2 podcasts per week, tracked their diet, weight, and physical activity, completed weekly surveys to report use of their assigned tracking app, and had their weight measures taken after 3 months. Objective measures of podcast usage and app usage were collected by study staff (experimental group only).

Both apps had diet and physical activity tracking features, but the Social POD app also included notifications to track diet and physical activity, messages sent from frequent app users to re-engage infrequent app users, a newsfeed to view other participants app tracking activity, stars awarded to frequent users of the app, points awarded for tracking, and prizes for earning points distributed at the final session by study staff. The Fat Secret app did not have any social support components but included a recipe database for looking up recipes by category.

Main outcome measures. The primary outcome was between-group differences in kilograms lost at 3 months. Secondary outcomes included group change in BMI after 3 months, as well as group differences in self-reported caloric intake, caloric expenditure, social support, self-efficacy, and outcome expectations scores, controlled for baseline measures.

Main results. Of the potential participants that inquired about the study (n = 189), those found to be eligible (n = 78) were invited to an orientation. Of those that attended the orientation (n = 62), 51 were randomized after completing baseline assessments (n = 25 to experimental group with Social POD app, n =  25 to comparison group with Fat Secret app), and 42 completed final weight measurements after 3 months. Participants were mostly white (57%) females (82%) with a mean BMI of 34.7 ± 6.0 kg/m² and mean age of 46.2 ± 12.4 years. Baseline characteristics were similar between groups except that more comparison group participants reported previously downloading an app to track their diet than experimental participants. Participation attrition was 12% (n = 3 in each group).

Experimental group participants lost significantly more weight (–5.3 kg [95% CI, –7.5 to –3.0]) than the comparison group (–2.23 kg [95% CI, –3.6 to 1.0; P = 0.02). Experimental group participants also had a greater reduction in mean BMI (–1.9 kg/m² [95% CI, –2.6 to –1.2]) vs. the comparison group (mean –0.9 kg/m² [95% CI, –1.4 to – 0.05], P = 0.02). While there were significant differences in positive outcome expectations between groups (P = 0.04), other secondary outcomes were not significant.

Conclusions. An intervention with theory-based podcasts, social support, and incentivized self-monitoring resulted in significantly greater weight loss than a comparison intervention with theory-based podcasts and a commercially available standard self-monitoring app. This study highlights key features to add to mobile health interventions for adult weight loss.

Commentary

Obesity prevalence rates have increased over the past several decades across all genders, ages, ethnicities, income levels, and education levels [1], and recent data show that over one-third of adults in the US are obese and over two-thirds are overweight [2,3]. Behavior or lifestyle modification, which incorporates (often tailored) diet, physical activity, and behavior therapy, is highly recommended as the first strategy for losing initial weight and sustaining weight management efforts [4,5]. Mobile health (mHealth) technologies and other web-based and technology-assisted approaches (eg, mobile applications or “apps”) to facilitate behavior change for weight loss and management have aimed to address many of the limitations posed by traditional face-to-face weight loss approaches [6–8]. Prevailing theories of health behavior change imply key intervention design features that may increase their likelihood of promoting and sustaining desired behavior changes, particularly those that impact self-efficacy, self-regulation, and social facilitation [9,10].

Despite the plethora of weight loss mobile apps available to the public, it remains unclear if these are guided by evidence-based behavior change strategies typically used in traditional programs and approaches [11,12]. Further, very few of these apps have been rigorously evaluated with scientific testing to determine true effectiveness and safety [13,14]. This study adds to the literature by evaluating a mobile app for weight loss (Social POD) that was developed by researchers and utilizes theory-based components to target specific constructs that lead to health behavior change. Additionally, while self-monitoring is commonly incorporated into most available weight loss/management apps [11], the Social POD mobile app also incorporates social support and motivational strategies, which are less often included. The findings from this study add to the limited literature that mobile phone app-based interventions may be useful tools for weight loss [13].

The authors outlined several strengths and limitations. Briefly, this study was particularly strengthened by its randomized assignment to equivalent intervention groups, the use of a researcher-developed experimental group app that targets several key theory-based constructs for behavior change, measurement of objective use of the intervention group app, a racially diverse sample (over one-third of participants in both groups identified as black), measurement of secondary psycho-social behavioral outcomes, significant efforts to ensure survey completion and compliance with the intervention (increase retention), as well efforts to decrease participation burden by limiting required in-person sessions.

However, several important aspects of the study limit the internal validity and generalizability of its findings. The study had a small sample size and included a highly educated study population. If possible, future studies should consider including a large, diverse population to enhance generalizability. Also, this study was limited to those with an Android device, and significant demographic differences between Android and iPhone users have been reported [15]. The comparison group reported significantly more prior downloading of a diet-tracking app compared to the experimental group, which may have impacted use of the comparison app. The extrinsic reward system built into the experimental group intervention could have impacted adherence to experimental app, and is likely not feasible in real-world application of the experimental group app. Findings may have been subject to recall bias and measurement error due to self-reporting of outcomes measures. Importantly, this was a short-term weight loss study, and long-term weight loss/maintenance data is needed to support findings since in the usual course of weight-loss therapy the greatest weight loss occurs within 6 months of treatment, after which weight is often regained, sometimes near original level [16].

Applications for Clinical Practice

With the increasing popularity of technology-assisted and mHealth applications for weight loss and other health behaviors, it is important for practitioners to be familiar with proven, theory-based approaches and advise patients accordingly. This study demonstrated that social support components added to self-monitoring components in a weight loss app can lead to significant weight loss compared to self-monitoring alone. Thus, those that offer obesity counseling should be mindful that tracking and controlling dietary and physical activity behaviors alone may not prove to be successful. Opportunities for social facilitation to support weight loss efforts should be discussed with patients, including sources of social influence, support and collaboration between individuals, families, and health care professionals.

 —Katrina F. Mateo, MPH

Study Overview

Objective. To test the efficacy of a weight loss app with incorporated social support and self-monitoring of diet, physical activity, and weight compared to a commercially available diet and PA tracking app.

Design. 2-group, randomized controlled trial.

Setting and participants. From October 2014 to January 2015, potential study participants were recruited via university/worksite listserv announcements, flyers, electronic newsletters, newspaper advertisements, social media posts, and a local research fair in 2 cities in South Carolina. Exclusion criteria included body mass index (BMI) outside the range of 25.0 to 49.9 kg/m², unable to attend required measurement sessions, unable to access a computer or internet for completing assessments, having a psychiatric illness, receiving treatment for drug or alcohol dependency, having an eating disorder, participating in another weight loss program, reporting weight loss of 10+ pounds in the past 6 months, being pregnant or planning on becoming pregnant during study, or breastfeeding, or endorsing items on the Physical Activity Readiness Questionnaire (PAR-Q) regarding having a heart condition, feeling chest pain during physical activity, experiencing chest pain, becoming dizzy/ever losing balance or consciousness, and not having a physician give consent to participate despite reporting joint problems or taking blood pressure medication. Those who were eligible were invited to an orientation to the study, signed consent, and completed baseline assessments.

Intervention. Participants were randomized to either the experimental group (theory-based podcasts plus the Social POD app) or the comparison group (theory-based podcasts plus a standard app [“Fat Secret” app]). Both groups attended a training session on how to access the podcasts and download and use their app, and also had their baseline height and weight taken by study staff. Both groups received 2 podcasts per week, tracked their diet, weight, and physical activity, completed weekly surveys to report use of their assigned tracking app, and had their weight measures taken after 3 months. Objective measures of podcast usage and app usage were collected by study staff (experimental group only).

Both apps had diet and physical activity tracking features, but the Social POD app also included notifications to track diet and physical activity, messages sent from frequent app users to re-engage infrequent app users, a newsfeed to view other participants app tracking activity, stars awarded to frequent users of the app, points awarded for tracking, and prizes for earning points distributed at the final session by study staff. The Fat Secret app did not have any social support components but included a recipe database for looking up recipes by category.

Main outcome measures. The primary outcome was between-group differences in kilograms lost at 3 months. Secondary outcomes included group change in BMI after 3 months, as well as group differences in self-reported caloric intake, caloric expenditure, social support, self-efficacy, and outcome expectations scores, controlled for baseline measures.

Main results. Of the potential participants that inquired about the study (n = 189), those found to be eligible (n = 78) were invited to an orientation. Of those that attended the orientation (n = 62), 51 were randomized after completing baseline assessments (n = 25 to experimental group with Social POD app, n =  25 to comparison group with Fat Secret app), and 42 completed final weight measurements after 3 months. Participants were mostly white (57%) females (82%) with a mean BMI of 34.7 ± 6.0 kg/m² and mean age of 46.2 ± 12.4 years. Baseline characteristics were similar between groups except that more comparison group participants reported previously downloading an app to track their diet than experimental participants. Participation attrition was 12% (n = 3 in each group).

Experimental group participants lost significantly more weight (–5.3 kg [95% CI, –7.5 to –3.0]) than the comparison group (–2.23 kg [95% CI, –3.6 to 1.0; P = 0.02). Experimental group participants also had a greater reduction in mean BMI (–1.9 kg/m² [95% CI, –2.6 to –1.2]) vs. the comparison group (mean –0.9 kg/m² [95% CI, –1.4 to – 0.05], P = 0.02). While there were significant differences in positive outcome expectations between groups (P = 0.04), other secondary outcomes were not significant.

Conclusions. An intervention with theory-based podcasts, social support, and incentivized self-monitoring resulted in significantly greater weight loss than a comparison intervention with theory-based podcasts and a commercially available standard self-monitoring app. This study highlights key features to add to mobile health interventions for adult weight loss.

Commentary

Obesity prevalence rates have increased over the past several decades across all genders, ages, ethnicities, income levels, and education levels [1], and recent data show that over one-third of adults in the US are obese and over two-thirds are overweight [2,3]. Behavior or lifestyle modification, which incorporates (often tailored) diet, physical activity, and behavior therapy, is highly recommended as the first strategy for losing initial weight and sustaining weight management efforts [4,5]. Mobile health (mHealth) technologies and other web-based and technology-assisted approaches (eg, mobile applications or “apps”) to facilitate behavior change for weight loss and management have aimed to address many of the limitations posed by traditional face-to-face weight loss approaches [6–8]. Prevailing theories of health behavior change imply key intervention design features that may increase their likelihood of promoting and sustaining desired behavior changes, particularly those that impact self-efficacy, self-regulation, and social facilitation [9,10].

Despite the plethora of weight loss mobile apps available to the public, it remains unclear if these are guided by evidence-based behavior change strategies typically used in traditional programs and approaches [11,12]. Further, very few of these apps have been rigorously evaluated with scientific testing to determine true effectiveness and safety [13,14]. This study adds to the literature by evaluating a mobile app for weight loss (Social POD) that was developed by researchers and utilizes theory-based components to target specific constructs that lead to health behavior change. Additionally, while self-monitoring is commonly incorporated into most available weight loss/management apps [11], the Social POD mobile app also incorporates social support and motivational strategies, which are less often included. The findings from this study add to the limited literature that mobile phone app-based interventions may be useful tools for weight loss [13].

The authors outlined several strengths and limitations. Briefly, this study was particularly strengthened by its randomized assignment to equivalent intervention groups, the use of a researcher-developed experimental group app that targets several key theory-based constructs for behavior change, measurement of objective use of the intervention group app, a racially diverse sample (over one-third of participants in both groups identified as black), measurement of secondary psycho-social behavioral outcomes, significant efforts to ensure survey completion and compliance with the intervention (increase retention), as well efforts to decrease participation burden by limiting required in-person sessions.

However, several important aspects of the study limit the internal validity and generalizability of its findings. The study had a small sample size and included a highly educated study population. If possible, future studies should consider including a large, diverse population to enhance generalizability. Also, this study was limited to those with an Android device, and significant demographic differences between Android and iPhone users have been reported [15]. The comparison group reported significantly more prior downloading of a diet-tracking app compared to the experimental group, which may have impacted use of the comparison app. The extrinsic reward system built into the experimental group intervention could have impacted adherence to experimental app, and is likely not feasible in real-world application of the experimental group app. Findings may have been subject to recall bias and measurement error due to self-reporting of outcomes measures. Importantly, this was a short-term weight loss study, and long-term weight loss/maintenance data is needed to support findings since in the usual course of weight-loss therapy the greatest weight loss occurs within 6 months of treatment, after which weight is often regained, sometimes near original level [16].

Applications for Clinical Practice

With the increasing popularity of technology-assisted and mHealth applications for weight loss and other health behaviors, it is important for practitioners to be familiar with proven, theory-based approaches and advise patients accordingly. This study demonstrated that social support components added to self-monitoring components in a weight loss app can lead to significant weight loss compared to self-monitoring alone. Thus, those that offer obesity counseling should be mindful that tracking and controlling dietary and physical activity behaviors alone may not prove to be successful. Opportunities for social facilitation to support weight loss efforts should be discussed with patients, including sources of social influence, support and collaboration between individuals, families, and health care professionals.

 —Katrina F. Mateo, MPH

Study Overview

Objective. To test the efficacy of a weight loss app with incorporated social support and self-monitoring of diet, physical activity, and weight compared to a commercially available diet and PA tracking app.

Design. 2-group, randomized controlled trial.

Setting and participants. From October 2014 to January 2015, potential study participants were recruited via university/worksite listserv announcements, flyers, electronic newsletters, newspaper advertisements, social media posts, and a local research fair in 2 cities in South Carolina. Exclusion criteria included body mass index (BMI) outside the range of 25.0 to 49.9 kg/m², unable to attend required measurement sessions, unable to access a computer or internet for completing assessments, having a psychiatric illness, receiving treatment for drug or alcohol dependency, having an eating disorder, participating in another weight loss program, reporting weight loss of 10+ pounds in the past 6 months, being pregnant or planning on becoming pregnant during study, or breastfeeding, or endorsing items on the Physical Activity Readiness Questionnaire (PAR-Q) regarding having a heart condition, feeling chest pain during physical activity, experiencing chest pain, becoming dizzy/ever losing balance or consciousness, and not having a physician give consent to participate despite reporting joint problems or taking blood pressure medication. Those who were eligible were invited to an orientation to the study, signed consent, and completed baseline assessments.

Intervention. Participants were randomized to either the experimental group (theory-based podcasts plus the Social POD app) or the comparison group (theory-based podcasts plus a standard app [“Fat Secret” app]). Both groups attended a training session on how to access the podcasts and download and use their app, and also had their baseline height and weight taken by study staff. Both groups received 2 podcasts per week, tracked their diet, weight, and physical activity, completed weekly surveys to report use of their assigned tracking app, and had their weight measures taken after 3 months. Objective measures of podcast usage and app usage were collected by study staff (experimental group only).

Both apps had diet and physical activity tracking features, but the Social POD app also included notifications to track diet and physical activity, messages sent from frequent app users to re-engage infrequent app users, a newsfeed to view other participants app tracking activity, stars awarded to frequent users of the app, points awarded for tracking, and prizes for earning points distributed at the final session by study staff. The Fat Secret app did not have any social support components but included a recipe database for looking up recipes by category.

Main outcome measures. The primary outcome was between-group differences in kilograms lost at 3 months. Secondary outcomes included group change in BMI after 3 months, as well as group differences in self-reported caloric intake, caloric expenditure, social support, self-efficacy, and outcome expectations scores, controlled for baseline measures.

Main results. Of the potential participants that inquired about the study (n = 189), those found to be eligible (n = 78) were invited to an orientation. Of those that attended the orientation (n = 62), 51 were randomized after completing baseline assessments (n = 25 to experimental group with Social POD app, n =  25 to comparison group with Fat Secret app), and 42 completed final weight measurements after 3 months. Participants were mostly white (57%) females (82%) with a mean BMI of 34.7 ± 6.0 kg/m² and mean age of 46.2 ± 12.4 years. Baseline characteristics were similar between groups except that more comparison group participants reported previously downloading an app to track their diet than experimental participants. Participation attrition was 12% (n = 3 in each group).

Experimental group participants lost significantly more weight (–5.3 kg [95% CI, –7.5 to –3.0]) than the comparison group (–2.23 kg [95% CI, –3.6 to 1.0; P = 0.02). Experimental group participants also had a greater reduction in mean BMI (–1.9 kg/m² [95% CI, –2.6 to –1.2]) vs. the comparison group (mean –0.9 kg/m² [95% CI, –1.4 to – 0.05], P = 0.02). While there were significant differences in positive outcome expectations between groups (P = 0.04), other secondary outcomes were not significant.

Conclusions. An intervention with theory-based podcasts, social support, and incentivized self-monitoring resulted in significantly greater weight loss than a comparison intervention with theory-based podcasts and a commercially available standard self-monitoring app. This study highlights key features to add to mobile health interventions for adult weight loss.

Commentary

Obesity prevalence rates have increased over the past several decades across all genders, ages, ethnicities, income levels, and education levels [1], and recent data show that over one-third of adults in the US are obese and over two-thirds are overweight [2,3]. Behavior or lifestyle modification, which incorporates (often tailored) diet, physical activity, and behavior therapy, is highly recommended as the first strategy for losing initial weight and sustaining weight management efforts [4,5]. Mobile health (mHealth) technologies and other web-based and technology-assisted approaches (eg, mobile applications or “apps”) to facilitate behavior change for weight loss and management have aimed to address many of the limitations posed by traditional face-to-face weight loss approaches [6–8]. Prevailing theories of health behavior change imply key intervention design features that may increase their likelihood of promoting and sustaining desired behavior changes, particularly those that impact self-efficacy, self-regulation, and social facilitation [9,10].

Despite the plethora of weight loss mobile apps available to the public, it remains unclear if these are guided by evidence-based behavior change strategies typically used in traditional programs and approaches [11,12]. Further, very few of these apps have been rigorously evaluated with scientific testing to determine true effectiveness and safety [13,14]. This study adds to the literature by evaluating a mobile app for weight loss (Social POD) that was developed by researchers and utilizes theory-based components to target specific constructs that lead to health behavior change. Additionally, while self-monitoring is commonly incorporated into most available weight loss/management apps [11], the Social POD mobile app also incorporates social support and motivational strategies, which are less often included. The findings from this study add to the limited literature that mobile phone app-based interventions may be useful tools for weight loss [13].

The authors outlined several strengths and limitations. Briefly, this study was particularly strengthened by its randomized assignment to equivalent intervention groups, the use of a researcher-developed experimental group app that targets several key theory-based constructs for behavior change, measurement of objective use of the intervention group app, a racially diverse sample (over one-third of participants in both groups identified as black), measurement of secondary psycho-social behavioral outcomes, significant efforts to ensure survey completion and compliance with the intervention (increase retention), as well efforts to decrease participation burden by limiting required in-person sessions.

However, several important aspects of the study limit the internal validity and generalizability of its findings. The study had a small sample size and included a highly educated study population. If possible, future studies should consider including a large, diverse population to enhance generalizability. Also, this study was limited to those with an Android device, and significant demographic differences between Android and iPhone users have been reported [15]. The comparison group reported significantly more prior downloading of a diet-tracking app compared to the experimental group, which may have impacted use of the comparison app. The extrinsic reward system built into the experimental group intervention could have impacted adherence to experimental app, and is likely not feasible in real-world application of the experimental group app. Findings may have been subject to recall bias and measurement error due to self-reporting of outcomes measures. Importantly, this was a short-term weight loss study, and long-term weight loss/maintenance data is needed to support findings since in the usual course of weight-loss therapy the greatest weight loss occurs within 6 months of treatment, after which weight is often regained, sometimes near original level [16].

Applications for Clinical Practice

With the increasing popularity of technology-assisted and mHealth applications for weight loss and other health behaviors, it is important for practitioners to be familiar with proven, theory-based approaches and advise patients accordingly. This study demonstrated that social support components added to self-monitoring components in a weight loss app can lead to significant weight loss compared to self-monitoring alone. Thus, those that offer obesity counseling should be mindful that tracking and controlling dietary and physical activity behaviors alone may not prove to be successful. Opportunities for social facilitation to support weight loss efforts should be discussed with patients, including sources of social influence, support and collaboration between individuals, families, and health care professionals.

 —Katrina F. Mateo, MPH

Study Overview

Objective. To determine the prevalence of hypotension using both clinic and ambulatory blood pressure monitoring (ABPM) in treated hypertensive patients and the factors associated with its presence.

Design. Registry-based study.

