Pharmacology

ACE inhibitors may be associated with an increased risk for schizophrenia and may affect psychiatric symptoms, new research suggests.

Investigators found individuals who carry a genetic variant associated with lower levels of the ACE gene and protein have increased liability to schizophrenia, suggesting that drugs that lower ACE levels or activity may do the same.

“Our findings warrant further investigation into the role of ACE in schizophrenia and closer monitoring by clinicians of individuals, especially those with schizophrenia, who may be on medication that lower ACE activity, such as ACE inhibitors,” Sonia Shah, PhD, Institute for Biomedical Sciences, University of Queensland, Brisbane, Australia, said in an interview.

The study was published online March 10, 2021, in JAMA Psychiatry.
 

Antihypertensives and mental illness

Hypertension is common in patients with psychiatric disorders and observational studies have reported associations between antihypertensive medication and these disorders, although the findings have been mixed.

Dr. Shah and colleagues estimated the potential of different antihypertensive drug classes on schizophrenia, bipolar disorder, and major depressive disorder.

In a two-sample Mendelian randomization study, they evaluated ties between a single-nucleotide variant and drug-target gene expression derived from expression quantitative trait loci data in blood (sample 1) and the SNV disease association from published case-control, genomewide association studies (sample 2).

The analyses included 40,675 patients with schizophrenia and 64,643 controls; 20,352 with bipolar disorder and 31,358 controls; and 135,458 with major depressive disorder and 344,901 controls.

The major finding was that a one standard deviation–lower expression of the ACE gene in blood was associated with lower systolic blood pressure of 4.0 mm Hg (95% confidence interval, 2.7-5.3), but also an increased risk of schizophrenia (odds ratio, 1.75; 95% CI, 1.28-2.38).
 

Could ACE inhibitors worsen symptoms or trigger episodes?

In their article, the researchers noted that, in most patients, onset of schizophrenia occurs in late adolescence or early adult life, ruling out ACE inhibitor treatment as a potential causal factor for most cases.

“However, if lower ACE levels play a causal role for schizophrenia risk, it would be reasonable to hypothesize that further lowering of ACE activity in existing patients could worsen symptoms or trigger a new episode,” they wrote.

Dr. Shah emphasized that evidence from genetic analyses alone is “not sufficient to justify changes in prescription guidelines.”

“Patients should not stop taking these medications if they are effective at controlling their blood pressure and they don’t suffer any adverse effects. But it would be reasonable to encourage greater pharmacovigilance,” she said in an interview.

“One way in which we are hoping to follow up these findings,” said Dr. Shah, “is to access electronic health record data for millions of individuals to investigate if there is evidence of increased rates of psychotic episodes in individuals who use ACE inhibitors, compared to other classes of blood pressure–lowering medication.”
 

Caution warranted

Reached for comment, Timothy Sullivan, MD, chair of psychiatry and behavioral sciences at Staten Island University Hospital in New York, noted that this is an “extremely complicated” study and urged caution in interpreting the results.

“Since most people develop schizophrenia earlier in life, before they usually develop problems with blood pressure, it’s not so much that these drugs might cause schizophrenia,” Dr. Sullivan said.

“But because of their effects on this particular gene, there’s a possibility that they might worsen symptoms or in somebody with borderline risk might cause them to develop symptoms later in life. This may apply to a relatively small number of people who develop symptoms of schizophrenia in their 40s and beyond,” he added.

That’s where “pharmacovigilance” comes into play, Dr. Sullivan said. “In other words, we should be looking at people we’re treating with these drugs to see – might we be tipping some of them into illness states that they otherwise wouldn’t experience?”

Support for the study was provided by the National Health and Medical Research Council (Australia) and U.S. National Institute for Mental Health. Dr. Shah and Dr. Sullivan disclosed no relevant financial relationships.

A version of this article first appeared on Medscape.com.

ACE inhibitors may be associated with an increased risk for schizophrenia and may affect psychiatric symptoms, new research suggests.

Investigators found individuals who carry a genetic variant associated with lower levels of the ACE gene and protein have increased liability to schizophrenia, suggesting that drugs that lower ACE levels or activity may do the same.

“Our findings warrant further investigation into the role of ACE in schizophrenia and closer monitoring by clinicians of individuals, especially those with schizophrenia, who may be on medication that lower ACE activity, such as ACE inhibitors,” Sonia Shah, PhD, Institute for Biomedical Sciences, University of Queensland, Brisbane, Australia, said in an interview.

The study was published online March 10, 2021, in JAMA Psychiatry.
 

Antihypertensives and mental illness

Hypertension is common in patients with psychiatric disorders and observational studies have reported associations between antihypertensive medication and these disorders, although the findings have been mixed.

Dr. Shah and colleagues estimated the potential of different antihypertensive drug classes on schizophrenia, bipolar disorder, and major depressive disorder.

In a two-sample Mendelian randomization study, they evaluated ties between a single-nucleotide variant and drug-target gene expression derived from expression quantitative trait loci data in blood (sample 1) and the SNV disease association from published case-control, genomewide association studies (sample 2).

The analyses included 40,675 patients with schizophrenia and 64,643 controls; 20,352 with bipolar disorder and 31,358 controls; and 135,458 with major depressive disorder and 344,901 controls.

The major finding was that a one standard deviation–lower expression of the ACE gene in blood was associated with lower systolic blood pressure of 4.0 mm Hg (95% confidence interval, 2.7-5.3), but also an increased risk of schizophrenia (odds ratio, 1.75; 95% CI, 1.28-2.38).
 

Could ACE inhibitors worsen symptoms or trigger episodes?

In their article, the researchers noted that, in most patients, onset of schizophrenia occurs in late adolescence or early adult life, ruling out ACE inhibitor treatment as a potential causal factor for most cases.

“However, if lower ACE levels play a causal role for schizophrenia risk, it would be reasonable to hypothesize that further lowering of ACE activity in existing patients could worsen symptoms or trigger a new episode,” they wrote.

Dr. Shah emphasized that evidence from genetic analyses alone is “not sufficient to justify changes in prescription guidelines.”

“Patients should not stop taking these medications if they are effective at controlling their blood pressure and they don’t suffer any adverse effects. But it would be reasonable to encourage greater pharmacovigilance,” she said in an interview.

“One way in which we are hoping to follow up these findings,” said Dr. Shah, “is to access electronic health record data for millions of individuals to investigate if there is evidence of increased rates of psychotic episodes in individuals who use ACE inhibitors, compared to other classes of blood pressure–lowering medication.”
 

Caution warranted

Reached for comment, Timothy Sullivan, MD, chair of psychiatry and behavioral sciences at Staten Island University Hospital in New York, noted that this is an “extremely complicated” study and urged caution in interpreting the results.

“Since most people develop schizophrenia earlier in life, before they usually develop problems with blood pressure, it’s not so much that these drugs might cause schizophrenia,” Dr. Sullivan said.

“But because of their effects on this particular gene, there’s a possibility that they might worsen symptoms or in somebody with borderline risk might cause them to develop symptoms later in life. This may apply to a relatively small number of people who develop symptoms of schizophrenia in their 40s and beyond,” he added.

That’s where “pharmacovigilance” comes into play, Dr. Sullivan said. “In other words, we should be looking at people we’re treating with these drugs to see – might we be tipping some of them into illness states that they otherwise wouldn’t experience?”

Support for the study was provided by the National Health and Medical Research Council (Australia) and U.S. National Institute for Mental Health. Dr. Shah and Dr. Sullivan disclosed no relevant financial relationships.

A version of this article first appeared on Medscape.com.

ACE inhibitors may be associated with an increased risk for schizophrenia and may affect psychiatric symptoms, new research suggests.

