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Pain problems prevalent in adults with hemophilia
TORONTO—A survey of adult hemophilia patients suggests there is room for improvement in assessing and managing disease-related pain.
Roughly 85% of patients surveyed for this study, known as P-FiQ, said they had experienced acute and/or chronic pain in the past 6 months.
Although most patients had no trouble caring for themselves, the pain often had an impact on their daily lives, especially with regard to physical activity and overall mobility.
“Pain and discomfort are significant challenges for people with hemophilia,” said study investigator Michael Recht, MD, PhD, of Oregon Health Sciences University in Portland.
“These results emphasize the importance of providing comprehensive care and support beyond traditional therapy to people living with bleeding disorders.”
Dr Recht and his colleagues presented results of the P-FiQ study in 3 posters at the ISTH 2015 Congress (abstracts PO277-MON, PO297-WED, and PO298-WED).
The study included adult males with mild to severe hemophilia who had a history of joint pain or bleeding. Subjects were asked to assess pain and functional impairment using patient-reported outcome instruments.
During routine visits over the course of a year, 164 participants completed a pain history and 5 questionnaires: the EQ-5D-5L; Brief Pain Inventory Short Form, version 2; International Physical Activity Questionnaire; SF-36v2; and Hemophilia Activities List.
The patients had a median age of 34. More patients had hemophilia A (n=122) than hemophilia B (n=42), and few (n=10) had inhibitors. Sixty-one percent of patients had self-reported arthritis, bone, or joint problems.
Current patient-reported treatment regimens (n=163) were prophylaxis (42%), on-demand treatment (39%), or mostly on-demand treatment (19%). Twenty-five of the 31 patients using on-demand treatment reported using infusions ahead of activity.
Pain prevalence and management
Most participants (85.2%) said they had experienced acute and/or chronic pain over the past 6 months. Twenty-nine percent said they had experienced acute and chronic pain, 32.7% had chronic pain only, 23.5% had acute pain only, and 14.8% reported no pain.
Acute pain was most frequently described as sharp, aching, shooting, and throbbing. Chronic pain was often described as aching, nagging, throbbing, and sharp.
The most common analgesics used for acute or chronic pain were acetaminophen (69.4% and 58%, respectively), NSAIDs (40% and 52%, respectively), and hydrocodone-acetaminophen (29.4% and 33%, respectively).
The most common nonanalgesic strategies used for acute or chronic pain were ice (72.9% and 37%, respectively), rest (48.2% and 34%, respectively), factor VIII/IX or bypassing agent (48.2% and 24%, respectively), elevation (34.1% and 28%, respectively), relaxation (30.6% and 23.0%, respectively), compression (27.1% and 21%, respectively), and heat (24.7% and 15%, respectively).
Impact of pain on daily life
When completing the EQ-5D-5L questionnaire, most patients reported problems with mobility, performing usual activities, and pain or discomfort. However, most patients said they had no problems with self-care (78%) or anxiety/depression (58.5%).
A similar proportion of patients reported slight and moderate pain and discomfort (29.9% and 31.1%, respectively). Pain and discomfort was severe for 11% of patients and extreme for 1.2%, but 26.8% of patients reported no pain or discomfort.
When it came to mobility, patients reported slight (32.3%), moderate (19.5%), and severe (8.5%) problems, and 1.2% of patients said they were unable to get around. However, 38.4% of patients reported having no such problems.
About 44% of patients reported no problems performing usual activities, but 37.2% had slight problems, 14.6% had moderate problems, and 1.8% of patients each had severe problems or were unable to perform usual activities.
For the Brief Pain Inventory, pain severity and interference with daily activities were rated on a scale of 0 to 10, with 0 being no pain/no interference and 10 being pain as bad as you can imagine/pain that completely interferes with daily life.
The overall median pain severity and pain interference were 3.0 (range, 1.3-4.8) and 2.9 (range, 0.7-5.2), respectively. The median worst pain was 6.0, least pain 2.0, average pain 3.0, and current pain 2.0. Ankles were the most frequently reported site of pain.
When completing the International Physical Activity Questionnaire, 49.3% of patients (73/148) reported no activity in the prior week.
The median SF-36v2 scores were lower for physical health domains than mental health domains, and the overall median health score was 3.0 (range, 2.0-3.0).
The median score on the Hemophilia Activities List was 76.1 (range, 59.2-95.1). And patients said hemophilia had a greater impact on their lower extremities than upper extremities.
Dr Recht and his colleagues said these results substantiate the high prevalence of pain in adults with hemophilia. And the study highlights opportunities to improve the assessment and management of pain in these patients.
Study investigators have received funding/consulting fees from—or are employees/shareholders of—Novo Nordisk, Baxter, Biogen, Bayer, OctaPharma, Pfizer, CSL Behring, Kendrion, Alexion, Grifols, OPKO Health, Sanofi, Merck, and ProMeticLife Sciences.
TORONTO—A survey of adult hemophilia patients suggests there is room for improvement in assessing and managing disease-related pain.
Roughly 85% of patients surveyed for this study, known as P-FiQ, said they had experienced acute and/or chronic pain in the past 6 months.
Although most patients had no trouble caring for themselves, the pain often had an impact on their daily lives, especially with regard to physical activity and overall mobility.
“Pain and discomfort are significant challenges for people with hemophilia,” said study investigator Michael Recht, MD, PhD, of Oregon Health Sciences University in Portland.
“These results emphasize the importance of providing comprehensive care and support beyond traditional therapy to people living with bleeding disorders.”
Dr Recht and his colleagues presented results of the P-FiQ study in 3 posters at the ISTH 2015 Congress (abstracts PO277-MON, PO297-WED, and PO298-WED).
The study included adult males with mild to severe hemophilia who had a history of joint pain or bleeding. Subjects were asked to assess pain and functional impairment using patient-reported outcome instruments.
During routine visits over the course of a year, 164 participants completed a pain history and 5 questionnaires: the EQ-5D-5L; Brief Pain Inventory Short Form, version 2; International Physical Activity Questionnaire; SF-36v2; and Hemophilia Activities List.
The patients had a median age of 34. More patients had hemophilia A (n=122) than hemophilia B (n=42), and few (n=10) had inhibitors. Sixty-one percent of patients had self-reported arthritis, bone, or joint problems.
Current patient-reported treatment regimens (n=163) were prophylaxis (42%), on-demand treatment (39%), or mostly on-demand treatment (19%). Twenty-five of the 31 patients using on-demand treatment reported using infusions ahead of activity.
Pain prevalence and management
Most participants (85.2%) said they had experienced acute and/or chronic pain over the past 6 months. Twenty-nine percent said they had experienced acute and chronic pain, 32.7% had chronic pain only, 23.5% had acute pain only, and 14.8% reported no pain.
Acute pain was most frequently described as sharp, aching, shooting, and throbbing. Chronic pain was often described as aching, nagging, throbbing, and sharp.
The most common analgesics used for acute or chronic pain were acetaminophen (69.4% and 58%, respectively), NSAIDs (40% and 52%, respectively), and hydrocodone-acetaminophen (29.4% and 33%, respectively).
The most common nonanalgesic strategies used for acute or chronic pain were ice (72.9% and 37%, respectively), rest (48.2% and 34%, respectively), factor VIII/IX or bypassing agent (48.2% and 24%, respectively), elevation (34.1% and 28%, respectively), relaxation (30.6% and 23.0%, respectively), compression (27.1% and 21%, respectively), and heat (24.7% and 15%, respectively).
Impact of pain on daily life
When completing the EQ-5D-5L questionnaire, most patients reported problems with mobility, performing usual activities, and pain or discomfort. However, most patients said they had no problems with self-care (78%) or anxiety/depression (58.5%).
A similar proportion of patients reported slight and moderate pain and discomfort (29.9% and 31.1%, respectively). Pain and discomfort was severe for 11% of patients and extreme for 1.2%, but 26.8% of patients reported no pain or discomfort.
When it came to mobility, patients reported slight (32.3%), moderate (19.5%), and severe (8.5%) problems, and 1.2% of patients said they were unable to get around. However, 38.4% of patients reported having no such problems.
About 44% of patients reported no problems performing usual activities, but 37.2% had slight problems, 14.6% had moderate problems, and 1.8% of patients each had severe problems or were unable to perform usual activities.
For the Brief Pain Inventory, pain severity and interference with daily activities were rated on a scale of 0 to 10, with 0 being no pain/no interference and 10 being pain as bad as you can imagine/pain that completely interferes with daily life.
The overall median pain severity and pain interference were 3.0 (range, 1.3-4.8) and 2.9 (range, 0.7-5.2), respectively. The median worst pain was 6.0, least pain 2.0, average pain 3.0, and current pain 2.0. Ankles were the most frequently reported site of pain.
When completing the International Physical Activity Questionnaire, 49.3% of patients (73/148) reported no activity in the prior week.
The median SF-36v2 scores were lower for physical health domains than mental health domains, and the overall median health score was 3.0 (range, 2.0-3.0).
The median score on the Hemophilia Activities List was 76.1 (range, 59.2-95.1). And patients said hemophilia had a greater impact on their lower extremities than upper extremities.
Dr Recht and his colleagues said these results substantiate the high prevalence of pain in adults with hemophilia. And the study highlights opportunities to improve the assessment and management of pain in these patients.
Study investigators have received funding/consulting fees from—or are employees/shareholders of—Novo Nordisk, Baxter, Biogen, Bayer, OctaPharma, Pfizer, CSL Behring, Kendrion, Alexion, Grifols, OPKO Health, Sanofi, Merck, and ProMeticLife Sciences.
TORONTO—A survey of adult hemophilia patients suggests there is room for improvement in assessing and managing disease-related pain.
Roughly 85% of patients surveyed for this study, known as P-FiQ, said they had experienced acute and/or chronic pain in the past 6 months.
Although most patients had no trouble caring for themselves, the pain often had an impact on their daily lives, especially with regard to physical activity and overall mobility.
“Pain and discomfort are significant challenges for people with hemophilia,” said study investigator Michael Recht, MD, PhD, of Oregon Health Sciences University in Portland.
“These results emphasize the importance of providing comprehensive care and support beyond traditional therapy to people living with bleeding disorders.”
Dr Recht and his colleagues presented results of the P-FiQ study in 3 posters at the ISTH 2015 Congress (abstracts PO277-MON, PO297-WED, and PO298-WED).
The study included adult males with mild to severe hemophilia who had a history of joint pain or bleeding. Subjects were asked to assess pain and functional impairment using patient-reported outcome instruments.
During routine visits over the course of a year, 164 participants completed a pain history and 5 questionnaires: the EQ-5D-5L; Brief Pain Inventory Short Form, version 2; International Physical Activity Questionnaire; SF-36v2; and Hemophilia Activities List.
The patients had a median age of 34. More patients had hemophilia A (n=122) than hemophilia B (n=42), and few (n=10) had inhibitors. Sixty-one percent of patients had self-reported arthritis, bone, or joint problems.
Current patient-reported treatment regimens (n=163) were prophylaxis (42%), on-demand treatment (39%), or mostly on-demand treatment (19%). Twenty-five of the 31 patients using on-demand treatment reported using infusions ahead of activity.
Pain prevalence and management
Most participants (85.2%) said they had experienced acute and/or chronic pain over the past 6 months. Twenty-nine percent said they had experienced acute and chronic pain, 32.7% had chronic pain only, 23.5% had acute pain only, and 14.8% reported no pain.
Acute pain was most frequently described as sharp, aching, shooting, and throbbing. Chronic pain was often described as aching, nagging, throbbing, and sharp.
The most common analgesics used for acute or chronic pain were acetaminophen (69.4% and 58%, respectively), NSAIDs (40% and 52%, respectively), and hydrocodone-acetaminophen (29.4% and 33%, respectively).
The most common nonanalgesic strategies used for acute or chronic pain were ice (72.9% and 37%, respectively), rest (48.2% and 34%, respectively), factor VIII/IX or bypassing agent (48.2% and 24%, respectively), elevation (34.1% and 28%, respectively), relaxation (30.6% and 23.0%, respectively), compression (27.1% and 21%, respectively), and heat (24.7% and 15%, respectively).
Impact of pain on daily life
When completing the EQ-5D-5L questionnaire, most patients reported problems with mobility, performing usual activities, and pain or discomfort. However, most patients said they had no problems with self-care (78%) or anxiety/depression (58.5%).
A similar proportion of patients reported slight and moderate pain and discomfort (29.9% and 31.1%, respectively). Pain and discomfort was severe for 11% of patients and extreme for 1.2%, but 26.8% of patients reported no pain or discomfort.
When it came to mobility, patients reported slight (32.3%), moderate (19.5%), and severe (8.5%) problems, and 1.2% of patients said they were unable to get around. However, 38.4% of patients reported having no such problems.
About 44% of patients reported no problems performing usual activities, but 37.2% had slight problems, 14.6% had moderate problems, and 1.8% of patients each had severe problems or were unable to perform usual activities.
For the Brief Pain Inventory, pain severity and interference with daily activities were rated on a scale of 0 to 10, with 0 being no pain/no interference and 10 being pain as bad as you can imagine/pain that completely interferes with daily life.
The overall median pain severity and pain interference were 3.0 (range, 1.3-4.8) and 2.9 (range, 0.7-5.2), respectively. The median worst pain was 6.0, least pain 2.0, average pain 3.0, and current pain 2.0. Ankles were the most frequently reported site of pain.
When completing the International Physical Activity Questionnaire, 49.3% of patients (73/148) reported no activity in the prior week.
The median SF-36v2 scores were lower for physical health domains than mental health domains, and the overall median health score was 3.0 (range, 2.0-3.0).
The median score on the Hemophilia Activities List was 76.1 (range, 59.2-95.1). And patients said hemophilia had a greater impact on their lower extremities than upper extremities.
Dr Recht and his colleagues said these results substantiate the high prevalence of pain in adults with hemophilia. And the study highlights opportunities to improve the assessment and management of pain in these patients.
Study investigators have received funding/consulting fees from—or are employees/shareholders of—Novo Nordisk, Baxter, Biogen, Bayer, OctaPharma, Pfizer, CSL Behring, Kendrion, Alexion, Grifols, OPKO Health, Sanofi, Merck, and ProMeticLife Sciences.
PI3Kδ/γ inhibitor generates rapid responses in CLL
VIENNA—New research indicates that duvelisib, a dual inhibitor of PI3Kδ and PI3Kγ, can generate rapid partial responses in treatment-naïve patients with chronic lymphocytic leukemia (CLL).
The 18 patients in the expansion cohort of a phase 1 study of duvelisib had a median time to response of 3.7 months, according to iwCLL response criteria.
And 47% of the responses occurred by the first assessment on day 1 of cycle 3.
“One thing that does seem to be different with this drug is that you’re getting your [partial responses] a bit faster than you see with some of the other drugs,” said Susan O’Brien, MD, of UC Irvine Health in Orange, California.
“[W]hat that means in the long run is not completely clear, but there’s no question that the responses are very rapid.”
Dr O’Brien presented these findings at the 20th Congress of the European Hematology Association (abstract S434*). The research was funded by Infinity Pharmaceuticals, Inc., the company developing duvelisib.
Older CLL patients with comorbidities and patients with high-risk genomic alterations, such as 17p deletion and TP53 mutations, often don’t fare well on the standard chemoimmunotherapy. Duvelisib is being developed as a potential alternative for these patients and others with hematologic malignancies.
In the dose-escalation portion of this phase 1 study, duvelisib at 25 mg twice daily was well-tolerated and exhibited clinical activity in relapsed/refractory CLL, even in those patients with TP53 mutations and 17p deletion.
So investigators conducted the expansion cohort with 18 patients who received duvelisib at the same dose in 28-day cycles. Duvelisib is given continuously until patients have an adverse event or lose their response.
Patient demographics
Dr O’Brien said there was nothing unusual about the demographics of the study population, except the risk factors: 83% of the patients were over 65, “which is very different from what you would see in a chemoimmunotherapy trial.”
She noted that the patients’ median age was 74, and 56% of patients had either a 17p deletion or TP53 mutation.
“And that’s very unusual because . . . the percentage of patients with that abnormality in frontline CLL is about 5% to 10%,” she added.
Patients were a median of 3 years (range, 0–9) from their initial diagnosis, 47% had Rai stage 3 or greater disease, 44% had splenomegaly, and 11% had grade 4 cytopenia.
Response
Patients stayed on treatment for a median of 14 months (range, 1–20). Eight (44%) discontinued treatment—6 (33%) due to an adverse event, 1 withdrew consent, and 1 discontinued for other reasons.
The best overall response rate was 88%, which consisted of 15 partial responses. Two patients (12%) had stable disease, and there were no complete responses or cases of progressive disease.
One patient with a TP53 mutation/17p deletion withdrew consent prior to the first efficacy assessment.
“There’s no upfront progression,” Dr O’Brien said, “and the response rate was identical for patients with high-risk disease or 17p deletion.”
The median progression-free survival was not yet reached, and the rate was 92% at 18 months. One patient progressed at cycle 13.
The median overall survival was also not reached, with a 94% survival rate at 18 months. One patient died of progressive disease approximately 5 months after the last dose.
Adverse events
The most frequent adverse events (AEs) occurring in more than 25% of patients were, in order of frequency, diarrhea, rash, cough, neutropenia, peripheral edema, fatigue, nausea, pyrexia, ALT/AST increase, anemia, and dizziness.
Grade 3 AEs included diarrhea (22%), ALT/AST increase (17%), rash (11%), neutropenia (6%), fatigue (6%), and anemia (6%). The only grade 4 AE was neutropenia (28%).