Setting and participants. Researchers studied patients in the Spanish Society of Hypertension ABPM Registry, which was established to evaluate the utility of the wider use of ABPM with the distribution of >1000 ambulatory BP monitors for routine use by primary care physicians and physicians from specialist units across Spain. The registry continues to expand since the first patient was recruited in June 2004. In June 2015, a total of 135,500 hypertensive patients were in the registry.

Measurements. Blood pressure readings in the clinic were taken according to current recommendations, with the patients in a seated position and their backs supported, after a 5-minute rest, using calibrated sphygmomanometers or validated automatic devices. The visit BP was the average of 2 separate readings. Validated devices (Spacelabs) were used for ABPM, which was performed during a working day with measurements taken every 30 minutes. Patients were told to keep their activity normal and to extend the arm without any movement during BP measurements. ABPM was considered successful in ≥ 80% systolic and diastolic BP valid readings. Patients were classified into 3 categories: hypotension, adequate BP control, or poor BP control for each type of blood pressure (office, daytime, nighttime, and 24-hour). The definitions for hypotension for each BP type were mainly based of the PROVE IT-TIMI study, ie, < 110 and/or 70 mm Hg for office, < 105 and/or 65 mm Hg for daytime ABPM, < 90 and or 50 mm Hg for nightime ABPM, and < 100 and/or 60 mm Hg for 24-hr ABPM.

Results. Of the 135,500 patients in the registry, only data from treated hypertensive patients were analyzed (n = 70,997). Mean age was 61.8 ± 12.8 years and 52.5% were men. The prevalence of hypotension was 8.2% with office BP, 12.2% with daytime ABPM, 3.9% with nightime ABPM, and 6.8% with 24-hour ABPM. Low diastolic BP values were responsible for the majority of hypotension. More than 68% of patients with hypotension detected with ABPM did not have hypotension according to office BP. Patients with hypotension were older, more likely to be female, and more likely to have high pulse pressue, lower heart rate, ischemic heart disease, and renal insufficiency. They were also more likely to be taking 3 or more drugs for hypertension.

Conclusion. The prevalence of hypotension is relatively high in treated hypertensive patients, and two-thirds are not identified with office BP measurement. Prevalence was higher in patients who were very elderly or with coronary or renal disease.

Commentary

Hypertension is a major public health concern worldwide [1]. In 2011–12 among US adults with hypertension, only 51.9% had their blood pressure controlled [2]. High blood pressure can effectively be reduced with antihypertensive treatment, and efforts are needed to improve clinical management of hypertension. However, excessive BP reduction may lead to patient harm.

In this study, researchers aimed to determine the prevalence of hypotension using both clinic and ABPM in hypertensive-treated patients and the factors associated with its presence, using descriptive statistics and multivariate analysis. The results highlight the need for health care providers to be aware of the individual response to antihypertensives in patients with high blood pressure and to individualize treatment to avoid complications of hypotension. A strength of this study was it large sample size.

Adherence to treatment recommendations was not a variable taken into consideration for this study and could be considered a confounder. Diet and behavioral interventions can have a significantly beneficial effect on hypertension and can reduce the need for drug therapy [3]. If patients were highly engaged and adopted lifestyle habits that can contribute to better blood pressure levels along with taking prescribed medications, this could have contributed to levels of hypotension.

Hypotension among hypertensive patients can be difficult to identify during clinical consultations due the “white coat effect.” This syndrome is characterized by a peak of high blood pressure caused by the stress of the individual in the presence of a healthcare provider or in a stressful medical environment [4]. This study showed that more than half of the patients in the sample with detected hypotension in the ABPM did not show hypotension during consultation at the medical office. This finding highlights the challenge in identifying hypotension and making adjustments to antihypertensive medication regimens as needed.

Women, patients with low body weight, and elderly patients were the groups more likely to develop hypo-tension. Thus, strategies specifically targeting these vulnerable groups are required. As suggested by the authors of this study, further longitudinal research is needed in order to identify gaps in the state of science in regards this topic and changes in the prevalence this population. The replication of this study in different populations is also encouraged.

Applications for Clinical Practice

The prevalence of hypotension is relatively high and may not be detected during office BP measurement. In patients with a higher risk of hypotension, such as the elderly those with cardiovascular disease, the use of ABPM should be considered.

—Paloma Cesar de Sales, BS, RN, MS

Study Overview

Objective. To determine the prevalence of hypotension using both clinic and ambulatory blood pressure monitoring (ABPM) in treated hypertensive patients and the factors associated with its presence.

Design. Registry-based study.

Setting and participants. Researchers studied patients in the Spanish Society of Hypertension ABPM Registry, which was established to evaluate the utility of the wider use of ABPM with the distribution of >1000 ambulatory BP monitors for routine use by primary care physicians and physicians from specialist units across Spain. The registry continues to expand since the first patient was recruited in June 2004. In June 2015, a total of 135,500 hypertensive patients were in the registry.

Measurements. Blood pressure readings in the clinic were taken according to current recommendations, with the patients in a seated position and their backs supported, after a 5-minute rest, using calibrated sphygmomanometers or validated automatic devices. The visit BP was the average of 2 separate readings. Validated devices (Spacelabs) were used for ABPM, which was performed during a working day with measurements taken every 30 minutes. Patients were told to keep their activity normal and to extend the arm without any movement during BP measurements. ABPM was considered successful in ≥ 80% systolic and diastolic BP valid readings. Patients were classified into 3 categories: hypotension, adequate BP control, or poor BP control for each type of blood pressure (office, daytime, nighttime, and 24-hour). The definitions for hypotension for each BP type were mainly based of the PROVE IT-TIMI study, ie, < 110 and/or 70 mm Hg for office, < 105 and/or 65 mm Hg for daytime ABPM, < 90 and or 50 mm Hg for nightime ABPM, and < 100 and/or 60 mm Hg for 24-hr ABPM.

Results. Of the 135,500 patients in the registry, only data from treated hypertensive patients were analyzed (n = 70,997). Mean age was 61.8 ± 12.8 years and 52.5% were men. The prevalence of hypotension was 8.2% with office BP, 12.2% with daytime ABPM, 3.9% with nightime ABPM, and 6.8% with 24-hour ABPM. Low diastolic BP values were responsible for the majority of hypotension. More than 68% of patients with hypotension detected with ABPM did not have hypotension according to office BP. Patients with hypotension were older, more likely to be female, and more likely to have high pulse pressue, lower heart rate, ischemic heart disease, and renal insufficiency. They were also more likely to be taking 3 or more drugs for hypertension.

Conclusion. The prevalence of hypotension is relatively high in treated hypertensive patients, and two-thirds are not identified with office BP measurement. Prevalence was higher in patients who were very elderly or with coronary or renal disease.

Commentary

Hypertension is a major public health concern worldwide [1]. In 2011–12 among US adults with hypertension, only 51.9% had their blood pressure controlled [2]. High blood pressure can effectively be reduced with antihypertensive treatment, and efforts are needed to improve clinical management of hypertension. However, excessive BP reduction may lead to patient harm.

In this study, researchers aimed to determine the prevalence of hypotension using both clinic and ABPM in hypertensive-treated patients and the factors associated with its presence, using descriptive statistics and multivariate analysis. The results highlight the need for health care providers to be aware of the individual response to antihypertensives in patients with high blood pressure and to individualize treatment to avoid complications of hypotension. A strength of this study was it large sample size.

Adherence to treatment recommendations was not a variable taken into consideration for this study and could be considered a confounder. Diet and behavioral interventions can have a significantly beneficial effect on hypertension and can reduce the need for drug therapy [3]. If patients were highly engaged and adopted lifestyle habits that can contribute to better blood pressure levels along with taking prescribed medications, this could have contributed to levels of hypotension.

Hypotension among hypertensive patients can be difficult to identify during clinical consultations due the “white coat effect.” This syndrome is characterized by a peak of high blood pressure caused by the stress of the individual in the presence of a healthcare provider or in a stressful medical environment [4]. This study showed that more than half of the patients in the sample with detected hypotension in the ABPM did not show hypotension during consultation at the medical office. This finding highlights the challenge in identifying hypotension and making adjustments to antihypertensive medication regimens as needed.

Women, patients with low body weight, and elderly patients were the groups more likely to develop hypo-tension. Thus, strategies specifically targeting these vulnerable groups are required. As suggested by the authors of this study, further longitudinal research is needed in order to identify gaps in the state of science in regards this topic and changes in the prevalence this population. The replication of this study in different populations is also encouraged.

Applications for Clinical Practice

The prevalence of hypotension is relatively high and may not be detected during office BP measurement. In patients with a higher risk of hypotension, such as the elderly those with cardiovascular disease, the use of ABPM should be considered.

—Paloma Cesar de Sales, BS, RN, MS

Study Overview

Objective. To determine the prevalence of hypotension using both clinic and ambulatory blood pressure monitoring (ABPM) in treated hypertensive patients and the factors associated with its presence.

Design. Registry-based study.

Setting and participants. Researchers studied patients in the Spanish Society of Hypertension ABPM Registry, which was established to evaluate the utility of the wider use of ABPM with the distribution of >1000 ambulatory BP monitors for routine use by primary care physicians and physicians from specialist units across Spain. The registry continues to expand since the first patient was recruited in June 2004. In June 2015, a total of 135,500 hypertensive patients were in the registry.

Measurements. Blood pressure readings in the clinic were taken according to current recommendations, with the patients in a seated position and their backs supported, after a 5-minute rest, using calibrated sphygmomanometers or validated automatic devices. The visit BP was the average of 2 separate readings. Validated devices (Spacelabs) were used for ABPM, which was performed during a working day with measurements taken every 30 minutes. Patients were told to keep their activity normal and to extend the arm without any movement during BP measurements. ABPM was considered successful in ≥ 80% systolic and diastolic BP valid readings. Patients were classified into 3 categories: hypotension, adequate BP control, or poor BP control for each type of blood pressure (office, daytime, nighttime, and 24-hour). The definitions for hypotension for each BP type were mainly based of the PROVE IT-TIMI study, ie, < 110 and/or 70 mm Hg for office, < 105 and/or 65 mm Hg for daytime ABPM, < 90 and or 50 mm Hg for nightime ABPM, and < 100 and/or 60 mm Hg for 24-hr ABPM.

Results. Of the 135,500 patients in the registry, only data from treated hypertensive patients were analyzed (n = 70,997). Mean age was 61.8 ± 12.8 years and 52.5% were men. The prevalence of hypotension was 8.2% with office BP, 12.2% with daytime ABPM, 3.9% with nightime ABPM, and 6.8% with 24-hour ABPM. Low diastolic BP values were responsible for the majority of hypotension. More than 68% of patients with hypotension detected with ABPM did not have hypotension according to office BP. Patients with hypotension were older, more likely to be female, and more likely to have high pulse pressue, lower heart rate, ischemic heart disease, and renal insufficiency. They were also more likely to be taking 3 or more drugs for hypertension.

Conclusion. The prevalence of hypotension is relatively high in treated hypertensive patients, and two-thirds are not identified with office BP measurement. Prevalence was higher in patients who were very elderly or with coronary or renal disease.

Commentary

Hypertension is a major public health concern worldwide [1]. In 2011–12 among US adults with hypertension, only 51.9% had their blood pressure controlled [2]. High blood pressure can effectively be reduced with antihypertensive treatment, and efforts are needed to improve clinical management of hypertension. However, excessive BP reduction may lead to patient harm.

In this study, researchers aimed to determine the prevalence of hypotension using both clinic and ABPM in hypertensive-treated patients and the factors associated with its presence, using descriptive statistics and multivariate analysis. The results highlight the need for health care providers to be aware of the individual response to antihypertensives in patients with high blood pressure and to individualize treatment to avoid complications of hypotension. A strength of this study was it large sample size.

Adherence to treatment recommendations was not a variable taken into consideration for this study and could be considered a confounder. Diet and behavioral interventions can have a significantly beneficial effect on hypertension and can reduce the need for drug therapy [3]. If patients were highly engaged and adopted lifestyle habits that can contribute to better blood pressure levels along with taking prescribed medications, this could have contributed to levels of hypotension.

Hypotension among hypertensive patients can be difficult to identify during clinical consultations due the “white coat effect.” This syndrome is characterized by a peak of high blood pressure caused by the stress of the individual in the presence of a healthcare provider or in a stressful medical environment [4]. This study showed that more than half of the patients in the sample with detected hypotension in the ABPM did not show hypotension during consultation at the medical office. This finding highlights the challenge in identifying hypotension and making adjustments to antihypertensive medication regimens as needed.

Women, patients with low body weight, and elderly patients were the groups more likely to develop hypo-tension. Thus, strategies specifically targeting these vulnerable groups are required. As suggested by the authors of this study, further longitudinal research is needed in order to identify gaps in the state of science in regards this topic and changes in the prevalence this population. The replication of this study in different populations is also encouraged.

Applications for Clinical Practice

The prevalence of hypotension is relatively high and may not be detected during office BP measurement. In patients with a higher risk of hypotension, such as the elderly those with cardiovascular disease, the use of ABPM should be considered.

—Paloma Cesar de Sales, BS, RN, MS

Study Overview

Objective. To assess whether noninvasive functional imaging strategies reduced unnecessary angiography compared with UK national guidelines–directed care.

Design. 3–parallel group, multicenter randomized clinical trial using a pragmatic comparative effectiveness design.

Setting and participants. Participants were patients from 6 UK centers (Leeds, Glasgow, Leicester, Bristol, Oxford, London) age 30 years or older with suspected angina pectoris, a coronary heart disease (CHD) pretest likelihood of 10% to 90%, and who were suitable for revascularization. They were randomly assigned at a 1:2:2 allocation ratio to the UK NICE (National Institute for Health Care Excellence) guidelines or to care guided by the results of cardiovascular magnetic resonance (CMR) or myocardial perfusion scintigraphy (MPS).

Main outcome measures. The primary outcome of the study was protocol-defined unnecessary coronary angiography occurring within 12 months, defined by a normal FFR (fractional flow reserve) > 0.8, or quantitative coronary angiography (QCA) showing no percentage diameter stenosis ≥ 70% in 1 view or ≥ 70% in 2 orthogonal views in all vessels 2.5 mm or more in diameter within 12 months. Because of the study design, this included any unnecessary angiography occurring after a false-positive test result, patients with high CHD pretest likelihood sent directly to coronary angiography in the NICE guidelines group, and imaging results that were either inconclusive or negative but overruled by the responsible physician.

Secondary endpoints included positive angiography rates, a composite of major adverse cardiovascular events (MACEs: cardiovascular death, myocardial infarction, unplanned coronary revascularization, and hospital admission for cardiovascular cause), and procedural complications.

Main results. Among 2205 patients assessed for eligibility between 23 November 2012 and 13 March 2015, 1202 patients (55% of eligible) were recruited and allocated to NICE guidelines–directed care (n = 240), or management by CMR (n = 481) or MPS (n = 481). While there were no statistical differences between the 3 groups in terms of baseline characteristics, the study population had a substantial burden of cardiovascular risk factors: 150 patients (12.5%) had diabetes, 458 patients (38.1%) had hypertension, 702 patients (58.4%) were past or current tobacco users, 483 patients (40.2%) had dyslipidemia, and 651 patients (54.2%) had a family history of premature CHD. All patients were symptomatic, with 401 patients (33.4%) reporting typical chest pain and 801 patients (66.6%) reporting atypical chest pain as their primary symptom. Overall, 265 patients (22.0%) underwent at least 1 coronary angiogram and 10 patients underwent 2 angiograms.

The number of patients with invasive coronary angiography after 12 months were as follows: 102 of the 240 patients in the NICE guidelines group (42.5% [95% confidence interval {CI} 36.2%–49.0%]), 85 of the 481 patients in the CMR group (17.7% [95% CI 14.4%–21.4%]), and 78 of the 481 patients in the MPS group (16.2% [95% CI 13.0%–19.8%]). The primary endpoint of unnecessary angiography occurred in 69 patients (28.8%) in the NICE guidelines group, 36 patients (7.5%) in the CMR group, and 34 patients (7.1%) in the MPS group. Using CMR group as reference, adjusted odds ratio (AOR) of unnecessary angiography for CMR group vs. NICE guidelines group was 0.21 (95% CI 0.12–0.34, P < 0.001), and the AOR for CMR group vs. the MPS groups was 1.27 (95% CI 0.79–2.03, P = 0.32).

For the secondary endpoints, positive angiography was observed in 29 patients (12.1% [95% CI 8.2%–16.9%]) in the NICE guidelines group, 47 patients (9.8% [95% CI 7.3%–12.8%]) in the CMR group, and 42 patients (8.7% [95% CI 6.4%–11.6%]) in the MPS group, overall P = 0.36. Annualized MACE rates ware 1.6% in the NICE guidelines group, 2.0% for the CMR group, and 2.0% for the MPS group. Adjusted hazard ratios for MACE were 1.37 (95% CI 0.52–3.57, P = 0.52) for the CMR group vs. NICE guidelines group and 0.95 (95% CI 0.46–1.95, P = 0.88) for the CMR group vs. the MPS group.

Conclusion. In patients with suspected CHD, investigation by CMR or MPS resulted in lower probability of unnecessary angiography within 12 months of care than using the NICE guideline–directed care. There was no difference in adverse outcomes as measured by MACE by using NICE guidelines, CMR, or MPS.

Commentary

Coronary heart disease is a leading cause of morbidity and mortality worldwide. Despite the advancement in noninvasive imaging and recommendations in international guidelines, invasive coronary angiography is still commonly used early in diagnostic pathways in patients with suspected CHD [1]. Previous studies demonstrated that majority of patients presenting with chest pain will not have significant obstructive coronary disease; a large US study reported that approximately 60% of elective cardiac catheterizations found no obstructive CHD [2]. Thus, avoiding unnecessary angiography should reduce patient risk and provide significant financial savings. Current guidelines for investigation of stable chest pain rely on pretest likelihood of CHD. These pretest likelihood models can overestimate CHD risk, resulting in the increase in probability of invasive coronary angiography [1,3].

The current study by Greenwood et al investigated whether CMR-guided care is superior to MPS or NICE guidelines–directed care in reducing the occurrence of unnecessary angiography within 12 months. Overall, rates of disease detection based on positive angiogram were comparable for the 3 strategies. In addition, there was no difference in adverse events as measured by a composite of MACE.

While this was an excellently performed multicenter study, there were several major limitations. First, the study population was predominately white northern European (92% were classified ethnically as white), and therefore the results may not translate to other populations. Second, the NICE guidelines for estimation of high-risk CHD changed after initiation of the study due to overestimation, and recent guidelines have adopted a recalibrated risk model [4,5]. Finally, MACE is not a proxy for a missed diagnosis or treatment. It remains debatable whether revascularization for stable angina has prognostic benefit over optimal medical therapy.

Applications for Clinical Practice

This multicenter randomized clinical trial provides strong evidence to use either cardiovascular magnetic resonance–guided care or myocardial perfusion scintigraphy–guided care instead of NICE guidelines–directed care for symptomatic patients with suspected CHD in reducing unnecessary angiography.

—Ka Ming Gordon Ngai, MD, MPH

Study Overview

Objective. To assess whether noninvasive functional imaging strategies reduced unnecessary angiography compared with UK national guidelines–directed care.

Design. 3–parallel group, multicenter randomized clinical trial using a pragmatic comparative effectiveness design.

Setting and participants. Participants were patients from 6 UK centers (Leeds, Glasgow, Leicester, Bristol, Oxford, London) age 30 years or older with suspected angina pectoris, a coronary heart disease (CHD) pretest likelihood of 10% to 90%, and who were suitable for revascularization. They were randomly assigned at a 1:2:2 allocation ratio to the UK NICE (National Institute for Health Care Excellence) guidelines or to care guided by the results of cardiovascular magnetic resonance (CMR) or myocardial perfusion scintigraphy (MPS).

Main outcome measures. The primary outcome of the study was protocol-defined unnecessary coronary angiography occurring within 12 months, defined by a normal FFR (fractional flow reserve) > 0.8, or quantitative coronary angiography (QCA) showing no percentage diameter stenosis ≥ 70% in 1 view or ≥ 70% in 2 orthogonal views in all vessels 2.5 mm or more in diameter within 12 months. Because of the study design, this included any unnecessary angiography occurring after a false-positive test result, patients with high CHD pretest likelihood sent directly to coronary angiography in the NICE guidelines group, and imaging results that were either inconclusive or negative but overruled by the responsible physician.