Investigators found individuals who carry a genetic variant associated with lower levels of the ACE gene and protein have increased liability to schizophrenia, suggesting that drugs that lower ACE levels or activity may do the same.

“Our findings warrant further investigation into the role of ACE in schizophrenia and closer monitoring by clinicians of individuals, especially those with schizophrenia, who may be on medication that lower ACE activity, such as ACE inhibitors,” Sonia Shah, PhD, Institute for Biomedical Sciences, University of Queensland, Brisbane, Australia, said in an interview.

The study was published online March 10, 2021, in JAMA Psychiatry.
 

Antihypertensives and mental illness

Hypertension is common in patients with psychiatric disorders and observational studies have reported associations between antihypertensive medication and these disorders, although the findings have been mixed.

Dr. Shah and colleagues estimated the potential of different antihypertensive drug classes on schizophrenia, bipolar disorder, and major depressive disorder.

In a two-sample Mendelian randomization study, they evaluated ties between a single-nucleotide variant and drug-target gene expression derived from expression quantitative trait loci data in blood (sample 1) and the SNV disease association from published case-control, genomewide association studies (sample 2).

The analyses included 40,675 patients with schizophrenia and 64,643 controls; 20,352 with bipolar disorder and 31,358 controls; and 135,458 with major depressive disorder and 344,901 controls.

The major finding was that a one standard deviation–lower expression of the ACE gene in blood was associated with lower systolic blood pressure of 4.0 mm Hg (95% confidence interval, 2.7-5.3), but also an increased risk of schizophrenia (odds ratio, 1.75; 95% CI, 1.28-2.38).
 

Could ACE inhibitors worsen symptoms or trigger episodes?

In their article, the researchers noted that, in most patients, onset of schizophrenia occurs in late adolescence or early adult life, ruling out ACE inhibitor treatment as a potential causal factor for most cases.

“However, if lower ACE levels play a causal role for schizophrenia risk, it would be reasonable to hypothesize that further lowering of ACE activity in existing patients could worsen symptoms or trigger a new episode,” they wrote.

Dr. Shah emphasized that evidence from genetic analyses alone is “not sufficient to justify changes in prescription guidelines.”

“Patients should not stop taking these medications if they are effective at controlling their blood pressure and they don’t suffer any adverse effects. But it would be reasonable to encourage greater pharmacovigilance,” she said in an interview.

“One way in which we are hoping to follow up these findings,” said Dr. Shah, “is to access electronic health record data for millions of individuals to investigate if there is evidence of increased rates of psychotic episodes in individuals who use ACE inhibitors, compared to other classes of blood pressure–lowering medication.”
 

Caution warranted

Reached for comment, Timothy Sullivan, MD, chair of psychiatry and behavioral sciences at Staten Island University Hospital in New York, noted that this is an “extremely complicated” study and urged caution in interpreting the results.

“Since most people develop schizophrenia earlier in life, before they usually develop problems with blood pressure, it’s not so much that these drugs might cause schizophrenia,” Dr. Sullivan said.

“But because of their effects on this particular gene, there’s a possibility that they might worsen symptoms or in somebody with borderline risk might cause them to develop symptoms later in life. This may apply to a relatively small number of people who develop symptoms of schizophrenia in their 40s and beyond,” he added.

That’s where “pharmacovigilance” comes into play, Dr. Sullivan said. “In other words, we should be looking at people we’re treating with these drugs to see – might we be tipping some of them into illness states that they otherwise wouldn’t experience?”

Support for the study was provided by the National Health and Medical Research Council (Australia) and U.S. National Institute for Mental Health. Dr. Shah and Dr. Sullivan disclosed no relevant financial relationships.

A version of this article first appeared on Medscape.com.

Two newly published studies highlight recent success toward delaying the onset of type 1 diabetes in people at high risk and slowing progression in those with recent onset of the condition.

Both studies were initially presented in June 2020 at the annual scientific sessions of the American Diabetes Association and reported by this news organization at the time.  

As yet, neither of the two strategies – preserving insulin-producing pancreatic beta-cell function soon after diagnosis or delaying type 1 diabetes onset in those at high risk – represent a cure or certain disease prevention.

However, both can potentially lead to better long-term glycemic control with less hypoglycemia and a lower risk for diabetes-related complications.
 

Combination treatment prolongs beta-cell function in new-onset disease

The first study, entitled, “Anti–interleukin-21 antibody and liraglutide for the preservation of beta-cell function in adults with recent-onset type 1 diabetes,” was published online March 1, 2021, in The Lancet Diabetes & Endocrinology by Matthias von Herrath, MD, of Novo Nordisk, Søborg, Denmark, and colleagues.

The randomized, placebo-controlled, double-blind, phase 2 combination treatment trial involved 308 individuals aged 18-45 years who had been diagnosed with type 1 diabetes in the previous 20 weeks and still had residual beta-cell function.

Patients were randomized with 77 per group to receive monoclonal anti-IL-21 plus liraglutide, anti-IL-21 alone, liraglutide alone, or placebo. The antibody was given intravenously every 6 weeks and liraglutide or matching placebo were self-administered by daily injections.

Compared with placebo (ratio to baseline, 0.61; 39% decrease), the decrease in mixed meal tolerance test stimulated C-peptide concentration from baseline to week 54 – the primary outcome – was significantly smaller with combination treatment (0.90, 10% decrease; estimated treatment ratio, 1.48; P = .0017), but not with anti-IL-21 alone (1.23; P = .093) or liraglutide alone (1.12; P = .38).

Despite greater insulin use in the placebo group, the decrease in hemoglobin A1c (a key secondary outcome) at week 54 was greater with all active treatments (–0.50 percentage points) than with placebo (–0.10 percentage points), although the differences versus placebo were not significant.

“The combination of anti-IL-21 and liraglutide could preserve beta-cell function in recently diagnosed type 1 diabetes,” the researchers said.

“These results suggest that this combination has the potential to offer a novel and valuable disease-modifying therapy for patients with recently diagnosed type 1 diabetes. However, the efficacy and safety need to be further investigated in a phase 3 program,” Dr. von Herrath and colleagues concluded.
 

Teplizumab: 3-year data continue to show benefit

The other study looked at delaying the onset of type 1 diabetes. Entitled, “Teplizumab improves and stabilizes beta cell function in antibody-positive high-risk individuals,” the article was published online March 3, 2021, in Science Translational Medicine by Emily K. Sims, MD, of the department of pediatrics, Indiana University, Indianapolis, and colleagues.

This trial of the anti-CD3 monoclonal antibody adds an additional year of follow-up to the “game-changer” 2-year data reported in 2019.

Among the 76 individuals aged 8-49 years who were positive for two or more type 1 diabetes–related autoantibodies, 50% of those randomized to a single 14-day infusion course of teplizumab remained diabetes free at a median follow-up of 923 days, compared with only 22% of those who received placebo infusions (hazard ratio, 0.457; P = .01).

The teplizumab group had a greater average C-peptide area under the curve, compared with placebo, reflecting improved beta-cell function (1.96 vs 1.68 pmol/mL; P = .006).

C-peptide levels declined over time in the placebo group but stabilized in those receiving teplizumab (P = .0015).

“It is very encouraging to see that a single course of teplizumab delayed insulin dependence in this high-risk population for approximately 3 years versus placebo,” said Frank Martin, PhD, JDRF director of research at Provention Bio, which is developing teplizumab.

“These exciting results have been made possible by the unwavering efforts of TrialNet and Provention Bio. Teplizumab, if approved by the FDA, could positively change the course of disease development for people at risk of developing T1D and their standard of care,” he concluded.

The teplizumab study was funded by TrialNet. Dr. von Herrath is an employee of Novo Nordisk, which funded the study involving its drug liraglutide. Dr. Sims reported no relevant financial relationships.