Serious AEs in more than 1 patient included diarrhea (n=3), colitis (n=2), dehydration (n=2), pneumonia (n=2), and pneumonitis (n=2).
The AEs leading to treatment discontinuation were increased ALT/AST, dehydration, and spinal stenosis (all in 1 patient), as well as arthritis, pneumonitis, colitis, diarrhea, and stomatitis.
“We tend to see the transaminitis and the pneumonitis earlier, and then the late toxicity tends to be the diarrhea and colitis,” Dr O’ Brien said. “The one toxicity where I would not be inclined to try and re-treat a patient is pneumonitis, but I do think colitis can be successfully re-treated.”
Pharmacodynamic studies show very rapid inhibition of phosphorylated AKT following treatment, which is sustained throughout the whole first cycle. And following 1 cycle of duvelisib, there is near-complete inhibition of CLL proliferation, as evidenced by the reduction in Ki67.
Given these data, the investigators recommended further development of duvelisib in treatment-naïve CLL.
*Information in the abstract differs from that presented at the meeting.
VIENNA—New research indicates that duvelisib, a dual inhibitor of PI3Kδ and PI3Kγ, can generate rapid partial responses in treatment-naïve patients with chronic lymphocytic leukemia (CLL).
The 18 patients in the expansion cohort of a phase 1 study of duvelisib had a median time to response of 3.7 months, according to iwCLL response criteria.
And 47% of the responses occurred by the first assessment on day 1 of cycle 3.
“One thing that does seem to be different with this drug is that you’re getting your [partial responses] a bit faster than you see with some of the other drugs,” said Susan O’Brien, MD, of UC Irvine Health in Orange, California.
“[W]hat that means in the long run is not completely clear, but there’s no question that the responses are very rapid.”
Dr O’Brien presented these findings at the 20th Congress of the European Hematology Association (abstract S434*). The research was funded by Infinity Pharmaceuticals, Inc., the company developing duvelisib.
Older CLL patients with comorbidities and patients with high-risk genomic alterations, such as 17p deletion and TP53 mutations, often don’t fare well on the standard chemoimmunotherapy. Duvelisib is being developed as a potential alternative for these patients and others with hematologic malignancies.
In the dose-escalation portion of this phase 1 study, duvelisib at 25 mg twice daily was well-tolerated and exhibited clinical activity in relapsed/refractory CLL, even in those patients with TP53 mutations and 17p deletion.
So investigators conducted the expansion cohort with 18 patients who received duvelisib at the same dose in 28-day cycles. Duvelisib is given continuously until patients have an adverse event or lose their response.
Patient demographics
Dr O’Brien said there was nothing unusual about the demographics of the study population, except the risk factors: 83% of the patients were over 65, “which is very different from what you would see in a chemoimmunotherapy trial.”
She noted that the patients’ median age was 74, and 56% of patients had either a 17p deletion or TP53 mutation.
“And that’s very unusual because . . . the percentage of patients with that abnormality in frontline CLL is about 5% to 10%,” she added.
Patients were a median of 3 years (range, 0–9) from their initial diagnosis, 47% had Rai stage 3 or greater disease, 44% had splenomegaly, and 11% had grade 4 cytopenia.
Response
Patients stayed on treatment for a median of 14 months (range, 1–20). Eight (44%) discontinued treatment—6 (33%) due to an adverse event, 1 withdrew consent, and 1 discontinued for other reasons.
The best overall response rate was 88%, which consisted of 15 partial responses. Two patients (12%) had stable disease, and there were no complete responses or cases of progressive disease.
One patient with a TP53 mutation/17p deletion withdrew consent prior to the first efficacy assessment.
“There’s no upfront progression,” Dr O’Brien said, “and the response rate was identical for patients with high-risk disease or 17p deletion.”
The median progression-free survival was not yet reached, and the rate was 92% at 18 months. One patient progressed at cycle 13.
The median overall survival was also not reached, with a 94% survival rate at 18 months. One patient died of progressive disease approximately 5 months after the last dose.
Adverse events
The most frequent adverse events (AEs) occurring in more than 25% of patients were, in order of frequency, diarrhea, rash, cough, neutropenia, peripheral edema, fatigue, nausea, pyrexia, ALT/AST increase, anemia, and dizziness.
Grade 3 AEs included diarrhea (22%), ALT/AST increase (17%), rash (11%), neutropenia (6%), fatigue (6%), and anemia (6%). The only grade 4 AE was neutropenia (28%).
Serious AEs in more than 1 patient included diarrhea (n=3), colitis (n=2), dehydration (n=2), pneumonia (n=2), and pneumonitis (n=2).
The AEs leading to treatment discontinuation were increased ALT/AST, dehydration, and spinal stenosis (all in 1 patient), as well as arthritis, pneumonitis, colitis, diarrhea, and stomatitis.
“We tend to see the transaminitis and the pneumonitis earlier, and then the late toxicity tends to be the diarrhea and colitis,” Dr O’ Brien said. “The one toxicity where I would not be inclined to try and re-treat a patient is pneumonitis, but I do think colitis can be successfully re-treated.”
Pharmacodynamic studies show very rapid inhibition of phosphorylated AKT following treatment, which is sustained throughout the whole first cycle. And following 1 cycle of duvelisib, there is near-complete inhibition of CLL proliferation, as evidenced by the reduction in Ki67.
Given these data, the investigators recommended further development of duvelisib in treatment-naïve CLL.
*Information in the abstract differs from that presented at the meeting.
VIENNA—New research indicates that duvelisib, a dual inhibitor of PI3Kδ and PI3Kγ, can generate rapid partial responses in treatment-naïve patients with chronic lymphocytic leukemia (CLL).
The 18 patients in the expansion cohort of a phase 1 study of duvelisib had a median time to response of 3.7 months, according to iwCLL response criteria.
And 47% of the responses occurred by the first assessment on day 1 of cycle 3.
“One thing that does seem to be different with this drug is that you’re getting your [partial responses] a bit faster than you see with some of the other drugs,” said Susan O’Brien, MD, of UC Irvine Health in Orange, California.
“[W]hat that means in the long run is not completely clear, but there’s no question that the responses are very rapid.”
Dr O’Brien presented these findings at the 20th Congress of the European Hematology Association (abstract S434*). The research was funded by Infinity Pharmaceuticals, Inc., the company developing duvelisib.
Older CLL patients with comorbidities and patients with high-risk genomic alterations, such as 17p deletion and TP53 mutations, often don’t fare well on the standard chemoimmunotherapy. Duvelisib is being developed as a potential alternative for these patients and others with hematologic malignancies.
In the dose-escalation portion of this phase 1 study, duvelisib at 25 mg twice daily was well-tolerated and exhibited clinical activity in relapsed/refractory CLL, even in those patients with TP53 mutations and 17p deletion.
So investigators conducted the expansion cohort with 18 patients who received duvelisib at the same dose in 28-day cycles. Duvelisib is given continuously until patients have an adverse event or lose their response.
Patient demographics
Dr O’Brien said there was nothing unusual about the demographics of the study population, except the risk factors: 83% of the patients were over 65, “which is very different from what you would see in a chemoimmunotherapy trial.”
She noted that the patients’ median age was 74, and 56% of patients had either a 17p deletion or TP53 mutation.
“And that’s very unusual because . . . the percentage of patients with that abnormality in frontline CLL is about 5% to 10%,” she added.
Patients were a median of 3 years (range, 0–9) from their initial diagnosis, 47% had Rai stage 3 or greater disease, 44% had splenomegaly, and 11% had grade 4 cytopenia.
Response
Patients stayed on treatment for a median of 14 months (range, 1–20). Eight (44%) discontinued treatment—6 (33%) due to an adverse event, 1 withdrew consent, and 1 discontinued for other reasons.
The best overall response rate was 88%, which consisted of 15 partial responses. Two patients (12%) had stable disease, and there were no complete responses or cases of progressive disease.
One patient with a TP53 mutation/17p deletion withdrew consent prior to the first efficacy assessment.
“There’s no upfront progression,” Dr O’Brien said, “and the response rate was identical for patients with high-risk disease or 17p deletion.”
The median progression-free survival was not yet reached, and the rate was 92% at 18 months. One patient progressed at cycle 13.
The median overall survival was also not reached, with a 94% survival rate at 18 months. One patient died of progressive disease approximately 5 months after the last dose.
Adverse events
The most frequent adverse events (AEs) occurring in more than 25% of patients were, in order of frequency, diarrhea, rash, cough, neutropenia, peripheral edema, fatigue, nausea, pyrexia, ALT/AST increase, anemia, and dizziness.
Grade 3 AEs included diarrhea (22%), ALT/AST increase (17%), rash (11%), neutropenia (6%), fatigue (6%), and anemia (6%). The only grade 4 AE was neutropenia (28%).
Serious AEs in more than 1 patient included diarrhea (n=3), colitis (n=2), dehydration (n=2), pneumonia (n=2), and pneumonitis (n=2).
The AEs leading to treatment discontinuation were increased ALT/AST, dehydration, and spinal stenosis (all in 1 patient), as well as arthritis, pneumonitis, colitis, diarrhea, and stomatitis.
“We tend to see the transaminitis and the pneumonitis earlier, and then the late toxicity tends to be the diarrhea and colitis,” Dr O’ Brien said. “The one toxicity where I would not be inclined to try and re-treat a patient is pneumonitis, but I do think colitis can be successfully re-treated.”
Pharmacodynamic studies show very rapid inhibition of phosphorylated AKT following treatment, which is sustained throughout the whole first cycle. And following 1 cycle of duvelisib, there is near-complete inhibition of CLL proliferation, as evidenced by the reduction in Ki67.
Given these data, the investigators recommended further development of duvelisib in treatment-naïve CLL.
*Information in the abstract differs from that presented at the meeting.
Mutations linked to response, survival in aplastic anemia
Photo by Graham Colm
Scientists have identified genetic mutations that appear to be associated with treatment outcomes in patients with aplastic anemia.
When compared to unmutated patients, individuals with mutations in PIGA, BCOR, and BCORL1 tended to have better responses to immunosuppressive therapy and superior survival rates.
Other mutations—such as DNMT3A, ASXL1, and RUNX1—were associated with inferior response and survival rates.
Still, the investigators noted that clonal dynamics were “highly variable” in the patient samples they analyzed and might not necessarily have predicted outcomes.
Neal S. Young, MD, of the National Heart, Lung, and Blood Institute in Bethesda, Maryland, and his colleagues described this research in NEJM.
The team used next-generation DNA sequencing and array-based karyotyping to analyze 668 blood samples from 439 patients, including serial samples from 82 patients.
The investigators identified 249 somatic mutations in 156 patients (36%). The most common mutations occurred in the BCOR (9.3%), BCORL1 (9.3%), DNMT3A (8.4%), PIGA (7.5%), and ASXL1 (6.2%) genes.
Thirty-six percent of patients had multiple mutations. And some patients had multiple mutations in
the same genes, including PIGA, BCOR, DNMT3A, ASXL1, RUNX1, and ZRSR2.
The investigators identified clonal hematopoiesis in 47% of patients, most frequently as acquired mutations.
The team also found that, largely, the presence and number of mutations a patient had was positively correlated with the patient’s age. The exceptions were PIGA, BCOR, and BCORL1 mutations.
Patients with mutations in PIGA, BCOR, or BCORL1 had better responses to immunosuppressive therapy and better overall and progression-free survival than unmutated patients.
Other mutations were associated with worse outcomes. Patients with mutations in ASXL1, DNMT3A, TP53, RUNX1, JAK2, JAK3, or CSMD1 did not respond as well as unmutated patients to immunosuppressive therapy.
Mutations in ASXL1, DNMT3A, TP53, RUNX1, and CSMD1 were associated with worse overall survival, and mutations in ASXL1, DNMT3A, RUNX1, JAK2, and JAK3 were associated with worse progression-free survival.
The investigators also observed an increase in the size of clones with DNMT3A, ASXL1, RUNX1, or U2AF1 mutations. But the size of clones with PIGA, BCOR, or BCORL1 mutations remained stable or decreased with time.
Photo by Graham Colm
Scientists have identified genetic mutations that appear to be associated with treatment outcomes in patients with aplastic anemia.
When compared to unmutated patients, individuals with mutations in PIGA, BCOR, and BCORL1 tended to have better responses to immunosuppressive therapy and superior survival rates.
Other mutations—such as DNMT3A, ASXL1, and RUNX1—were associated with inferior response and survival rates.
Still, the investigators noted that clonal dynamics were “highly variable” in the patient samples they analyzed and might not necessarily have predicted outcomes.
Neal S. Young, MD, of the National Heart, Lung, and Blood Institute in Bethesda, Maryland, and his colleagues described this research in NEJM.
The team used next-generation DNA sequencing and array-based karyotyping to analyze 668 blood samples from 439 patients, including serial samples from 82 patients.
The investigators identified 249 somatic mutations in 156 patients (36%). The most common mutations occurred in the BCOR (9.3%), BCORL1 (9.3%), DNMT3A (8.4%), PIGA (7.5%), and ASXL1 (6.2%) genes.
Thirty-six percent of patients had multiple mutations. And some patients had multiple mutations in
the same genes, including PIGA, BCOR, DNMT3A, ASXL1, RUNX1, and ZRSR2.
The investigators identified clonal hematopoiesis in 47% of patients, most frequently as acquired mutations.
The team also found that, largely, the presence and number of mutations a patient had was positively correlated with the patient’s age. The exceptions were PIGA, BCOR, and BCORL1 mutations.
Patients with mutations in PIGA, BCOR, or BCORL1 had better responses to immunosuppressive therapy and better overall and progression-free survival than unmutated patients.
Other mutations were associated with worse outcomes. Patients with mutations in ASXL1, DNMT3A, TP53, RUNX1, JAK2, JAK3, or CSMD1 did not respond as well as unmutated patients to immunosuppressive therapy.
Mutations in ASXL1, DNMT3A, TP53, RUNX1, and CSMD1 were associated with worse overall survival, and mutations in ASXL1, DNMT3A, RUNX1, JAK2, and JAK3 were associated with worse progression-free survival.
The investigators also observed an increase in the size of clones with DNMT3A, ASXL1, RUNX1, or U2AF1 mutations. But the size of clones with PIGA, BCOR, or BCORL1 mutations remained stable or decreased with time.
Photo by Graham Colm
Scientists have identified genetic mutations that appear to be associated with treatment outcomes in patients with aplastic anemia.
When compared to unmutated patients, individuals with mutations in PIGA, BCOR, and BCORL1 tended to have better responses to immunosuppressive therapy and superior survival rates.
Other mutations—such as DNMT3A, ASXL1, and RUNX1—were associated with inferior response and survival rates.
Still, the investigators noted that clonal dynamics were “highly variable” in the patient samples they analyzed and might not necessarily have predicted outcomes.
Neal S. Young, MD, of the National Heart, Lung, and Blood Institute in Bethesda, Maryland, and his colleagues described this research in NEJM.
The team used next-generation DNA sequencing and array-based karyotyping to analyze 668 blood samples from 439 patients, including serial samples from 82 patients.
The investigators identified 249 somatic mutations in 156 patients (36%). The most common mutations occurred in the BCOR (9.3%), BCORL1 (9.3%), DNMT3A (8.4%), PIGA (7.5%), and ASXL1 (6.2%) genes.
Thirty-six percent of patients had multiple mutations. And some patients had multiple mutations in
the same genes, including PIGA, BCOR, DNMT3A, ASXL1, RUNX1, and ZRSR2.
The investigators identified clonal hematopoiesis in 47% of patients, most frequently as acquired mutations.
The team also found that, largely, the presence and number of mutations a patient had was positively correlated with the patient’s age. The exceptions were PIGA, BCOR, and BCORL1 mutations.
Patients with mutations in PIGA, BCOR, or BCORL1 had better responses to immunosuppressive therapy and better overall and progression-free survival than unmutated patients.
Other mutations were associated with worse outcomes. Patients with mutations in ASXL1, DNMT3A, TP53, RUNX1, JAK2, JAK3, or CSMD1 did not respond as well as unmutated patients to immunosuppressive therapy.
Mutations in ASXL1, DNMT3A, TP53, RUNX1, and CSMD1 were associated with worse overall survival, and mutations in ASXL1, DNMT3A, RUNX1, JAK2, and JAK3 were associated with worse progression-free survival.
The investigators also observed an increase in the size of clones with DNMT3A, ASXL1, RUNX1, or U2AF1 mutations. But the size of clones with PIGA, BCOR, or BCORL1 mutations remained stable or decreased with time.
LISTEN NOW: Gastroenterologist, John Pandolfino, MD, on Best Practices for Colonoscopies, Treating C. diff Infections
John Pandolfino, MD, chief of gastroenterology and hepatology at Northwestern University’s Feinberg School of Medicine in Chicago, talks about best practices for colonoscopies and treating C. diff infections.
John Pandolfino, MD, chief of gastroenterology and hepatology at Northwestern University’s Feinberg School of Medicine in Chicago, talks about best practices for colonoscopies and treating C. diff infections.
John Pandolfino, MD, chief of gastroenterology and hepatology at Northwestern University’s Feinberg School of Medicine in Chicago, talks about best practices for colonoscopies and treating C. diff infections.
LISTEN NOW: Hospitalist Lisa Shieh on Choosing Wisely
Excerpt of our interviews with Choosing Wisely, Lisa Shieh, MD, PhD, of Stanford University School of Medicine, discusses an example of a Choosing Wisely program.