Secondary endpoints included positive angiography rates, a composite of major adverse cardiovascular events (MACEs: cardiovascular death, myocardial infarction, unplanned coronary revascularization, and hospital admission for cardiovascular cause), and procedural complications.

Main results. Among 2205 patients assessed for eligibility between 23 November 2012 and 13 March 2015, 1202 patients (55% of eligible) were recruited and allocated to NICE guidelines–directed care (n = 240), or management by CMR (n = 481) or MPS (n = 481). While there were no statistical differences between the 3 groups in terms of baseline characteristics, the study population had a substantial burden of cardiovascular risk factors: 150 patients (12.5%) had diabetes, 458 patients (38.1%) had hypertension, 702 patients (58.4%) were past or current tobacco users, 483 patients (40.2%) had dyslipidemia, and 651 patients (54.2%) had a family history of premature CHD. All patients were symptomatic, with 401 patients (33.4%) reporting typical chest pain and 801 patients (66.6%) reporting atypical chest pain as their primary symptom. Overall, 265 patients (22.0%) underwent at least 1 coronary angiogram and 10 patients underwent 2 angiograms.

The number of patients with invasive coronary angiography after 12 months were as follows: 102 of the 240 patients in the NICE guidelines group (42.5% [95% confidence interval {CI} 36.2%–49.0%]), 85 of the 481 patients in the CMR group (17.7% [95% CI 14.4%–21.4%]), and 78 of the 481 patients in the MPS group (16.2% [95% CI 13.0%–19.8%]). The primary endpoint of unnecessary angiography occurred in 69 patients (28.8%) in the NICE guidelines group, 36 patients (7.5%) in the CMR group, and 34 patients (7.1%) in the MPS group. Using CMR group as reference, adjusted odds ratio (AOR) of unnecessary angiography for CMR group vs. NICE guidelines group was 0.21 (95% CI 0.12–0.34, P < 0.001), and the AOR for CMR group vs. the MPS groups was 1.27 (95% CI 0.79–2.03, P = 0.32).

For the secondary endpoints, positive angiography was observed in 29 patients (12.1% [95% CI 8.2%–16.9%]) in the NICE guidelines group, 47 patients (9.8% [95% CI 7.3%–12.8%]) in the CMR group, and 42 patients (8.7% [95% CI 6.4%–11.6%]) in the MPS group, overall P = 0.36. Annualized MACE rates ware 1.6% in the NICE guidelines group, 2.0% for the CMR group, and 2.0% for the MPS group. Adjusted hazard ratios for MACE were 1.37 (95% CI 0.52–3.57, P = 0.52) for the CMR group vs. NICE guidelines group and 0.95 (95% CI 0.46–1.95, P = 0.88) for the CMR group vs. the MPS group.

Conclusion. In patients with suspected CHD, investigation by CMR or MPS resulted in lower probability of unnecessary angiography within 12 months of care than using the NICE guideline–directed care. There was no difference in adverse outcomes as measured by MACE by using NICE guidelines, CMR, or MPS.

Commentary

Coronary heart disease is a leading cause of morbidity and mortality worldwide. Despite the advancement in noninvasive imaging and recommendations in international guidelines, invasive coronary angiography is still commonly used early in diagnostic pathways in patients with suspected CHD [1]. Previous studies demonstrated that majority of patients presenting with chest pain will not have significant obstructive coronary disease; a large US study reported that approximately 60% of elective cardiac catheterizations found no obstructive CHD [2]. Thus, avoiding unnecessary angiography should reduce patient risk and provide significant financial savings. Current guidelines for investigation of stable chest pain rely on pretest likelihood of CHD. These pretest likelihood models can overestimate CHD risk, resulting in the increase in probability of invasive coronary angiography [1,3].

The current study by Greenwood et al investigated whether CMR-guided care is superior to MPS or NICE guidelines–directed care in reducing the occurrence of unnecessary angiography within 12 months. Overall, rates of disease detection based on positive angiogram were comparable for the 3 strategies. In addition, there was no difference in adverse events as measured by a composite of MACE.

While this was an excellently performed multicenter study, there were several major limitations. First, the study population was predominately white northern European (92% were classified ethnically as white), and therefore the results may not translate to other populations. Second, the NICE guidelines for estimation of high-risk CHD changed after initiation of the study due to overestimation, and recent guidelines have adopted a recalibrated risk model [4,5]. Finally, MACE is not a proxy for a missed diagnosis or treatment. It remains debatable whether revascularization for stable angina has prognostic benefit over optimal medical therapy.

Applications for Clinical Practice

This multicenter randomized clinical trial provides strong evidence to use either cardiovascular magnetic resonance–guided care or myocardial perfusion scintigraphy–guided care instead of NICE guidelines–directed care for symptomatic patients with suspected CHD in reducing unnecessary angiography.

—Ka Ming Gordon Ngai, MD, MPH

Study Overview

Objective. To assess whether noninvasive functional imaging strategies reduced unnecessary angiography compared with UK national guidelines–directed care.

Design. 3–parallel group, multicenter randomized clinical trial using a pragmatic comparative effectiveness design.

Setting and participants. Participants were patients from 6 UK centers (Leeds, Glasgow, Leicester, Bristol, Oxford, London) age 30 years or older with suspected angina pectoris, a coronary heart disease (CHD) pretest likelihood of 10% to 90%, and who were suitable for revascularization. They were randomly assigned at a 1:2:2 allocation ratio to the UK NICE (National Institute for Health Care Excellence) guidelines or to care guided by the results of cardiovascular magnetic resonance (CMR) or myocardial perfusion scintigraphy (MPS).

Main outcome measures. The primary outcome of the study was protocol-defined unnecessary coronary angiography occurring within 12 months, defined by a normal FFR (fractional flow reserve) > 0.8, or quantitative coronary angiography (QCA) showing no percentage diameter stenosis ≥ 70% in 1 view or ≥ 70% in 2 orthogonal views in all vessels 2.5 mm or more in diameter within 12 months. Because of the study design, this included any unnecessary angiography occurring after a false-positive test result, patients with high CHD pretest likelihood sent directly to coronary angiography in the NICE guidelines group, and imaging results that were either inconclusive or negative but overruled by the responsible physician.

Secondary endpoints included positive angiography rates, a composite of major adverse cardiovascular events (MACEs: cardiovascular death, myocardial infarction, unplanned coronary revascularization, and hospital admission for cardiovascular cause), and procedural complications.

Main results. Among 2205 patients assessed for eligibility between 23 November 2012 and 13 March 2015, 1202 patients (55% of eligible) were recruited and allocated to NICE guidelines–directed care (n = 240), or management by CMR (n = 481) or MPS (n = 481). While there were no statistical differences between the 3 groups in terms of baseline characteristics, the study population had a substantial burden of cardiovascular risk factors: 150 patients (12.5%) had diabetes, 458 patients (38.1%) had hypertension, 702 patients (58.4%) were past or current tobacco users, 483 patients (40.2%) had dyslipidemia, and 651 patients (54.2%) had a family history of premature CHD. All patients were symptomatic, with 401 patients (33.4%) reporting typical chest pain and 801 patients (66.6%) reporting atypical chest pain as their primary symptom. Overall, 265 patients (22.0%) underwent at least 1 coronary angiogram and 10 patients underwent 2 angiograms.

The number of patients with invasive coronary angiography after 12 months were as follows: 102 of the 240 patients in the NICE guidelines group (42.5% [95% confidence interval {CI} 36.2%–49.0%]), 85 of the 481 patients in the CMR group (17.7% [95% CI 14.4%–21.4%]), and 78 of the 481 patients in the MPS group (16.2% [95% CI 13.0%–19.8%]). The primary endpoint of unnecessary angiography occurred in 69 patients (28.8%) in the NICE guidelines group, 36 patients (7.5%) in the CMR group, and 34 patients (7.1%) in the MPS group. Using CMR group as reference, adjusted odds ratio (AOR) of unnecessary angiography for CMR group vs. NICE guidelines group was 0.21 (95% CI 0.12–0.34, P < 0.001), and the AOR for CMR group vs. the MPS groups was 1.27 (95% CI 0.79–2.03, P = 0.32).

For the secondary endpoints, positive angiography was observed in 29 patients (12.1% [95% CI 8.2%–16.9%]) in the NICE guidelines group, 47 patients (9.8% [95% CI 7.3%–12.8%]) in the CMR group, and 42 patients (8.7% [95% CI 6.4%–11.6%]) in the MPS group, overall P = 0.36. Annualized MACE rates ware 1.6% in the NICE guidelines group, 2.0% for the CMR group, and 2.0% for the MPS group. Adjusted hazard ratios for MACE were 1.37 (95% CI 0.52–3.57, P = 0.52) for the CMR group vs. NICE guidelines group and 0.95 (95% CI 0.46–1.95, P = 0.88) for the CMR group vs. the MPS group.

Conclusion. In patients with suspected CHD, investigation by CMR or MPS resulted in lower probability of unnecessary angiography within 12 months of care than using the NICE guideline–directed care. There was no difference in adverse outcomes as measured by MACE by using NICE guidelines, CMR, or MPS.

Commentary

Coronary heart disease is a leading cause of morbidity and mortality worldwide. Despite the advancement in noninvasive imaging and recommendations in international guidelines, invasive coronary angiography is still commonly used early in diagnostic pathways in patients with suspected CHD [1]. Previous studies demonstrated that majority of patients presenting with chest pain will not have significant obstructive coronary disease; a large US study reported that approximately 60% of elective cardiac catheterizations found no obstructive CHD [2]. Thus, avoiding unnecessary angiography should reduce patient risk and provide significant financial savings. Current guidelines for investigation of stable chest pain rely on pretest likelihood of CHD. These pretest likelihood models can overestimate CHD risk, resulting in the increase in probability of invasive coronary angiography [1,3].

The current study by Greenwood et al investigated whether CMR-guided care is superior to MPS or NICE guidelines–directed care in reducing the occurrence of unnecessary angiography within 12 months. Overall, rates of disease detection based on positive angiogram were comparable for the 3 strategies. In addition, there was no difference in adverse events as measured by a composite of MACE.

While this was an excellently performed multicenter study, there were several major limitations. First, the study population was predominately white northern European (92% were classified ethnically as white), and therefore the results may not translate to other populations. Second, the NICE guidelines for estimation of high-risk CHD changed after initiation of the study due to overestimation, and recent guidelines have adopted a recalibrated risk model [4,5]. Finally, MACE is not a proxy for a missed diagnosis or treatment. It remains debatable whether revascularization for stable angina has prognostic benefit over optimal medical therapy.

Applications for Clinical Practice

This multicenter randomized clinical trial provides strong evidence to use either cardiovascular magnetic resonance–guided care or myocardial perfusion scintigraphy–guided care instead of NICE guidelines–directed care for symptomatic patients with suspected CHD in reducing unnecessary angiography.

—Ka Ming Gordon Ngai, MD, MPH

Study Overview

Objective. To determine if there is an additive benefit of weight loss for pain and functioning in patients with established symptomatic osteoarthritis (OA) of the knee.

Design. Cohort study.

Setting and participants. Participants living in Australia who had completed the Osteoarthritis Healthy Weight For Life program (OAHWFL), a program run by Prima Health Solutions on behalf of participating health funds in Australia and New Zealand; its full cost is borne by the insurance/health care fund. Patients in the program are invited to enroll based on age (≥ 50) and claims data indicating knee OA; patients wishing to enroll must obtain a referral from their doctor confirming weight and height and radiographic or arthroscopic diagnosis of knee OA. Participants in the program had a body mass index (BMI) > 28 kg/m² and met 1986 American College of Rheumatology clinical criteria for knee OA. Further, participants were deemed to clinically require referral to orthopedic surgeon and were surgical candidates by medical opinion.

Intervention. The OAHWFL program is a specialized knee and hip OA management program that focuses on weight loss, utilizing a portion-controlled eating plan with meal replacements, an activity plan, a personalized online tracker, and personal support. It is delivered remotely via phone, texts, email, message board, and mail. The 18-week program consists of 3 phases. During the first 6-week phase, participants were instructed to consume a nutritionally complete very low calorie meal replacement (KicStart, Prima Health Solutions) for 2 meals per day with controlled portions and “free foods” (eg, berries and leafy greens). During the second 6-week phase, participants were transitioned off the meal replacements onto a portion-controlled meal plan, with 1 meal replacement per day. In the final phase, participants consumed portion-controlled whole foods for all 3 meals. All phases included recommendations for moderate aerobic exercise 3 times per week for an increasing time period and intensity, online healthy eating and lifestyle education, and telephone motivation and support at predetermined intervals and on demand.

Main outcome measure. The main outcome measure was percentage of body weight lost from baseline to 18 weeks. Additionally, the validated Knee Injury and Osteoarthritis Outcome Score (KOOS) questionnaire was administered to all participants. The 5 KOOS subscales (pain, other symptoms, function in daily living, function in recreation, and knee-related quality of life) were co-primary outcomes. The validated Western Ontario McMaster Universities Osteoarthritis Index (WOMAC) function score was derived from KOOS. The dose-response relationship was assessed using weight change categories (< 2.5%, 2.5–5.0%, 5.1–7.5%, 7.6%–10%, and > 10%) and change in KOOS scores.

Main results. At the time of analysis, 3827 persons with knee or hip OA were approved by their doctor to participate. Of these 155 had not yet started the program, 728 were undergoing the program, and 846 had discontinued or were lost to follow-up. Of the 2098 who completed the program, 715 were excluded because of incomplete data or OA of the hip, leaving 1383 participants. Overall the baseline mean weight was 95.12 ± 17.2 kg with a mean BMI of 34.39 ± 5.17. Average age was 64 ± 8.7.

94.2% (1304 participants) had a greater than 2.5% reduction in body weight at the end of 18 weeks. 31.1% lost ≥ 10% body weight, 22.9% lost between 7.5 and 10%, 24% lost between 5 and 7.5%, 16.1% lost between 2.5–5%, and 5.7% of participants lost ≤ 2.5%. The greatest amount of weight loss was associated with the greatest improvement of both KOOS and WOMAC scores, with a significant dose-response relationship between weight loss and knee OA symptoms. This persisted in regression analysis adjusted for baseline KOOS and weight, sex, and age. Those with the largest weight loss improved their KOOS scores by 16.17 ± 16.1. The second highest weight loss group has an improvement in KOOS scores by 13.3 ± 15.1, then next highest 12.0 ± 17.1, followed by 9.9 ± 16.8 and finally an improvement of 6.1 ± 13.0 in the weight loss of ≤ 2.5% cohort.

Conclusion. This study showed a relationship between weight loss and improvement in knee OA pain and functioning, with greater weight loss resulting in greater improvement in both categories. Those who were better functioning at the commencement of the study required less weight loss to reach a meaningful improvement in functioning and pain compared to those who started with worse functional status. The OAHWFL intervention was shown to be an effective method of weight loss over an 18-month period.

Commentary

OA is the most common form of arthritis in the United States and the incidence has been rising. A recent study conducted by the Mayo Clinic found OA to be the second most common reason for ambulatory primary care visits, second only to dermatologic complaints [1].It is estimated that the average direct cost of OA per patient is $2600 per year [2], with job-related costs of $3.4 to $13.2 billion per year [3]. Knee replacements alone amounted to $28.5 billion in 2009 [4]. Aside from the financial burden of OA is its impact on quality of life. While genetic predisposition is important in disease pathogenesis, there are well established modifiable risk factors for OA. Among these is maintenance of a healthy weight and physical activity, both of which were addressed in this study.

There is high-quality evidence that weight loss improves the symptoms of knee OA [5]. The current study evaluated whether a dietary intervention for knee OA would be effective in a real-world setting, outside the controlled conditions of a randomized trial. Short-term weight loss did provide pain relief and increase functioning; however, the study does not report weight trajectory after cessation of the intervention. It would be more meaningful to know how many of the participants maintained weight loss after a longer period of time. In addition, it is unclear if the gain in function and pain control was from the weight loss or regular physical activity. A control group that participated in the physical activity without significant weight loss would have strengthened the association between weight loss and KOOS and WOMAC measures.

Though this study took place in a community setting and was tested in both rural and urban settings, the results may not be generalizable to patients who are not already motivated to lose weight, as patients self-nominated themselves to enroll in the program. This study also made use of meal supplements, which were supplied at no cost to patients. Without dedicated funding to supply the meal replacements in addition to the support program, it would be difficult to replicate these results. However, some insurance carriers will cover similar programs that provide validated methods for weight loss, which may be a feasible alternative. Other limitations to the study included lack of a control group, reliance on self-reported weight loss data, and that persons who discontinued the program were not included in the analysis.

Applications for Clinical Practice

Body mechanics and increased inflammation associated with obesity both contribute to worsening of knee OA. The dose-response relationship shown in this study of weight loss in overweight or obese people with OA of the knee is encouraging. Previous studies have shown a clear relationship between weight loss and improvement in pain. The most well-known is perhaps the 4-pound weight rule, which states that for every pound of weight lost, there is a 4-pound reduction in the load exerted on the knee for each step taken [5].Concrete examples of the benefits of weight loss that providers can share with their patients makes discussion about weight loss tangible. Further, the study teased out that those with better physical functioning at the start of the study required less weight loss to achieve gains in pain reduction and functional status. As the hazards of obesity continue to come to light, more community-based weight loss programs are becoming available. Most of the participants in this study successfully lost weight using a community-based approach, highlighting the usefulness of these programs. Weight loss in a community setting is a challenge to all providers. Knowing which patients will benefit the most from a weight loss program can help direct providers to personalized recommendations.

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

Study Overview

Objective. To determine if there is an additive benefit of weight loss for pain and functioning in patients with established symptomatic osteoarthritis (OA) of the knee.

Design. Cohort study.

Setting and participants. Participants living in Australia who had completed the Osteoarthritis Healthy Weight For Life program (OAHWFL), a program run by Prima Health Solutions on behalf of participating health funds in Australia and New Zealand; its full cost is borne by the insurance/health care fund. Patients in the program are invited to enroll based on age (≥ 50) and claims data indicating knee OA; patients wishing to enroll must obtain a referral from their doctor confirming weight and height and radiographic or arthroscopic diagnosis of knee OA. Participants in the program had a body mass index (BMI) > 28 kg/m² and met 1986 American College of Rheumatology clinical criteria for knee OA. Further, participants were deemed to clinically require referral to orthopedic surgeon and were surgical candidates by medical opinion.

Intervention. The OAHWFL program is a specialized knee and hip OA management program that focuses on weight loss, utilizing a portion-controlled eating plan with meal replacements, an activity plan, a personalized online tracker, and personal support. It is delivered remotely via phone, texts, email, message board, and mail. The 18-week program consists of 3 phases. During the first 6-week phase, participants were instructed to consume a nutritionally complete very low calorie meal replacement (KicStart, Prima Health Solutions) for 2 meals per day with controlled portions and “free foods” (eg, berries and leafy greens). During the second 6-week phase, participants were transitioned off the meal replacements onto a portion-controlled meal plan, with 1 meal replacement per day. In the final phase, participants consumed portion-controlled whole foods for all 3 meals. All phases included recommendations for moderate aerobic exercise 3 times per week for an increasing time period and intensity, online healthy eating and lifestyle education, and telephone motivation and support at predetermined intervals and on demand.

Main outcome measure. The main outcome measure was percentage of body weight lost from baseline to 18 weeks. Additionally, the validated Knee Injury and Osteoarthritis Outcome Score (KOOS) questionnaire was administered to all participants. The 5 KOOS subscales (pain, other symptoms, function in daily living, function in recreation, and knee-related quality of life) were co-primary outcomes. The validated Western Ontario McMaster Universities Osteoarthritis Index (WOMAC) function score was derived from KOOS. The dose-response relationship was assessed using weight change categories (< 2.5%, 2.5–5.0%, 5.1–7.5%, 7.6%–10%, and > 10%) and change in KOOS scores.

Main results. At the time of analysis, 3827 persons with knee or hip OA were approved by their doctor to participate. Of these 155 had not yet started the program, 728 were undergoing the program, and 846 had discontinued or were lost to follow-up. Of the 2098 who completed the program, 715 were excluded because of incomplete data or OA of the hip, leaving 1383 participants. Overall the baseline mean weight was 95.12 ± 17.2 kg with a mean BMI of 34.39 ± 5.17. Average age was 64 ± 8.7.