A version of this article first appeared on Medscape.com.

Two newly published studies highlight recent success toward delaying the onset of type 1 diabetes in people at high risk and slowing progression in those with recent onset of the condition.

Both studies were initially presented in June 2020 at the annual scientific sessions of the American Diabetes Association and reported by this news organization at the time.  

As yet, neither of the two strategies – preserving insulin-producing pancreatic beta-cell function soon after diagnosis or delaying type 1 diabetes onset in those at high risk – represent a cure or certain disease prevention.

However, both can potentially lead to better long-term glycemic control with less hypoglycemia and a lower risk for diabetes-related complications.
 

Combination treatment prolongs beta-cell function in new-onset disease

The first study, entitled, “Anti–interleukin-21 antibody and liraglutide for the preservation of beta-cell function in adults with recent-onset type 1 diabetes,” was published online March 1, 2021, in The Lancet Diabetes & Endocrinology by Matthias von Herrath, MD, of Novo Nordisk, Søborg, Denmark, and colleagues.

The randomized, placebo-controlled, double-blind, phase 2 combination treatment trial involved 308 individuals aged 18-45 years who had been diagnosed with type 1 diabetes in the previous 20 weeks and still had residual beta-cell function.

Patients were randomized with 77 per group to receive monoclonal anti-IL-21 plus liraglutide, anti-IL-21 alone, liraglutide alone, or placebo. The antibody was given intravenously every 6 weeks and liraglutide or matching placebo were self-administered by daily injections.

Compared with placebo (ratio to baseline, 0.61; 39% decrease), the decrease in mixed meal tolerance test stimulated C-peptide concentration from baseline to week 54 – the primary outcome – was significantly smaller with combination treatment (0.90, 10% decrease; estimated treatment ratio, 1.48; P = .0017), but not with anti-IL-21 alone (1.23; P = .093) or liraglutide alone (1.12; P = .38).

Despite greater insulin use in the placebo group, the decrease in hemoglobin A1c (a key secondary outcome) at week 54 was greater with all active treatments (–0.50 percentage points) than with placebo (–0.10 percentage points), although the differences versus placebo were not significant.

“The combination of anti-IL-21 and liraglutide could preserve beta-cell function in recently diagnosed type 1 diabetes,” the researchers said.

“These results suggest that this combination has the potential to offer a novel and valuable disease-modifying therapy for patients with recently diagnosed type 1 diabetes. However, the efficacy and safety need to be further investigated in a phase 3 program,” Dr. von Herrath and colleagues concluded.
 

Teplizumab: 3-year data continue to show benefit

The other study looked at delaying the onset of type 1 diabetes. Entitled, “Teplizumab improves and stabilizes beta cell function in antibody-positive high-risk individuals,” the article was published online March 3, 2021, in Science Translational Medicine by Emily K. Sims, MD, of the department of pediatrics, Indiana University, Indianapolis, and colleagues.

This trial of the anti-CD3 monoclonal antibody adds an additional year of follow-up to the “game-changer” 2-year data reported in 2019.

Among the 76 individuals aged 8-49 years who were positive for two or more type 1 diabetes–related autoantibodies, 50% of those randomized to a single 14-day infusion course of teplizumab remained diabetes free at a median follow-up of 923 days, compared with only 22% of those who received placebo infusions (hazard ratio, 0.457; P = .01).

The teplizumab group had a greater average C-peptide area under the curve, compared with placebo, reflecting improved beta-cell function (1.96 vs 1.68 pmol/mL; P = .006).

C-peptide levels declined over time in the placebo group but stabilized in those receiving teplizumab (P = .0015).

“It is very encouraging to see that a single course of teplizumab delayed insulin dependence in this high-risk population for approximately 3 years versus placebo,” said Frank Martin, PhD, JDRF director of research at Provention Bio, which is developing teplizumab.

“These exciting results have been made possible by the unwavering efforts of TrialNet and Provention Bio. Teplizumab, if approved by the FDA, could positively change the course of disease development for people at risk of developing T1D and their standard of care,” he concluded.

The teplizumab study was funded by TrialNet. Dr. von Herrath is an employee of Novo Nordisk, which funded the study involving its drug liraglutide. Dr. Sims reported no relevant financial relationships.

A version of this article first appeared on Medscape.com.

Two newly published studies highlight recent success toward delaying the onset of type 1 diabetes in people at high risk and slowing progression in those with recent onset of the condition.

Both studies were initially presented in June 2020 at the annual scientific sessions of the American Diabetes Association and reported by this news organization at the time.  

As yet, neither of the two strategies – preserving insulin-producing pancreatic beta-cell function soon after diagnosis or delaying type 1 diabetes onset in those at high risk – represent a cure or certain disease prevention.

However, both can potentially lead to better long-term glycemic control with less hypoglycemia and a lower risk for diabetes-related complications.
 

Combination treatment prolongs beta-cell function in new-onset disease

The first study, entitled, “Anti–interleukin-21 antibody and liraglutide for the preservation of beta-cell function in adults with recent-onset type 1 diabetes,” was published online March 1, 2021, in The Lancet Diabetes & Endocrinology by Matthias von Herrath, MD, of Novo Nordisk, Søborg, Denmark, and colleagues.

The randomized, placebo-controlled, double-blind, phase 2 combination treatment trial involved 308 individuals aged 18-45 years who had been diagnosed with type 1 diabetes in the previous 20 weeks and still had residual beta-cell function.

Patients were randomized with 77 per group to receive monoclonal anti-IL-21 plus liraglutide, anti-IL-21 alone, liraglutide alone, or placebo. The antibody was given intravenously every 6 weeks and liraglutide or matching placebo were self-administered by daily injections.

Compared with placebo (ratio to baseline, 0.61; 39% decrease), the decrease in mixed meal tolerance test stimulated C-peptide concentration from baseline to week 54 – the primary outcome – was significantly smaller with combination treatment (0.90, 10% decrease; estimated treatment ratio, 1.48; P = .0017), but not with anti-IL-21 alone (1.23; P = .093) or liraglutide alone (1.12; P = .38).

Despite greater insulin use in the placebo group, the decrease in hemoglobin A1c (a key secondary outcome) at week 54 was greater with all active treatments (–0.50 percentage points) than with placebo (–0.10 percentage points), although the differences versus placebo were not significant.

“The combination of anti-IL-21 and liraglutide could preserve beta-cell function in recently diagnosed type 1 diabetes,” the researchers said.

“These results suggest that this combination has the potential to offer a novel and valuable disease-modifying therapy for patients with recently diagnosed type 1 diabetes. However, the efficacy and safety need to be further investigated in a phase 3 program,” Dr. von Herrath and colleagues concluded.
 

Teplizumab: 3-year data continue to show benefit

The other study looked at delaying the onset of type 1 diabetes. Entitled, “Teplizumab improves and stabilizes beta cell function in antibody-positive high-risk individuals,” the article was published online March 3, 2021, in Science Translational Medicine by Emily K. Sims, MD, of the department of pediatrics, Indiana University, Indianapolis, and colleagues.

This trial of the anti-CD3 monoclonal antibody adds an additional year of follow-up to the “game-changer” 2-year data reported in 2019.

Among the 76 individuals aged 8-49 years who were positive for two or more type 1 diabetes–related autoantibodies, 50% of those randomized to a single 14-day infusion course of teplizumab remained diabetes free at a median follow-up of 923 days, compared with only 22% of those who received placebo infusions (hazard ratio, 0.457; P = .01).

The teplizumab group had a greater average C-peptide area under the curve, compared with placebo, reflecting improved beta-cell function (1.96 vs 1.68 pmol/mL; P = .006).

C-peptide levels declined over time in the placebo group but stabilized in those receiving teplizumab (P = .0015).