Excerpt of our interviews with Choosing Wisely, Lisa Shieh, MD, PhD, of Stanford University School of Medicine, discusses an example of a Choosing Wisely program.
Excerpt of our interviews with Choosing Wisely, Lisa Shieh, MD, PhD, of Stanford University School of Medicine, discusses an example of a Choosing Wisely program.
LISTEN NOW: Gregory Seymann, MD, on Choosing Wisely
Gregory Seymann, MD, discusses a Choosing Wisely program.
Gregory Seymann, MD, discusses a Choosing Wisely program.
Gregory Seymann, MD, discusses a Choosing Wisely program.
Perceptions of Current Note Quality
The electronic health record (EHR) has revolutionized the practice of medicine. As part of the economic stimulus package in 2009, Congress enacted the Health Information Technology for Economic and Clinical Health Act, which included incentives for physicians and hospitals to adopt an EHR by 2015. In the setting of more limited duty hours and demands for increased clinical productivity, EHRs have functions that may improve the quality and efficiency of clinical documentation.[1, 2, 3, 4, 5]
The process of note writing and the use of notes for clinical care have changed substantially with EHR implementation. Use of efficiency tools (ie, copy forward functions and autopopulation of data) may increase the speed of documentation.[5] Notes in an EHR are more legible and accessible and may be able to organize data to improve clinical care.[6]
Yet, many have commented on the negative consequences of documentation in an EHR. In a New England Journal of Medicine Perspective article, Drs. Hartzband and Groopman wrote, we have observed the electronic medical record become a powerful vehicle for perpetuating erroneous information, leading to diagnostic errors that gain momentum when passed on electronically.[7] As a result, the copy forward and autopopulation functions have come under significant scrutiny.[8, 9, 10] A survey conducted at 2 academic institutions found that 71% of residents and attendings believed that the copy forward function led to inconsistencies and outdated information.[11] Autopopulation has been criticized for creating lengthy notes full of trivial or redundant data, a phenomenon termed note bloat. Bloated notes may be less effective as a communication tool.[12] Additionally, the process of composing a note often stimulates critical thinking and may lead to changes in care. The act of copying forward a previous note and autopopulating data bypasses that process and in effect may suppress critical thinking.[13] Previous studies have raised numerous concerns regarding copy forward and autopopulation functionality in the EHR. Many have described the duplication of outdated data and the possibility of the introduction and perpetuation of errors.[14, 15, 16] The Veterans Affairs (VA) Puget Sound Health system evaluated 6322 copy events and found that 1 in 10 electronic patient charts contained an instance of high‐risk copying.[17] In a survey of faculty and residents at a single academic medical center, the majority of users of copy and paste functionality recognized the hazards; they responded that their notes may contain more outdated (66%) and more inconsistent information (69%). Yet, most felt copy forwarding improved the documentation of the entire hospital course (87%), overall physician documentation (69%), and should definitely be continued (91%).[11] Others have complained about the impact of copy forward on the expression of clinical reasoning.[7, 9, 18]
Previous discussions on the topic of overall note quality following EHR implementation have been limited to perspectives or opinion pieces of individual attending providers.[18] We conducted a survey across 4 academic institutions to analyze both housestaff and attendings perceptions of the quality of notes since the implementation of an EHR to better inform the discussion of the impact of an EHR on note quality.
METHODS
Participants
Surveys were administered via email to interns, residents (second‐, third‐, or fourth‐year residents, hereafter referred to as residents) and attendings at 4 academic hospitals that use the Epic EHR (Epic Corp., Madison, WI). The 4 institutions each adopted the Epic EHR, with mandatory faculty and resident training, between 1 and 5 years prior to the survey. Three of the institutions previously used systems with electronic notes, whereas the fourth institution previously used a system with handwritten notes. The study participation emails included a link to an online survey in REDCap.[19] We included interns and residents from the following types of residency programs: internal medicine categorical or primary care, medicine‐pediatrics, or medicine‐psychiatry. For housestaff (the combination of both interns and residents), exclusion criteria included preliminary or transitional year interns, or any interns or residents from other specialties who rotate on the medicine service. For attendings, participants included hospitalists, general internal medicine attendings, chief residents, and subspecialty medicine attendings, each of whom had worked for any amount of time on the inpatient medicine teaching service in the prior 12 months.
Design
We developed 3 unique surveys for interns, residents, and attendings to assess their perception of inpatient progress notes (see Supporting Information, Appendix, in the online version of this article). The surveys incorporated questions from 2 previously published sources, the 9‐item Physician Documentation Quality Instrument (PDQI‐9) (see online Appendix), a validated note‐scoring tool, and the Accreditation Council for Graduate Medical Education note‐writing competency checklists.[20] Additionally, faculty at the participating institutions developed questions to address practices and attitudes toward autopopulation, copy forward, and the purposes of a progress note. Responses were based on a 5‐point Likert scale. The intern and resident surveys asked for self‐evaluation of their own progress notes and those of their peers, whereas the attending surveys asked for assessment of housestaff notes.
The survey was left open for a total of 55 days and participants were sent reminder emails. The study received a waiver from the institutional review board at all 4 institutions.
Data Analysis
Study data were collected and managed using REDCap electronic data capture tools hosted at the University of California, San Francisco (UCSF).[19] The survey data were analyzed and the figures were created using Microsoft Excel 2008 (Microsoft Corp., Redmond, WA). Mean values for each survey question were calculated. Differences between the means among the groups were assessed using 2‐sample t tests. P values <0.05 were considered statistically significant.
RESULTS
Demographics
We received 99 completed surveys from interns, 155 completed surveys from residents, and 153 completed surveys from attendings across the 4 institutions. The overall response rate for interns was 68%, ranging from 59% at the University of California, San Diego (UCSD) to 74% at the University of Iowa. The overall response rate for residents was 49%, ranging from 38% at UCSF to 66% at the University of California, Los Angeles. The overall response rate for attendings was 70%, ranging from 53% at UCSD to 74% at UCSF.
A total of 78% of interns and 72% of residents had used an EHR at a prior institution. Of the residents, 90 were second‐year residents, 64 were third‐year residents, and 2 were fourth‐year residents. A total of 76% of attendings self‐identified as hospitalists.
Overall Assessment of Note Quality
Participants were asked to rate the quality of progress notes on a 5‐point scale (poor, fair, good, very good, excellent). Half of interns and residents rated their own progress notes as very good or excellent. A total of 44% percent of interns and 24% of residents rated their peers notes as very good or excellent, whereas only 15% of attending physicians rated housestaff notes as very good or excellent.
When asked to rate the change in progress note quality since their hospital had adopted the EHR, the majority of residents answered unchanged or better, and the majority of attendings answered unchanged or worse (Figure 1).

PDQI‐9 Framework
Participants answered each PDQI‐9 question on a 5‐point Likert scale ranging from not at all (1) to extremely (5). In 8 of the 9 PDQI‐9 domains, there were no significant differences between interns and residents. Across each domain, attending perceptions of housestaff notes were significantly lower than housestaff perceptions of their own notes (P<0.001) (Figure 2). Both housestaff and attendings gave the highest ratings to thorough, up to date, and synthesized and the lowest rating to succinct.

Copy Forward and Autopopulation
Overall, the effect of copy forward and autopopulation on critical thinking, note accuracy, and prioritizing the problem list was thought to be neutral or somewhat positive by interns, neutral by residents, and neutral or somewhat negative by attendings (P<0.001) (Figure 3). In all, 16% of interns, 22% of residents, and 55% of attendings reported that copy forward had a somewhat negative or very negative impact on critical thinking (P<0.001). In all, 16% of interns, 29% of residents and 39% of attendings thought that autopopulation had a somewhat negative or very negative impact on critical thinking (P<0.001).

Purpose of Progress Notes
Participants were provided with 7 possible purposes of a progress note and asked to rate the importance of each stated purpose. There was nearly perfect agreement between interns, residents, and attendings in the rank order of the importance of each purpose of a progress note (Table 1). Attendings and housestaff ranked communication with other providers and documenting important events and the plan for the day as the 2 most important purposes of a progress note, and billing and quality improvement as less important.
Interns | Residents | Attendings | |
---|---|---|---|
Communication with other providers | 1 | 1 | 2 |
Documenting important events and the plan for the day | 2 | 2 | 1 |
Prioritizing issues going forward in the patient's care | 3 | 3 | 3 |
Medicolegal | 4 | 4 | 4 |
Stimulate critical thinking | 5 | 5 | 5 |
Billing | 6 | 6 | 6 |
Quality improvement | 7 | 7 | 7 |
DISCUSSION
This is the first large multicenter analysis of both attendings and housestaff perceptions of note quality in the EHR era. The findings provide insight into important differences and similarities in the perceptions of the 2 groups. Most striking is the difference in opinion of overall note quality, with only a small minority of faculty rating current housestaff notes as very good or excellent, whereas a much larger proportion of housestaff rated their own notes and those of their peers to be of high quality. Though participants were not specifically asked why note quality in general was suboptimal, housestaff and faculty rankings of specific domains from the PDQI‐9 may yield an important clue. Specifically, all groups expressed that the weakest attribute of current progress notes is succinct. This finding is consistent with the note bloat phenomenon, which has been maligned as a consequence of EHR implementation.[7, 14, 18, 21, 22]
One interesting finding was that only 5% of interns rated the notes of other housestaff as fair or poor. One possible explanation for this may be the tendency for an individual to enhance or augment the status or performance of the group to which he or she belongs as a mechanism to increase self‐image, known as the social identity theory.[23] Thus, housestaff may not criticize their peers to allow for identification with a group that is not deficient in note writing.
The more positive assessment of overall note quality among housestaff could be related to the different roles of housestaff and attendings on a teaching service. On a teaching service, housestaff are typically the writer, whereas attendings are almost exclusively the reader of progress notes. Housestaff may reap benefits, including efficiency, beyond the finished product. A perception of higher quality may reflect the process of note writing, data gathering, and critical thinking required to build an assessment and plan. The scores on the PDQI‐9 support this notion, as housestaff rated all 9 domains significantly higher than attendings.
Housestaff and attendings held greater differences of opinion with respect to the EHR's impact on note quality. Generally, housestaff perceived the EHR to have improved progress note quality, whereas attendings perceived the opposite. One explanation could be that these results reflect changing stages of development of physicians well described through the RIME framework (reporter, interpreter, manager, educator). Attendings may expect notes to reflect synthesis and analysis, whereas trainees may be satisfied with the data gathering that an EHR facilitates. In our survey, the trend of answers from intern to resident to attending suggests an evolving process of attitudes toward note quality.
The above reasons may also explain why housestaff were generally more positive than attendings about the effect of copy forward and autopopulation functions on critical thinking. Perhaps, as these functions can potentially increase efficiency and decrease time spent at the computer, although data are mixed on this finding, housestaff may have more time to spend with patients or develop a thorough plan and thus rate these functions positively.
Notably, housestaff and attendings had excellent agreement on the purposes of a progress note. They agreed that the 2 most important purposes were communication with other providers and documenting important events and the plan for the day. These are the 2 listed purposes that are most directly related to patient care. If future interventions to improve note quality require housestaff and attendings to significantly change their behavior, a focus on the impact on patient care might yield the best results.
There were several limitations in our study. Any study based on self‐assessment is subject to bias. A previous meta‐analysis and review described poor to moderate correlations between self‐assessed and external measures of performance.[24, 25] The survey data were aggregated from 4 institutions despite somewhat different, though relatively high, response rates between the institutions. There could be a response bias; those who did not respond may have systematically different perceptions of note quality. It should be noted that the general demographics of the respondents reflected those of the housestaff and attendings at 4 academic centers. All 4 of the participating institutions adopted the Epic EHR within the last several years of the survey being administered, and perceptions of note quality may be biased depending on the prior system used (ie, change from handwritten to electronic vs electronic to other electronic system). In addition, the survey results reflect experience with only 1 EHR, and our results may not apply to other EHR vendors or institutions like the VA, which have a long‐standing system in place. Last, we did not explore the impact of perceived note quality on the measured or perceived quality of care. One previous study found no direct correlation between note quality and clinical quality.[26]
There are several future directions for research based on our findings. First, potential differences between housestaff and attending perceptions of note quality could be further teased apart by studying the perceptions of attendings on a nonteaching service who write their own daily progress notes. Second, housestaff perceptions on why copy forward and autopopulation may increase critical thinking could be explored further with more direct questioning. Finally, although our study captured only perceptions of note quality, validated tools could be used to objectively measure note quality; these measurements could then be compared to perception of note quality as well as clinical outcomes.
Given the prevalence and the apparent belief that the benefits of an EHR outweigh the hazards, institutions should embrace these innovations but take steps to mitigate the potential errors and problems associated with copy forward and autopopulation. The results of our study should help inform future interventions.
Acknowledgements
The authors acknowledge the contributions of Russell Leslie from the University of Iowa.
Disclosure: Nothing to report.
- Systematic review: impact of health information technology on quality, efficiency, and costs of medical care. Ann Intern Med. 2006;144(10):742–752. , , , et al.
- Clinical information technologies and inpatient outcomes: a multiple hospital study. Arch Intern Med. 2009;169(2):108–114. , , , , .
- Effect of computerized physician order entry and a team intervention on prevention of serious medication errors. JAMA. 1998;280(15):1311–1316. , , , et al.
- Electronic health records and quality of diabetes care. N Engl J Med. 2011;365(9):825–833. , , , .
- The impact of a clinical information system in an intensive care unit. J Clin Monit Comput. 2008;22(1):31–36. , , , et al.
- Can electronic clinical documentation help prevent diagnostic errors? N Engl J Med. 2010;362(12):1066–1069. , .
- Off the record—avoiding the pitfalls of going electronic. N Eng J Med. 2008;358(16):1656–1658. , .
- Copying and pasting of examinations within the electronic medical record. Int J Med Inform. 2007;76(suppl 1):S122–S128. , , .
- Copy and paste: a remediable hazard of electronic health records. Am J Med. 2009;122(6):495–496. , .
- The role of copy‐and‐paste in the hospital electronic health record. JAMA Intern Med. 2014;174(8):1217–1218. , , .
- Physicians’ attitudes towards copy and pasting in electronic note writing. J Gen Intern Med. 2009;24(1):63–68. , , , , , .
- Medical education in the electronic medical record (EMR) era: benefits, challenges, and future directions. Acad Med. 2013;88(6):748–752. , , , , .
- Educational impact of the electronic medical record. J Surg Educ. 2012;69(1):105–112. , .
- Direct text entry in electronic progress notes. An evaluation of input errors. Methods Inf Med. 2003;42(1):61–67. , , , , , .
- The clinical record: a 200‐year‐old 21st‐century challenge. Ann Intern Med. 2010;153(10):682–683. .
- http://www.webmm.ahrq.gov/case.aspx?caseID=274. Published July 2012. Accessed September 26, 2014. . Sloppy and paste. Morbidity and Mortality Rounds on the Web. Available at:
- Are electronic medical records trustworthy? Observations on copying, pasting and duplication. AMIA Annu Symp Proc. 2003:269–273. , , , .
- A piece of my mind. John Lennon's elbow. JAMA. 2012;308(5):463–464. .
- Research electronic data capture (REDCap)—a metadata‐driven methodology and workflow process for providing translational research informatics support. J Biomed Inform. 2009;42(2):377–381. , , , , , .
- http://www.im.org/p/cm/ld/fid=831. Accessed August 8, 2013. , , . ACGME competency note checklist. Available at:
- Assessing electronic note quality using the Physician Documentation Quality Instrument (PDQI‐9). Appl Clin Inform. 2012;3(2):164–174. , , , .
- Quantifying clinical narrative redundancy in an electronic health record. J Am Med Inform Assoc. 2010;17(1):49–53. , , , .
- The social identity theory of intergroup behavior. In: Psychology of Intergroup Relations. 2nd ed. Chicago, IL: Nelson‐Hall Publishers; 1986:7–24. , .
- Student self‐assessment in higher education: a meta‐analysis. Rev Educ Res. 1989;59:395–430. , .
- A review of the validity and accuracy of self‐assessments in health professions training. Acad Med. 1991;66:762–769. .
- Association of note quality and quality of care: a cross‐sectional study. BMJ Qual Saf. 2014;23(5):406–413. , , , , .