94.2% (1304 participants) had a greater than 2.5% reduction in body weight at the end of 18 weeks. 31.1% lost ≥ 10% body weight, 22.9% lost between 7.5 and 10%, 24% lost between 5 and 7.5%, 16.1% lost between 2.5–5%, and 5.7% of participants lost ≤ 2.5%. The greatest amount of weight loss was associated with the greatest improvement of both KOOS and WOMAC scores, with a significant dose-response relationship between weight loss and knee OA symptoms. This persisted in regression analysis adjusted for baseline KOOS and weight, sex, and age. Those with the largest weight loss improved their KOOS scores by 16.17 ± 16.1. The second highest weight loss group has an improvement in KOOS scores by 13.3 ± 15.1, then next highest 12.0 ± 17.1, followed by 9.9 ± 16.8 and finally an improvement of 6.1 ± 13.0 in the weight loss of ≤ 2.5% cohort.

Conclusion. This study showed a relationship between weight loss and improvement in knee OA pain and functioning, with greater weight loss resulting in greater improvement in both categories. Those who were better functioning at the commencement of the study required less weight loss to reach a meaningful improvement in functioning and pain compared to those who started with worse functional status. The OAHWFL intervention was shown to be an effective method of weight loss over an 18-month period.

Commentary

OA is the most common form of arthritis in the United States and the incidence has been rising. A recent study conducted by the Mayo Clinic found OA to be the second most common reason for ambulatory primary care visits, second only to dermatologic complaints [1].It is estimated that the average direct cost of OA per patient is $2600 per year [2], with job-related costs of $3.4 to $13.2 billion per year [3]. Knee replacements alone amounted to $28.5 billion in 2009 [4]. Aside from the financial burden of OA is its impact on quality of life. While genetic predisposition is important in disease pathogenesis, there are well established modifiable risk factors for OA. Among these is maintenance of a healthy weight and physical activity, both of which were addressed in this study.

There is high-quality evidence that weight loss improves the symptoms of knee OA [5]. The current study evaluated whether a dietary intervention for knee OA would be effective in a real-world setting, outside the controlled conditions of a randomized trial. Short-term weight loss did provide pain relief and increase functioning; however, the study does not report weight trajectory after cessation of the intervention. It would be more meaningful to know how many of the participants maintained weight loss after a longer period of time. In addition, it is unclear if the gain in function and pain control was from the weight loss or regular physical activity. A control group that participated in the physical activity without significant weight loss would have strengthened the association between weight loss and KOOS and WOMAC measures.

Though this study took place in a community setting and was tested in both rural and urban settings, the results may not be generalizable to patients who are not already motivated to lose weight, as patients self-nominated themselves to enroll in the program. This study also made use of meal supplements, which were supplied at no cost to patients. Without dedicated funding to supply the meal replacements in addition to the support program, it would be difficult to replicate these results. However, some insurance carriers will cover similar programs that provide validated methods for weight loss, which may be a feasible alternative. Other limitations to the study included lack of a control group, reliance on self-reported weight loss data, and that persons who discontinued the program were not included in the analysis.

Applications for Clinical Practice

Body mechanics and increased inflammation associated with obesity both contribute to worsening of knee OA. The dose-response relationship shown in this study of weight loss in overweight or obese people with OA of the knee is encouraging. Previous studies have shown a clear relationship between weight loss and improvement in pain. The most well-known is perhaps the 4-pound weight rule, which states that for every pound of weight lost, there is a 4-pound reduction in the load exerted on the knee for each step taken [5].Concrete examples of the benefits of weight loss that providers can share with their patients makes discussion about weight loss tangible. Further, the study teased out that those with better physical functioning at the start of the study required less weight loss to achieve gains in pain reduction and functional status. As the hazards of obesity continue to come to light, more community-based weight loss programs are becoming available. Most of the participants in this study successfully lost weight using a community-based approach, highlighting the usefulness of these programs. Weight loss in a community setting is a challenge to all providers. Knowing which patients will benefit the most from a weight loss program can help direct providers to personalized recommendations.

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

Study Overview

Objective. To determine if there is an additive benefit of weight loss for pain and functioning in patients with established symptomatic osteoarthritis (OA) of the knee.

Design. Cohort study.

Setting and participants. Participants living in Australia who had completed the Osteoarthritis Healthy Weight For Life program (OAHWFL), a program run by Prima Health Solutions on behalf of participating health funds in Australia and New Zealand; its full cost is borne by the insurance/health care fund. Patients in the program are invited to enroll based on age (≥ 50) and claims data indicating knee OA; patients wishing to enroll must obtain a referral from their doctor confirming weight and height and radiographic or arthroscopic diagnosis of knee OA. Participants in the program had a body mass index (BMI) > 28 kg/m² and met 1986 American College of Rheumatology clinical criteria for knee OA. Further, participants were deemed to clinically require referral to orthopedic surgeon and were surgical candidates by medical opinion.

Intervention. The OAHWFL program is a specialized knee and hip OA management program that focuses on weight loss, utilizing a portion-controlled eating plan with meal replacements, an activity plan, a personalized online tracker, and personal support. It is delivered remotely via phone, texts, email, message board, and mail. The 18-week program consists of 3 phases. During the first 6-week phase, participants were instructed to consume a nutritionally complete very low calorie meal replacement (KicStart, Prima Health Solutions) for 2 meals per day with controlled portions and “free foods” (eg, berries and leafy greens). During the second 6-week phase, participants were transitioned off the meal replacements onto a portion-controlled meal plan, with 1 meal replacement per day. In the final phase, participants consumed portion-controlled whole foods for all 3 meals. All phases included recommendations for moderate aerobic exercise 3 times per week for an increasing time period and intensity, online healthy eating and lifestyle education, and telephone motivation and support at predetermined intervals and on demand.

Main outcome measure. The main outcome measure was percentage of body weight lost from baseline to 18 weeks. Additionally, the validated Knee Injury and Osteoarthritis Outcome Score (KOOS) questionnaire was administered to all participants. The 5 KOOS subscales (pain, other symptoms, function in daily living, function in recreation, and knee-related quality of life) were co-primary outcomes. The validated Western Ontario McMaster Universities Osteoarthritis Index (WOMAC) function score was derived from KOOS. The dose-response relationship was assessed using weight change categories (< 2.5%, 2.5–5.0%, 5.1–7.5%, 7.6%–10%, and > 10%) and change in KOOS scores.

Main results. At the time of analysis, 3827 persons with knee or hip OA were approved by their doctor to participate. Of these 155 had not yet started the program, 728 were undergoing the program, and 846 had discontinued or were lost to follow-up. Of the 2098 who completed the program, 715 were excluded because of incomplete data or OA of the hip, leaving 1383 participants. Overall the baseline mean weight was 95.12 ± 17.2 kg with a mean BMI of 34.39 ± 5.17. Average age was 64 ± 8.7.

94.2% (1304 participants) had a greater than 2.5% reduction in body weight at the end of 18 weeks. 31.1% lost ≥ 10% body weight, 22.9% lost between 7.5 and 10%, 24% lost between 5 and 7.5%, 16.1% lost between 2.5–5%, and 5.7% of participants lost ≤ 2.5%. The greatest amount of weight loss was associated with the greatest improvement of both KOOS and WOMAC scores, with a significant dose-response relationship between weight loss and knee OA symptoms. This persisted in regression analysis adjusted for baseline KOOS and weight, sex, and age. Those with the largest weight loss improved their KOOS scores by 16.17 ± 16.1. The second highest weight loss group has an improvement in KOOS scores by 13.3 ± 15.1, then next highest 12.0 ± 17.1, followed by 9.9 ± 16.8 and finally an improvement of 6.1 ± 13.0 in the weight loss of ≤ 2.5% cohort.

Conclusion. This study showed a relationship between weight loss and improvement in knee OA pain and functioning, with greater weight loss resulting in greater improvement in both categories. Those who were better functioning at the commencement of the study required less weight loss to reach a meaningful improvement in functioning and pain compared to those who started with worse functional status. The OAHWFL intervention was shown to be an effective method of weight loss over an 18-month period.

Commentary

OA is the most common form of arthritis in the United States and the incidence has been rising. A recent study conducted by the Mayo Clinic found OA to be the second most common reason for ambulatory primary care visits, second only to dermatologic complaints [1].It is estimated that the average direct cost of OA per patient is $2600 per year [2], with job-related costs of $3.4 to $13.2 billion per year [3]. Knee replacements alone amounted to $28.5 billion in 2009 [4]. Aside from the financial burden of OA is its impact on quality of life. While genetic predisposition is important in disease pathogenesis, there are well established modifiable risk factors for OA. Among these is maintenance of a healthy weight and physical activity, both of which were addressed in this study.

There is high-quality evidence that weight loss improves the symptoms of knee OA [5]. The current study evaluated whether a dietary intervention for knee OA would be effective in a real-world setting, outside the controlled conditions of a randomized trial. Short-term weight loss did provide pain relief and increase functioning; however, the study does not report weight trajectory after cessation of the intervention. It would be more meaningful to know how many of the participants maintained weight loss after a longer period of time. In addition, it is unclear if the gain in function and pain control was from the weight loss or regular physical activity. A control group that participated in the physical activity without significant weight loss would have strengthened the association between weight loss and KOOS and WOMAC measures.

Though this study took place in a community setting and was tested in both rural and urban settings, the results may not be generalizable to patients who are not already motivated to lose weight, as patients self-nominated themselves to enroll in the program. This study also made use of meal supplements, which were supplied at no cost to patients. Without dedicated funding to supply the meal replacements in addition to the support program, it would be difficult to replicate these results. However, some insurance carriers will cover similar programs that provide validated methods for weight loss, which may be a feasible alternative. Other limitations to the study included lack of a control group, reliance on self-reported weight loss data, and that persons who discontinued the program were not included in the analysis.

Applications for Clinical Practice

Body mechanics and increased inflammation associated with obesity both contribute to worsening of knee OA. The dose-response relationship shown in this study of weight loss in overweight or obese people with OA of the knee is encouraging. Previous studies have shown a clear relationship between weight loss and improvement in pain. The most well-known is perhaps the 4-pound weight rule, which states that for every pound of weight lost, there is a 4-pound reduction in the load exerted on the knee for each step taken [5].Concrete examples of the benefits of weight loss that providers can share with their patients makes discussion about weight loss tangible. Further, the study teased out that those with better physical functioning at the start of the study required less weight loss to achieve gains in pain reduction and functional status. As the hazards of obesity continue to come to light, more community-based weight loss programs are becoming available. Most of the participants in this study successfully lost weight using a community-based approach, highlighting the usefulness of these programs. Weight loss in a community setting is a challenge to all providers. Knowing which patients will benefit the most from a weight loss program can help direct providers to personalized recommendations.

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

Study Overview

Objective. To determine whether nurse-managed protocols are effective for the outpatient management of adults with diabetes, hypertension, and hyperlipidemia.

Study design. Systematic review and meta-analysis.

Data sources. The authors searched MEDLINE, Cochrane Central Register of Controlled Trials, EMBASE, and CINAHL for English-language peer-reviewed studies published between January 1980 and January 2014 that evaluated interventions that compared nurse-managed protocols with usual care in investigations targeting adults with chronic conditions. Two reviewers used eligibility criteria to assess titles, abstracts, and full texts, and resolved their disagreements by discussion or by consulting a third reviewer. Eligibility criteria included the involvement of an RN or LPN functioning beyond the usual scope of practice, such as adjusting medications, and conducting interventions based on a written protocol.

Main outcome measures. The effects of nurse-managed protocols on biophysical markers, patient treatment adherence, nurse protocol adherence, adverse effects, and resource use. When quantitative synthesis was feasible, dichotomous outcomes were combined using odds ratios and continuous outcomes were combined using mean differences in random-effects models. When quantitative synthesis was not feasible, the authors annualized data qualitatively, giving more weight to evidence from higher-quality studies. They evaluated overall strength of evidence (SOE) by assessing risk of bias, consistency, directness, and precision, and assigned a rating of high, moderate, or low SOE, or insufficient evidence.

Main results. Of the 2954 studies in the search results, 18 were ultimately eligible and included in the review, 16 randomized controlled trials and 2 before and after diabetes studies. Eleven were done in Western Europe and 7 in the United States. An RN or non-US equivalent was the interventionist in all studies (none used an LPN). In only 11 of the 18 studies were nurses independently allowed to initiate new medications. The meta-analysis found that hemoglobin A1c (HbA1c) level decreased by 0.4% (moderate SOE) (95% confidence interval {CI}, 0.1% to 0.7%) (n = 8), systolic and diastolic blood pressure decreased by 3.68 mm Hg (CI, 1.05 to 6.31) and 1.56 mm Hg (CI, 0.36 to 2.76), respectively (moderate SOE) (n = 12); total cholesterol level decreased by 9.37 mg/dL (20.77-mg/dL decrease to 2.02-mg/dL increase) (n = 9); and low-density-lipoprotein cholesterol level decreased by 12.07 mg/dL (CI, 28.27-mg/dL decrease to 4.13-mg/dL increase) (low SOE) (n = 6). The SOE was insufficient to estimate a treatment effect for all other outcomes.

Conclusion. A team approach that uses nurse-managed protocols may have positive effects on the outpatient management of adults with chronic conditions such as diabetes, hypertension, and hyperlipidemia.

Commentary

Hypertension, diabetes, and hyperlipidemia are major causes of morbidity and mortality worldwide and are widely prevalent in the United States. These chronic illnesses require long-term medical management, often requiring management of multiple medications and patient lifestyle changes and self-monitoring [1]. The patient-centered medical home, which involves a team approach, is increasingly being recognized as a promising model for delivering effective chronic disease care. Likewise, expanding the role of nurses as part of team care is increasingly being explored to help achieve high quality patient outcomes. The use of nurse-managed protocols can be an appropriate strategy in this scenario.

In this study, the researchers aimed to determine whether nurse-managed protocols are effective for outpatient management of adults with diabetes, hypertension, and hyperlipidemia and performed a systematic review and meta-analysis. Researchers followed a standardized procedure to conduct their search and carefully reviewed the studies, including contacting authors for missing data or clarification. They followed the approach recommended by the Agency for Healthcare Research and Quality (AHRQ) to evaluate the overall strength of the body of evidence [2].

However, some limitations must be taken into account. They acknowledge that they may have missed studies in which nurses had autonomy to practice in capacities beyond their scope of practice. In addition, the literature lacked details about the interventions and protocols used. Also, the researchers searched for studies across a 34-year range (1980–2014). Changes occurring in the nursing profession over these years may have impacted the findings.

Applications for Clinical Practice

Team-based care that includes nurse-managed protocols for titrating medications can be beneficial in the management of chronic conditions in primary care patients. With physician shortages predicted, which will impact primary care more than other specialties, team approaches using nurse-managed protocols have the potential to help lighten physician workloads and ensure quality care.

                                                                                                                                                                                                                                    —Paloma Cesar de Sales, BN, RN, MS

Study Overview

Objective. To determine whether nurse-managed protocols are effective for the outpatient management of adults with diabetes, hypertension, and hyperlipidemia.

Study design. Systematic review and meta-analysis.

Data sources. The authors searched MEDLINE, Cochrane Central Register of Controlled Trials, EMBASE, and CINAHL for English-language peer-reviewed studies published between January 1980 and January 2014 that evaluated interventions that compared nurse-managed protocols with usual care in investigations targeting adults with chronic conditions. Two reviewers used eligibility criteria to assess titles, abstracts, and full texts, and resolved their disagreements by discussion or by consulting a third reviewer. Eligibility criteria included the involvement of an RN or LPN functioning beyond the usual scope of practice, such as adjusting medications, and conducting interventions based on a written protocol.

Main outcome measures. The effects of nurse-managed protocols on biophysical markers, patient treatment adherence, nurse protocol adherence, adverse effects, and resource use. When quantitative synthesis was feasible, dichotomous outcomes were combined using odds ratios and continuous outcomes were combined using mean differences in random-effects models. When quantitative synthesis was not feasible, the authors annualized data qualitatively, giving more weight to evidence from higher-quality studies. They evaluated overall strength of evidence (SOE) by assessing risk of bias, consistency, directness, and precision, and assigned a rating of high, moderate, or low SOE, or insufficient evidence.

Main results. Of the 2954 studies in the search results, 18 were ultimately eligible and included in the review, 16 randomized controlled trials and 2 before and after diabetes studies. Eleven were done in Western Europe and 7 in the United States. An RN or non-US equivalent was the interventionist in all studies (none used an LPN). In only 11 of the 18 studies were nurses independently allowed to initiate new medications. The meta-analysis found that hemoglobin A1c (HbA1c) level decreased by 0.4% (moderate SOE) (95% confidence interval {CI}, 0.1% to 0.7%) (n = 8), systolic and diastolic blood pressure decreased by 3.68 mm Hg (CI, 1.05 to 6.31) and 1.56 mm Hg (CI, 0.36 to 2.76), respectively (moderate SOE) (n = 12); total cholesterol level decreased by 9.37 mg/dL (20.77-mg/dL decrease to 2.02-mg/dL increase) (n = 9); and low-density-lipoprotein cholesterol level decreased by 12.07 mg/dL (CI, 28.27-mg/dL decrease to 4.13-mg/dL increase) (low SOE) (n = 6). The SOE was insufficient to estimate a treatment effect for all other outcomes.

Conclusion. A team approach that uses nurse-managed protocols may have positive effects on the outpatient management of adults with chronic conditions such as diabetes, hypertension, and hyperlipidemia.

Commentary

Hypertension, diabetes, and hyperlipidemia are major causes of morbidity and mortality worldwide and are widely prevalent in the United States. These chronic illnesses require long-term medical management, often requiring management of multiple medications and patient lifestyle changes and self-monitoring [1]. The patient-centered medical home, which involves a team approach, is increasingly being recognized as a promising model for delivering effective chronic disease care. Likewise, expanding the role of nurses as part of team care is increasingly being explored to help achieve high quality patient outcomes. The use of nurse-managed protocols can be an appropriate strategy in this scenario.

In this study, the researchers aimed to determine whether nurse-managed protocols are effective for outpatient management of adults with diabetes, hypertension, and hyperlipidemia and performed a systematic review and meta-analysis. Researchers followed a standardized procedure to conduct their search and carefully reviewed the studies, including contacting authors for missing data or clarification. They followed the approach recommended by the Agency for Healthcare Research and Quality (AHRQ) to evaluate the overall strength of the body of evidence [2].

However, some limitations must be taken into account. They acknowledge that they may have missed studies in which nurses had autonomy to practice in capacities beyond their scope of practice. In addition, the literature lacked details about the interventions and protocols used. Also, the researchers searched for studies across a 34-year range (1980–2014). Changes occurring in the nursing profession over these years may have impacted the findings.

Applications for Clinical Practice

Team-based care that includes nurse-managed protocols for titrating medications can be beneficial in the management of chronic conditions in primary care patients. With physician shortages predicted, which will impact primary care more than other specialties, team approaches using nurse-managed protocols have the potential to help lighten physician workloads and ensure quality care.

                                                                                                                                                                                                                                    —Paloma Cesar de Sales, BN, RN, MS

Study Overview

Objective. To determine whether nurse-managed protocols are effective for the outpatient management of adults with diabetes, hypertension, and hyperlipidemia.

Study design. Systematic review and meta-analysis.

Data sources. The authors searched MEDLINE, Cochrane Central Register of Controlled Trials, EMBASE, and CINAHL for English-language peer-reviewed studies published between January 1980 and January 2014 that evaluated interventions that compared nurse-managed protocols with usual care in investigations targeting adults with chronic conditions. Two reviewers used eligibility criteria to assess titles, abstracts, and full texts, and resolved their disagreements by discussion or by consulting a third reviewer. Eligibility criteria included the involvement of an RN or LPN functioning beyond the usual scope of practice, such as adjusting medications, and conducting interventions based on a written protocol.