“It is very encouraging to see that a single course of teplizumab delayed insulin dependence in this high-risk population for approximately 3 years versus placebo,” said Frank Martin, PhD, JDRF director of research at Provention Bio, which is developing teplizumab.

“These exciting results have been made possible by the unwavering efforts of TrialNet and Provention Bio. Teplizumab, if approved by the FDA, could positively change the course of disease development for people at risk of developing T1D and their standard of care,” he concluded.

The teplizumab study was funded by TrialNet. Dr. von Herrath is an employee of Novo Nordisk, which funded the study involving its drug liraglutide. Dr. Sims reported no relevant financial relationships.

A version of this article first appeared on Medscape.com.

Approximately a third of older patients treated with thyroid hormones report the concurrent use of medications that can interfere with the accuracy of thyroid function tests, potentially compromising treatment decisions, new research shows.

juststock/Thinkstock

“We know from previous studies that thyroid hormone use is common in older adults and that there are a multitude of medications that can interfere with thyroid function tests in different ways,” senior author Maria Papaleontiou, MD, told Medscape Medical News.

“However, to our knowledge, the extent of concurrent use of thyroid hormone and interfering medications in older adults, age 65 years and older, has not been previously explored,” added Dr. Papaleontiou, of the Division of Metabolism, Endocrinology and Diabetes, Department of Internal Medicine, University of Michigan, Ann Arbor.

The findings were presented as a poster during virtual ENDO 2021, the Endocrine Society’s annual meeting.

Commenting on the study, Thanh Duc Hoang, DO, an endocrinologist with the Walter Reed National Military Medical Center, in Bethesda, Md., said: “It is important for clinicians to be aware of various interactions and interferences of medications affecting the accuracy of thyroid function tests.”

“If patients are not able to discontinue the medications shortly before the bloodwork, the clinicians may consider ordering different thyroid tests or assays that avoid the interferences,” he told Medscape Medical News.
 

32% of patients taking meds that could interfere with tests

In evaluating data on 538,137 patients treated with thyroid hormones from the Corporate Data Warehouse of the Veterans Health Administration, spanning 2004-2017, first author Rachel Beeson, MD, and colleagues with the University of Michigan found most patients in the study were men (96.5%), White (77.1%), and had two or more comorbidities (62.6%).

Of this total, 170,261 (31.6%) patients treated with thyroid hormones, over a median follow-up of 56 months, were taking at least one drug that could potentially interfere with thyroid function tests.

Among the drugs with potential thyroid test interference, about 28% of patients were taking prednisone or prednisolone, 8% were taking amiodarone, and 1.42% were taking phenytoin. Other reported drugs that could potentially interfere included carbamazepine (0.91%), phenobarbital (0.15%), lithium (0.40%), and tamoxifen (0.11%).

Multivariate analysis showed that characteristics associated with those most likely to have concurrent medication use included non-Whites (OR, 1.18 vs Whites), Hispanic ethnicity (OR 1.11 vs non-Hispanic), female sex (OR 1.12 vs males), and presence of comorbidities (eg, Charlson-Deyo comorbidity score ≥ 2, OR,  2.47 vs score of 0).

Meanwhile, older patients age 85 years and over had a lower likelihood of concurrent medications interfering with thyroid tests (OR, 0.47 vs age 65-74 years).

The findings are concerning given the wide use of levothyroxine to treat hypothyroidism, which is the most widely prescribed drug in the United States.

“Our findings not only highlight the complexity of thyroid hormone management in older adults in the context of polypharmacy and multimorbidity, but they also draw attention to vulnerable groups for this practice, which included female patients, non-Whites, patients of Hispanic ethnicity, and patients with comorbidities,” Dr. Papaleontiou said.
 

Nature of interference possibilities varies

Medications or supplements can interfere with thyroid function tests in a variety of ways, she explained. “Some medications could lead to a decrease in the absorption of levothyroxine, others may affect how well the pill dissolves.”

In addition, certain medications can affect the circulation of thyroid hormone in the blood and how it binds with proteins, or they can lead to decreasing thyroid hormone levels due to a variety of interactions.

And in contrast, “What is even more challenging is that some medications or supplements may appear to affect thyroid function based on lab tests when in reality they don’t actually affect thyroid function and may lead to dose adjustments unnecessarily,” Dr. Papaleontiou noted.
 

Recommendations to counter interference

Current recommendations to try to counter the effects of polypharmacy on thyroid treatment include advising patients to take thyroid hormones on an empty stomach at least 30-60 minutes prior to eating for optimal absorption.

If the patient is taking medications known to interfere with absorption of thyroid hormones, the recommendation is to space those out by at least 4 hours.

“The big challenge in older adults is that many of them do experience polypharmacy, being at risk for multiple drug-drug interactions,” Dr. Papaleontiou said.

“Physicians and patients should be vigilant and communicate closely every time there is initiation of a new medication or supplement to consider whether there may be interference.”

The authors have reported no relevant financial relationships. Dr. Hoang has reported being a speaker for Acella Pharmaceuticals.

A version of this article first appeared on Medscape.com.

Approximately a third of older patients treated with thyroid hormones report the concurrent use of medications that can interfere with the accuracy of thyroid function tests, potentially compromising treatment decisions, new research shows.

juststock/Thinkstock

“We know from previous studies that thyroid hormone use is common in older adults and that there are a multitude of medications that can interfere with thyroid function tests in different ways,” senior author Maria Papaleontiou, MD, told Medscape Medical News.

“However, to our knowledge, the extent of concurrent use of thyroid hormone and interfering medications in older adults, age 65 years and older, has not been previously explored,” added Dr. Papaleontiou, of the Division of Metabolism, Endocrinology and Diabetes, Department of Internal Medicine, University of Michigan, Ann Arbor.

The findings were presented as a poster during virtual ENDO 2021, the Endocrine Society’s annual meeting.

Commenting on the study, Thanh Duc Hoang, DO, an endocrinologist with the Walter Reed National Military Medical Center, in Bethesda, Md., said: “It is important for clinicians to be aware of various interactions and interferences of medications affecting the accuracy of thyroid function tests.”

“If patients are not able to discontinue the medications shortly before the bloodwork, the clinicians may consider ordering different thyroid tests or assays that avoid the interferences,” he told Medscape Medical News.
 

32% of patients taking meds that could interfere with tests

In evaluating data on 538,137 patients treated with thyroid hormones from the Corporate Data Warehouse of the Veterans Health Administration, spanning 2004-2017, first author Rachel Beeson, MD, and colleagues with the University of Michigan found most patients in the study were men (96.5%), White (77.1%), and had two or more comorbidities (62.6%).

Of this total, 170,261 (31.6%) patients treated with thyroid hormones, over a median follow-up of 56 months, were taking at least one drug that could potentially interfere with thyroid function tests.

Among the drugs with potential thyroid test interference, about 28% of patients were taking prednisone or prednisolone, 8% were taking amiodarone, and 1.42% were taking phenytoin. Other reported drugs that could potentially interfere included carbamazepine (0.91%), phenobarbital (0.15%), lithium (0.40%), and tamoxifen (0.11%).

Multivariate analysis showed that characteristics associated with those most likely to have concurrent medication use included non-Whites (OR, 1.18 vs Whites), Hispanic ethnicity (OR 1.11 vs non-Hispanic), female sex (OR 1.12 vs males), and presence of comorbidities (eg, Charlson-Deyo comorbidity score ≥ 2, OR,  2.47 vs score of 0).

Meanwhile, older patients age 85 years and over had a lower likelihood of concurrent medications interfering with thyroid tests (OR, 0.47 vs age 65-74 years).

The findings are concerning given the wide use of levothyroxine to treat hypothyroidism, which is the most widely prescribed drug in the United States.