The electronic health record (EHR) has revolutionized the practice of medicine. As part of the economic stimulus package in 2009, Congress enacted the Health Information Technology for Economic and Clinical Health Act, which included incentives for physicians and hospitals to adopt an EHR by 2015. In the setting of more limited duty hours and demands for increased clinical productivity, EHRs have functions that may improve the quality and efficiency of clinical documentation.[1, 2, 3, 4, 5]
The process of note writing and the use of notes for clinical care have changed substantially with EHR implementation. Use of efficiency tools (ie, copy forward functions and autopopulation of data) may increase the speed of documentation.[5] Notes in an EHR are more legible and accessible and may be able to organize data to improve clinical care.[6]
Yet, many have commented on the negative consequences of documentation in an EHR. In a New England Journal of Medicine Perspective article, Drs. Hartzband and Groopman wrote, we have observed the electronic medical record become a powerful vehicle for perpetuating erroneous information, leading to diagnostic errors that gain momentum when passed on electronically.[7] As a result, the copy forward and autopopulation functions have come under significant scrutiny.[8, 9, 10] A survey conducted at 2 academic institutions found that 71% of residents and attendings believed that the copy forward function led to inconsistencies and outdated information.[11] Autopopulation has been criticized for creating lengthy notes full of trivial or redundant data, a phenomenon termed note bloat. Bloated notes may be less effective as a communication tool.[12] Additionally, the process of composing a note often stimulates critical thinking and may lead to changes in care. The act of copying forward a previous note and autopopulating data bypasses that process and in effect may suppress critical thinking.[13] Previous studies have raised numerous concerns regarding copy forward and autopopulation functionality in the EHR. Many have described the duplication of outdated data and the possibility of the introduction and perpetuation of errors.[14, 15, 16] The Veterans Affairs (VA) Puget Sound Health system evaluated 6322 copy events and found that 1 in 10 electronic patient charts contained an instance of high‐risk copying.[17] In a survey of faculty and residents at a single academic medical center, the majority of users of copy and paste functionality recognized the hazards; they responded that their notes may contain more outdated (66%) and more inconsistent information (69%). Yet, most felt copy forwarding improved the documentation of the entire hospital course (87%), overall physician documentation (69%), and should definitely be continued (91%).[11] Others have complained about the impact of copy forward on the expression of clinical reasoning.[7, 9, 18]
Previous discussions on the topic of overall note quality following EHR implementation have been limited to perspectives or opinion pieces of individual attending providers.[18] We conducted a survey across 4 academic institutions to analyze both housestaff and attendings perceptions of the quality of notes since the implementation of an EHR to better inform the discussion of the impact of an EHR on note quality.
METHODS
Participants
Surveys were administered via email to interns, residents (second‐, third‐, or fourth‐year residents, hereafter referred to as residents) and attendings at 4 academic hospitals that use the Epic EHR (Epic Corp., Madison, WI). The 4 institutions each adopted the Epic EHR, with mandatory faculty and resident training, between 1 and 5 years prior to the survey. Three of the institutions previously used systems with electronic notes, whereas the fourth institution previously used a system with handwritten notes. The study participation emails included a link to an online survey in REDCap.[19] We included interns and residents from the following types of residency programs: internal medicine categorical or primary care, medicine‐pediatrics, or medicine‐psychiatry. For housestaff (the combination of both interns and residents), exclusion criteria included preliminary or transitional year interns, or any interns or residents from other specialties who rotate on the medicine service. For attendings, participants included hospitalists, general internal medicine attendings, chief residents, and subspecialty medicine attendings, each of whom had worked for any amount of time on the inpatient medicine teaching service in the prior 12 months.
Design
We developed 3 unique surveys for interns, residents, and attendings to assess their perception of inpatient progress notes (see Supporting Information, Appendix, in the online version of this article). The surveys incorporated questions from 2 previously published sources, the 9‐item Physician Documentation Quality Instrument (PDQI‐9) (see online Appendix), a validated note‐scoring tool, and the Accreditation Council for Graduate Medical Education note‐writing competency checklists.[20] Additionally, faculty at the participating institutions developed questions to address practices and attitudes toward autopopulation, copy forward, and the purposes of a progress note. Responses were based on a 5‐point Likert scale. The intern and resident surveys asked for self‐evaluation of their own progress notes and those of their peers, whereas the attending surveys asked for assessment of housestaff notes.
The survey was left open for a total of 55 days and participants were sent reminder emails. The study received a waiver from the institutional review board at all 4 institutions.
Data Analysis
Study data were collected and managed using REDCap electronic data capture tools hosted at the University of California, San Francisco (UCSF).[19] The survey data were analyzed and the figures were created using Microsoft Excel 2008 (Microsoft Corp., Redmond, WA). Mean values for each survey question were calculated. Differences between the means among the groups were assessed using 2‐sample t tests. P values <0.05 were considered statistically significant.
RESULTS
Demographics
We received 99 completed surveys from interns, 155 completed surveys from residents, and 153 completed surveys from attendings across the 4 institutions. The overall response rate for interns was 68%, ranging from 59% at the University of California, San Diego (UCSD) to 74% at the University of Iowa. The overall response rate for residents was 49%, ranging from 38% at UCSF to 66% at the University of California, Los Angeles. The overall response rate for attendings was 70%, ranging from 53% at UCSD to 74% at UCSF.
A total of 78% of interns and 72% of residents had used an EHR at a prior institution. Of the residents, 90 were second‐year residents, 64 were third‐year residents, and 2 were fourth‐year residents. A total of 76% of attendings self‐identified as hospitalists.
Overall Assessment of Note Quality
Participants were asked to rate the quality of progress notes on a 5‐point scale (poor, fair, good, very good, excellent). Half of interns and residents rated their own progress notes as very good or excellent. A total of 44% percent of interns and 24% of residents rated their peers notes as very good or excellent, whereas only 15% of attending physicians rated housestaff notes as very good or excellent.
When asked to rate the change in progress note quality since their hospital had adopted the EHR, the majority of residents answered unchanged or better, and the majority of attendings answered unchanged or worse (Figure 1).

PDQI‐9 Framework
Participants answered each PDQI‐9 question on a 5‐point Likert scale ranging from not at all (1) to extremely (5). In 8 of the 9 PDQI‐9 domains, there were no significant differences between interns and residents. Across each domain, attending perceptions of housestaff notes were significantly lower than housestaff perceptions of their own notes (P<0.001) (Figure 2). Both housestaff and attendings gave the highest ratings to thorough, up to date, and synthesized and the lowest rating to succinct.

Copy Forward and Autopopulation
Overall, the effect of copy forward and autopopulation on critical thinking, note accuracy, and prioritizing the problem list was thought to be neutral or somewhat positive by interns, neutral by residents, and neutral or somewhat negative by attendings (P<0.001) (Figure 3). In all, 16% of interns, 22% of residents, and 55% of attendings reported that copy forward had a somewhat negative or very negative impact on critical thinking (P<0.001). In all, 16% of interns, 29% of residents and 39% of attendings thought that autopopulation had a somewhat negative or very negative impact on critical thinking (P<0.001).

Purpose of Progress Notes
Participants were provided with 7 possible purposes of a progress note and asked to rate the importance of each stated purpose. There was nearly perfect agreement between interns, residents, and attendings in the rank order of the importance of each purpose of a progress note (Table 1). Attendings and housestaff ranked communication with other providers and documenting important events and the plan for the day as the 2 most important purposes of a progress note, and billing and quality improvement as less important.
Interns | Residents | Attendings | |
---|---|---|---|
Communication with other providers | 1 | 1 | 2 |
Documenting important events and the plan for the day | 2 | 2 | 1 |
Prioritizing issues going forward in the patient's care | 3 | 3 | 3 |
Medicolegal | 4 | 4 | 4 |
Stimulate critical thinking | 5 | 5 | 5 |
Billing | 6 | 6 | 6 |
Quality improvement | 7 | 7 | 7 |
DISCUSSION
This is the first large multicenter analysis of both attendings and housestaff perceptions of note quality in the EHR era. The findings provide insight into important differences and similarities in the perceptions of the 2 groups. Most striking is the difference in opinion of overall note quality, with only a small minority of faculty rating current housestaff notes as very good or excellent, whereas a much larger proportion of housestaff rated their own notes and those of their peers to be of high quality. Though participants were not specifically asked why note quality in general was suboptimal, housestaff and faculty rankings of specific domains from the PDQI‐9 may yield an important clue. Specifically, all groups expressed that the weakest attribute of current progress notes is succinct. This finding is consistent with the note bloat phenomenon, which has been maligned as a consequence of EHR implementation.[7, 14, 18, 21, 22]
One interesting finding was that only 5% of interns rated the notes of other housestaff as fair or poor. One possible explanation for this may be the tendency for an individual to enhance or augment the status or performance of the group to which he or she belongs as a mechanism to increase self‐image, known as the social identity theory.[23] Thus, housestaff may not criticize their peers to allow for identification with a group that is not deficient in note writing.
The more positive assessment of overall note quality among housestaff could be related to the different roles of housestaff and attendings on a teaching service. On a teaching service, housestaff are typically the writer, whereas attendings are almost exclusively the reader of progress notes. Housestaff may reap benefits, including efficiency, beyond the finished product. A perception of higher quality may reflect the process of note writing, data gathering, and critical thinking required to build an assessment and plan. The scores on the PDQI‐9 support this notion, as housestaff rated all 9 domains significantly higher than attendings.
Housestaff and attendings held greater differences of opinion with respect to the EHR's impact on note quality. Generally, housestaff perceived the EHR to have improved progress note quality, whereas attendings perceived the opposite. One explanation could be that these results reflect changing stages of development of physicians well described through the RIME framework (reporter, interpreter, manager, educator). Attendings may expect notes to reflect synthesis and analysis, whereas trainees may be satisfied with the data gathering that an EHR facilitates. In our survey, the trend of answers from intern to resident to attending suggests an evolving process of attitudes toward note quality.
The above reasons may also explain why housestaff were generally more positive than attendings about the effect of copy forward and autopopulation functions on critical thinking. Perhaps, as these functions can potentially increase efficiency and decrease time spent at the computer, although data are mixed on this finding, housestaff may have more time to spend with patients or develop a thorough plan and thus rate these functions positively.
Notably, housestaff and attendings had excellent agreement on the purposes of a progress note. They agreed that the 2 most important purposes were communication with other providers and documenting important events and the plan for the day. These are the 2 listed purposes that are most directly related to patient care. If future interventions to improve note quality require housestaff and attendings to significantly change their behavior, a focus on the impact on patient care might yield the best results.
There were several limitations in our study. Any study based on self‐assessment is subject to bias. A previous meta‐analysis and review described poor to moderate correlations between self‐assessed and external measures of performance.[24, 25] The survey data were aggregated from 4 institutions despite somewhat different, though relatively high, response rates between the institutions. There could be a response bias; those who did not respond may have systematically different perceptions of note quality. It should be noted that the general demographics of the respondents reflected those of the housestaff and attendings at 4 academic centers. All 4 of the participating institutions adopted the Epic EHR within the last several years of the survey being administered, and perceptions of note quality may be biased depending on the prior system used (ie, change from handwritten to electronic vs electronic to other electronic system). In addition, the survey results reflect experience with only 1 EHR, and our results may not apply to other EHR vendors or institutions like the VA, which have a long‐standing system in place. Last, we did not explore the impact of perceived note quality on the measured or perceived quality of care. One previous study found no direct correlation between note quality and clinical quality.[26]
There are several future directions for research based on our findings. First, potential differences between housestaff and attending perceptions of note quality could be further teased apart by studying the perceptions of attendings on a nonteaching service who write their own daily progress notes. Second, housestaff perceptions on why copy forward and autopopulation may increase critical thinking could be explored further with more direct questioning. Finally, although our study captured only perceptions of note quality, validated tools could be used to objectively measure note quality; these measurements could then be compared to perception of note quality as well as clinical outcomes.
Given the prevalence and the apparent belief that the benefits of an EHR outweigh the hazards, institutions should embrace these innovations but take steps to mitigate the potential errors and problems associated with copy forward and autopopulation. The results of our study should help inform future interventions.
Acknowledgements
The authors acknowledge the contributions of Russell Leslie from the University of Iowa.
Disclosure: Nothing to report.
The electronic health record (EHR) has revolutionized the practice of medicine. As part of the economic stimulus package in 2009, Congress enacted the Health Information Technology for Economic and Clinical Health Act, which included incentives for physicians and hospitals to adopt an EHR by 2015. In the setting of more limited duty hours and demands for increased clinical productivity, EHRs have functions that may improve the quality and efficiency of clinical documentation.[1, 2, 3, 4, 5]
The process of note writing and the use of notes for clinical care have changed substantially with EHR implementation. Use of efficiency tools (ie, copy forward functions and autopopulation of data) may increase the speed of documentation.[5] Notes in an EHR are more legible and accessible and may be able to organize data to improve clinical care.[6]
Yet, many have commented on the negative consequences of documentation in an EHR. In a New England Journal of Medicine Perspective article, Drs. Hartzband and Groopman wrote, we have observed the electronic medical record become a powerful vehicle for perpetuating erroneous information, leading to diagnostic errors that gain momentum when passed on electronically.[7] As a result, the copy forward and autopopulation functions have come under significant scrutiny.[8, 9, 10] A survey conducted at 2 academic institutions found that 71% of residents and attendings believed that the copy forward function led to inconsistencies and outdated information.[11] Autopopulation has been criticized for creating lengthy notes full of trivial or redundant data, a phenomenon termed note bloat. Bloated notes may be less effective as a communication tool.[12] Additionally, the process of composing a note often stimulates critical thinking and may lead to changes in care. The act of copying forward a previous note and autopopulating data bypasses that process and in effect may suppress critical thinking.[13] Previous studies have raised numerous concerns regarding copy forward and autopopulation functionality in the EHR. Many have described the duplication of outdated data and the possibility of the introduction and perpetuation of errors.[14, 15, 16] The Veterans Affairs (VA) Puget Sound Health system evaluated 6322 copy events and found that 1 in 10 electronic patient charts contained an instance of high‐risk copying.[17] In a survey of faculty and residents at a single academic medical center, the majority of users of copy and paste functionality recognized the hazards; they responded that their notes may contain more outdated (66%) and more inconsistent information (69%). Yet, most felt copy forwarding improved the documentation of the entire hospital course (87%), overall physician documentation (69%), and should definitely be continued (91%).[11] Others have complained about the impact of copy forward on the expression of clinical reasoning.[7, 9, 18]
Previous discussions on the topic of overall note quality following EHR implementation have been limited to perspectives or opinion pieces of individual attending providers.[18] We conducted a survey across 4 academic institutions to analyze both housestaff and attendings perceptions of the quality of notes since the implementation of an EHR to better inform the discussion of the impact of an EHR on note quality.
METHODS
Participants
Surveys were administered via email to interns, residents (second‐, third‐, or fourth‐year residents, hereafter referred to as residents) and attendings at 4 academic hospitals that use the Epic EHR (Epic Corp., Madison, WI). The 4 institutions each adopted the Epic EHR, with mandatory faculty and resident training, between 1 and 5 years prior to the survey. Three of the institutions previously used systems with electronic notes, whereas the fourth institution previously used a system with handwritten notes. The study participation emails included a link to an online survey in REDCap.[19] We included interns and residents from the following types of residency programs: internal medicine categorical or primary care, medicine‐pediatrics, or medicine‐psychiatry. For housestaff (the combination of both interns and residents), exclusion criteria included preliminary or transitional year interns, or any interns or residents from other specialties who rotate on the medicine service. For attendings, participants included hospitalists, general internal medicine attendings, chief residents, and subspecialty medicine attendings, each of whom had worked for any amount of time on the inpatient medicine teaching service in the prior 12 months.
Design
We developed 3 unique surveys for interns, residents, and attendings to assess their perception of inpatient progress notes (see Supporting Information, Appendix, in the online version of this article). The surveys incorporated questions from 2 previously published sources, the 9‐item Physician Documentation Quality Instrument (PDQI‐9) (see online Appendix), a validated note‐scoring tool, and the Accreditation Council for Graduate Medical Education note‐writing competency checklists.[20] Additionally, faculty at the participating institutions developed questions to address practices and attitudes toward autopopulation, copy forward, and the purposes of a progress note. Responses were based on a 5‐point Likert scale. The intern and resident surveys asked for self‐evaluation of their own progress notes and those of their peers, whereas the attending surveys asked for assessment of housestaff notes.
The survey was left open for a total of 55 days and participants were sent reminder emails. The study received a waiver from the institutional review board at all 4 institutions.
Data Analysis
Study data were collected and managed using REDCap electronic data capture tools hosted at the University of California, San Francisco (UCSF).[19] The survey data were analyzed and the figures were created using Microsoft Excel 2008 (Microsoft Corp., Redmond, WA). Mean values for each survey question were calculated. Differences between the means among the groups were assessed using 2‐sample t tests. P values <0.05 were considered statistically significant.
RESULTS
Demographics
We received 99 completed surveys from interns, 155 completed surveys from residents, and 153 completed surveys from attendings across the 4 institutions. The overall response rate for interns was 68%, ranging from 59% at the University of California, San Diego (UCSD) to 74% at the University of Iowa. The overall response rate for residents was 49%, ranging from 38% at UCSF to 66% at the University of California, Los Angeles. The overall response rate for attendings was 70%, ranging from 53% at UCSD to 74% at UCSF.
A total of 78% of interns and 72% of residents had used an EHR at a prior institution. Of the residents, 90 were second‐year residents, 64 were third‐year residents, and 2 were fourth‐year residents. A total of 76% of attendings self‐identified as hospitalists.
Overall Assessment of Note Quality
Participants were asked to rate the quality of progress notes on a 5‐point scale (poor, fair, good, very good, excellent). Half of interns and residents rated their own progress notes as very good or excellent. A total of 44% percent of interns and 24% of residents rated their peers notes as very good or excellent, whereas only 15% of attending physicians rated housestaff notes as very good or excellent.
When asked to rate the change in progress note quality since their hospital had adopted the EHR, the majority of residents answered unchanged or better, and the majority of attendings answered unchanged or worse (Figure 1).

PDQI‐9 Framework
Participants answered each PDQI‐9 question on a 5‐point Likert scale ranging from not at all (1) to extremely (5). In 8 of the 9 PDQI‐9 domains, there were no significant differences between interns and residents. Across each domain, attending perceptions of housestaff notes were significantly lower than housestaff perceptions of their own notes (P<0.001) (Figure 2). Both housestaff and attendings gave the highest ratings to thorough, up to date, and synthesized and the lowest rating to succinct.