Main outcome measures. The effects of nurse-managed protocols on biophysical markers, patient treatment adherence, nurse protocol adherence, adverse effects, and resource use. When quantitative synthesis was feasible, dichotomous outcomes were combined using odds ratios and continuous outcomes were combined using mean differences in random-effects models. When quantitative synthesis was not feasible, the authors annualized data qualitatively, giving more weight to evidence from higher-quality studies. They evaluated overall strength of evidence (SOE) by assessing risk of bias, consistency, directness, and precision, and assigned a rating of high, moderate, or low SOE, or insufficient evidence.

Main results. Of the 2954 studies in the search results, 18 were ultimately eligible and included in the review, 16 randomized controlled trials and 2 before and after diabetes studies. Eleven were done in Western Europe and 7 in the United States. An RN or non-US equivalent was the interventionist in all studies (none used an LPN). In only 11 of the 18 studies were nurses independently allowed to initiate new medications. The meta-analysis found that hemoglobin A1c (HbA1c) level decreased by 0.4% (moderate SOE) (95% confidence interval {CI}, 0.1% to 0.7%) (n = 8), systolic and diastolic blood pressure decreased by 3.68 mm Hg (CI, 1.05 to 6.31) and 1.56 mm Hg (CI, 0.36 to 2.76), respectively (moderate SOE) (n = 12); total cholesterol level decreased by 9.37 mg/dL (20.77-mg/dL decrease to 2.02-mg/dL increase) (n = 9); and low-density-lipoprotein cholesterol level decreased by 12.07 mg/dL (CI, 28.27-mg/dL decrease to 4.13-mg/dL increase) (low SOE) (n = 6). The SOE was insufficient to estimate a treatment effect for all other outcomes.

Conclusion. A team approach that uses nurse-managed protocols may have positive effects on the outpatient management of adults with chronic conditions such as diabetes, hypertension, and hyperlipidemia.

Commentary

Hypertension, diabetes, and hyperlipidemia are major causes of morbidity and mortality worldwide and are widely prevalent in the United States. These chronic illnesses require long-term medical management, often requiring management of multiple medications and patient lifestyle changes and self-monitoring [1]. The patient-centered medical home, which involves a team approach, is increasingly being recognized as a promising model for delivering effective chronic disease care. Likewise, expanding the role of nurses as part of team care is increasingly being explored to help achieve high quality patient outcomes. The use of nurse-managed protocols can be an appropriate strategy in this scenario.

In this study, the researchers aimed to determine whether nurse-managed protocols are effective for outpatient management of adults with diabetes, hypertension, and hyperlipidemia and performed a systematic review and meta-analysis. Researchers followed a standardized procedure to conduct their search and carefully reviewed the studies, including contacting authors for missing data or clarification. They followed the approach recommended by the Agency for Healthcare Research and Quality (AHRQ) to evaluate the overall strength of the body of evidence [2].

However, some limitations must be taken into account. They acknowledge that they may have missed studies in which nurses had autonomy to practice in capacities beyond their scope of practice. In addition, the literature lacked details about the interventions and protocols used. Also, the researchers searched for studies across a 34-year range (1980–2014). Changes occurring in the nursing profession over these years may have impacted the findings.

Applications for Clinical Practice

Team-based care that includes nurse-managed protocols for titrating medications can be beneficial in the management of chronic conditions in primary care patients. With physician shortages predicted, which will impact primary care more than other specialties, team approaches using nurse-managed protocols have the potential to help lighten physician workloads and ensure quality care.

                                                                                                                                                                                                                                    —Paloma Cesar de Sales, BN, RN, MS

Study Overview

Objective. To determine the association between antihypertensive medication adherence and visit-to-visit variability of blood pressure (BP).

Design. Post hoc analysis of ALLHAT, a randomized, double-blind, multicenter trial to determine whether treatment with calcium-channel blockers, angiotensin-converting enzyme inhibitors, or α-adrenergic blockers, all newer antihypertensive classes at the time of the study, was superior to treatment with a thiazide diuretic for lowering risk for fatal coronary heart disease (CHD) or nonfatal myocardial infarction (MI) (primary outcomes), with secondary outcomes including all-cause mortality, stroke, and combined cardiovascular disease (CHD death, nonfatal MI, stroke, angina, coronary revascularization, congestive heart failure, and peripheral arterial disease).

Setting and participants. Participants who had BP and medication adherence data from at least 5 of the 7 study visits conducted 6 to 28 months after randomization. Only patients who had no outcome events within the 28 months were included in the analysis (ie, no fatal CHD or nonfatal MI, stroke, all-cause mortality, or heart failure). In a secondary analysis, participants who had data from 5 of the 7 study visits between 32 to 56 months after randomization were included.

Measures. Adherence to medication was assessed at each visit by a study clinician using the Adherence Survival Kit developed for ALLHAT. Participants were asked whether they had taken at least 80% of their assigned study drug since the last follow-up visit. For primary analyses, participants were categorized as nonadherent if they reported having taken < 80% of their assigned antihypertensive medication at ≥ 1 visits during the 6- to 28-month time period after randomization. For secondary analyses, participants were categorized as nonadherent if they reported having taken < 80% of their assigned medication at ≥ 1 visits during the 32 to 56 months after randomization. In a sensitivity analysis, participants were categorized as nonadherent if they reported taking < 80% of the prescribed antihypertensive medication at ≥ 2 visits during the 6 to 28 months post-randomization time period. Visit-to-visit variability of BP was calculated using 3 metrics based on each ALLHAT participants’ BP measurements: standard deviation independent of mean (SDIM), SD, and average real variability. The BP used for these calculations was the mean of 2 measurements taken during each follow-up study visit according to a standardized BP measurement protocol. Participants were followed from the end of the visit-to-visit variability of BP assessment period to the date of each outcome, their date of death, or end of active ALLHAT follow-up.

Results. Of 33,357 participants randomized, 19,970 participants met eligibility criteria for primary analyses. Of these, 2912 participants (15%) were considered nonadherent. Compared with adherent participants, nonadherent participants were slightly older and more likely to be Hispanic or black. Nonadherent participants were more likely to have evidence of end-organ damage as signified by major ST segment depression or T wave inversion or left ventricular hypertrophy on electrocardiogram but were less likely to have a history of MI, stroke, or coronary revascularization. Nonadherent participants were also less likely to have used BP medications before randomization and less likely to use statins during follow-up. Nonadherent participants were more likely to have changes in BP medication classes during follow-up, were more likely to have uncontrolled BP between 6 and 28 months after randomization, and had higher mean systolic blood pressure (SBP) and diastolic blood pressure (DBP) at the visits. The association between nonadherence and higher BP remained statistically significant in adjusted analyses.

SDIM of SBP was higher among those who were nonadherent (11.4 ± 4.9 versus 10.5 ± 4.5; P < 0.001). After full adjustment, nonadherent participants had 0.8 (95% CI, 0.7–1.0; P < 0.001) higher SDIM of SBP than adherent participants. In addition, compared with adherent participants, nonadherent participants had higher SD and average real variability of SBP. Researcher found the same pattern when the sample was restricted to 11,290 participants without antihypertensive medication changes. The association between adherence status and visit-to-visit variability of SBP was consistent across antihypertensive drug randomization assignment for interaction term for all definitions of visit-to-visit variability of SBP (P > 0.8). Nonadherent participants also had higher visit-to-visit variability of DBP.

Overall, 4.6% of participants had ≥ 2 visits with < 80% adherence. SDIM of SBP was higher among nonadherent participants versus adherent participants according to this more stringent categorization of nonadherence (11.0 ± 4.6 vs. 10.6 ± 4.6; P = 0.01). After full multivariable adjustment, SDIM of SBP was 0.5 (95% CI, 0.2–0.9; P = 0.001) higher among nonadherent than among adherent participants. Participants who were nonadherent in both the early and late study periods had higher SDIMs of SBP than those who were adherent in both study periods. Minimal changes were found in the SDIM of SBP between the early and late study periods for participants who were adherent in both study periods and nonadherent in both study periods. However, a significant number of participants, had a change in adherence between the early and late study period, with 6.5% switching from adherent to nonadherent and 10.0% switching from nonadherent to adherent. Compared with participants who were adherent in both time periods, participants who changed from adherent to non-adherent had an increase in SDIM of SBP (0.9; 95% CI, 0.5–1.3; P < 0.001), whereas participants who changed from nonadherent to adherent had a decrease in SDIM of SBP (−0.7; 95% CI, −1.0 to −0.3; P < 0.001). Among participants in the primary analysis without a cardiovascular event before the 28-month visit (n = 18 442), being in the highest versus lowest quintile of SDIM of SBP was associated with increased risk of fatal CHD or nonfatal MI, stroke, heart failure, and all-cause mortality after multivariable adjustment. In a mediation analysis, further adjustment for adherence status did not explain the association between SDIM of SBP and any of our cardiovascular or mortality outcomes.

Conclusion. The study provided significant evidence that medication adherence reduces visit-to-visit variability of BP. However, visit-to-visit variability of BP is associated with cardiovascular outcomes independent of medication adherence. Further work is needed to examine both the mechanisms underlying the association between visit-to-visit variability of BP and cardiovascular outcomes and whether decreasing visit-to-visit variability of BP can improve health outcomes.

Commentary

Hypertension remains one of the most important preventable contributors to disease and death [1]. Health care providers continue to reinforce the importance of adherence to medication treatment in conjunction with the adoption of healthy lifestyle habits, which have been shown to be effective interventions [2]. Low adherence to antihypertensive medication has been hypothesized to increase visit-to-visit variability of BP. Literature has shown that visit-to-visit variability of BP is associated with increased risk for stroke, CHD, and mortality [3]. In this post hoc analysis of ALLHAT, the researchers found that nonadherence was associated with increased visit-to-visit variability of BP. The study extended the findings of only a few studies that have tested this association.

Efforts to improve adherence could impact the occurrence of visit-to-visit variability of BP. Current methods of improving medication adherence for chronic health problems are mostly complex and not very effective. Awareness and commitment are essential to promote and ensure adherence in the treatment of disease [4]. Advances in this field of research are needed, including improved design of feasible long-term interventions, objective adherence measures, and sufficient study power to detect improvements outcomes that patients care about [4].

However, in this study, medication nonadherence did not explain the association between visit-to-visit variability of BP levels and cardiovascular risk. The researchers posit that in light of this, improving adherence is unlikely to offset the increased risk associated with visit-to-visit variability of BP found in treated patients with hypertension.

Limitations of this study include the use of self-report for adherence measurement, use of a summary measure for adherence, and the exclusion of a substantial number of participants who had < 5 visits in which adherence was assessed.

Applications for Clinical Practice

Although nonadherence to medication treatment contributed to visit-to-visit variability of BP, nonadherence did not explain why individuals with higher visit-to-visit of BP were at increased cardiovascular risk. Additional research is suggested in order to better understand how visit-to-visit variability of BP levels influences prognosis of hypertension.

—Paloma Cesar de Sales, BS, RN, MS

Study Overview

Objective. To determine the association between antihypertensive medication adherence and visit-to-visit variability of blood pressure (BP).

Design. Post hoc analysis of ALLHAT, a randomized, double-blind, multicenter trial to determine whether treatment with calcium-channel blockers, angiotensin-converting enzyme inhibitors, or α-adrenergic blockers, all newer antihypertensive classes at the time of the study, was superior to treatment with a thiazide diuretic for lowering risk for fatal coronary heart disease (CHD) or nonfatal myocardial infarction (MI) (primary outcomes), with secondary outcomes including all-cause mortality, stroke, and combined cardiovascular disease (CHD death, nonfatal MI, stroke, angina, coronary revascularization, congestive heart failure, and peripheral arterial disease).

Setting and participants. Participants who had BP and medication adherence data from at least 5 of the 7 study visits conducted 6 to 28 months after randomization. Only patients who had no outcome events within the 28 months were included in the analysis (ie, no fatal CHD or nonfatal MI, stroke, all-cause mortality, or heart failure). In a secondary analysis, participants who had data from 5 of the 7 study visits between 32 to 56 months after randomization were included.

Measures. Adherence to medication was assessed at each visit by a study clinician using the Adherence Survival Kit developed for ALLHAT. Participants were asked whether they had taken at least 80% of their assigned study drug since the last follow-up visit. For primary analyses, participants were categorized as nonadherent if they reported having taken < 80% of their assigned antihypertensive medication at ≥ 1 visits during the 6- to 28-month time period after randomization. For secondary analyses, participants were categorized as nonadherent if they reported having taken < 80% of their assigned medication at ≥ 1 visits during the 32 to 56 months after randomization. In a sensitivity analysis, participants were categorized as nonadherent if they reported taking < 80% of the prescribed antihypertensive medication at ≥ 2 visits during the 6 to 28 months post-randomization time period. Visit-to-visit variability of BP was calculated using 3 metrics based on each ALLHAT participants’ BP measurements: standard deviation independent of mean (SDIM), SD, and average real variability. The BP used for these calculations was the mean of 2 measurements taken during each follow-up study visit according to a standardized BP measurement protocol. Participants were followed from the end of the visit-to-visit variability of BP assessment period to the date of each outcome, their date of death, or end of active ALLHAT follow-up.

Results. Of 33,357 participants randomized, 19,970 participants met eligibility criteria for primary analyses. Of these, 2912 participants (15%) were considered nonadherent. Compared with adherent participants, nonadherent participants were slightly older and more likely to be Hispanic or black. Nonadherent participants were more likely to have evidence of end-organ damage as signified by major ST segment depression or T wave inversion or left ventricular hypertrophy on electrocardiogram but were less likely to have a history of MI, stroke, or coronary revascularization. Nonadherent participants were also less likely to have used BP medications before randomization and less likely to use statins during follow-up. Nonadherent participants were more likely to have changes in BP medication classes during follow-up, were more likely to have uncontrolled BP between 6 and 28 months after randomization, and had higher mean systolic blood pressure (SBP) and diastolic blood pressure (DBP) at the visits. The association between nonadherence and higher BP remained statistically significant in adjusted analyses.

SDIM of SBP was higher among those who were nonadherent (11.4 ± 4.9 versus 10.5 ± 4.5; P < 0.001). After full adjustment, nonadherent participants had 0.8 (95% CI, 0.7–1.0; P < 0.001) higher SDIM of SBP than adherent participants. In addition, compared with adherent participants, nonadherent participants had higher SD and average real variability of SBP. Researcher found the same pattern when the sample was restricted to 11,290 participants without antihypertensive medication changes. The association between adherence status and visit-to-visit variability of SBP was consistent across antihypertensive drug randomization assignment for interaction term for all definitions of visit-to-visit variability of SBP (P > 0.8). Nonadherent participants also had higher visit-to-visit variability of DBP.

Overall, 4.6% of participants had ≥ 2 visits with < 80% adherence. SDIM of SBP was higher among nonadherent participants versus adherent participants according to this more stringent categorization of nonadherence (11.0 ± 4.6 vs. 10.6 ± 4.6; P = 0.01). After full multivariable adjustment, SDIM of SBP was 0.5 (95% CI, 0.2–0.9; P = 0.001) higher among nonadherent than among adherent participants. Participants who were nonadherent in both the early and late study periods had higher SDIMs of SBP than those who were adherent in both study periods. Minimal changes were found in the SDIM of SBP between the early and late study periods for participants who were adherent in both study periods and nonadherent in both study periods. However, a significant number of participants, had a change in adherence between the early and late study period, with 6.5% switching from adherent to nonadherent and 10.0% switching from nonadherent to adherent. Compared with participants who were adherent in both time periods, participants who changed from adherent to non-adherent had an increase in SDIM of SBP (0.9; 95% CI, 0.5–1.3; P < 0.001), whereas participants who changed from nonadherent to adherent had a decrease in SDIM of SBP (−0.7; 95% CI, −1.0 to −0.3; P < 0.001). Among participants in the primary analysis without a cardiovascular event before the 28-month visit (n = 18 442), being in the highest versus lowest quintile of SDIM of SBP was associated with increased risk of fatal CHD or nonfatal MI, stroke, heart failure, and all-cause mortality after multivariable adjustment. In a mediation analysis, further adjustment for adherence status did not explain the association between SDIM of SBP and any of our cardiovascular or mortality outcomes.

Conclusion. The study provided significant evidence that medication adherence reduces visit-to-visit variability of BP. However, visit-to-visit variability of BP is associated with cardiovascular outcomes independent of medication adherence. Further work is needed to examine both the mechanisms underlying the association between visit-to-visit variability of BP and cardiovascular outcomes and whether decreasing visit-to-visit variability of BP can improve health outcomes.

Commentary

Hypertension remains one of the most important preventable contributors to disease and death [1]. Health care providers continue to reinforce the importance of adherence to medication treatment in conjunction with the adoption of healthy lifestyle habits, which have been shown to be effective interventions [2]. Low adherence to antihypertensive medication has been hypothesized to increase visit-to-visit variability of BP. Literature has shown that visit-to-visit variability of BP is associated with increased risk for stroke, CHD, and mortality [3]. In this post hoc analysis of ALLHAT, the researchers found that nonadherence was associated with increased visit-to-visit variability of BP. The study extended the findings of only a few studies that have tested this association.

Efforts to improve adherence could impact the occurrence of visit-to-visit variability of BP. Current methods of improving medication adherence for chronic health problems are mostly complex and not very effective. Awareness and commitment are essential to promote and ensure adherence in the treatment of disease [4]. Advances in this field of research are needed, including improved design of feasible long-term interventions, objective adherence measures, and sufficient study power to detect improvements outcomes that patients care about [4].

However, in this study, medication nonadherence did not explain the association between visit-to-visit variability of BP levels and cardiovascular risk. The researchers posit that in light of this, improving adherence is unlikely to offset the increased risk associated with visit-to-visit variability of BP found in treated patients with hypertension.

Limitations of this study include the use of self-report for adherence measurement, use of a summary measure for adherence, and the exclusion of a substantial number of participants who had < 5 visits in which adherence was assessed.

Applications for Clinical Practice

Although nonadherence to medication treatment contributed to visit-to-visit variability of BP, nonadherence did not explain why individuals with higher visit-to-visit of BP were at increased cardiovascular risk. Additional research is suggested in order to better understand how visit-to-visit variability of BP levels influences prognosis of hypertension.

—Paloma Cesar de Sales, BS, RN, MS

Study Overview

Objective. To determine the association between antihypertensive medication adherence and visit-to-visit variability of blood pressure (BP).

Design. Post hoc analysis of ALLHAT, a randomized, double-blind, multicenter trial to determine whether treatment with calcium-channel blockers, angiotensin-converting enzyme inhibitors, or α-adrenergic blockers, all newer antihypertensive classes at the time of the study, was superior to treatment with a thiazide diuretic for lowering risk for fatal coronary heart disease (CHD) or nonfatal myocardial infarction (MI) (primary outcomes), with secondary outcomes including all-cause mortality, stroke, and combined cardiovascular disease (CHD death, nonfatal MI, stroke, angina, coronary revascularization, congestive heart failure, and peripheral arterial disease).

Setting and participants. Participants who had BP and medication adherence data from at least 5 of the 7 study visits conducted 6 to 28 months after randomization. Only patients who had no outcome events within the 28 months were included in the analysis (ie, no fatal CHD or nonfatal MI, stroke, all-cause mortality, or heart failure). In a secondary analysis, participants who had data from 5 of the 7 study visits between 32 to 56 months after randomization were included.

Measures. Adherence to medication was assessed at each visit by a study clinician using the Adherence Survival Kit developed for ALLHAT. Participants were asked whether they had taken at least 80% of their assigned study drug since the last follow-up visit. For primary analyses, participants were categorized as nonadherent if they reported having taken < 80% of their assigned antihypertensive medication at ≥ 1 visits during the 6- to 28-month time period after randomization. For secondary analyses, participants were categorized as nonadherent if they reported having taken < 80% of their assigned medication at ≥ 1 visits during the 32 to 56 months after randomization. In a sensitivity analysis, participants were categorized as nonadherent if they reported taking < 80% of the prescribed antihypertensive medication at ≥ 2 visits during the 6 to 28 months post-randomization time period. Visit-to-visit variability of BP was calculated using 3 metrics based on each ALLHAT participants’ BP measurements: standard deviation independent of mean (SDIM), SD, and average real variability. The BP used for these calculations was the mean of 2 measurements taken during each follow-up study visit according to a standardized BP measurement protocol. Participants were followed from the end of the visit-to-visit variability of BP assessment period to the date of each outcome, their date of death, or end of active ALLHAT follow-up.