“Our findings not only highlight the complexity of thyroid hormone management in older adults in the context of polypharmacy and multimorbidity, but they also draw attention to vulnerable groups for this practice, which included female patients, non-Whites, patients of Hispanic ethnicity, and patients with comorbidities,” Dr. Papaleontiou said.
 

Nature of interference possibilities varies

Medications or supplements can interfere with thyroid function tests in a variety of ways, she explained. “Some medications could lead to a decrease in the absorption of levothyroxine, others may affect how well the pill dissolves.”

In addition, certain medications can affect the circulation of thyroid hormone in the blood and how it binds with proteins, or they can lead to decreasing thyroid hormone levels due to a variety of interactions.

And in contrast, “What is even more challenging is that some medications or supplements may appear to affect thyroid function based on lab tests when in reality they don’t actually affect thyroid function and may lead to dose adjustments unnecessarily,” Dr. Papaleontiou noted.
 

Recommendations to counter interference

Current recommendations to try to counter the effects of polypharmacy on thyroid treatment include advising patients to take thyroid hormones on an empty stomach at least 30-60 minutes prior to eating for optimal absorption.

If the patient is taking medications known to interfere with absorption of thyroid hormones, the recommendation is to space those out by at least 4 hours.

“The big challenge in older adults is that many of them do experience polypharmacy, being at risk for multiple drug-drug interactions,” Dr. Papaleontiou said.

“Physicians and patients should be vigilant and communicate closely every time there is initiation of a new medication or supplement to consider whether there may be interference.”

The authors have reported no relevant financial relationships. Dr. Hoang has reported being a speaker for Acella Pharmaceuticals.

A version of this article first appeared on Medscape.com.

Approximately a third of older patients treated with thyroid hormones report the concurrent use of medications that can interfere with the accuracy of thyroid function tests, potentially compromising treatment decisions, new research shows.

juststock/Thinkstock

“We know from previous studies that thyroid hormone use is common in older adults and that there are a multitude of medications that can interfere with thyroid function tests in different ways,” senior author Maria Papaleontiou, MD, told Medscape Medical News.

“However, to our knowledge, the extent of concurrent use of thyroid hormone and interfering medications in older adults, age 65 years and older, has not been previously explored,” added Dr. Papaleontiou, of the Division of Metabolism, Endocrinology and Diabetes, Department of Internal Medicine, University of Michigan, Ann Arbor.

The findings were presented as a poster during virtual ENDO 2021, the Endocrine Society’s annual meeting.

Commenting on the study, Thanh Duc Hoang, DO, an endocrinologist with the Walter Reed National Military Medical Center, in Bethesda, Md., said: “It is important for clinicians to be aware of various interactions and interferences of medications affecting the accuracy of thyroid function tests.”

“If patients are not able to discontinue the medications shortly before the bloodwork, the clinicians may consider ordering different thyroid tests or assays that avoid the interferences,” he told Medscape Medical News.
 

32% of patients taking meds that could interfere with tests

In evaluating data on 538,137 patients treated with thyroid hormones from the Corporate Data Warehouse of the Veterans Health Administration, spanning 2004-2017, first author Rachel Beeson, MD, and colleagues with the University of Michigan found most patients in the study were men (96.5%), White (77.1%), and had two or more comorbidities (62.6%).

Of this total, 170,261 (31.6%) patients treated with thyroid hormones, over a median follow-up of 56 months, were taking at least one drug that could potentially interfere with thyroid function tests.

Among the drugs with potential thyroid test interference, about 28% of patients were taking prednisone or prednisolone, 8% were taking amiodarone, and 1.42% were taking phenytoin. Other reported drugs that could potentially interfere included carbamazepine (0.91%), phenobarbital (0.15%), lithium (0.40%), and tamoxifen (0.11%).

Multivariate analysis showed that characteristics associated with those most likely to have concurrent medication use included non-Whites (OR, 1.18 vs Whites), Hispanic ethnicity (OR 1.11 vs non-Hispanic), female sex (OR 1.12 vs males), and presence of comorbidities (eg, Charlson-Deyo comorbidity score ≥ 2, OR,  2.47 vs score of 0).

Meanwhile, older patients age 85 years and over had a lower likelihood of concurrent medications interfering with thyroid tests (OR, 0.47 vs age 65-74 years).

The findings are concerning given the wide use of levothyroxine to treat hypothyroidism, which is the most widely prescribed drug in the United States.

“Our findings not only highlight the complexity of thyroid hormone management in older adults in the context of polypharmacy and multimorbidity, but they also draw attention to vulnerable groups for this practice, which included female patients, non-Whites, patients of Hispanic ethnicity, and patients with comorbidities,” Dr. Papaleontiou said.
 

Nature of interference possibilities varies

Medications or supplements can interfere with thyroid function tests in a variety of ways, she explained. “Some medications could lead to a decrease in the absorption of levothyroxine, others may affect how well the pill dissolves.”

In addition, certain medications can affect the circulation of thyroid hormone in the blood and how it binds with proteins, or they can lead to decreasing thyroid hormone levels due to a variety of interactions.

And in contrast, “What is even more challenging is that some medications or supplements may appear to affect thyroid function based on lab tests when in reality they don’t actually affect thyroid function and may lead to dose adjustments unnecessarily,” Dr. Papaleontiou noted.
 

Recommendations to counter interference

Current recommendations to try to counter the effects of polypharmacy on thyroid treatment include advising patients to take thyroid hormones on an empty stomach at least 30-60 minutes prior to eating for optimal absorption.

If the patient is taking medications known to interfere with absorption of thyroid hormones, the recommendation is to space those out by at least 4 hours.

“The big challenge in older adults is that many of them do experience polypharmacy, being at risk for multiple drug-drug interactions,” Dr. Papaleontiou said.

“Physicians and patients should be vigilant and communicate closely every time there is initiation of a new medication or supplement to consider whether there may be interference.”

The authors have reported no relevant financial relationships. Dr. Hoang has reported being a speaker for Acella Pharmaceuticals.

A version of this article first appeared on Medscape.com.

In a placebo-controlled randomized trial, a preprocedural dose of colchicine administered immediately before percutaneous coronary intervention (PCI) for an acute ST-segment elevated myocardial infarction (STEMI) did not reduce the no-reflow phenomenon or improve outcomes.

No-reflow, in which insufficient myocardial perfusion is present even though the coronary artery appears patent, was the primary outcome, and the proportion of patients experiencing this event was exactly the same (14.4%) in the colchicine and placebo groups, reported Yaser Jenab, MD, at CRT 2021 sponsored by MedStar Heart & Vascular Institute.

The hypothesis that colchicine would offer benefit in this setting was largely based on the Colchicine Cardiovascular Outcomes Trial (COLCOT). In that study, colchicine was associated with a 23% reduction in risk for major adverse cardiovascular events (MACE) relative to placebo when administered within 30 days after a myocardial infarction (hazard ratio, 0.77; P = .02).

The benefit in that trial was attributed to an anti-inflammatory effect, according to Dr. Jenab, associate professor of cardiology at Tehran (Iran) Heart Center. In particular as it relates to vascular disease, he cited experimental studies associating colchicine with a reduction in neutrophil activation and adherence to vascular endothelium.

The rationale for a preprocedural approach to colchicine was supplied by a subsequent time-to-treatment COLCOT analysis. In this study, MACE risk reduction for colchicine climbed to 48% (HR 0.52) for those treated within 3 days of the MI but largely disappeared (HR 0.96) if treatment was started at least 8 days post MI.
 

PodCAST-PCI trial

In the preprocedural study, called the PodCAST-PCI trial, 321 acute STEMI patients were randomized. Patients received a 1-mg dose of oral colchicine or placebo at the time PCI was scheduled. Another dose of colchicine (0.5 mg) or placebo was administered 1 hour after the procedure.