Copy Forward and Autopopulation
Overall, the effect of copy forward and autopopulation on critical thinking, note accuracy, and prioritizing the problem list was thought to be neutral or somewhat positive by interns, neutral by residents, and neutral or somewhat negative by attendings (P<0.001) (Figure 3). In all, 16% of interns, 22% of residents, and 55% of attendings reported that copy forward had a somewhat negative or very negative impact on critical thinking (P<0.001). In all, 16% of interns, 29% of residents and 39% of attendings thought that autopopulation had a somewhat negative or very negative impact on critical thinking (P<0.001).

Purpose of Progress Notes
Participants were provided with 7 possible purposes of a progress note and asked to rate the importance of each stated purpose. There was nearly perfect agreement between interns, residents, and attendings in the rank order of the importance of each purpose of a progress note (Table 1). Attendings and housestaff ranked communication with other providers and documenting important events and the plan for the day as the 2 most important purposes of a progress note, and billing and quality improvement as less important.
Interns | Residents | Attendings | |
---|---|---|---|
Communication with other providers | 1 | 1 | 2 |
Documenting important events and the plan for the day | 2 | 2 | 1 |
Prioritizing issues going forward in the patient's care | 3 | 3 | 3 |
Medicolegal | 4 | 4 | 4 |
Stimulate critical thinking | 5 | 5 | 5 |
Billing | 6 | 6 | 6 |
Quality improvement | 7 | 7 | 7 |
DISCUSSION
This is the first large multicenter analysis of both attendings and housestaff perceptions of note quality in the EHR era. The findings provide insight into important differences and similarities in the perceptions of the 2 groups. Most striking is the difference in opinion of overall note quality, with only a small minority of faculty rating current housestaff notes as very good or excellent, whereas a much larger proportion of housestaff rated their own notes and those of their peers to be of high quality. Though participants were not specifically asked why note quality in general was suboptimal, housestaff and faculty rankings of specific domains from the PDQI‐9 may yield an important clue. Specifically, all groups expressed that the weakest attribute of current progress notes is succinct. This finding is consistent with the note bloat phenomenon, which has been maligned as a consequence of EHR implementation.[7, 14, 18, 21, 22]
One interesting finding was that only 5% of interns rated the notes of other housestaff as fair or poor. One possible explanation for this may be the tendency for an individual to enhance or augment the status or performance of the group to which he or she belongs as a mechanism to increase self‐image, known as the social identity theory.[23] Thus, housestaff may not criticize their peers to allow for identification with a group that is not deficient in note writing.
The more positive assessment of overall note quality among housestaff could be related to the different roles of housestaff and attendings on a teaching service. On a teaching service, housestaff are typically the writer, whereas attendings are almost exclusively the reader of progress notes. Housestaff may reap benefits, including efficiency, beyond the finished product. A perception of higher quality may reflect the process of note writing, data gathering, and critical thinking required to build an assessment and plan. The scores on the PDQI‐9 support this notion, as housestaff rated all 9 domains significantly higher than attendings.
Housestaff and attendings held greater differences of opinion with respect to the EHR's impact on note quality. Generally, housestaff perceived the EHR to have improved progress note quality, whereas attendings perceived the opposite. One explanation could be that these results reflect changing stages of development of physicians well described through the RIME framework (reporter, interpreter, manager, educator). Attendings may expect notes to reflect synthesis and analysis, whereas trainees may be satisfied with the data gathering that an EHR facilitates. In our survey, the trend of answers from intern to resident to attending suggests an evolving process of attitudes toward note quality.
The above reasons may also explain why housestaff were generally more positive than attendings about the effect of copy forward and autopopulation functions on critical thinking. Perhaps, as these functions can potentially increase efficiency and decrease time spent at the computer, although data are mixed on this finding, housestaff may have more time to spend with patients or develop a thorough plan and thus rate these functions positively.
Notably, housestaff and attendings had excellent agreement on the purposes of a progress note. They agreed that the 2 most important purposes were communication with other providers and documenting important events and the plan for the day. These are the 2 listed purposes that are most directly related to patient care. If future interventions to improve note quality require housestaff and attendings to significantly change their behavior, a focus on the impact on patient care might yield the best results.
There were several limitations in our study. Any study based on self‐assessment is subject to bias. A previous meta‐analysis and review described poor to moderate correlations between self‐assessed and external measures of performance.[24, 25] The survey data were aggregated from 4 institutions despite somewhat different, though relatively high, response rates between the institutions. There could be a response bias; those who did not respond may have systematically different perceptions of note quality. It should be noted that the general demographics of the respondents reflected those of the housestaff and attendings at 4 academic centers. All 4 of the participating institutions adopted the Epic EHR within the last several years of the survey being administered, and perceptions of note quality may be biased depending on the prior system used (ie, change from handwritten to electronic vs electronic to other electronic system). In addition, the survey results reflect experience with only 1 EHR, and our results may not apply to other EHR vendors or institutions like the VA, which have a long‐standing system in place. Last, we did not explore the impact of perceived note quality on the measured or perceived quality of care. One previous study found no direct correlation between note quality and clinical quality.[26]
There are several future directions for research based on our findings. First, potential differences between housestaff and attending perceptions of note quality could be further teased apart by studying the perceptions of attendings on a nonteaching service who write their own daily progress notes. Second, housestaff perceptions on why copy forward and autopopulation may increase critical thinking could be explored further with more direct questioning. Finally, although our study captured only perceptions of note quality, validated tools could be used to objectively measure note quality; these measurements could then be compared to perception of note quality as well as clinical outcomes.
Given the prevalence and the apparent belief that the benefits of an EHR outweigh the hazards, institutions should embrace these innovations but take steps to mitigate the potential errors and problems associated with copy forward and autopopulation. The results of our study should help inform future interventions.
Acknowledgements
The authors acknowledge the contributions of Russell Leslie from the University of Iowa.
Disclosure: Nothing to report.
- Systematic review: impact of health information technology on quality, efficiency, and costs of medical care. Ann Intern Med. 2006;144(10):742–752. , , , et al.
- Clinical information technologies and inpatient outcomes: a multiple hospital study. Arch Intern Med. 2009;169(2):108–114. , , , , .
- Effect of computerized physician order entry and a team intervention on prevention of serious medication errors. JAMA. 1998;280(15):1311–1316. , , , et al.
- Electronic health records and quality of diabetes care. N Engl J Med. 2011;365(9):825–833. , , , .
- The impact of a clinical information system in an intensive care unit. J Clin Monit Comput. 2008;22(1):31–36. , , , et al.
- Can electronic clinical documentation help prevent diagnostic errors? N Engl J Med. 2010;362(12):1066–1069. , .
- Off the record—avoiding the pitfalls of going electronic. N Eng J Med. 2008;358(16):1656–1658. , .
- Copying and pasting of examinations within the electronic medical record. Int J Med Inform. 2007;76(suppl 1):S122–S128. , , .
- Copy and paste: a remediable hazard of electronic health records. Am J Med. 2009;122(6):495–496. , .
- The role of copy‐and‐paste in the hospital electronic health record. JAMA Intern Med. 2014;174(8):1217–1218. , , .
- Physicians’ attitudes towards copy and pasting in electronic note writing. J Gen Intern Med. 2009;24(1):63–68. , , , , , .
- Medical education in the electronic medical record (EMR) era: benefits, challenges, and future directions. Acad Med. 2013;88(6):748–752. , , , , .
- Educational impact of the electronic medical record. J Surg Educ. 2012;69(1):105–112. , .
- Direct text entry in electronic progress notes. An evaluation of input errors. Methods Inf Med. 2003;42(1):61–67. , , , , , .
- The clinical record: a 200‐year‐old 21st‐century challenge. Ann Intern Med. 2010;153(10):682–683. .
- http://www.webmm.ahrq.gov/case.aspx?caseID=274. Published July 2012. Accessed September 26, 2014. . Sloppy and paste. Morbidity and Mortality Rounds on the Web. Available at:
- Are electronic medical records trustworthy? Observations on copying, pasting and duplication. AMIA Annu Symp Proc. 2003:269–273. , , , .
- A piece of my mind. John Lennon's elbow. JAMA. 2012;308(5):463–464. .
- Research electronic data capture (REDCap)—a metadata‐driven methodology and workflow process for providing translational research informatics support. J Biomed Inform. 2009;42(2):377–381. , , , , , .
- http://www.im.org/p/cm/ld/fid=831. Accessed August 8, 2013. , , . ACGME competency note checklist. Available at:
- Assessing electronic note quality using the Physician Documentation Quality Instrument (PDQI‐9). Appl Clin Inform. 2012;3(2):164–174. , , , .
- Quantifying clinical narrative redundancy in an electronic health record. J Am Med Inform Assoc. 2010;17(1):49–53. , , , .
- The social identity theory of intergroup behavior. In: Psychology of Intergroup Relations. 2nd ed. Chicago, IL: Nelson‐Hall Publishers; 1986:7–24. , .
- Student self‐assessment in higher education: a meta‐analysis. Rev Educ Res. 1989;59:395–430. , .
- A review of the validity and accuracy of self‐assessments in health professions training. Acad Med. 1991;66:762–769. .
- Association of note quality and quality of care: a cross‐sectional study. BMJ Qual Saf. 2014;23(5):406–413. , , , , .
- Systematic review: impact of health information technology on quality, efficiency, and costs of medical care. Ann Intern Med. 2006;144(10):742–752. , , , et al.
- Clinical information technologies and inpatient outcomes: a multiple hospital study. Arch Intern Med. 2009;169(2):108–114. , , , , .
- Effect of computerized physician order entry and a team intervention on prevention of serious medication errors. JAMA. 1998;280(15):1311–1316. , , , et al.
- Electronic health records and quality of diabetes care. N Engl J Med. 2011;365(9):825–833. , , , .
- The impact of a clinical information system in an intensive care unit. J Clin Monit Comput. 2008;22(1):31–36. , , , et al.
- Can electronic clinical documentation help prevent diagnostic errors? N Engl J Med. 2010;362(12):1066–1069. , .
- Off the record—avoiding the pitfalls of going electronic. N Eng J Med. 2008;358(16):1656–1658. , .
- Copying and pasting of examinations within the electronic medical record. Int J Med Inform. 2007;76(suppl 1):S122–S128. , , .
- Copy and paste: a remediable hazard of electronic health records. Am J Med. 2009;122(6):495–496. , .
- The role of copy‐and‐paste in the hospital electronic health record. JAMA Intern Med. 2014;174(8):1217–1218. , , .
- Physicians’ attitudes towards copy and pasting in electronic note writing. J Gen Intern Med. 2009;24(1):63–68. , , , , , .
- Medical education in the electronic medical record (EMR) era: benefits, challenges, and future directions. Acad Med. 2013;88(6):748–752. , , , , .
- Educational impact of the electronic medical record. J Surg Educ. 2012;69(1):105–112. , .
- Direct text entry in electronic progress notes. An evaluation of input errors. Methods Inf Med. 2003;42(1):61–67. , , , , , .
- The clinical record: a 200‐year‐old 21st‐century challenge. Ann Intern Med. 2010;153(10):682–683. .
- http://www.webmm.ahrq.gov/case.aspx?caseID=274. Published July 2012. Accessed September 26, 2014. . Sloppy and paste. Morbidity and Mortality Rounds on the Web. Available at:
- Are electronic medical records trustworthy? Observations on copying, pasting and duplication. AMIA Annu Symp Proc. 2003:269–273. , , , .
- A piece of my mind. John Lennon's elbow. JAMA. 2012;308(5):463–464. .
- Research electronic data capture (REDCap)—a metadata‐driven methodology and workflow process for providing translational research informatics support. J Biomed Inform. 2009;42(2):377–381. , , , , , .
- http://www.im.org/p/cm/ld/fid=831. Accessed August 8, 2013. , , . ACGME competency note checklist. Available at:
- Assessing electronic note quality using the Physician Documentation Quality Instrument (PDQI‐9). Appl Clin Inform. 2012;3(2):164–174. , , , .
- Quantifying clinical narrative redundancy in an electronic health record. J Am Med Inform Assoc. 2010;17(1):49–53. , , , .
- The social identity theory of intergroup behavior. In: Psychology of Intergroup Relations. 2nd ed. Chicago, IL: Nelson‐Hall Publishers; 1986:7–24. , .
- Student self‐assessment in higher education: a meta‐analysis. Rev Educ Res. 1989;59:395–430. , .
- A review of the validity and accuracy of self‐assessments in health professions training. Acad Med. 1991;66:762–769. .
- Association of note quality and quality of care: a cross‐sectional study. BMJ Qual Saf. 2014;23(5):406–413. , , , , .
© 2015 Society of Hospital Medicine
Clonal hematopoiesis explored in aplastic anemia
Clonal hematopoiesis was detected in DNA samples from approximately half of 439 patients with aplastic anemia, and a third of the study population carried mutations in candidate genes that correlated with clinical outcomes, according to a report published online July 2 in the New England Journal of Medicine.
Most patients with aplastic anemia respond to immunosuppressive therapy or bone marrow transplantation, but about 15% later develop myelodysplastic syndromes, acute myeloid leukemia (AML), or both. Historically, this has been attributed to “clonal evolution,” but a more accurate term is clonal hematopoiesis. However, not all patients with clonal hematopoiesis go on to develop late myelodysplastic syndromes or AML, said Dr. Tetsuichi Yoshizato of the department of pathology and tumor biology at Kyoto (Japan) University and associates.
To clarify the role of clonal hematopoiesis in aplastic anemia, the investigators analyzed DNA in blood, bone marrow, and buccal samples from 439 patients with bone marrow failure who were treated at three specialized centers in the United States and Japan.
Targeted sequencing of a panel of genes that are recurrently mutated in myeloid cancers was performed; 249 mutations were detected in candidate genes for myelodysplastic syndromes/AML in 36% of the study population. And about one-third of patients whose DNA harbored mutations had multiple (as many as 7) mutations. The most frequently mutated genes were BCOR and BCORL1 (in 9.3% of patients), PIGA (7.5%), DNMT3A (8.4%), and ASXL1 (6.2%), which together accounted for 77% of all mutation-positive patients, the investigators reported.
In addition, 47% of patients had expanded hematopoietic cell clones. Clones carrying certain mutations were associated with a better response to immunosuppressive treatment, while clones carrying several other mutations were associated with a poor treatment response, lower survival, and progression to myelodysplastic syndromes/AML. Mutations in PIGA and BCOR and BCORL1 correlated with a better response to immunosuppressive therapy and better overall and progression-free survival; mutations in a subgroup of genes that included DNMT3A and ASXL1 were associated with worse outcomes.
The pattern of mutations in individual patients, however, varied markedly over time and was often unpredictable. “It should be underscored that the complex dynamics of clonal hematopoiesis are highly variable and not necessarily determinative,” Dr. Yoshizato and associates said (N. Engl. J. Med. 2015 July 2 [doi:10.1056/NEJMoa1414799]).
Although further genetic research is needed before these findings can be applied clinically to guide prognosis and treatment, they already “have implications for bone marrow failure, for early events in leukemogenesis, and for normal aging,” the investigators added.
Clonal hematopoiesis was detected in DNA samples from approximately half of 439 patients with aplastic anemia, and a third of the study population carried mutations in candidate genes that correlated with clinical outcomes, according to a report published online July 2 in the New England Journal of Medicine.
Most patients with aplastic anemia respond to immunosuppressive therapy or bone marrow transplantation, but about 15% later develop myelodysplastic syndromes, acute myeloid leukemia (AML), or both. Historically, this has been attributed to “clonal evolution,” but a more accurate term is clonal hematopoiesis. However, not all patients with clonal hematopoiesis go on to develop late myelodysplastic syndromes or AML, said Dr. Tetsuichi Yoshizato of the department of pathology and tumor biology at Kyoto (Japan) University and associates.
To clarify the role of clonal hematopoiesis in aplastic anemia, the investigators analyzed DNA in blood, bone marrow, and buccal samples from 439 patients with bone marrow failure who were treated at three specialized centers in the United States and Japan.
Targeted sequencing of a panel of genes that are recurrently mutated in myeloid cancers was performed; 249 mutations were detected in candidate genes for myelodysplastic syndromes/AML in 36% of the study population. And about one-third of patients whose DNA harbored mutations had multiple (as many as 7) mutations. The most frequently mutated genes were BCOR and BCORL1 (in 9.3% of patients), PIGA (7.5%), DNMT3A (8.4%), and ASXL1 (6.2%), which together accounted for 77% of all mutation-positive patients, the investigators reported.
In addition, 47% of patients had expanded hematopoietic cell clones. Clones carrying certain mutations were associated with a better response to immunosuppressive treatment, while clones carrying several other mutations were associated with a poor treatment response, lower survival, and progression to myelodysplastic syndromes/AML. Mutations in PIGA and BCOR and BCORL1 correlated with a better response to immunosuppressive therapy and better overall and progression-free survival; mutations in a subgroup of genes that included DNMT3A and ASXL1 were associated with worse outcomes.
The pattern of mutations in individual patients, however, varied markedly over time and was often unpredictable. “It should be underscored that the complex dynamics of clonal hematopoiesis are highly variable and not necessarily determinative,” Dr. Yoshizato and associates said (N. Engl. J. Med. 2015 July 2 [doi:10.1056/NEJMoa1414799]).
Although further genetic research is needed before these findings can be applied clinically to guide prognosis and treatment, they already “have implications for bone marrow failure, for early events in leukemogenesis, and for normal aging,” the investigators added.