Results. Of 33,357 participants randomized, 19,970 participants met eligibility criteria for primary analyses. Of these, 2912 participants (15%) were considered nonadherent. Compared with adherent participants, nonadherent participants were slightly older and more likely to be Hispanic or black. Nonadherent participants were more likely to have evidence of end-organ damage as signified by major ST segment depression or T wave inversion or left ventricular hypertrophy on electrocardiogram but were less likely to have a history of MI, stroke, or coronary revascularization. Nonadherent participants were also less likely to have used BP medications before randomization and less likely to use statins during follow-up. Nonadherent participants were more likely to have changes in BP medication classes during follow-up, were more likely to have uncontrolled BP between 6 and 28 months after randomization, and had higher mean systolic blood pressure (SBP) and diastolic blood pressure (DBP) at the visits. The association between nonadherence and higher BP remained statistically significant in adjusted analyses.

SDIM of SBP was higher among those who were nonadherent (11.4 ± 4.9 versus 10.5 ± 4.5; P < 0.001). After full adjustment, nonadherent participants had 0.8 (95% CI, 0.7–1.0; P < 0.001) higher SDIM of SBP than adherent participants. In addition, compared with adherent participants, nonadherent participants had higher SD and average real variability of SBP. Researcher found the same pattern when the sample was restricted to 11,290 participants without antihypertensive medication changes. The association between adherence status and visit-to-visit variability of SBP was consistent across antihypertensive drug randomization assignment for interaction term for all definitions of visit-to-visit variability of SBP (P > 0.8). Nonadherent participants also had higher visit-to-visit variability of DBP.

Overall, 4.6% of participants had ≥ 2 visits with < 80% adherence. SDIM of SBP was higher among nonadherent participants versus adherent participants according to this more stringent categorization of nonadherence (11.0 ± 4.6 vs. 10.6 ± 4.6; P = 0.01). After full multivariable adjustment, SDIM of SBP was 0.5 (95% CI, 0.2–0.9; P = 0.001) higher among nonadherent than among adherent participants. Participants who were nonadherent in both the early and late study periods had higher SDIMs of SBP than those who were adherent in both study periods. Minimal changes were found in the SDIM of SBP between the early and late study periods for participants who were adherent in both study periods and nonadherent in both study periods. However, a significant number of participants, had a change in adherence between the early and late study period, with 6.5% switching from adherent to nonadherent and 10.0% switching from nonadherent to adherent. Compared with participants who were adherent in both time periods, participants who changed from adherent to non-adherent had an increase in SDIM of SBP (0.9; 95% CI, 0.5–1.3; P < 0.001), whereas participants who changed from nonadherent to adherent had a decrease in SDIM of SBP (−0.7; 95% CI, −1.0 to −0.3; P < 0.001). Among participants in the primary analysis without a cardiovascular event before the 28-month visit (n = 18 442), being in the highest versus lowest quintile of SDIM of SBP was associated with increased risk of fatal CHD or nonfatal MI, stroke, heart failure, and all-cause mortality after multivariable adjustment. In a mediation analysis, further adjustment for adherence status did not explain the association between SDIM of SBP and any of our cardiovascular or mortality outcomes.

Conclusion. The study provided significant evidence that medication adherence reduces visit-to-visit variability of BP. However, visit-to-visit variability of BP is associated with cardiovascular outcomes independent of medication adherence. Further work is needed to examine both the mechanisms underlying the association between visit-to-visit variability of BP and cardiovascular outcomes and whether decreasing visit-to-visit variability of BP can improve health outcomes.

Commentary

Hypertension remains one of the most important preventable contributors to disease and death [1]. Health care providers continue to reinforce the importance of adherence to medication treatment in conjunction with the adoption of healthy lifestyle habits, which have been shown to be effective interventions [2]. Low adherence to antihypertensive medication has been hypothesized to increase visit-to-visit variability of BP. Literature has shown that visit-to-visit variability of BP is associated with increased risk for stroke, CHD, and mortality [3]. In this post hoc analysis of ALLHAT, the researchers found that nonadherence was associated with increased visit-to-visit variability of BP. The study extended the findings of only a few studies that have tested this association.

Efforts to improve adherence could impact the occurrence of visit-to-visit variability of BP. Current methods of improving medication adherence for chronic health problems are mostly complex and not very effective. Awareness and commitment are essential to promote and ensure adherence in the treatment of disease [4]. Advances in this field of research are needed, including improved design of feasible long-term interventions, objective adherence measures, and sufficient study power to detect improvements outcomes that patients care about [4].

However, in this study, medication nonadherence did not explain the association between visit-to-visit variability of BP levels and cardiovascular risk. The researchers posit that in light of this, improving adherence is unlikely to offset the increased risk associated with visit-to-visit variability of BP found in treated patients with hypertension.

Limitations of this study include the use of self-report for adherence measurement, use of a summary measure for adherence, and the exclusion of a substantial number of participants who had < 5 visits in which adherence was assessed.

Applications for Clinical Practice

Although nonadherence to medication treatment contributed to visit-to-visit variability of BP, nonadherence did not explain why individuals with higher visit-to-visit of BP were at increased cardiovascular risk. Additional research is suggested in order to better understand how visit-to-visit variability of BP levels influences prognosis of hypertension.

—Paloma Cesar de Sales, BS, RN, MS

Study Overview

Objective. To determine the effects of intensive (≤ 120 mm Hg) compared with standard (< 140 mm Hg) systolic blood pressure (SBP) targets in adults aged 75 years and older with hypertension.

Design. Randomized controlled trial.

Setting and participants. Participants were a pre-specified subgroup of adults aged 75 years and older from the Systolic Blood Pressure Intervention Trial (SPRINT), an open-label trial conducted at 102 clinical sites in the United States [1]. Participants were included if they had a systolic blood pressure of 130–180 mm Hg and were at increased risk for cardiovascular disease, based on a history of clinical or subclinical cardiovascular disease, chronic kidney disease, or a 10-year Framingham general cardiovascular disease risk score ≥ 15%. Adults with type 2 diabetes, a history of stroke, symptomatic heart failure within the previous 6 months or reduced left ventricular ejection fraction of less than 35%, a clinical diagnosis of dementia, an expected survival of less than 3 years, unintentional weight loss greater than 10% of body weight in the previous 5 months, a systolic blood pressure < 110 mm Hg following 1 minute of standing, or residing in a nursing home were excluded.

Intervention. Participants were randomized to SBP targets of ≤ 120 mm Hg (intensive treatment group) or SBP targets of < 140 mm Hg (standard treatment group). After randomization, the baseline antihypertensive regimens were adjusted according to treatment algorithms used in the Action to Control Cardiovascular Risk in Diabetes (ACCORD) trial [2]. All major classes of antihypertensive agents were included in the formulary and were provided at no cost to the participants. Investigators could also prescribe other antihypertensive medications, which were not provided by the study. The protocol encouraged, but did not mandate, the use of drug classes with the strongest evidence for reduction in cardiovascular outcomes. Participants were seen monthly for the first 3 months and then every 3 months thereafter for measurement of their blood pressure to adjust medications to target SBP. The length of follow-up period was planned to be an average of 5 years.

Main outcome measures. The primary study outcome was a composite of non-fatal myocardial infarction, acute coronary syndrome, non-fatal stroke, non-fatal acute decompensated heart failure, and death from cardiovascular causes. Secondary outcomes included all-cause mortality and the composite of primary study outcomes and all-cause mortality. Study outcomes were adjudicated by investigators unaware of study group assignments. Because it is not clear from previous literature if the treatment effect may be modified by the frailty status of the study participants, the study included in its baseline measurements for participants frailty status and an exploratory analysis to examine if the treatment effect varied by frailty status.

Main results. Average age of participants was 80 years, 62% were men, and the baseline systolic blood pressure was 142 mm Hg on average. Overall 31% of participants were classified as frail. The mean SBP achieved in the intensive treatment group was 123 mm Hg during follow-up, and the mean SBP in the standard treatment group was 135 mm Hg. Participants in the intensive treatment group received on average 1 more medication to reach lower SBP. Participants in the intensive group had a lower incidence of the primary outcome, 2.59% per year compared to 3.85% per year in the standard treatment group with a hazard ratio of 0.66 (95% CI, 0.51–0.85). At 3.14 years, the number needed to treat (NNT) for the primary outcome was 27. For all-cause mortality, the intensive treatment group also had lower rates: 73 deaths compared to 107 deaths in the standard treatment group (NNT, 41). In the exploratory analysis, frailty status did not significantly modify the effect of intensive treatment (P = 0.84 for interaction). The rate of adverse events in the intensive treatment group was not statistically significantly different from the standard treatment group; the rate of orthostatic hypotension was also not different between the groups.

Conclusion. Treatment of hypertension to an SBP target of ≤ 120 mm Hg compared with an SBP target of < 140 mm Hg led to lower rates of cardiovascular events and mortality among ambulatory older adults aged 75 and older.

Commentary

Published in 2012, the largest randomized controlled trial on the treatment of hypertension in older adults—the Hypertension in the Very Elderly Trial (HYVET)—found that treatment of older adults aged 80 and older with an SBP of 160 mm Hg with a target of < 150 mm Hg led to a reduction in cardiovascular deaths, strokes, and death from any cause [3]. The current SPRINT study went a step further by lowering the target SBP to 120 mm Hg and found that when compared to a target of < 140 mm Hg, the more intensive control also yielded significant benefits in reducing rates of cardiovascular events and mortality among older adults. Although average SBP reached in the intensive group was higher than the targeted goal of 120 mm Hg (an average of 123 mm Hg during follow-up), it demonstrated the clinical benefits of reducing SBP by over 10 mm Hg when compared with standard treatment group by adding on average 1 antihypertensive medication. The study did not directly tackle the issue of diastolic blood pressure (DBP) levels, though noting that treatment goal should lower DBP to < 90 mm Hg. The intensive treatment group also did not have significantly higher rates of adverse events including orthostatic hypotension and injurious falls, alleviating some of the concerns of clinicians when considering intensifying treatment of hypertension in older adults.

Clinicians often hesitate to intensify hypertension treatment among older adults because previously there has been a lack of evidence that demonstrated conclusively that lowering blood pressure yields clinical benefits [4]. The older adult population is often underrepresented in previous trials of hypertension, and prior observational studies often failed to demonstrate that lower blood pressures associate with better clinical outcomes [5]. Coupled with the concern for the high prevalence of white coat hypertension, orthostatic hypotension, falls, and frailty in the older adult population, clinicians are often concerned that intensifying hypertension treatment may do more harm than good [4]. The current study took great care in tackling some of these issues by including a measurement of frailty, by allowing older adults with postural changes in blood pressure to be included (except for those with standing blood pressure in very low range of < 110 mm Hg), and by tracking adverse events including orthostatic hypotension and injurious falls. The results should help to provide the evidence to convince clinicians that there is substantial value in intensifying hypertension treatment among ambulatory older adults and dispel some of the concerns that clinicians may have regarding its potential harms. Of note, the study excluded older adults that perhaps represent the frailest group of the older adult population—those living in nursing homes, those with dementia, and those with life expectancy of less than 3 years. The study results should not extrapolate to these groups. The analysis examining if treatment effect is consistent among those who are frail should be considered exploratory in nature, as pointed out by the study authors and the editorial to the article [6]. Further studies are needed to examine this issue.

Applications for Clinical Practice

The current study provides strong evidence that intensifying antihypertensive treatment to SBP in the range of 120 mm Hg confers clinical benefits to older ambulatory adults aged 75 and older. The current guidelines published by the Eighth Joint National Committee (JNC 8) recommends that treatment in the general population aged ≥ 60 years should consist of initiating pharmacologic treatment at SBP ≥ 150 mm Hg and treat to a goal SBP < 150 mm Hg [7]. Given the findings from the current study, the guidelines should be revised to reflect the new evidence generated from the current study. Although cardiovascular events and mortality are important clinical outcomes, other outcomes important to the older adult population should also be examined such as quality of life and functional outcomes. The SPRINT study did include these outcomes in its protocol and we look forward to additional insights regarding treatment impact on these important outcomes.

—William W. Hung, MD, MPH

Study Overview

Objective. To determine the effects of intensive (≤ 120 mm Hg) compared with standard (< 140 mm Hg) systolic blood pressure (SBP) targets in adults aged 75 years and older with hypertension.

Design. Randomized controlled trial.

Setting and participants. Participants were a pre-specified subgroup of adults aged 75 years and older from the Systolic Blood Pressure Intervention Trial (SPRINT), an open-label trial conducted at 102 clinical sites in the United States [1]. Participants were included if they had a systolic blood pressure of 130–180 mm Hg and were at increased risk for cardiovascular disease, based on a history of clinical or subclinical cardiovascular disease, chronic kidney disease, or a 10-year Framingham general cardiovascular disease risk score ≥ 15%. Adults with type 2 diabetes, a history of stroke, symptomatic heart failure within the previous 6 months or reduced left ventricular ejection fraction of less than 35%, a clinical diagnosis of dementia, an expected survival of less than 3 years, unintentional weight loss greater than 10% of body weight in the previous 5 months, a systolic blood pressure < 110 mm Hg following 1 minute of standing, or residing in a nursing home were excluded.

Intervention. Participants were randomized to SBP targets of ≤ 120 mm Hg (intensive treatment group) or SBP targets of < 140 mm Hg (standard treatment group). After randomization, the baseline antihypertensive regimens were adjusted according to treatment algorithms used in the Action to Control Cardiovascular Risk in Diabetes (ACCORD) trial [2]. All major classes of antihypertensive agents were included in the formulary and were provided at no cost to the participants. Investigators could also prescribe other antihypertensive medications, which were not provided by the study. The protocol encouraged, but did not mandate, the use of drug classes with the strongest evidence for reduction in cardiovascular outcomes. Participants were seen monthly for the first 3 months and then every 3 months thereafter for measurement of their blood pressure to adjust medications to target SBP. The length of follow-up period was planned to be an average of 5 years.

Main outcome measures. The primary study outcome was a composite of non-fatal myocardial infarction, acute coronary syndrome, non-fatal stroke, non-fatal acute decompensated heart failure, and death from cardiovascular causes. Secondary outcomes included all-cause mortality and the composite of primary study outcomes and all-cause mortality. Study outcomes were adjudicated by investigators unaware of study group assignments. Because it is not clear from previous literature if the treatment effect may be modified by the frailty status of the study participants, the study included in its baseline measurements for participants frailty status and an exploratory analysis to examine if the treatment effect varied by frailty status.

Main results. Average age of participants was 80 years, 62% were men, and the baseline systolic blood pressure was 142 mm Hg on average. Overall 31% of participants were classified as frail. The mean SBP achieved in the intensive treatment group was 123 mm Hg during follow-up, and the mean SBP in the standard treatment group was 135 mm Hg. Participants in the intensive treatment group received on average 1 more medication to reach lower SBP. Participants in the intensive group had a lower incidence of the primary outcome, 2.59% per year compared to 3.85% per year in the standard treatment group with a hazard ratio of 0.66 (95% CI, 0.51–0.85). At 3.14 years, the number needed to treat (NNT) for the primary outcome was 27. For all-cause mortality, the intensive treatment group also had lower rates: 73 deaths compared to 107 deaths in the standard treatment group (NNT, 41). In the exploratory analysis, frailty status did not significantly modify the effect of intensive treatment (P = 0.84 for interaction). The rate of adverse events in the intensive treatment group was not statistically significantly different from the standard treatment group; the rate of orthostatic hypotension was also not different between the groups.

Conclusion. Treatment of hypertension to an SBP target of ≤ 120 mm Hg compared with an SBP target of < 140 mm Hg led to lower rates of cardiovascular events and mortality among ambulatory older adults aged 75 and older.

Commentary

Published in 2012, the largest randomized controlled trial on the treatment of hypertension in older adults—the Hypertension in the Very Elderly Trial (HYVET)—found that treatment of older adults aged 80 and older with an SBP of 160 mm Hg with a target of < 150 mm Hg led to a reduction in cardiovascular deaths, strokes, and death from any cause [3]. The current SPRINT study went a step further by lowering the target SBP to 120 mm Hg and found that when compared to a target of < 140 mm Hg, the more intensive control also yielded significant benefits in reducing rates of cardiovascular events and mortality among older adults. Although average SBP reached in the intensive group was higher than the targeted goal of 120 mm Hg (an average of 123 mm Hg during follow-up), it demonstrated the clinical benefits of reducing SBP by over 10 mm Hg when compared with standard treatment group by adding on average 1 antihypertensive medication. The study did not directly tackle the issue of diastolic blood pressure (DBP) levels, though noting that treatment goal should lower DBP to < 90 mm Hg. The intensive treatment group also did not have significantly higher rates of adverse events including orthostatic hypotension and injurious falls, alleviating some of the concerns of clinicians when considering intensifying treatment of hypertension in older adults.

Clinicians often hesitate to intensify hypertension treatment among older adults because previously there has been a lack of evidence that demonstrated conclusively that lowering blood pressure yields clinical benefits [4]. The older adult population is often underrepresented in previous trials of hypertension, and prior observational studies often failed to demonstrate that lower blood pressures associate with better clinical outcomes [5]. Coupled with the concern for the high prevalence of white coat hypertension, orthostatic hypotension, falls, and frailty in the older adult population, clinicians are often concerned that intensifying hypertension treatment may do more harm than good [4]. The current study took great care in tackling some of these issues by including a measurement of frailty, by allowing older adults with postural changes in blood pressure to be included (except for those with standing blood pressure in very low range of < 110 mm Hg), and by tracking adverse events including orthostatic hypotension and injurious falls. The results should help to provide the evidence to convince clinicians that there is substantial value in intensifying hypertension treatment among ambulatory older adults and dispel some of the concerns that clinicians may have regarding its potential harms. Of note, the study excluded older adults that perhaps represent the frailest group of the older adult population—those living in nursing homes, those with dementia, and those with life expectancy of less than 3 years. The study results should not extrapolate to these groups. The analysis examining if treatment effect is consistent among those who are frail should be considered exploratory in nature, as pointed out by the study authors and the editorial to the article [6]. Further studies are needed to examine this issue.

Applications for Clinical Practice

The current study provides strong evidence that intensifying antihypertensive treatment to SBP in the range of 120 mm Hg confers clinical benefits to older ambulatory adults aged 75 and older. The current guidelines published by the Eighth Joint National Committee (JNC 8) recommends that treatment in the general population aged ≥ 60 years should consist of initiating pharmacologic treatment at SBP ≥ 150 mm Hg and treat to a goal SBP < 150 mm Hg [7]. Given the findings from the current study, the guidelines should be revised to reflect the new evidence generated from the current study. Although cardiovascular events and mortality are important clinical outcomes, other outcomes important to the older adult population should also be examined such as quality of life and functional outcomes. The SPRINT study did include these outcomes in its protocol and we look forward to additional insights regarding treatment impact on these important outcomes.

—William W. Hung, MD, MPH

Study Overview

Objective. To determine the effects of intensive (≤ 120 mm Hg) compared with standard (< 140 mm Hg) systolic blood pressure (SBP) targets in adults aged 75 years and older with hypertension.

Design. Randomized controlled trial.

Setting and participants. Participants were a pre-specified subgroup of adults aged 75 years and older from the Systolic Blood Pressure Intervention Trial (SPRINT), an open-label trial conducted at 102 clinical sites in the United States [1]. Participants were included if they had a systolic blood pressure of 130–180 mm Hg and were at increased risk for cardiovascular disease, based on a history of clinical or subclinical cardiovascular disease, chronic kidney disease, or a 10-year Framingham general cardiovascular disease risk score ≥ 15%. Adults with type 2 diabetes, a history of stroke, symptomatic heart failure within the previous 6 months or reduced left ventricular ejection fraction of less than 35%, a clinical diagnosis of dementia, an expected survival of less than 3 years, unintentional weight loss greater than 10% of body weight in the previous 5 months, a systolic blood pressure < 110 mm Hg following 1 minute of standing, or residing in a nursing home were excluded.

Intervention. Participants were randomized to SBP targets of ≤ 120 mm Hg (intensive treatment group) or SBP targets of < 140 mm Hg (standard treatment group). After randomization, the baseline antihypertensive regimens were adjusted according to treatment algorithms used in the Action to Control Cardiovascular Risk in Diabetes (ACCORD) trial [2]. All major classes of antihypertensive agents were included in the formulary and were provided at no cost to the participants. Investigators could also prescribe other antihypertensive medications, which were not provided by the study. The protocol encouraged, but did not mandate, the use of drug classes with the strongest evidence for reduction in cardiovascular outcomes. Participants were seen monthly for the first 3 months and then every 3 months thereafter for measurement of their blood pressure to adjust medications to target SBP. The length of follow-up period was planned to be an average of 5 years.