Of secondary outcomes, which included MACE at 1 month and 1 year, ST-segment resolution at 1 month, and change in inflammatory markers at 1 month, none were significant. Few even trended for significance.

For MACE, which included cardiac death, stroke, nonfatal MI, new hospitalization due to heart failure, or target vessel revascularization, the rates were lower in the colchicine group at 1 month (4.3% vs. 7.5%) and 1 year (9.3% vs. 11.2%), but neither approached significance.

For ST-segment resolution, the proportions were generally comparable among the colchicine and placebo groups, respectively, for the proportion below 50% (18.6% vs. 23.1%), between 50% and 70% (16.8% vs. 15.6%), and above 70% (64.6% vs. 61.3%).

The average troponin levels were nonsignificantly lower at 6 hours (1,847 vs. 2,883 ng/mL) in the colchicine group but higher at 48 hours (1,197 vs. 1,147 ng/mL). The average C-reactive protein (CRP) levels at 48 hours were nonsignificantly lower on colchicine (176.5 vs. 244.5 mg/L).

There were no significant differences in postprocedural perfusion, as measured with TIMI blood flow, or in the rate of stent thrombosis, which occurred in roughly 3% of each group of patients.

The small sample size was one limitation of this study, Dr. Jenab acknowledged. For this and other reasons, he cautioned that these data are not definitive and do not preclude a benefit on clinical outcomes in a study with a larger size, a different design, or different dosing.
 

Timing might be the issue

However, even if colchicine has a potential benefit in this setting, timing might be a major obstacle, according to Binata Shah, MD, associate director of research for the Cardiac Catheterization Laboratory at New York University.

“We have learned from our rheumatology colleagues that peak plasma levels of colchicine are not achieved for at least 1 hour after the full loading dose,” Dr. Shah said. “With us moving so quickly in a primary PCI setting, it is hard to imagine that colchicine would have had time to really kick in and exert its anti-inflammatory effect.”

Indeed, the problem might be worse than reaching the peak plasma level.

“Even though peak plasma levels occur as early as 1 hour after a full loading dose, we see that it takes about 24 hours to really see the effects translate downstream into more systemic inflammatory markers such as CRP and interleukin-6,” she added. If lowering these signals of inflammation is predictive of benefit, than this might be the biggest obstacle to benefit from colchicine in an urgent treatment setting.

Dr. Jenab and Dr. Shah reported no potential conflicts of interest.

In a placebo-controlled randomized trial, a preprocedural dose of colchicine administered immediately before percutaneous coronary intervention (PCI) for an acute ST-segment elevated myocardial infarction (STEMI) did not reduce the no-reflow phenomenon or improve outcomes.

No-reflow, in which insufficient myocardial perfusion is present even though the coronary artery appears patent, was the primary outcome, and the proportion of patients experiencing this event was exactly the same (14.4%) in the colchicine and placebo groups, reported Yaser Jenab, MD, at CRT 2021 sponsored by MedStar Heart & Vascular Institute.

The hypothesis that colchicine would offer benefit in this setting was largely based on the Colchicine Cardiovascular Outcomes Trial (COLCOT). In that study, colchicine was associated with a 23% reduction in risk for major adverse cardiovascular events (MACE) relative to placebo when administered within 30 days after a myocardial infarction (hazard ratio, 0.77; P = .02).

The benefit in that trial was attributed to an anti-inflammatory effect, according to Dr. Jenab, associate professor of cardiology at Tehran (Iran) Heart Center. In particular as it relates to vascular disease, he cited experimental studies associating colchicine with a reduction in neutrophil activation and adherence to vascular endothelium.

The rationale for a preprocedural approach to colchicine was supplied by a subsequent time-to-treatment COLCOT analysis. In this study, MACE risk reduction for colchicine climbed to 48% (HR 0.52) for those treated within 3 days of the MI but largely disappeared (HR 0.96) if treatment was started at least 8 days post MI.
 

PodCAST-PCI trial

In the preprocedural study, called the PodCAST-PCI trial, 321 acute STEMI patients were randomized. Patients received a 1-mg dose of oral colchicine or placebo at the time PCI was scheduled. Another dose of colchicine (0.5 mg) or placebo was administered 1 hour after the procedure.

Of secondary outcomes, which included MACE at 1 month and 1 year, ST-segment resolution at 1 month, and change in inflammatory markers at 1 month, none were significant. Few even trended for significance.

For MACE, which included cardiac death, stroke, nonfatal MI, new hospitalization due to heart failure, or target vessel revascularization, the rates were lower in the colchicine group at 1 month (4.3% vs. 7.5%) and 1 year (9.3% vs. 11.2%), but neither approached significance.

For ST-segment resolution, the proportions were generally comparable among the colchicine and placebo groups, respectively, for the proportion below 50% (18.6% vs. 23.1%), between 50% and 70% (16.8% vs. 15.6%), and above 70% (64.6% vs. 61.3%).

The average troponin levels were nonsignificantly lower at 6 hours (1,847 vs. 2,883 ng/mL) in the colchicine group but higher at 48 hours (1,197 vs. 1,147 ng/mL). The average C-reactive protein (CRP) levels at 48 hours were nonsignificantly lower on colchicine (176.5 vs. 244.5 mg/L).

There were no significant differences in postprocedural perfusion, as measured with TIMI blood flow, or in the rate of stent thrombosis, which occurred in roughly 3% of each group of patients.

The small sample size was one limitation of this study, Dr. Jenab acknowledged. For this and other reasons, he cautioned that these data are not definitive and do not preclude a benefit on clinical outcomes in a study with a larger size, a different design, or different dosing.
 

Timing might be the issue

However, even if colchicine has a potential benefit in this setting, timing might be a major obstacle, according to Binata Shah, MD, associate director of research for the Cardiac Catheterization Laboratory at New York University.

“We have learned from our rheumatology colleagues that peak plasma levels of colchicine are not achieved for at least 1 hour after the full loading dose,” Dr. Shah said. “With us moving so quickly in a primary PCI setting, it is hard to imagine that colchicine would have had time to really kick in and exert its anti-inflammatory effect.”

Indeed, the problem might be worse than reaching the peak plasma level.

“Even though peak plasma levels occur as early as 1 hour after a full loading dose, we see that it takes about 24 hours to really see the effects translate downstream into more systemic inflammatory markers such as CRP and interleukin-6,” she added. If lowering these signals of inflammation is predictive of benefit, than this might be the biggest obstacle to benefit from colchicine in an urgent treatment setting.

Dr. Jenab and Dr. Shah reported no potential conflicts of interest.

In a placebo-controlled randomized trial, a preprocedural dose of colchicine administered immediately before percutaneous coronary intervention (PCI) for an acute ST-segment elevated myocardial infarction (STEMI) did not reduce the no-reflow phenomenon or improve outcomes.

No-reflow, in which insufficient myocardial perfusion is present even though the coronary artery appears patent, was the primary outcome, and the proportion of patients experiencing this event was exactly the same (14.4%) in the colchicine and placebo groups, reported Yaser Jenab, MD, at CRT 2021 sponsored by MedStar Heart & Vascular Institute.

The hypothesis that colchicine would offer benefit in this setting was largely based on the Colchicine Cardiovascular Outcomes Trial (COLCOT). In that study, colchicine was associated with a 23% reduction in risk for major adverse cardiovascular events (MACE) relative to placebo when administered within 30 days after a myocardial infarction (hazard ratio, 0.77; P = .02).

The benefit in that trial was attributed to an anti-inflammatory effect, according to Dr. Jenab, associate professor of cardiology at Tehran (Iran) Heart Center. In particular as it relates to vascular disease, he cited experimental studies associating colchicine with a reduction in neutrophil activation and adherence to vascular endothelium.