Clonal hematopoiesis was detected in DNA samples from approximately half of 439 patients with aplastic anemia, and a third of the study population carried mutations in candidate genes that correlated with clinical outcomes, according to a report published online July 2 in the New England Journal of Medicine.
Most patients with aplastic anemia respond to immunosuppressive therapy or bone marrow transplantation, but about 15% later develop myelodysplastic syndromes, acute myeloid leukemia (AML), or both. Historically, this has been attributed to “clonal evolution,” but a more accurate term is clonal hematopoiesis. However, not all patients with clonal hematopoiesis go on to develop late myelodysplastic syndromes or AML, said Dr. Tetsuichi Yoshizato of the department of pathology and tumor biology at Kyoto (Japan) University and associates.
To clarify the role of clonal hematopoiesis in aplastic anemia, the investigators analyzed DNA in blood, bone marrow, and buccal samples from 439 patients with bone marrow failure who were treated at three specialized centers in the United States and Japan.
Targeted sequencing of a panel of genes that are recurrently mutated in myeloid cancers was performed; 249 mutations were detected in candidate genes for myelodysplastic syndromes/AML in 36% of the study population. And about one-third of patients whose DNA harbored mutations had multiple (as many as 7) mutations. The most frequently mutated genes were BCOR and BCORL1 (in 9.3% of patients), PIGA (7.5%), DNMT3A (8.4%), and ASXL1 (6.2%), which together accounted for 77% of all mutation-positive patients, the investigators reported.
In addition, 47% of patients had expanded hematopoietic cell clones. Clones carrying certain mutations were associated with a better response to immunosuppressive treatment, while clones carrying several other mutations were associated with a poor treatment response, lower survival, and progression to myelodysplastic syndromes/AML. Mutations in PIGA and BCOR and BCORL1 correlated with a better response to immunosuppressive therapy and better overall and progression-free survival; mutations in a subgroup of genes that included DNMT3A and ASXL1 were associated with worse outcomes.
The pattern of mutations in individual patients, however, varied markedly over time and was often unpredictable. “It should be underscored that the complex dynamics of clonal hematopoiesis are highly variable and not necessarily determinative,” Dr. Yoshizato and associates said (N. Engl. J. Med. 2015 July 2 [doi:10.1056/NEJMoa1414799]).
Although further genetic research is needed before these findings can be applied clinically to guide prognosis and treatment, they already “have implications for bone marrow failure, for early events in leukemogenesis, and for normal aging,” the investigators added.
FROM THE NEW ENGLAND JOURNAL OF MEDICINE
Key clinical point: Clonal hematopoiesis was detected in 47% of 439 patients with aplastic anemia, and some of the mutations were related to clinical outcomes.
Major finding: The most frequently mutated genes were BCOR and BCORL1 (in 9.3% of patients), PIGA (7.5%), DNMT3A (8.4%), and ASXL1 (6.2%), which together accounted for 77% of all mutation-positive patients.
Data source: DNA analysis of blood, bone marrow, and buccal samples from 439 patients with aplastic anemia treated at three medical centers in the United States and Japan.
Disclosures: This work was supported by the Ministry of Health, Labor, and Welfare of Japan; the Japan Society for the Promotion of Science; the National Heart, Lung, and Blood Institute; the Aplastic Anemia and MDS International Foundation; and the Scott Hamilton Cancer Alliance for Research, Education, and Survivorship Foundation. Dr. Yoshizato reported having no relevant financial disclosures; an associate reported receiving a grant from Daiichi-Sankyo unrelated to this work.
It’s time to reconsider early-morning testosterone tests
Early-morning testosterone tests are necessary only for men younger than age 45. Because the natural diurnal variation in testosterone levels tends to diminish with age, it is acceptable to test men ages 45 and older before 2 pm.1
Strength of recommendation
B: Based on a retrospective cohort study.
Welliver RC Jr, Wiser HJ, Brannigan RE, et al. Validity of midday total testosterone levels in older men with erectile dysfunction. J Urol. 2014;192:165-169.
Illustrative case
It’s noon, you are finishing up a visit with a 62-year-old man with erectile dysfunction (ED), and you want to evaluate for androgen deficiency. Should you ask him to return for an early-morning visit so you can test his testosterone level?
Increasing public awareness of androgen deficiency has led to more men being tested for testosterone levels. Current Endocrine Society guidelines recommend against routine screening for androgen deficiency in men who do not have symptoms.2 However, for men with classic symptoms of androgen deficiency—such as decreased libido, ED, infertility, depression, osteoporosis, loss of secondary sexual characteristics, or reduced muscle bulk or strength—measurement of total testosterone level is recommended.2
Due to the natural diurnal variation in serum testosterone levels, the guidelines recommend collecting the sample in the early morning.2 This recommendation is based on small observational studies that included men mostly younger than 45 years of age that found a significant difference in testosterone levels between samples drawn early in the morning and in the afternoon.3-5
In recent years, several studies have indicated that this variation declines as men age.4-6 Recently, researchers evaluated the effects of age and time of testing on men’s total testosterone levels.
STUDY SUMMARY: Differences in testosterone levels are significant only in younger men
Welliver et al1 performed a retrospective chart review of 2569 men seen at a Minneapolis Veterans Affairs hospital for ED who had total testosterone levels measured between 7 am and 2 pm over a 15-year period. Men whose total testosterone levels were outside the normal range (>1000 or <50 ng/dL) or who had total testosterone drawn after 2 pm were excluded. The authors analyzed the results based on age, creating one group for men ages <40 years and 5-year age groups for all other men. Using scatterplot techniques, they separated each age group into 2 subgroups based on draw times—7 am to 9 am, or 9 am to 2 pm—and compared the mean total testosterone level for each age and time.
The participants’ mean age was 63 years. Younger men (<45 years) had the largest variation in serum total testosterone, with a large and significant decrease after 9 am. Only the youngest 2 groups (ages <40 and 40-44 years) showed a large decrease in total testosterone in specimens collected after 9 am compared to those drawn between 7 am and 9 am (mean difference 207 and 149 ng/dL, respectively). This variation was not observed in patients over age 45. Although there was a statistically significant difference between early and later testosterone levels in men ages 70 to 74 years, the absolute difference—34 ng/dL (452 vs 418 ng/dL)—was unlikely to be clinically significant.
WHAT'S NEW: For older men, later testing will not affect results
This study confirms previous research showing that the diurnal effect on testosterone levels becomes blunted with increasing age, at least in this group of men with ED. Allowing older men to have total testosterone levels drawn until 2 pm would allow for greater patient flexibility in draw times with little change in results.
CAVEATS: Study's methodology cannot account for several potential confounders
This retrospective study analyzed only a single random testosterone level measurement from each participant, rather than repeat testosterone levels over the course of a day. However, the study was large (2569 men) and it used mean values, which should at least partially mitigate the effect of having only a single level from each participant.
The study measured total testosterone and did not account for potential confounding factors—such as obesity or use of testosterone replacement therapy or androgen deprivation therapy—that could affect sexhormone binding globulin, thus potentially altering total testosterone level. However, the authors estimated that less than 2% of the entire cohort were likely to have unrecognized hormonal manipulation with exogenous gonadotropins.
All of the men in the study were seen for ED, and it could be that men with ED have more flattening of the diurnal variation than men without ED; however, we are unaware of other data that support this.
Up to 30% of men who have an early-morning testosterone level that is low may have a normal result when testing is repeated.2,5 Therefore, for all men who have low testosterone level test results, draw a repeat total testosterone level before 9 am to confirm the diagnosis. Also, this study did not evaluate the course of testosterone levels throughout the later afternoon and evening, and it remains unclear whether levels can be drawn even later in the day.
CHALLENGES TO IMPLEMENTATION: Your lab's policies might require early-morning draws
There will probably be few barriers to implementing this change, unless local laboratory policies are inflexible regarding the timing of testosterone draws.
ACKNOWLEDGEMENT
The PURLs Surveillance System was supported in part by Grant Number UL1RR024999 from the National Center For Research Resources, a Clinical Translational Science Award to the University of Chicago. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Center For Research Resources or the National Institutes of Health.
1. Welliver RC Jr, Wiser HJ, Brannigan RE, et al. Validity of midday total testosterone levels in older men with erectile dysfunction. J Urol. 2014;192:165-169.
2. Bhasin S, Cunningham GR, Hayes FJ, et al. Testosterone therapy in men with androgen deficiency syndromes: an Endocrine Society clinical practice guideline. J Clin Endocrinol Metab. 2010;95:2536-2559.
3. Cooke RR, McIntosh JE, McIntosh RP. Circadian variation in serum free and non-SHBG-bound testosterone in normal men: measurements, and simulation using a mass action model. Clin Endocrinol (Oxf). 1993;39:163-171.
4. Bremner WJ, Vitiello MV, Prinz PN. Loss of circadian rhythmicity in blood testosterone levels with aging in normal men. J Clin Endocrinol Metab. 1983;56:1278-1281.
5. Brambilla DJ, Matsumoto AM, Araujo AB, et al. The effect of diurnal variation on clinical measurement of serum testosterone and other sex hormone levels in men. J Clin Endocrinol Metab. 2009;94:907-913.
6. Crawford ED, Barqawi AB, O’Donnell C, et al. The association of time of day and serum testosterone concentration in a large screening population. BJU Int. 2007;100:509-513.
Early-morning testosterone tests are necessary only for men younger than age 45. Because the natural diurnal variation in testosterone levels tends to diminish with age, it is acceptable to test men ages 45 and older before 2 pm.1
Strength of recommendation
B: Based on a retrospective cohort study.
Welliver RC Jr, Wiser HJ, Brannigan RE, et al. Validity of midday total testosterone levels in older men with erectile dysfunction. J Urol. 2014;192:165-169.
Illustrative case
It’s noon, you are finishing up a visit with a 62-year-old man with erectile dysfunction (ED), and you want to evaluate for androgen deficiency. Should you ask him to return for an early-morning visit so you can test his testosterone level?
Increasing public awareness of androgen deficiency has led to more men being tested for testosterone levels. Current Endocrine Society guidelines recommend against routine screening for androgen deficiency in men who do not have symptoms.2 However, for men with classic symptoms of androgen deficiency—such as decreased libido, ED, infertility, depression, osteoporosis, loss of secondary sexual characteristics, or reduced muscle bulk or strength—measurement of total testosterone level is recommended.2
Due to the natural diurnal variation in serum testosterone levels, the guidelines recommend collecting the sample in the early morning.2 This recommendation is based on small observational studies that included men mostly younger than 45 years of age that found a significant difference in testosterone levels between samples drawn early in the morning and in the afternoon.3-5
In recent years, several studies have indicated that this variation declines as men age.4-6 Recently, researchers evaluated the effects of age and time of testing on men’s total testosterone levels.
STUDY SUMMARY: Differences in testosterone levels are significant only in younger men
Welliver et al1 performed a retrospective chart review of 2569 men seen at a Minneapolis Veterans Affairs hospital for ED who had total testosterone levels measured between 7 am and 2 pm over a 15-year period. Men whose total testosterone levels were outside the normal range (>1000 or <50 ng/dL) or who had total testosterone drawn after 2 pm were excluded. The authors analyzed the results based on age, creating one group for men ages <40 years and 5-year age groups for all other men. Using scatterplot techniques, they separated each age group into 2 subgroups based on draw times—7 am to 9 am, or 9 am to 2 pm—and compared the mean total testosterone level for each age and time.
The participants’ mean age was 63 years. Younger men (<45 years) had the largest variation in serum total testosterone, with a large and significant decrease after 9 am. Only the youngest 2 groups (ages <40 and 40-44 years) showed a large decrease in total testosterone in specimens collected after 9 am compared to those drawn between 7 am and 9 am (mean difference 207 and 149 ng/dL, respectively). This variation was not observed in patients over age 45. Although there was a statistically significant difference between early and later testosterone levels in men ages 70 to 74 years, the absolute difference—34 ng/dL (452 vs 418 ng/dL)—was unlikely to be clinically significant.
WHAT'S NEW: For older men, later testing will not affect results
This study confirms previous research showing that the diurnal effect on testosterone levels becomes blunted with increasing age, at least in this group of men with ED. Allowing older men to have total testosterone levels drawn until 2 pm would allow for greater patient flexibility in draw times with little change in results.
CAVEATS: Study's methodology cannot account for several potential confounders
This retrospective study analyzed only a single random testosterone level measurement from each participant, rather than repeat testosterone levels over the course of a day. However, the study was large (2569 men) and it used mean values, which should at least partially mitigate the effect of having only a single level from each participant.
The study measured total testosterone and did not account for potential confounding factors—such as obesity or use of testosterone replacement therapy or androgen deprivation therapy—that could affect sexhormone binding globulin, thus potentially altering total testosterone level. However, the authors estimated that less than 2% of the entire cohort were likely to have unrecognized hormonal manipulation with exogenous gonadotropins.
All of the men in the study were seen for ED, and it could be that men with ED have more flattening of the diurnal variation than men without ED; however, we are unaware of other data that support this.
Up to 30% of men who have an early-morning testosterone level that is low may have a normal result when testing is repeated.2,5 Therefore, for all men who have low testosterone level test results, draw a repeat total testosterone level before 9 am to confirm the diagnosis. Also, this study did not evaluate the course of testosterone levels throughout the later afternoon and evening, and it remains unclear whether levels can be drawn even later in the day.
CHALLENGES TO IMPLEMENTATION: Your lab's policies might require early-morning draws
There will probably be few barriers to implementing this change, unless local laboratory policies are inflexible regarding the timing of testosterone draws.
ACKNOWLEDGEMENT
The PURLs Surveillance System was supported in part by Grant Number UL1RR024999 from the National Center For Research Resources, a Clinical Translational Science Award to the University of Chicago. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Center For Research Resources or the National Institutes of Health.
Early-morning testosterone tests are necessary only for men younger than age 45. Because the natural diurnal variation in testosterone levels tends to diminish with age, it is acceptable to test men ages 45 and older before 2 pm.1
Strength of recommendation
B: Based on a retrospective cohort study.
Welliver RC Jr, Wiser HJ, Brannigan RE, et al. Validity of midday total testosterone levels in older men with erectile dysfunction. J Urol. 2014;192:165-169.
Illustrative case
It’s noon, you are finishing up a visit with a 62-year-old man with erectile dysfunction (ED), and you want to evaluate for androgen deficiency. Should you ask him to return for an early-morning visit so you can test his testosterone level?
Increasing public awareness of androgen deficiency has led to more men being tested for testosterone levels. Current Endocrine Society guidelines recommend against routine screening for androgen deficiency in men who do not have symptoms.2 However, for men with classic symptoms of androgen deficiency—such as decreased libido, ED, infertility, depression, osteoporosis, loss of secondary sexual characteristics, or reduced muscle bulk or strength—measurement of total testosterone level is recommended.2
Due to the natural diurnal variation in serum testosterone levels, the guidelines recommend collecting the sample in the early morning.2 This recommendation is based on small observational studies that included men mostly younger than 45 years of age that found a significant difference in testosterone levels between samples drawn early in the morning and in the afternoon.3-5
In recent years, several studies have indicated that this variation declines as men age.4-6 Recently, researchers evaluated the effects of age and time of testing on men’s total testosterone levels.
STUDY SUMMARY: Differences in testosterone levels are significant only in younger men
Welliver et al1 performed a retrospective chart review of 2569 men seen at a Minneapolis Veterans Affairs hospital for ED who had total testosterone levels measured between 7 am and 2 pm over a 15-year period. Men whose total testosterone levels were outside the normal range (>1000 or <50 ng/dL) or who had total testosterone drawn after 2 pm were excluded. The authors analyzed the results based on age, creating one group for men ages <40 years and 5-year age groups for all other men. Using scatterplot techniques, they separated each age group into 2 subgroups based on draw times—7 am to 9 am, or 9 am to 2 pm—and compared the mean total testosterone level for each age and time.
The participants’ mean age was 63 years. Younger men (<45 years) had the largest variation in serum total testosterone, with a large and significant decrease after 9 am. Only the youngest 2 groups (ages <40 and 40-44 years) showed a large decrease in total testosterone in specimens collected after 9 am compared to those drawn between 7 am and 9 am (mean difference 207 and 149 ng/dL, respectively). This variation was not observed in patients over age 45. Although there was a statistically significant difference between early and later testosterone levels in men ages 70 to 74 years, the absolute difference—34 ng/dL (452 vs 418 ng/dL)—was unlikely to be clinically significant.
WHAT'S NEW: For older men, later testing will not affect results
This study confirms previous research showing that the diurnal effect on testosterone levels becomes blunted with increasing age, at least in this group of men with ED. Allowing older men to have total testosterone levels drawn until 2 pm would allow for greater patient flexibility in draw times with little change in results.
CAVEATS: Study's methodology cannot account for several potential confounders
This retrospective study analyzed only a single random testosterone level measurement from each participant, rather than repeat testosterone levels over the course of a day. However, the study was large (2569 men) and it used mean values, which should at least partially mitigate the effect of having only a single level from each participant.
The study measured total testosterone and did not account for potential confounding factors—such as obesity or use of testosterone replacement therapy or androgen deprivation therapy—that could affect sexhormone binding globulin, thus potentially altering total testosterone level. However, the authors estimated that less than 2% of the entire cohort were likely to have unrecognized hormonal manipulation with exogenous gonadotropins.
All of the men in the study were seen for ED, and it could be that men with ED have more flattening of the diurnal variation than men without ED; however, we are unaware of other data that support this.