Main outcome measures. The primary study outcome was a composite of non-fatal myocardial infarction, acute coronary syndrome, non-fatal stroke, non-fatal acute decompensated heart failure, and death from cardiovascular causes. Secondary outcomes included all-cause mortality and the composite of primary study outcomes and all-cause mortality. Study outcomes were adjudicated by investigators unaware of study group assignments. Because it is not clear from previous literature if the treatment effect may be modified by the frailty status of the study participants, the study included in its baseline measurements for participants frailty status and an exploratory analysis to examine if the treatment effect varied by frailty status.

Main results. Average age of participants was 80 years, 62% were men, and the baseline systolic blood pressure was 142 mm Hg on average. Overall 31% of participants were classified as frail. The mean SBP achieved in the intensive treatment group was 123 mm Hg during follow-up, and the mean SBP in the standard treatment group was 135 mm Hg. Participants in the intensive treatment group received on average 1 more medication to reach lower SBP. Participants in the intensive group had a lower incidence of the primary outcome, 2.59% per year compared to 3.85% per year in the standard treatment group with a hazard ratio of 0.66 (95% CI, 0.51–0.85). At 3.14 years, the number needed to treat (NNT) for the primary outcome was 27. For all-cause mortality, the intensive treatment group also had lower rates: 73 deaths compared to 107 deaths in the standard treatment group (NNT, 41). In the exploratory analysis, frailty status did not significantly modify the effect of intensive treatment (P = 0.84 for interaction). The rate of adverse events in the intensive treatment group was not statistically significantly different from the standard treatment group; the rate of orthostatic hypotension was also not different between the groups.

Conclusion. Treatment of hypertension to an SBP target of ≤ 120 mm Hg compared with an SBP target of < 140 mm Hg led to lower rates of cardiovascular events and mortality among ambulatory older adults aged 75 and older.

Commentary

Published in 2012, the largest randomized controlled trial on the treatment of hypertension in older adults—the Hypertension in the Very Elderly Trial (HYVET)—found that treatment of older adults aged 80 and older with an SBP of 160 mm Hg with a target of < 150 mm Hg led to a reduction in cardiovascular deaths, strokes, and death from any cause [3]. The current SPRINT study went a step further by lowering the target SBP to 120 mm Hg and found that when compared to a target of < 140 mm Hg, the more intensive control also yielded significant benefits in reducing rates of cardiovascular events and mortality among older adults. Although average SBP reached in the intensive group was higher than the targeted goal of 120 mm Hg (an average of 123 mm Hg during follow-up), it demonstrated the clinical benefits of reducing SBP by over 10 mm Hg when compared with standard treatment group by adding on average 1 antihypertensive medication. The study did not directly tackle the issue of diastolic blood pressure (DBP) levels, though noting that treatment goal should lower DBP to < 90 mm Hg. The intensive treatment group also did not have significantly higher rates of adverse events including orthostatic hypotension and injurious falls, alleviating some of the concerns of clinicians when considering intensifying treatment of hypertension in older adults.

Clinicians often hesitate to intensify hypertension treatment among older adults because previously there has been a lack of evidence that demonstrated conclusively that lowering blood pressure yields clinical benefits [4]. The older adult population is often underrepresented in previous trials of hypertension, and prior observational studies often failed to demonstrate that lower blood pressures associate with better clinical outcomes [5]. Coupled with the concern for the high prevalence of white coat hypertension, orthostatic hypotension, falls, and frailty in the older adult population, clinicians are often concerned that intensifying hypertension treatment may do more harm than good [4]. The current study took great care in tackling some of these issues by including a measurement of frailty, by allowing older adults with postural changes in blood pressure to be included (except for those with standing blood pressure in very low range of < 110 mm Hg), and by tracking adverse events including orthostatic hypotension and injurious falls. The results should help to provide the evidence to convince clinicians that there is substantial value in intensifying hypertension treatment among ambulatory older adults and dispel some of the concerns that clinicians may have regarding its potential harms. Of note, the study excluded older adults that perhaps represent the frailest group of the older adult population—those living in nursing homes, those with dementia, and those with life expectancy of less than 3 years. The study results should not extrapolate to these groups. The analysis examining if treatment effect is consistent among those who are frail should be considered exploratory in nature, as pointed out by the study authors and the editorial to the article [6]. Further studies are needed to examine this issue.

Applications for Clinical Practice

The current study provides strong evidence that intensifying antihypertensive treatment to SBP in the range of 120 mm Hg confers clinical benefits to older ambulatory adults aged 75 and older. The current guidelines published by the Eighth Joint National Committee (JNC 8) recommends that treatment in the general population aged ≥ 60 years should consist of initiating pharmacologic treatment at SBP ≥ 150 mm Hg and treat to a goal SBP < 150 mm Hg [7]. Given the findings from the current study, the guidelines should be revised to reflect the new evidence generated from the current study. Although cardiovascular events and mortality are important clinical outcomes, other outcomes important to the older adult population should also be examined such as quality of life and functional outcomes. The SPRINT study did include these outcomes in its protocol and we look forward to additional insights regarding treatment impact on these important outcomes.

—William W. Hung, MD, MPH

Study Overview

Objective. To understand the risk of diabetes, coronary heart disease (CHD), stroke, and death over time by comparing adults who were “metabolically healthy” but obese at baseline and those with baseline cardiometabolic abnormalities, and to understand the stability of metabolic health over time.

Design. Secondary analysis of data from 2 large prospective epidemiologic cohort studies of cardiovascular risk and outcomes.

Setting and participants.  This study relied on data from the Atherosclerosis Risk in Communities (ARIC) study and the Coronary Artery Risk Development in Young Adults (CARDIA) study. ARIC includes adults who were recruited in late middle-age (45–64 years at baseline) from several clinical sites in the Southeastern and Midwestern United States and who have been followed over time with multiple examinations to assess cardiovascular risk factors and outcomes. CARDIA similarly assessed cardiovascular risk behaviors and events over time in a large cohort of American men and women, however, it recruited younger participants at baseline (18–30 years old). For the present study, the authors used data from all available ARIC and CARDIA participants who had complete information on body mass index (BMI) and cardiometabolic health status and who had not already developed one of the outcomes of interest at baseline, which led to a final sample of 4990 individuals from CARDIA and 14,685 from ARIC.

The independent variable of interest in this study was twofold, describing baseline status in terms of cardiometabolic risk markers and weight. Cardiometabolic risk was categorized as either “healthy,” “suboptimal,” or “unhealthy” based on the presence or absence of 3 risk factors: (1) elevated blood pressure (with untreated threshold of < 130/85 mm Hg considered negative); (2) elevated blood glucose (with untreated threshold of fasting < 100 mg/dL or hemoglobin A1c < 5.7% considered negative); and (3) dyslipidemia (with untreated total cholesterol < 240 mg/dL and HDL cholesterol > 40 for men or > 50 for women considered negative). Participants who were negative for all 3 risk factors were deemed metabolically healthy, those with 1 or 2 risk factors “suboptimal,” and those with all 3 risk factors “unhealthy.” Participants were then further characterized by baseline weight status as “lean” (BMI < 25), “overweight” (BMI 25–29.9), or “obese” (BMI ≥ 30). Combining a participant’s metabolic and weight status therefore yielded 9 possible exposure categories, ranging from  healthy-lean to unhealthy-obesity. The group of greatest interest for this study was participants in the metabolic-ally healthy-obesity (MHO) category—those with a BMI ≥ 30 but with zero of the 3 cardiometabolic risk factors.

Main outcome measures. The investigators assessed  both the stability of MHO over time, and the relative contribution of BMI status vs. cardiometabolic abnormalities to key health outcomes.

To assess the stability of MHO over time, the investigators used follow-up data from both studies to create descriptive statistics on the frequency with which patients (1) changed weight status or (2) changed metabolic status, over up to 10 years of follow-up in ARIC and up to 20 years of follow-up in CARDIA.

Among only ARIC participants (the older adults at baseline), risk of several health outcomes over up to 10 years of follow-up was compared across groups. The health outcomes of interest were incident diabetes, incident CHD (myocardial infarction or coronary death), incident stroke, or all-cause mortality. To visually represent incidence of these outcomes over time, the investigators constructed Kaplan-Meier survival curves. To determine whether the risk of an outcome differed significantly according to baseline exposure category, they used Cox proportional hazards modeling, adjusting for covariates including age, sex, race, income, education, and tobacco and alcohol use. All available follow-up time was used from baseline until an outcome of interest developed or a participant was censored. Reasons for censoring a participant were not outlined. Multivariable Cox models were separately conducted for the 4 outcomes of diabetes, CHD, stroke, and mortality across the 9 main exposure categories and across 15 categories in an additional analysis where “suboptimal cardiometabolic health” was split according to whether participants had 1 or 2 baseline risk factors. The reference group for all analyses was patients with MHO. A P value of < 0.05 was specified as statistically significant.

Results. Baseline characteristics were presented only for ARIC patients. Among that group (n = 14,685), just 2% (n = 260) were characterized as MHO at baseline. Just over one-quarter (27%) were obese at baseline, and the vast majority of patients with obesity at baseline (94%) had either suboptimal cardiometabolic risk (SO) or metabolically unhealthy obesity (MUO—all 3 risk factors present). Mean follow-up time for ARIC participants was 18.7 years.

Just under half of the ARIC sample were women (45%), 25% were black (the remaining were white), mean age was 54.3 years, and mean BMI was 27.7. Covariates such as education and income were not reported in the table of patient characteristics. No statistical testing was reported comparing exposure categories at baseline, however, within the “healthy”, “suboptimal,” and “unhealthy” categories, increasing weight status appeared to track with increasing blood pressure, fasting glucose, insulin resistance, and waist circumference.

With MHO participants as the reference group, there were no significant differences between baseline weight categories (lean, overweight, obese) of “healthy” (zero risk factors) participants for CHD, stroke, or mortality during follow-up. In other words, baseline weight status did not significantly impact the risk of these 3 outcomes, assuming someone started out metabolically healthy. However, significant differences did emerge among participants with 1 or more risk factor at baseline. For those in the “suboptimal” (SO) category (1 or 2 risk factors), all 3 weight subgroups (lean, overweight, and obese) had significantly higher risk of CHD and stroke during follow-up relative to the MHO participants (hazard ratios [HRs] for CHD: lean 2.3, overweight 2.5, obese 3.0; HRs for stroke: lean 2.6, overweight 2.7, obese 3.0), and mortality risk was higher among lean-SOs (HR 1.4) and obese-SOs (HR 1.7). For those in the unhealthy category at baseline, there was significantly higher risk of CHD, stroke, and mortality across all 3 baseline weight categories relative to participants who were MHO at baseline – that is, even “lean” at baseline patients who had 3 risk factors had significantly higher risk of all of these outcomes than “healthy obese” patients (CHD HR 3.6; stroke HR 2.9; mortality HR 1.9).

Diabetes results differed slightly. For this outcome, participants in the lean-healthy baseline category had about half the risk of developing diabetes during follow-up (HR 0.47) compared to the MHO participants. Those in the overweight-healthy and lean-suboptimal health categories had no difference in risk of diabetes compared to MHO. All other subgroups had higher risk of developing diabetes over time (eg, lean-unhealthy diabetes HR 2.3; obese-unhealthy diabetes HR 5.4) relative to MHO.

Data from both ARIC and CARDIA were used to evaluate the stability of weight and metabolic health during follow-up. Consistent with nationally observed trends in the U.S., many participants gained weight during follow-up, with 17.5% of initially lean and 67.3% of overweight CARDIA patients transitioning to obesity over time. For patients initially categorized as metabolically healthy, a large fraction developed 1 or 2 metabolic abnormalities in follow-up (52% in ARIC and 35% in CARDIA). Very few participants from either study transitioned from a healthy state of 0 risk factors to the unhealthy state of 3 risk factors during follow-up.

Conclusion. The authors conclude that patients with MHO have lower risk for diabetes, CHD, stroke, and mortality than unhealthy subjects regardless of weight status. They did note that obesity increased diabetes risk, even in the absence of detectable baseline abnormalities, relative to lean healthy individuals.

Commentary

Metabolically healthy obesity describes a state where a patient’s body mass index is above 30 kg/m² yet the individual lacks traditional measures of cardiometabolic derangement often associated with excess adiposity. The definition of MHO varies between studies but often requires that a patient with obesity display less than 3 metabolic syndrome criteria, sometimes allowing for even fewer abnormalities (eg, 0 or 1) [1]. It is estimated that anywhere between 10% to one-third of adults with obesity may fall into this category of relative metabolic health despite an elevated BMI [1,2]. Some controversy surrounds how the MHO state should be viewed and its practical implications for clinical management. It is unclear whether patients with MHO are simply in a transient state (ie, “pre-metabolic,” akin to “pre-diabetic”) that will later convert to metabolically unhealthy obesity (MUO), or whether they are truly somehow genetically able to handle excess weight without ever developing the sequelae that are so commonly observed in most patients with obesity. This is an important distinction for clinicians, as it may have implications for how aggressively weight loss is pursued and how long-term risks of excess weight are framed for these individuals. Consider a 40-year-old female patient with a BMI of 32 who is otherwise healthy and active, on no BP medications, with an optimal lipid profile and no signs of insulin resistance. Should this patient be encouraged to lose weight? What health risks does she face in the next few decades if she does not?

In this secondary data analysis from 2 large cohort studies of cardiovascular risk, Guo and Garvey conclude that it is the cardiometabolic risk markers of elevated blood pressure, dyslipidemia, and elevated blood glucose that confer far more risk in terms of long-term cardiovascular outcomes than excess weight in and of itself. Their analyses make use of data from 2 large and rigorous cohort studies of cardiovascular outcomes, which lend credibility to the outcomes they aimed to study (ie, we can be confident that if someone is listed as having had a myocardial infarction in ARIC or CARDIA, they probably did) and provided them with the unique ability to study long-term outcomes on a large sample size. In short, this study would have been difficult to do with many other sources of data or methodologies. Their statistical methods for comparing the risk of the outcomes over long-term follow-up appear robust, particularly given the high event rates in some of the groups and therefore inevitable high levels of censoring over time. Importantly, they control for a number of potential confounders in their study, including tobacco use. On the other hand, they perform quite a large number of statistical comparisons, therefore it is possible they may have found fewer significant differences between groups with a more stringent cutoff for their P value (eg, with a Bonferroni correction).

Regarding the stability of the metabolically healthy state over time, it appears there was significant crossover of participants from “healthy” to “suboptimal,” and significant weight gain occurred during follow-up. It is not clear whether an individual’s baseline exposure category was permitted to change over time in the statistical models, which could have impacted their results. Clinically, it is not surprising that there was a lot of movement between categories over up to 20 years of follow-up. It underscores the notion that even if a patient is obese and metabolically healthy cross-sectionally, many of these individuals will not remain metabolically healthy over time. Additionally, although the study abstract describes using data from both ARIC and CARDIA, the health outcomes component relied solely on ARIC participants. These were a group of relatively older adults at baseline who had already made it through much of their adult lives without developing any of the outcomes of interest (diabetes, CHD, stroke or mortality), therefore could have represented a sample that is somehow more metabolically resilient than the general population. As stated by the authors in their limitation section, the assertion that MHO patients are not at increased risk of cardiovascular disease (CVD) outcomes should not be extrapolated to younger patients based on this cohort. This is particularly true because, again, the stability of metabolic health appears relatively low—over half of baseline “healthy” participants in ARIC and over one-third in CARDIA developed 1 or more risk factors in follow-up, and therefore presumably also developed greater risk of CVD than if they had remained “metabolically healthy.” The likelihood that young adults with MHO will go on to develop new risk factors over time is underscored by how rare the MHO state was in the ARIC sample—it represented only 2% of the overall population, and 6% of those with obesity.

Additionally, as the authors noted, while CVD appeared to be much more influenced by the risk factor trio than by obesity alone, obesity did increase diabetes risk even in the “metabolically healthy” group. This finding aligns with prior work suggesting that patients with MHO are at increased risk of diabetes but not CVD, compared with their normal weight metabolically healthy counterparts [3].

Applications for Clinical Practice

Regardless of weight status, patients with risk factors such as elevated blood pressure, glucose, or lipids would benefit from interventions to reduce their long-term cardiovascular risk and mortality. On the other hand, patients with obesity who lack traditional cardiometabolic risk factors represent a clinical population where it is more difficult to advise on some of the potential benefits of weight loss. Adults with MHO can be advised with confidence that weight loss may reduce their risk of developing diabetes, and they may have other important motivations for weight loss that can be supported as well. Importantly, young adults with MHO who are not interested in weight loss should not be assumed to be “in the clear” for cardiovascular risk; they should be monitored for development of new risk factors over time and for the ensuing need for increased intensity of weight loss recommendations and interventions.

—Kristina Lewis, MD, MPH

Study Overview

Objective. To understand the risk of diabetes, coronary heart disease (CHD), stroke, and death over time by comparing adults who were “metabolically healthy” but obese at baseline and those with baseline cardiometabolic abnormalities, and to understand the stability of metabolic health over time.

Design. Secondary analysis of data from 2 large prospective epidemiologic cohort studies of cardiovascular risk and outcomes.

Setting and participants.  This study relied on data from the Atherosclerosis Risk in Communities (ARIC) study and the Coronary Artery Risk Development in Young Adults (CARDIA) study. ARIC includes adults who were recruited in late middle-age (45–64 years at baseline) from several clinical sites in the Southeastern and Midwestern United States and who have been followed over time with multiple examinations to assess cardiovascular risk factors and outcomes. CARDIA similarly assessed cardiovascular risk behaviors and events over time in a large cohort of American men and women, however, it recruited younger participants at baseline (18–30 years old). For the present study, the authors used data from all available ARIC and CARDIA participants who had complete information on body mass index (BMI) and cardiometabolic health status and who had not already developed one of the outcomes of interest at baseline, which led to a final sample of 4990 individuals from CARDIA and 14,685 from ARIC.

The independent variable of interest in this study was twofold, describing baseline status in terms of cardiometabolic risk markers and weight. Cardiometabolic risk was categorized as either “healthy,” “suboptimal,” or “unhealthy” based on the presence or absence of 3 risk factors: (1) elevated blood pressure (with untreated threshold of < 130/85 mm Hg considered negative); (2) elevated blood glucose (with untreated threshold of fasting < 100 mg/dL or hemoglobin A1c < 5.7% considered negative); and (3) dyslipidemia (with untreated total cholesterol < 240 mg/dL and HDL cholesterol > 40 for men or > 50 for women considered negative). Participants who were negative for all 3 risk factors were deemed metabolically healthy, those with 1 or 2 risk factors “suboptimal,” and those with all 3 risk factors “unhealthy.” Participants were then further characterized by baseline weight status as “lean” (BMI < 25), “overweight” (BMI 25–29.9), or “obese” (BMI ≥ 30). Combining a participant’s metabolic and weight status therefore yielded 9 possible exposure categories, ranging from  healthy-lean to unhealthy-obesity. The group of greatest interest for this study was participants in the metabolic-ally healthy-obesity (MHO) category—those with a BMI ≥ 30 but with zero of the 3 cardiometabolic risk factors.

Main outcome measures. The investigators assessed  both the stability of MHO over time, and the relative contribution of BMI status vs. cardiometabolic abnormalities to key health outcomes.

To assess the stability of MHO over time, the investigators used follow-up data from both studies to create descriptive statistics on the frequency with which patients (1) changed weight status or (2) changed metabolic status, over up to 10 years of follow-up in ARIC and up to 20 years of follow-up in CARDIA.