The rationale for a preprocedural approach to colchicine was supplied by a subsequent time-to-treatment COLCOT analysis. In this study, MACE risk reduction for colchicine climbed to 48% (HR 0.52) for those treated within 3 days of the MI but largely disappeared (HR 0.96) if treatment was started at least 8 days post MI.
 

PodCAST-PCI trial

In the preprocedural study, called the PodCAST-PCI trial, 321 acute STEMI patients were randomized. Patients received a 1-mg dose of oral colchicine or placebo at the time PCI was scheduled. Another dose of colchicine (0.5 mg) or placebo was administered 1 hour after the procedure.

Of secondary outcomes, which included MACE at 1 month and 1 year, ST-segment resolution at 1 month, and change in inflammatory markers at 1 month, none were significant. Few even trended for significance.

For MACE, which included cardiac death, stroke, nonfatal MI, new hospitalization due to heart failure, or target vessel revascularization, the rates were lower in the colchicine group at 1 month (4.3% vs. 7.5%) and 1 year (9.3% vs. 11.2%), but neither approached significance.

For ST-segment resolution, the proportions were generally comparable among the colchicine and placebo groups, respectively, for the proportion below 50% (18.6% vs. 23.1%), between 50% and 70% (16.8% vs. 15.6%), and above 70% (64.6% vs. 61.3%).

The average troponin levels were nonsignificantly lower at 6 hours (1,847 vs. 2,883 ng/mL) in the colchicine group but higher at 48 hours (1,197 vs. 1,147 ng/mL). The average C-reactive protein (CRP) levels at 48 hours were nonsignificantly lower on colchicine (176.5 vs. 244.5 mg/L).

There were no significant differences in postprocedural perfusion, as measured with TIMI blood flow, or in the rate of stent thrombosis, which occurred in roughly 3% of each group of patients.

The small sample size was one limitation of this study, Dr. Jenab acknowledged. For this and other reasons, he cautioned that these data are not definitive and do not preclude a benefit on clinical outcomes in a study with a larger size, a different design, or different dosing.
 

Timing might be the issue

However, even if colchicine has a potential benefit in this setting, timing might be a major obstacle, according to Binata Shah, MD, associate director of research for the Cardiac Catheterization Laboratory at New York University.

“We have learned from our rheumatology colleagues that peak plasma levels of colchicine are not achieved for at least 1 hour after the full loading dose,” Dr. Shah said. “With us moving so quickly in a primary PCI setting, it is hard to imagine that colchicine would have had time to really kick in and exert its anti-inflammatory effect.”

Indeed, the problem might be worse than reaching the peak plasma level.

“Even though peak plasma levels occur as early as 1 hour after a full loading dose, we see that it takes about 24 hours to really see the effects translate downstream into more systemic inflammatory markers such as CRP and interleukin-6,” she added. If lowering these signals of inflammation is predictive of benefit, than this might be the biggest obstacle to benefit from colchicine in an urgent treatment setting.

Dr. Jenab and Dr. Shah reported no potential conflicts of interest.

After 10 years of follow-up, event-free survival and overall survival were similar between conventional chemotherapy treated patients with aggressive B-cell lymphoma and those receiving high-dose chemotherapy followed by autologous hematopoietic stem-cell transplantation (HSCT), according to a report published online in the Lancet Hematology.

Michael Bonert/WikimediaCommons/CC BY-SA 3.0

The open-label, randomized, phase 3 trial (NCT00129090) was conducted across 61 centers in Germany on patients aged 18-60 years who had newly diagnosed, high-risk, aggressive B-cell lymphoma, according to Fabian Frontzek, MD, of the University Hospital Münster (Germany) and colleagues.

Between March 2003 and April 2009, patients were randomly assigned to eight cycles of conventional chemotherapy (cyclophosphamide, doxorubicin, vincristine, etoposide, and prednisolone) plus rituximab (R-CHOEP-14) or four cycles of high-dose chemotherapy plus rituximab followed by autologous HSCT (R-MegaCHOEP). The intention-to-treat population comprised 130 patients in the R-CHOEP-14 group and 132 patients in the R-MegaCHOEP group. The median follow-up was 9.3 years.
 

Similar outcomes

The 10-year event-free survival was 51% in the R-MegaCHOEP group and 57% in the R-CHOEP-14 group, a nonsignificant difference (P = .23). Similarly, the 10-year progression-free survival was 59% in the

R-MegaCHOEP group and 60% (P = .64). The 10-year overall survival was 66% in the R-MegaCHOEP group and 72% in the R-CHOEP-14 group (P = .26). Among the 190 patients who had complete remission or unconfirmed complete remission, relapse occurred in 30 (16%); 17 (17%) of 100 patients in the R-CHOEP-14 group and 13 (14%) of 90 patients in the R-MegaCHOEP group.

In terms of secondary malignancies, 22 were reported in the intention-to-treat population; comprising 12 (9%) of 127 patients in the R-CHOEP-14 group and 10 (8%) of 126 patients in the R-MegaCHOEP group.

Patients who relapsed with aggressive histology and with CNS involvement in particular had worse outcomes and “represent a group with an unmet medical need, for which new molecular and cellular therapies should be studied,” the authors stated.

“This study shows that, in the rituximab era, high-dose therapy and autologous HSCT in first-line treatment does not improve long-term survival of younger high-risk patients with aggressive B-cell lymphoma. The R-CHOEP-14 regimen led to favorable outcomes, supporting its continued use in such patients,” the researchers concluded.

In an accompanying commentary, Gita Thanarajasingam, MD, of the Mayo Clinic, Rochester, Minn., and colleagues added that the issue of long-term outcomes is critical to evaluating these new regimens.

They applauded the inclusion of secondary malignancies in the long-term follow-up, but regretted the lack of the, admittedly resource-intensive, information on long-term nonneoplastic adverse events. They added that “the burden of late adverse events such as cardiotoxicity, cumulative neuropathy, delayed infections, or lasting cognitive effects, among others that might drive substantial morbidity, does matter to lymphoma survivors.”

They also commented on the importance of considering effects on fertility in these patients, noting that R-MegaCHOEP patients would be unable to conceive naturally, but that the effect of R-CHOEP-14 was less clear.

“We encourage ongoing emphasis on this type of longitudinal follow-up of secondary malignancies and other nonneoplastic late toxicities in phase 3 studies as well as in the real world in hematological malignancies, so that after prioritizing cure in the front-line setting, we do not neglect the life we have helped survivors achieve for years and decades to come,” they concluded.

The study was sponsored by the German High-Grade Non-Hodgkin’s Lymphoma Study Group. The authors reported grants, personal fees, and non-financial support from multiple pharmaceutical and biotechnology companies. Dr. Thanarajasingam and her colleagues reported that they had no competing interests.

[email protected]

After 10 years of follow-up, event-free survival and overall survival were similar between conventional chemotherapy treated patients with aggressive B-cell lymphoma and those receiving high-dose chemotherapy followed by autologous hematopoietic stem-cell transplantation (HSCT), according to a report published online in the Lancet Hematology.

Michael Bonert/WikimediaCommons/CC BY-SA 3.0

The open-label, randomized, phase 3 trial (NCT00129090) was conducted across 61 centers in Germany on patients aged 18-60 years who had newly diagnosed, high-risk, aggressive B-cell lymphoma, according to Fabian Frontzek, MD, of the University Hospital Münster (Germany) and colleagues.