Up to 30% of men who have an early-morning testosterone level that is low may have a normal result when testing is repeated.2,5 Therefore, for all men who have low testosterone level test results, draw a repeat total testosterone level before 9 am to confirm the diagnosis. Also, this study did not evaluate the course of testosterone levels throughout the later afternoon and evening, and it remains unclear whether levels can be drawn even later in the day.
CHALLENGES TO IMPLEMENTATION: Your lab's policies might require early-morning draws
There will probably be few barriers to implementing this change, unless local laboratory policies are inflexible regarding the timing of testosterone draws.
ACKNOWLEDGEMENT
The PURLs Surveillance System was supported in part by Grant Number UL1RR024999 from the National Center For Research Resources, a Clinical Translational Science Award to the University of Chicago. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Center For Research Resources or the National Institutes of Health.
1. Welliver RC Jr, Wiser HJ, Brannigan RE, et al. Validity of midday total testosterone levels in older men with erectile dysfunction. J Urol. 2014;192:165-169.
2. Bhasin S, Cunningham GR, Hayes FJ, et al. Testosterone therapy in men with androgen deficiency syndromes: an Endocrine Society clinical practice guideline. J Clin Endocrinol Metab. 2010;95:2536-2559.
3. Cooke RR, McIntosh JE, McIntosh RP. Circadian variation in serum free and non-SHBG-bound testosterone in normal men: measurements, and simulation using a mass action model. Clin Endocrinol (Oxf). 1993;39:163-171.
4. Bremner WJ, Vitiello MV, Prinz PN. Loss of circadian rhythmicity in blood testosterone levels with aging in normal men. J Clin Endocrinol Metab. 1983;56:1278-1281.
5. Brambilla DJ, Matsumoto AM, Araujo AB, et al. The effect of diurnal variation on clinical measurement of serum testosterone and other sex hormone levels in men. J Clin Endocrinol Metab. 2009;94:907-913.
6. Crawford ED, Barqawi AB, O’Donnell C, et al. The association of time of day and serum testosterone concentration in a large screening population. BJU Int. 2007;100:509-513.
1. Welliver RC Jr, Wiser HJ, Brannigan RE, et al. Validity of midday total testosterone levels in older men with erectile dysfunction. J Urol. 2014;192:165-169.
2. Bhasin S, Cunningham GR, Hayes FJ, et al. Testosterone therapy in men with androgen deficiency syndromes: an Endocrine Society clinical practice guideline. J Clin Endocrinol Metab. 2010;95:2536-2559.
3. Cooke RR, McIntosh JE, McIntosh RP. Circadian variation in serum free and non-SHBG-bound testosterone in normal men: measurements, and simulation using a mass action model. Clin Endocrinol (Oxf). 1993;39:163-171.
4. Bremner WJ, Vitiello MV, Prinz PN. Loss of circadian rhythmicity in blood testosterone levels with aging in normal men. J Clin Endocrinol Metab. 1983;56:1278-1281.
5. Brambilla DJ, Matsumoto AM, Araujo AB, et al. The effect of diurnal variation on clinical measurement of serum testosterone and other sex hormone levels in men. J Clin Endocrinol Metab. 2009;94:907-913.
6. Crawford ED, Barqawi AB, O’Donnell C, et al. The association of time of day and serum testosterone concentration in a large screening population. BJU Int. 2007;100:509-513.
Copyright © 2015 Family Physicians Inquiries Network. All rights reserved.
Breast cancer screening: The latest from the USPSTF
The United States Preventive Services Task Force (USPSTF) recently released draft recommendations on breast cancer screening, which could be finalized within the next few months.1 The last time the Task Force (TF) weighed in on this topic was in 2009, just as the Affordable Care Act (ACA) was being debated. At that time, the TF recommendations were so controversial that Congress specified in the ACA that they should not be used to determine insurance coverage (more on this later).
The draft recommendations (TABLE 1)1 carry a C grade for women ages 40 to 49 years (ie, offer or provide screening mammography for selected patients depending on individual circumstances) and a B grade for biennial screening of women ages 50 to 74. The proposed recommendations are basically the same as the ones made in 2009, with more detailed wording to explain the rationale for the C recommendation, and to address 2 new issues: tomosynthesis (3-D mammography) and adjunctive screening for women with dense breasts. The previous D recommendation against self breast examination was left unchanged.
Benefit of mammography screening varies by decade of life
Breast cancer is the leading cause of non-skin cancers in women and, after lung cancer, the second leading cause of cancer deaths in women. In 2014 there were 233,000 new cases diagnosed and 40,000 breast cancer deaths.1,2 While the TF found that mammography reduces deaths from breast cancer in women between the ages of 40 and 74, women ages 40 to 49 benefit the least; those ages 60 to 69 benefit the most.1,3
If 10,000 women are screened routinely for 10 years, 4 breast cancer deaths will be prevented in those ages 40 to 49, 8 in those 50 to 59, and 21 in those 60 to 69.1 And harms appear to be higher in the younger age group. TABLE 21,3 shows some of the harms resulting from one-time mammography screening of 10,000 women in each age group. Notice the benefits listed previously are from repeated screenings over a 10-year period and the harms in TABLE 21,3 are from a single mammogram.
The total benefits and harms of biennial screening in 1000 women starting at age 40 (vs age 50) include 8 cancer deaths prevented (vs 7) with a cost of 1529 false positive tests (vs 953); 204 unnecessary breast biopsies (vs 146); and 20 overdiagnoses (vs 18). However, the confidence intervals on these estimates are wide, and in each case, they overlap between the 2 groups.1
The TF recommended biennial screening for women between the ages of 50 and 74 because observational studies and modeling show no clear benefit with annual screening vs every 2 years, while annual screening results in more false positives and biopsies.
Overdiagnosis may occur in nearly 20% of cases
The potential for overdiagnosis and overtreatment is increasingly recognized as a harm of cancer screening. Overdiagnosis results from detecting a tumor during screening that would not have been detected otherwise and that would not have caused death or disease but is treated anyway. This sometimes occurs with the detection of early tumors that would not have progressed or would have progressed slowly, not causing health problems before the woman dies of other causes.
The TF is one of the only organizations that considers the potential harmful effects of this problem. While it is not possible to know for certain the rate of overdiagnosis that occurs with cancer screening, high-quality studies indicate it is close to 20% for breast cancer.3
Guidance regarding women ages 40 to 49
The new draft recommendations carefully point out that, while the overall benefit of screening women ages 40 to 49 is small, the decision to begin screening before age 50 should be an individual one, and an informed one. They state that women who value the small potential benefit over the potential for harm may choose to be screened, as might women who have a family history of breast cancer. And the recommendations do not apply to women who have a genotype that places them at increased risk for breast cancer.
Tomosynthesis: Evidence of benefit is insufficient
Tomosynthesis as a primary breast cancer screening tool was studied in a separate evidence report commissioned by the TF.4 While tomosynthesis, compared with routine mammography, appears to have increased sensitivity and specificity in detecting breast cancer, no studies looked at this technology as a primary screening tool and its effect on breast cancer mortality, overall mortality, and quality of life. Sticking to its nationally-recognized methodological rigor, the TF states that information at this time is insufficient to make a recommendation on the use of tomosynthesis.
Dense breasts: Usefulness of adjunctive screening modalities
Breast density is categorized into 4 groups, from category a (breasts are almost all fatty with little fibro nodular tissue) to category d (breasts are extremely dense).1 About 43% of women ages 40 to 74 are in categories c and d.1 Dense breasts adversely affect the accuracy of mammography, decreasing sensitivity and specificity. In one study, sensitivity was 87% in category a and 63% in category d; specificities were 97% and 89%, respectively.5
Tomosynthesis, magnetic resonance imaging, and ultrasound, when used in addition to mammography, all appear to detect more cancers, but they also yield more false-positive results.6 The long-term outcome of detecting more tumors is not known. For an individual, there are 3 possibilities when a tumor is detected earlier: a better outcome, no difference in outcome, or a worse outcome resulting from overdiagnosis and overtreatment. The TF felt that the available data are insufficient to judge benefits and harms of an increased frequency of screening or the use of adjunctive screening methods in women with dense breasts.
Benefit for women ≥75 years is inconclusive
There are limited data on the impact of mammography on outcomes for women older than 70. The TF feels that, since women ages 60 to 69 benefit the most from mammography, this benefit is likely to carry over into the next decade. Modeling also predicts this.
However, women ages 70 to 74 who have chronic illnesses are unlikely to benefit from mammography. The conditions specifically mentioned are cardiovascular disease, diabetes, lung disease, liver disease, renal failure, acquired immunodeficiency syndrome, and dementia.
For all women ages 75 and older, the TF feels the evidence is insufficient to make a recommendation.
Insurance coverage
The ACA mandates that 4 sets of preventive services be included in commercial health insurance plans with no out-of-pocket expenses to the patient: immunizations recommended by the Advisory Committee on Immunization Practices; children’s preventive services recommended by the Health Resources and Services Administration (HRSA); women’s preventive services recommended by HRSA; and recommendations with an A or B rating from the USPSTF.7
For children, HRSA opted to use those preventive services listed by the American Academy of Pediatrics in Bright Futures, the society’s national initiative providing recommendations on prevention screenings and well-child visits.8 For women, HRSA asked the Institute of Medicine to form a panel to construct a list of recommended preventive services.
At the time the ACA was passed, the TF had just made new recommendations on breast cancer screening, which were very similar to the current draft recommendations. Due to the resulting controversy, Congress mandated that the new recommendations not be used to determine first-dollar insurance coverage, and it cited the TF’s pre-2009 recommendations as the applicable standard.
Those earlier recommendations included annual mammography starting at age 40. The wording of the law, however, was not clear as to future mammography recommendations. One interpretation is that the TF recommendations in place before 2009 are the basis for first-dollar coverage until changed by Congress. Another interpretation is that the ACA special provision trumped only the 2009 recommendations and the 2015 recommendations will become the standard. If the latter turns out to be true, it is not clear if commercial insurance plans will begin to charge co-payments for mammography before age 50 or for mammograms ordered more frequently than every 2 years for women ages 50 to 74.
The issue of insurance coverage is important because of the lack of uniformity in recommendations regarding mammography. The American Congress of Obstetricians and Gynecologists,9 the American Cancer Society,10 and the American College of Radiology11 all recommend annual mammography starting at age 40. The American Academy of Family Physicians recommendations12 mirror those of the USPSTF, and the Canadian Task Force on Preventive Health Care recommends against routine screening for women ages 40 to 49 and recommends mammography every 2 to 3 years for women ages 50 to 74.13
USPSTF rationale is informed and accessible for review
Breast cancer screening remains a highly controversial and emotional topic. The USPSTF has made a set of recommendations based on extensive and rigorous evidence reports that consider both benefits and harms. There will be those who vigorously disagree. The evidence reports, recommendations, and rationale behind them are easily accessible on the TF Web site (www.uspreventiveservicestaskforce.org) for those who want to read them.1
1. USPSTF. Draft recommendation statement. Breast cancer: screening. Available at: http://www.uspreventiveservicestaskforce.org/Page/Document/RecommendationStatementDraft/breast-cancer-screening1#tab1. Accessed May 25, 2015.
2. National Cancer Institute. SEER Stat Fact Sheets: Breast Cancer. Available at: http://seer.cancer.gov/statfacts/html/breast.html. Accessed June 11, 2015.
3. Nelson HD, Cantor A, Humphrey L, et al. Screening for breast cancer; a systematic review to update the 2009 U.S. Preventive Services Task Force recommendation. Available at: http://www.uspreventiveservicestaskforce.org/Page/Document/draftevidence-review-screening-for-breast-cancer/breast-cancerscreening1. Accessed May 25, 2015.
4. Melnikow J, Fenton JJ, Miglioretti D, et al. Screening for Breast Cancer with Digital Tomosynthesis. Available at: http://www.uspreventiveservicestaskforce.org/Page/Document/draft-evidence-review-screening-for-breast-cancer-with-digit/breastcancer-screening1. Accessed May 25, 2015.
5. Carney PA, Miglioretti D, Yaankaskas BC, et al. Individual and combined effects of age, breast density, and hormone replacement therapy use on the accuracy of screening mammography. Ann Intern Med. 2003;138:168-175.
6. Melnikow J, Fenton JJ, Whitlock EP, et al. Adjunctive screening for breast cancer in women with dense breasts: a systematic review for the U.S. Preventive Services Task Force. AHRQ Publication No. 14-05201-EF-2.
7. 111th Congress Public Law 111-148, section 2713. Available at: http://www.gpo.gov/fdsys/pkg/PLAW-111publ148/html/PLAW-111publ148.htm. Accessed May 25, 2015.
8. American Academy of Pediatrics. Bright Futures. Available at: https://brightfutures.aap.org/Pages/default.aspx. Accessed May 25, 2015.
9. American Congress of Obstetricians and Gynecologists. ACOG statement on breast cancer screening. Available at: http://www.acog.org/About-ACOG/News-Room/Statements/2015/ACOGStatement-on-Breast-Cancer-Screening. Accessed May 25, 2015.
10. Smith RA, Manassaram-Baptiste D, Brooks D, et al. Cancer screening in the United States, 2015: a review of current American Cancer Society guidelines and current issues in cancer screening. CA Cancer J Clin. 2015;65:30-54.
11. Lee CH, Dershaw DD, Kopans D, et al. Breast cancer screening with imaging: recommendations from the Society of Breast Imaging and the ACR on the use of mammography, breast MRI, breast ultrasound, and other technologies for the detection of clinically occult breast cancer. J Am Coll Radiol. 2010;7:18-27.
12. American Academy of Family Physicians. Breast cancer. Available at: http://www.aafp.org/patient-care/clinical-recommendations/all/breast-cancer.html. Accessed May 25, 2015.
13. Canadian Task Force on Preventive Health Care. Screening for breast cancer. Available at: http://canadiantaskforce.ca/ctfphcguidelines/2011-breast-cancer. Accessed May 25, 2015.
The United States Preventive Services Task Force (USPSTF) recently released draft recommendations on breast cancer screening, which could be finalized within the next few months.1 The last time the Task Force (TF) weighed in on this topic was in 2009, just as the Affordable Care Act (ACA) was being debated. At that time, the TF recommendations were so controversial that Congress specified in the ACA that they should not be used to determine insurance coverage (more on this later).
The draft recommendations (TABLE 1)1 carry a C grade for women ages 40 to 49 years (ie, offer or provide screening mammography for selected patients depending on individual circumstances) and a B grade for biennial screening of women ages 50 to 74. The proposed recommendations are basically the same as the ones made in 2009, with more detailed wording to explain the rationale for the C recommendation, and to address 2 new issues: tomosynthesis (3-D mammography) and adjunctive screening for women with dense breasts. The previous D recommendation against self breast examination was left unchanged.
Benefit of mammography screening varies by decade of life
Breast cancer is the leading cause of non-skin cancers in women and, after lung cancer, the second leading cause of cancer deaths in women. In 2014 there were 233,000 new cases diagnosed and 40,000 breast cancer deaths.1,2 While the TF found that mammography reduces deaths from breast cancer in women between the ages of 40 and 74, women ages 40 to 49 benefit the least; those ages 60 to 69 benefit the most.1,3
If 10,000 women are screened routinely for 10 years, 4 breast cancer deaths will be prevented in those ages 40 to 49, 8 in those 50 to 59, and 21 in those 60 to 69.1 And harms appear to be higher in the younger age group. TABLE 21,3 shows some of the harms resulting from one-time mammography screening of 10,000 women in each age group. Notice the benefits listed previously are from repeated screenings over a 10-year period and the harms in TABLE 21,3 are from a single mammogram.
The total benefits and harms of biennial screening in 1000 women starting at age 40 (vs age 50) include 8 cancer deaths prevented (vs 7) with a cost of 1529 false positive tests (vs 953); 204 unnecessary breast biopsies (vs 146); and 20 overdiagnoses (vs 18). However, the confidence intervals on these estimates are wide, and in each case, they overlap between the 2 groups.1
The TF recommended biennial screening for women between the ages of 50 and 74 because observational studies and modeling show no clear benefit with annual screening vs every 2 years, while annual screening results in more false positives and biopsies.
Overdiagnosis may occur in nearly 20% of cases
The potential for overdiagnosis and overtreatment is increasingly recognized as a harm of cancer screening. Overdiagnosis results from detecting a tumor during screening that would not have been detected otherwise and that would not have caused death or disease but is treated anyway. This sometimes occurs with the detection of early tumors that would not have progressed or would have progressed slowly, not causing health problems before the woman dies of other causes.
The TF is one of the only organizations that considers the potential harmful effects of this problem. While it is not possible to know for certain the rate of overdiagnosis that occurs with cancer screening, high-quality studies indicate it is close to 20% for breast cancer.3
Guidance regarding women ages 40 to 49
The new draft recommendations carefully point out that, while the overall benefit of screening women ages 40 to 49 is small, the decision to begin screening before age 50 should be an individual one, and an informed one. They state that women who value the small potential benefit over the potential for harm may choose to be screened, as might women who have a family history of breast cancer. And the recommendations do not apply to women who have a genotype that places them at increased risk for breast cancer.
Tomosynthesis: Evidence of benefit is insufficient
Tomosynthesis as a primary breast cancer screening tool was studied in a separate evidence report commissioned by the TF.4 While tomosynthesis, compared with routine mammography, appears to have increased sensitivity and specificity in detecting breast cancer, no studies looked at this technology as a primary screening tool and its effect on breast cancer mortality, overall mortality, and quality of life. Sticking to its nationally-recognized methodological rigor, the TF states that information at this time is insufficient to make a recommendation on the use of tomosynthesis.