Among only ARIC participants (the older adults at baseline), risk of several health outcomes over up to 10 years of follow-up was compared across groups. The health outcomes of interest were incident diabetes, incident CHD (myocardial infarction or coronary death), incident stroke, or all-cause mortality. To visually represent incidence of these outcomes over time, the investigators constructed Kaplan-Meier survival curves. To determine whether the risk of an outcome differed significantly according to baseline exposure category, they used Cox proportional hazards modeling, adjusting for covariates including age, sex, race, income, education, and tobacco and alcohol use. All available follow-up time was used from baseline until an outcome of interest developed or a participant was censored. Reasons for censoring a participant were not outlined. Multivariable Cox models were separately conducted for the 4 outcomes of diabetes, CHD, stroke, and mortality across the 9 main exposure categories and across 15 categories in an additional analysis where “suboptimal cardiometabolic health” was split according to whether participants had 1 or 2 baseline risk factors. The reference group for all analyses was patients with MHO. A P value of < 0.05 was specified as statistically significant.

Results. Baseline characteristics were presented only for ARIC patients. Among that group (n = 14,685), just 2% (n = 260) were characterized as MHO at baseline. Just over one-quarter (27%) were obese at baseline, and the vast majority of patients with obesity at baseline (94%) had either suboptimal cardiometabolic risk (SO) or metabolically unhealthy obesity (MUO—all 3 risk factors present). Mean follow-up time for ARIC participants was 18.7 years.

Just under half of the ARIC sample were women (45%), 25% were black (the remaining were white), mean age was 54.3 years, and mean BMI was 27.7. Covariates such as education and income were not reported in the table of patient characteristics. No statistical testing was reported comparing exposure categories at baseline, however, within the “healthy”, “suboptimal,” and “unhealthy” categories, increasing weight status appeared to track with increasing blood pressure, fasting glucose, insulin resistance, and waist circumference.

With MHO participants as the reference group, there were no significant differences between baseline weight categories (lean, overweight, obese) of “healthy” (zero risk factors) participants for CHD, stroke, or mortality during follow-up. In other words, baseline weight status did not significantly impact the risk of these 3 outcomes, assuming someone started out metabolically healthy. However, significant differences did emerge among participants with 1 or more risk factor at baseline. For those in the “suboptimal” (SO) category (1 or 2 risk factors), all 3 weight subgroups (lean, overweight, and obese) had significantly higher risk of CHD and stroke during follow-up relative to the MHO participants (hazard ratios [HRs] for CHD: lean 2.3, overweight 2.5, obese 3.0; HRs for stroke: lean 2.6, overweight 2.7, obese 3.0), and mortality risk was higher among lean-SOs (HR 1.4) and obese-SOs (HR 1.7). For those in the unhealthy category at baseline, there was significantly higher risk of CHD, stroke, and mortality across all 3 baseline weight categories relative to participants who were MHO at baseline – that is, even “lean” at baseline patients who had 3 risk factors had significantly higher risk of all of these outcomes than “healthy obese” patients (CHD HR 3.6; stroke HR 2.9; mortality HR 1.9).

Diabetes results differed slightly. For this outcome, participants in the lean-healthy baseline category had about half the risk of developing diabetes during follow-up (HR 0.47) compared to the MHO participants. Those in the overweight-healthy and lean-suboptimal health categories had no difference in risk of diabetes compared to MHO. All other subgroups had higher risk of developing diabetes over time (eg, lean-unhealthy diabetes HR 2.3; obese-unhealthy diabetes HR 5.4) relative to MHO.

Data from both ARIC and CARDIA were used to evaluate the stability of weight and metabolic health during follow-up. Consistent with nationally observed trends in the U.S., many participants gained weight during follow-up, with 17.5% of initially lean and 67.3% of overweight CARDIA patients transitioning to obesity over time. For patients initially categorized as metabolically healthy, a large fraction developed 1 or 2 metabolic abnormalities in follow-up (52% in ARIC and 35% in CARDIA). Very few participants from either study transitioned from a healthy state of 0 risk factors to the unhealthy state of 3 risk factors during follow-up.

Conclusion. The authors conclude that patients with MHO have lower risk for diabetes, CHD, stroke, and mortality than unhealthy subjects regardless of weight status. They did note that obesity increased diabetes risk, even in the absence of detectable baseline abnormalities, relative to lean healthy individuals.

Commentary

Metabolically healthy obesity describes a state where a patient’s body mass index is above 30 kg/m² yet the individual lacks traditional measures of cardiometabolic derangement often associated with excess adiposity. The definition of MHO varies between studies but often requires that a patient with obesity display less than 3 metabolic syndrome criteria, sometimes allowing for even fewer abnormalities (eg, 0 or 1) [1]. It is estimated that anywhere between 10% to one-third of adults with obesity may fall into this category of relative metabolic health despite an elevated BMI [1,2]. Some controversy surrounds how the MHO state should be viewed and its practical implications for clinical management. It is unclear whether patients with MHO are simply in a transient state (ie, “pre-metabolic,” akin to “pre-diabetic”) that will later convert to metabolically unhealthy obesity (MUO), or whether they are truly somehow genetically able to handle excess weight without ever developing the sequelae that are so commonly observed in most patients with obesity. This is an important distinction for clinicians, as it may have implications for how aggressively weight loss is pursued and how long-term risks of excess weight are framed for these individuals. Consider a 40-year-old female patient with a BMI of 32 who is otherwise healthy and active, on no BP medications, with an optimal lipid profile and no signs of insulin resistance. Should this patient be encouraged to lose weight? What health risks does she face in the next few decades if she does not?

In this secondary data analysis from 2 large cohort studies of cardiovascular risk, Guo and Garvey conclude that it is the cardiometabolic risk markers of elevated blood pressure, dyslipidemia, and elevated blood glucose that confer far more risk in terms of long-term cardiovascular outcomes than excess weight in and of itself. Their analyses make use of data from 2 large and rigorous cohort studies of cardiovascular outcomes, which lend credibility to the outcomes they aimed to study (ie, we can be confident that if someone is listed as having had a myocardial infarction in ARIC or CARDIA, they probably did) and provided them with the unique ability to study long-term outcomes on a large sample size. In short, this study would have been difficult to do with many other sources of data or methodologies. Their statistical methods for comparing the risk of the outcomes over long-term follow-up appear robust, particularly given the high event rates in some of the groups and therefore inevitable high levels of censoring over time. Importantly, they control for a number of potential confounders in their study, including tobacco use. On the other hand, they perform quite a large number of statistical comparisons, therefore it is possible they may have found fewer significant differences between groups with a more stringent cutoff for their P value (eg, with a Bonferroni correction).

Regarding the stability of the metabolically healthy state over time, it appears there was significant crossover of participants from “healthy” to “suboptimal,” and significant weight gain occurred during follow-up. It is not clear whether an individual’s baseline exposure category was permitted to change over time in the statistical models, which could have impacted their results. Clinically, it is not surprising that there was a lot of movement between categories over up to 20 years of follow-up. It underscores the notion that even if a patient is obese and metabolically healthy cross-sectionally, many of these individuals will not remain metabolically healthy over time. Additionally, although the study abstract describes using data from both ARIC and CARDIA, the health outcomes component relied solely on ARIC participants. These were a group of relatively older adults at baseline who had already made it through much of their adult lives without developing any of the outcomes of interest (diabetes, CHD, stroke or mortality), therefore could have represented a sample that is somehow more metabolically resilient than the general population. As stated by the authors in their limitation section, the assertion that MHO patients are not at increased risk of cardiovascular disease (CVD) outcomes should not be extrapolated to younger patients based on this cohort. This is particularly true because, again, the stability of metabolic health appears relatively low—over half of baseline “healthy” participants in ARIC and over one-third in CARDIA developed 1 or more risk factors in follow-up, and therefore presumably also developed greater risk of CVD than if they had remained “metabolically healthy.” The likelihood that young adults with MHO will go on to develop new risk factors over time is underscored by how rare the MHO state was in the ARIC sample—it represented only 2% of the overall population, and 6% of those with obesity.

Additionally, as the authors noted, while CVD appeared to be much more influenced by the risk factor trio than by obesity alone, obesity did increase diabetes risk even in the “metabolically healthy” group. This finding aligns with prior work suggesting that patients with MHO are at increased risk of diabetes but not CVD, compared with their normal weight metabolically healthy counterparts [3].

Applications for Clinical Practice

Regardless of weight status, patients with risk factors such as elevated blood pressure, glucose, or lipids would benefit from interventions to reduce their long-term cardiovascular risk and mortality. On the other hand, patients with obesity who lack traditional cardiometabolic risk factors represent a clinical population where it is more difficult to advise on some of the potential benefits of weight loss. Adults with MHO can be advised with confidence that weight loss may reduce their risk of developing diabetes, and they may have other important motivations for weight loss that can be supported as well. Importantly, young adults with MHO who are not interested in weight loss should not be assumed to be “in the clear” for cardiovascular risk; they should be monitored for development of new risk factors over time and for the ensuing need for increased intensity of weight loss recommendations and interventions.

—Kristina Lewis, MD, MPH

Study Overview

Objective. To understand the risk of diabetes, coronary heart disease (CHD), stroke, and death over time by comparing adults who were “metabolically healthy” but obese at baseline and those with baseline cardiometabolic abnormalities, and to understand the stability of metabolic health over time.

Design. Secondary analysis of data from 2 large prospective epidemiologic cohort studies of cardiovascular risk and outcomes.

Setting and participants.  This study relied on data from the Atherosclerosis Risk in Communities (ARIC) study and the Coronary Artery Risk Development in Young Adults (CARDIA) study. ARIC includes adults who were recruited in late middle-age (45–64 years at baseline) from several clinical sites in the Southeastern and Midwestern United States and who have been followed over time with multiple examinations to assess cardiovascular risk factors and outcomes. CARDIA similarly assessed cardiovascular risk behaviors and events over time in a large cohort of American men and women, however, it recruited younger participants at baseline (18–30 years old). For the present study, the authors used data from all available ARIC and CARDIA participants who had complete information on body mass index (BMI) and cardiometabolic health status and who had not already developed one of the outcomes of interest at baseline, which led to a final sample of 4990 individuals from CARDIA and 14,685 from ARIC.

The independent variable of interest in this study was twofold, describing baseline status in terms of cardiometabolic risk markers and weight. Cardiometabolic risk was categorized as either “healthy,” “suboptimal,” or “unhealthy” based on the presence or absence of 3 risk factors: (1) elevated blood pressure (with untreated threshold of < 130/85 mm Hg considered negative); (2) elevated blood glucose (with untreated threshold of fasting < 100 mg/dL or hemoglobin A1c < 5.7% considered negative); and (3) dyslipidemia (with untreated total cholesterol < 240 mg/dL and HDL cholesterol > 40 for men or > 50 for women considered negative). Participants who were negative for all 3 risk factors were deemed metabolically healthy, those with 1 or 2 risk factors “suboptimal,” and those with all 3 risk factors “unhealthy.” Participants were then further characterized by baseline weight status as “lean” (BMI < 25), “overweight” (BMI 25–29.9), or “obese” (BMI ≥ 30). Combining a participant’s metabolic and weight status therefore yielded 9 possible exposure categories, ranging from  healthy-lean to unhealthy-obesity. The group of greatest interest for this study was participants in the metabolic-ally healthy-obesity (MHO) category—those with a BMI ≥ 30 but with zero of the 3 cardiometabolic risk factors.

Main outcome measures. The investigators assessed  both the stability of MHO over time, and the relative contribution of BMI status vs. cardiometabolic abnormalities to key health outcomes.

To assess the stability of MHO over time, the investigators used follow-up data from both studies to create descriptive statistics on the frequency with which patients (1) changed weight status or (2) changed metabolic status, over up to 10 years of follow-up in ARIC and up to 20 years of follow-up in CARDIA.

Among only ARIC participants (the older adults at baseline), risk of several health outcomes over up to 10 years of follow-up was compared across groups. The health outcomes of interest were incident diabetes, incident CHD (myocardial infarction or coronary death), incident stroke, or all-cause mortality. To visually represent incidence of these outcomes over time, the investigators constructed Kaplan-Meier survival curves. To determine whether the risk of an outcome differed significantly according to baseline exposure category, they used Cox proportional hazards modeling, adjusting for covariates including age, sex, race, income, education, and tobacco and alcohol use. All available follow-up time was used from baseline until an outcome of interest developed or a participant was censored. Reasons for censoring a participant were not outlined. Multivariable Cox models were separately conducted for the 4 outcomes of diabetes, CHD, stroke, and mortality across the 9 main exposure categories and across 15 categories in an additional analysis where “suboptimal cardiometabolic health” was split according to whether participants had 1 or 2 baseline risk factors. The reference group for all analyses was patients with MHO. A P value of < 0.05 was specified as statistically significant.

Results. Baseline characteristics were presented only for ARIC patients. Among that group (n = 14,685), just 2% (n = 260) were characterized as MHO at baseline. Just over one-quarter (27%) were obese at baseline, and the vast majority of patients with obesity at baseline (94%) had either suboptimal cardiometabolic risk (SO) or metabolically unhealthy obesity (MUO—all 3 risk factors present). Mean follow-up time for ARIC participants was 18.7 years.

Just under half of the ARIC sample were women (45%), 25% were black (the remaining were white), mean age was 54.3 years, and mean BMI was 27.7. Covariates such as education and income were not reported in the table of patient characteristics. No statistical testing was reported comparing exposure categories at baseline, however, within the “healthy”, “suboptimal,” and “unhealthy” categories, increasing weight status appeared to track with increasing blood pressure, fasting glucose, insulin resistance, and waist circumference.

With MHO participants as the reference group, there were no significant differences between baseline weight categories (lean, overweight, obese) of “healthy” (zero risk factors) participants for CHD, stroke, or mortality during follow-up. In other words, baseline weight status did not significantly impact the risk of these 3 outcomes, assuming someone started out metabolically healthy. However, significant differences did emerge among participants with 1 or more risk factor at baseline. For those in the “suboptimal” (SO) category (1 or 2 risk factors), all 3 weight subgroups (lean, overweight, and obese) had significantly higher risk of CHD and stroke during follow-up relative to the MHO participants (hazard ratios [HRs] for CHD: lean 2.3, overweight 2.5, obese 3.0; HRs for stroke: lean 2.6, overweight 2.7, obese 3.0), and mortality risk was higher among lean-SOs (HR 1.4) and obese-SOs (HR 1.7). For those in the unhealthy category at baseline, there was significantly higher risk of CHD, stroke, and mortality across all 3 baseline weight categories relative to participants who were MHO at baseline – that is, even “lean” at baseline patients who had 3 risk factors had significantly higher risk of all of these outcomes than “healthy obese” patients (CHD HR 3.6; stroke HR 2.9; mortality HR 1.9).

Diabetes results differed slightly. For this outcome, participants in the lean-healthy baseline category had about half the risk of developing diabetes during follow-up (HR 0.47) compared to the MHO participants. Those in the overweight-healthy and lean-suboptimal health categories had no difference in risk of diabetes compared to MHO. All other subgroups had higher risk of developing diabetes over time (eg, lean-unhealthy diabetes HR 2.3; obese-unhealthy diabetes HR 5.4) relative to MHO.

Data from both ARIC and CARDIA were used to evaluate the stability of weight and metabolic health during follow-up. Consistent with nationally observed trends in the U.S., many participants gained weight during follow-up, with 17.5% of initially lean and 67.3% of overweight CARDIA patients transitioning to obesity over time. For patients initially categorized as metabolically healthy, a large fraction developed 1 or 2 metabolic abnormalities in follow-up (52% in ARIC and 35% in CARDIA). Very few participants from either study transitioned from a healthy state of 0 risk factors to the unhealthy state of 3 risk factors during follow-up.

Conclusion. The authors conclude that patients with MHO have lower risk for diabetes, CHD, stroke, and mortality than unhealthy subjects regardless of weight status. They did note that obesity increased diabetes risk, even in the absence of detectable baseline abnormalities, relative to lean healthy individuals.

Commentary

Metabolically healthy obesity describes a state where a patient’s body mass index is above 30 kg/m² yet the individual lacks traditional measures of cardiometabolic derangement often associated with excess adiposity. The definition of MHO varies between studies but often requires that a patient with obesity display less than 3 metabolic syndrome criteria, sometimes allowing for even fewer abnormalities (eg, 0 or 1) [1]. It is estimated that anywhere between 10% to one-third of adults with obesity may fall into this category of relative metabolic health despite an elevated BMI [1,2]. Some controversy surrounds how the MHO state should be viewed and its practical implications for clinical management. It is unclear whether patients with MHO are simply in a transient state (ie, “pre-metabolic,” akin to “pre-diabetic”) that will later convert to metabolically unhealthy obesity (MUO), or whether they are truly somehow genetically able to handle excess weight without ever developing the sequelae that are so commonly observed in most patients with obesity. This is an important distinction for clinicians, as it may have implications for how aggressively weight loss is pursued and how long-term risks of excess weight are framed for these individuals. Consider a 40-year-old female patient with a BMI of 32 who is otherwise healthy and active, on no BP medications, with an optimal lipid profile and no signs of insulin resistance. Should this patient be encouraged to lose weight? What health risks does she face in the next few decades if she does not?

In this secondary data analysis from 2 large cohort studies of cardiovascular risk, Guo and Garvey conclude that it is the cardiometabolic risk markers of elevated blood pressure, dyslipidemia, and elevated blood glucose that confer far more risk in terms of long-term cardiovascular outcomes than excess weight in and of itself. Their analyses make use of data from 2 large and rigorous cohort studies of cardiovascular outcomes, which lend credibility to the outcomes they aimed to study (ie, we can be confident that if someone is listed as having had a myocardial infarction in ARIC or CARDIA, they probably did) and provided them with the unique ability to study long-term outcomes on a large sample size. In short, this study would have been difficult to do with many other sources of data or methodologies. Their statistical methods for comparing the risk of the outcomes over long-term follow-up appear robust, particularly given the high event rates in some of the groups and therefore inevitable high levels of censoring over time. Importantly, they control for a number of potential confounders in their study, including tobacco use. On the other hand, they perform quite a large number of statistical comparisons, therefore it is possible they may have found fewer significant differences between groups with a more stringent cutoff for their P value (eg, with a Bonferroni correction).

Regarding the stability of the metabolically healthy state over time, it appears there was significant crossover of participants from “healthy” to “suboptimal,” and significant weight gain occurred during follow-up. It is not clear whether an individual’s baseline exposure category was permitted to change over time in the statistical models, which could have impacted their results. Clinically, it is not surprising that there was a lot of movement between categories over up to 20 years of follow-up. It underscores the notion that even if a patient is obese and metabolically healthy cross-sectionally, many of these individuals will not remain metabolically healthy over time. Additionally, although the study abstract describes using data from both ARIC and CARDIA, the health outcomes component relied solely on ARIC participants. These were a group of relatively older adults at baseline who had already made it through much of their adult lives without developing any of the outcomes of interest (diabetes, CHD, stroke or mortality), therefore could have represented a sample that is somehow more metabolically resilient than the general population. As stated by the authors in their limitation section, the assertion that MHO patients are not at increased risk of cardiovascular disease (CVD) outcomes should not be extrapolated to younger patients based on this cohort. This is particularly true because, again, the stability of metabolic health appears relatively low—over half of baseline “healthy” participants in ARIC and over one-third in CARDIA developed 1 or more risk factors in follow-up, and therefore presumably also developed greater risk of CVD than if they had remained “metabolically healthy.” The likelihood that young adults with MHO will go on to develop new risk factors over time is underscored by how rare the MHO state was in the ARIC sample—it represented only 2% of the overall population, and 6% of those with obesity.

Additionally, as the authors noted, while CVD appeared to be much more influenced by the risk factor trio than by obesity alone, obesity did increase diabetes risk even in the “metabolically healthy” group. This finding aligns with prior work suggesting that patients with MHO are at increased risk of diabetes but not CVD, compared with their normal weight metabolically healthy counterparts [3].

Applications for Clinical Practice

Regardless of weight status, patients with risk factors such as elevated blood pressure, glucose, or lipids would benefit from interventions to reduce their long-term cardiovascular risk and mortality. On the other hand, patients with obesity who lack traditional cardiometabolic risk factors represent a clinical population where it is more difficult to advise on some of the potential benefits of weight loss. Adults with MHO can be advised with confidence that weight loss may reduce their risk of developing diabetes, and they may have other important motivations for weight loss that can be supported as well. Importantly, young adults with MHO who are not interested in weight loss should not be assumed to be “in the clear” for cardiovascular risk; they should be monitored for development of new risk factors over time and for the ensuing need for increased intensity of weight loss recommendations and interventions.

—Kristina Lewis, MD, MPH