Dense breasts: Usefulness of adjunctive screening modalities
Breast density is categorized into 4 groups, from category a (breasts are almost all fatty with little fibro nodular tissue) to category d (breasts are extremely dense).1 About 43% of women ages 40 to 74 are in categories c and d.1 Dense breasts adversely affect the accuracy of mammography, decreasing sensitivity and specificity. In one study, sensitivity was 87% in category a and 63% in category d; specificities were 97% and 89%, respectively.5
Tomosynthesis, magnetic resonance imaging, and ultrasound, when used in addition to mammography, all appear to detect more cancers, but they also yield more false-positive results.6 The long-term outcome of detecting more tumors is not known. For an individual, there are 3 possibilities when a tumor is detected earlier: a better outcome, no difference in outcome, or a worse outcome resulting from overdiagnosis and overtreatment. The TF felt that the available data are insufficient to judge benefits and harms of an increased frequency of screening or the use of adjunctive screening methods in women with dense breasts.
Benefit for women ≥75 years is inconclusive
There are limited data on the impact of mammography on outcomes for women older than 70. The TF feels that, since women ages 60 to 69 benefit the most from mammography, this benefit is likely to carry over into the next decade. Modeling also predicts this.
However, women ages 70 to 74 who have chronic illnesses are unlikely to benefit from mammography. The conditions specifically mentioned are cardiovascular disease, diabetes, lung disease, liver disease, renal failure, acquired immunodeficiency syndrome, and dementia.
For all women ages 75 and older, the TF feels the evidence is insufficient to make a recommendation.
Insurance coverage
The ACA mandates that 4 sets of preventive services be included in commercial health insurance plans with no out-of-pocket expenses to the patient: immunizations recommended by the Advisory Committee on Immunization Practices; children’s preventive services recommended by the Health Resources and Services Administration (HRSA); women’s preventive services recommended by HRSA; and recommendations with an A or B rating from the USPSTF.7
For children, HRSA opted to use those preventive services listed by the American Academy of Pediatrics in Bright Futures, the society’s national initiative providing recommendations on prevention screenings and well-child visits.8 For women, HRSA asked the Institute of Medicine to form a panel to construct a list of recommended preventive services.
At the time the ACA was passed, the TF had just made new recommendations on breast cancer screening, which were very similar to the current draft recommendations. Due to the resulting controversy, Congress mandated that the new recommendations not be used to determine first-dollar insurance coverage, and it cited the TF’s pre-2009 recommendations as the applicable standard.
Those earlier recommendations included annual mammography starting at age 40. The wording of the law, however, was not clear as to future mammography recommendations. One interpretation is that the TF recommendations in place before 2009 are the basis for first-dollar coverage until changed by Congress. Another interpretation is that the ACA special provision trumped only the 2009 recommendations and the 2015 recommendations will become the standard. If the latter turns out to be true, it is not clear if commercial insurance plans will begin to charge co-payments for mammography before age 50 or for mammograms ordered more frequently than every 2 years for women ages 50 to 74.
The issue of insurance coverage is important because of the lack of uniformity in recommendations regarding mammography. The American Congress of Obstetricians and Gynecologists,9 the American Cancer Society,10 and the American College of Radiology11 all recommend annual mammography starting at age 40. The American Academy of Family Physicians recommendations12 mirror those of the USPSTF, and the Canadian Task Force on Preventive Health Care recommends against routine screening for women ages 40 to 49 and recommends mammography every 2 to 3 years for women ages 50 to 74.13
USPSTF rationale is informed and accessible for review
Breast cancer screening remains a highly controversial and emotional topic. The USPSTF has made a set of recommendations based on extensive and rigorous evidence reports that consider both benefits and harms. There will be those who vigorously disagree. The evidence reports, recommendations, and rationale behind them are easily accessible on the TF Web site (www.uspreventiveservicestaskforce.org) for those who want to read them.1
The United States Preventive Services Task Force (USPSTF) recently released draft recommendations on breast cancer screening, which could be finalized within the next few months.1 The last time the Task Force (TF) weighed in on this topic was in 2009, just as the Affordable Care Act (ACA) was being debated. At that time, the TF recommendations were so controversial that Congress specified in the ACA that they should not be used to determine insurance coverage (more on this later).
The draft recommendations (TABLE 1)1 carry a C grade for women ages 40 to 49 years (ie, offer or provide screening mammography for selected patients depending on individual circumstances) and a B grade for biennial screening of women ages 50 to 74. The proposed recommendations are basically the same as the ones made in 2009, with more detailed wording to explain the rationale for the C recommendation, and to address 2 new issues: tomosynthesis (3-D mammography) and adjunctive screening for women with dense breasts. The previous D recommendation against self breast examination was left unchanged.
Benefit of mammography screening varies by decade of life
Breast cancer is the leading cause of non-skin cancers in women and, after lung cancer, the second leading cause of cancer deaths in women. In 2014 there were 233,000 new cases diagnosed and 40,000 breast cancer deaths.1,2 While the TF found that mammography reduces deaths from breast cancer in women between the ages of 40 and 74, women ages 40 to 49 benefit the least; those ages 60 to 69 benefit the most.1,3
If 10,000 women are screened routinely for 10 years, 4 breast cancer deaths will be prevented in those ages 40 to 49, 8 in those 50 to 59, and 21 in those 60 to 69.1 And harms appear to be higher in the younger age group. TABLE 21,3 shows some of the harms resulting from one-time mammography screening of 10,000 women in each age group. Notice the benefits listed previously are from repeated screenings over a 10-year period and the harms in TABLE 21,3 are from a single mammogram.
The total benefits and harms of biennial screening in 1000 women starting at age 40 (vs age 50) include 8 cancer deaths prevented (vs 7) with a cost of 1529 false positive tests (vs 953); 204 unnecessary breast biopsies (vs 146); and 20 overdiagnoses (vs 18). However, the confidence intervals on these estimates are wide, and in each case, they overlap between the 2 groups.1
The TF recommended biennial screening for women between the ages of 50 and 74 because observational studies and modeling show no clear benefit with annual screening vs every 2 years, while annual screening results in more false positives and biopsies.
Overdiagnosis may occur in nearly 20% of cases
The potential for overdiagnosis and overtreatment is increasingly recognized as a harm of cancer screening. Overdiagnosis results from detecting a tumor during screening that would not have been detected otherwise and that would not have caused death or disease but is treated anyway. This sometimes occurs with the detection of early tumors that would not have progressed or would have progressed slowly, not causing health problems before the woman dies of other causes.
The TF is one of the only organizations that considers the potential harmful effects of this problem. While it is not possible to know for certain the rate of overdiagnosis that occurs with cancer screening, high-quality studies indicate it is close to 20% for breast cancer.3
Guidance regarding women ages 40 to 49
The new draft recommendations carefully point out that, while the overall benefit of screening women ages 40 to 49 is small, the decision to begin screening before age 50 should be an individual one, and an informed one. They state that women who value the small potential benefit over the potential for harm may choose to be screened, as might women who have a family history of breast cancer. And the recommendations do not apply to women who have a genotype that places them at increased risk for breast cancer.
Tomosynthesis: Evidence of benefit is insufficient
Tomosynthesis as a primary breast cancer screening tool was studied in a separate evidence report commissioned by the TF.4 While tomosynthesis, compared with routine mammography, appears to have increased sensitivity and specificity in detecting breast cancer, no studies looked at this technology as a primary screening tool and its effect on breast cancer mortality, overall mortality, and quality of life. Sticking to its nationally-recognized methodological rigor, the TF states that information at this time is insufficient to make a recommendation on the use of tomosynthesis.
Dense breasts: Usefulness of adjunctive screening modalities
Breast density is categorized into 4 groups, from category a (breasts are almost all fatty with little fibro nodular tissue) to category d (breasts are extremely dense).1 About 43% of women ages 40 to 74 are in categories c and d.1 Dense breasts adversely affect the accuracy of mammography, decreasing sensitivity and specificity. In one study, sensitivity was 87% in category a and 63% in category d; specificities were 97% and 89%, respectively.5
Tomosynthesis, magnetic resonance imaging, and ultrasound, when used in addition to mammography, all appear to detect more cancers, but they also yield more false-positive results.6 The long-term outcome of detecting more tumors is not known. For an individual, there are 3 possibilities when a tumor is detected earlier: a better outcome, no difference in outcome, or a worse outcome resulting from overdiagnosis and overtreatment. The TF felt that the available data are insufficient to judge benefits and harms of an increased frequency of screening or the use of adjunctive screening methods in women with dense breasts.
Benefit for women ≥75 years is inconclusive
There are limited data on the impact of mammography on outcomes for women older than 70. The TF feels that, since women ages 60 to 69 benefit the most from mammography, this benefit is likely to carry over into the next decade. Modeling also predicts this.
However, women ages 70 to 74 who have chronic illnesses are unlikely to benefit from mammography. The conditions specifically mentioned are cardiovascular disease, diabetes, lung disease, liver disease, renal failure, acquired immunodeficiency syndrome, and dementia.
For all women ages 75 and older, the TF feels the evidence is insufficient to make a recommendation.
Insurance coverage
The ACA mandates that 4 sets of preventive services be included in commercial health insurance plans with no out-of-pocket expenses to the patient: immunizations recommended by the Advisory Committee on Immunization Practices; children’s preventive services recommended by the Health Resources and Services Administration (HRSA); women’s preventive services recommended by HRSA; and recommendations with an A or B rating from the USPSTF.7
For children, HRSA opted to use those preventive services listed by the American Academy of Pediatrics in Bright Futures, the society’s national initiative providing recommendations on prevention screenings and well-child visits.8 For women, HRSA asked the Institute of Medicine to form a panel to construct a list of recommended preventive services.
At the time the ACA was passed, the TF had just made new recommendations on breast cancer screening, which were very similar to the current draft recommendations. Due to the resulting controversy, Congress mandated that the new recommendations not be used to determine first-dollar insurance coverage, and it cited the TF’s pre-2009 recommendations as the applicable standard.
Those earlier recommendations included annual mammography starting at age 40. The wording of the law, however, was not clear as to future mammography recommendations. One interpretation is that the TF recommendations in place before 2009 are the basis for first-dollar coverage until changed by Congress. Another interpretation is that the ACA special provision trumped only the 2009 recommendations and the 2015 recommendations will become the standard. If the latter turns out to be true, it is not clear if commercial insurance plans will begin to charge co-payments for mammography before age 50 or for mammograms ordered more frequently than every 2 years for women ages 50 to 74.
The issue of insurance coverage is important because of the lack of uniformity in recommendations regarding mammography. The American Congress of Obstetricians and Gynecologists,9 the American Cancer Society,10 and the American College of Radiology11 all recommend annual mammography starting at age 40. The American Academy of Family Physicians recommendations12 mirror those of the USPSTF, and the Canadian Task Force on Preventive Health Care recommends against routine screening for women ages 40 to 49 and recommends mammography every 2 to 3 years for women ages 50 to 74.13
USPSTF rationale is informed and accessible for review
Breast cancer screening remains a highly controversial and emotional topic. The USPSTF has made a set of recommendations based on extensive and rigorous evidence reports that consider both benefits and harms. There will be those who vigorously disagree. The evidence reports, recommendations, and rationale behind them are easily accessible on the TF Web site (www.uspreventiveservicestaskforce.org) for those who want to read them.1
1. USPSTF. Draft recommendation statement. Breast cancer: screening. Available at: http://www.uspreventiveservicestaskforce.org/Page/Document/RecommendationStatementDraft/breast-cancer-screening1#tab1. Accessed May 25, 2015.
2. National Cancer Institute. SEER Stat Fact Sheets: Breast Cancer. Available at: http://seer.cancer.gov/statfacts/html/breast.html. Accessed June 11, 2015.
3. Nelson HD, Cantor A, Humphrey L, et al. Screening for breast cancer; a systematic review to update the 2009 U.S. Preventive Services Task Force recommendation. Available at: http://www.uspreventiveservicestaskforce.org/Page/Document/draftevidence-review-screening-for-breast-cancer/breast-cancerscreening1. Accessed May 25, 2015.
4. Melnikow J, Fenton JJ, Miglioretti D, et al. Screening for Breast Cancer with Digital Tomosynthesis. Available at: http://www.uspreventiveservicestaskforce.org/Page/Document/draft-evidence-review-screening-for-breast-cancer-with-digit/breastcancer-screening1. Accessed May 25, 2015.
5. Carney PA, Miglioretti D, Yaankaskas BC, et al. Individual and combined effects of age, breast density, and hormone replacement therapy use on the accuracy of screening mammography. Ann Intern Med. 2003;138:168-175.
6. Melnikow J, Fenton JJ, Whitlock EP, et al. Adjunctive screening for breast cancer in women with dense breasts: a systematic review for the U.S. Preventive Services Task Force. AHRQ Publication No. 14-05201-EF-2.
7. 111th Congress Public Law 111-148, section 2713. Available at: http://www.gpo.gov/fdsys/pkg/PLAW-111publ148/html/PLAW-111publ148.htm. Accessed May 25, 2015.
8. American Academy of Pediatrics. Bright Futures. Available at: https://brightfutures.aap.org/Pages/default.aspx. Accessed May 25, 2015.
9. American Congress of Obstetricians and Gynecologists. ACOG statement on breast cancer screening. Available at: http://www.acog.org/About-ACOG/News-Room/Statements/2015/ACOGStatement-on-Breast-Cancer-Screening. Accessed May 25, 2015.
10. Smith RA, Manassaram-Baptiste D, Brooks D, et al. Cancer screening in the United States, 2015: a review of current American Cancer Society guidelines and current issues in cancer screening. CA Cancer J Clin. 2015;65:30-54.
11. Lee CH, Dershaw DD, Kopans D, et al. Breast cancer screening with imaging: recommendations from the Society of Breast Imaging and the ACR on the use of mammography, breast MRI, breast ultrasound, and other technologies for the detection of clinically occult breast cancer. J Am Coll Radiol. 2010;7:18-27.
12. American Academy of Family Physicians. Breast cancer. Available at: http://www.aafp.org/patient-care/clinical-recommendations/all/breast-cancer.html. Accessed May 25, 2015.
13. Canadian Task Force on Preventive Health Care. Screening for breast cancer. Available at: http://canadiantaskforce.ca/ctfphcguidelines/2011-breast-cancer. Accessed May 25, 2015.
1. USPSTF. Draft recommendation statement. Breast cancer: screening. Available at: http://www.uspreventiveservicestaskforce.org/Page/Document/RecommendationStatementDraft/breast-cancer-screening1#tab1. Accessed May 25, 2015.
2. National Cancer Institute. SEER Stat Fact Sheets: Breast Cancer. Available at: http://seer.cancer.gov/statfacts/html/breast.html. Accessed June 11, 2015.
3. Nelson HD, Cantor A, Humphrey L, et al. Screening for breast cancer; a systematic review to update the 2009 U.S. Preventive Services Task Force recommendation. Available at: http://www.uspreventiveservicestaskforce.org/Page/Document/draftevidence-review-screening-for-breast-cancer/breast-cancerscreening1. Accessed May 25, 2015.
4. Melnikow J, Fenton JJ, Miglioretti D, et al. Screening for Breast Cancer with Digital Tomosynthesis. Available at: http://www.uspreventiveservicestaskforce.org/Page/Document/draft-evidence-review-screening-for-breast-cancer-with-digit/breastcancer-screening1. Accessed May 25, 2015.
5. Carney PA, Miglioretti D, Yaankaskas BC, et al. Individual and combined effects of age, breast density, and hormone replacement therapy use on the accuracy of screening mammography. Ann Intern Med. 2003;138:168-175.
6. Melnikow J, Fenton JJ, Whitlock EP, et al. Adjunctive screening for breast cancer in women with dense breasts: a systematic review for the U.S. Preventive Services Task Force. AHRQ Publication No. 14-05201-EF-2.
7. 111th Congress Public Law 111-148, section 2713. Available at: http://www.gpo.gov/fdsys/pkg/PLAW-111publ148/html/PLAW-111publ148.htm. Accessed May 25, 2015.
8. American Academy of Pediatrics. Bright Futures. Available at: https://brightfutures.aap.org/Pages/default.aspx. Accessed May 25, 2015.
9. American Congress of Obstetricians and Gynecologists. ACOG statement on breast cancer screening. Available at: http://www.acog.org/About-ACOG/News-Room/Statements/2015/ACOGStatement-on-Breast-Cancer-Screening. Accessed May 25, 2015.
10. Smith RA, Manassaram-Baptiste D, Brooks D, et al. Cancer screening in the United States, 2015: a review of current American Cancer Society guidelines and current issues in cancer screening. CA Cancer J Clin. 2015;65:30-54.
11. Lee CH, Dershaw DD, Kopans D, et al. Breast cancer screening with imaging: recommendations from the Society of Breast Imaging and the ACR on the use of mammography, breast MRI, breast ultrasound, and other technologies for the detection of clinically occult breast cancer. J Am Coll Radiol. 2010;7:18-27.
12. American Academy of Family Physicians. Breast cancer. Available at: http://www.aafp.org/patient-care/clinical-recommendations/all/breast-cancer.html. Accessed May 25, 2015.
13. Canadian Task Force on Preventive Health Care. Screening for breast cancer. Available at: http://canadiantaskforce.ca/ctfphcguidelines/2011-breast-cancer. Accessed May 25, 2015.