Between March 2003 and April 2009, patients were randomly assigned to eight cycles of conventional chemotherapy (cyclophosphamide, doxorubicin, vincristine, etoposide, and prednisolone) plus rituximab (R-CHOEP-14) or four cycles of high-dose chemotherapy plus rituximab followed by autologous HSCT (R-MegaCHOEP). The intention-to-treat population comprised 130 patients in the R-CHOEP-14 group and 132 patients in the R-MegaCHOEP group. The median follow-up was 9.3 years.
 

Similar outcomes

The 10-year event-free survival was 51% in the R-MegaCHOEP group and 57% in the R-CHOEP-14 group, a nonsignificant difference (P = .23). Similarly, the 10-year progression-free survival was 59% in the

R-MegaCHOEP group and 60% (P = .64). The 10-year overall survival was 66% in the R-MegaCHOEP group and 72% in the R-CHOEP-14 group (P = .26). Among the 190 patients who had complete remission or unconfirmed complete remission, relapse occurred in 30 (16%); 17 (17%) of 100 patients in the R-CHOEP-14 group and 13 (14%) of 90 patients in the R-MegaCHOEP group.

In terms of secondary malignancies, 22 were reported in the intention-to-treat population; comprising 12 (9%) of 127 patients in the R-CHOEP-14 group and 10 (8%) of 126 patients in the R-MegaCHOEP group.

Patients who relapsed with aggressive histology and with CNS involvement in particular had worse outcomes and “represent a group with an unmet medical need, for which new molecular and cellular therapies should be studied,” the authors stated.

“This study shows that, in the rituximab era, high-dose therapy and autologous HSCT in first-line treatment does not improve long-term survival of younger high-risk patients with aggressive B-cell lymphoma. The R-CHOEP-14 regimen led to favorable outcomes, supporting its continued use in such patients,” the researchers concluded.

In an accompanying commentary, Gita Thanarajasingam, MD, of the Mayo Clinic, Rochester, Minn., and colleagues added that the issue of long-term outcomes is critical to evaluating these new regimens.

They applauded the inclusion of secondary malignancies in the long-term follow-up, but regretted the lack of the, admittedly resource-intensive, information on long-term nonneoplastic adverse events. They added that “the burden of late adverse events such as cardiotoxicity, cumulative neuropathy, delayed infections, or lasting cognitive effects, among others that might drive substantial morbidity, does matter to lymphoma survivors.”

They also commented on the importance of considering effects on fertility in these patients, noting that R-MegaCHOEP patients would be unable to conceive naturally, but that the effect of R-CHOEP-14 was less clear.

“We encourage ongoing emphasis on this type of longitudinal follow-up of secondary malignancies and other nonneoplastic late toxicities in phase 3 studies as well as in the real world in hematological malignancies, so that after prioritizing cure in the front-line setting, we do not neglect the life we have helped survivors achieve for years and decades to come,” they concluded.

The study was sponsored by the German High-Grade Non-Hodgkin’s Lymphoma Study Group. The authors reported grants, personal fees, and non-financial support from multiple pharmaceutical and biotechnology companies. Dr. Thanarajasingam and her colleagues reported that they had no competing interests.

[email protected]

After 10 years of follow-up, event-free survival and overall survival were similar between conventional chemotherapy treated patients with aggressive B-cell lymphoma and those receiving high-dose chemotherapy followed by autologous hematopoietic stem-cell transplantation (HSCT), according to a report published online in the Lancet Hematology.

Michael Bonert/WikimediaCommons/CC BY-SA 3.0

The open-label, randomized, phase 3 trial (NCT00129090) was conducted across 61 centers in Germany on patients aged 18-60 years who had newly diagnosed, high-risk, aggressive B-cell lymphoma, according to Fabian Frontzek, MD, of the University Hospital Münster (Germany) and colleagues.

Between March 2003 and April 2009, patients were randomly assigned to eight cycles of conventional chemotherapy (cyclophosphamide, doxorubicin, vincristine, etoposide, and prednisolone) plus rituximab (R-CHOEP-14) or four cycles of high-dose chemotherapy plus rituximab followed by autologous HSCT (R-MegaCHOEP). The intention-to-treat population comprised 130 patients in the R-CHOEP-14 group and 132 patients in the R-MegaCHOEP group. The median follow-up was 9.3 years.
 

Similar outcomes

The 10-year event-free survival was 51% in the R-MegaCHOEP group and 57% in the R-CHOEP-14 group, a nonsignificant difference (P = .23). Similarly, the 10-year progression-free survival was 59% in the

R-MegaCHOEP group and 60% (P = .64). The 10-year overall survival was 66% in the R-MegaCHOEP group and 72% in the R-CHOEP-14 group (P = .26). Among the 190 patients who had complete remission or unconfirmed complete remission, relapse occurred in 30 (16%); 17 (17%) of 100 patients in the R-CHOEP-14 group and 13 (14%) of 90 patients in the R-MegaCHOEP group.

In terms of secondary malignancies, 22 were reported in the intention-to-treat population; comprising 12 (9%) of 127 patients in the R-CHOEP-14 group and 10 (8%) of 126 patients in the R-MegaCHOEP group.

Patients who relapsed with aggressive histology and with CNS involvement in particular had worse outcomes and “represent a group with an unmet medical need, for which new molecular and cellular therapies should be studied,” the authors stated.

“This study shows that, in the rituximab era, high-dose therapy and autologous HSCT in first-line treatment does not improve long-term survival of younger high-risk patients with aggressive B-cell lymphoma. The R-CHOEP-14 regimen led to favorable outcomes, supporting its continued use in such patients,” the researchers concluded.

In an accompanying commentary, Gita Thanarajasingam, MD, of the Mayo Clinic, Rochester, Minn., and colleagues added that the issue of long-term outcomes is critical to evaluating these new regimens.

They applauded the inclusion of secondary malignancies in the long-term follow-up, but regretted the lack of the, admittedly resource-intensive, information on long-term nonneoplastic adverse events. They added that “the burden of late adverse events such as cardiotoxicity, cumulative neuropathy, delayed infections, or lasting cognitive effects, among others that might drive substantial morbidity, does matter to lymphoma survivors.”

They also commented on the importance of considering effects on fertility in these patients, noting that R-MegaCHOEP patients would be unable to conceive naturally, but that the effect of R-CHOEP-14 was less clear.

“We encourage ongoing emphasis on this type of longitudinal follow-up of secondary malignancies and other nonneoplastic late toxicities in phase 3 studies as well as in the real world in hematological malignancies, so that after prioritizing cure in the front-line setting, we do not neglect the life we have helped survivors achieve for years and decades to come,” they concluded.

The study was sponsored by the German High-Grade Non-Hodgkin’s Lymphoma Study Group. The authors reported grants, personal fees, and non-financial support from multiple pharmaceutical and biotechnology companies. Dr. Thanarajasingam and her colleagues reported that they had no competing interests.

[email protected]

Medicare payments for branded neurologic drugs jumped 50% over a 5-year period, while claims for these medications increased by just 8%, new research shows. Results of the retrospective study also showed that most of the increased costs for these agents were due to rising costs for neuroimmunology drugs, mainly for those used to treat multiple sclerosis (MS).

“The same brand name medication in 2017 cost approximately 50% more than in 2013,” said Adam de Havenon, MD, assistant professor of neurology, University of Utah, Salt Lake City.

“An analogy would be if you bought an iPhone 5 in 2013 for $500, and then in 2017, you were asked to pay $750 for the exact same iPhone 5,” Dr. de Havenon added.

The study findings were published online March 10 in the journal Neurology.
 

$26 billion in payments

Both neurologists and patients are concerned about the high cost of prescription drugs for neurologic diseases, and Medicare Part D data indicate that these drugs are the most expensive component of neurologic care, the researchers noted. In addition, out-of-pocket costs have increased significantly for patients with neurologic disease such as Parkinson’s disease, epilepsy, and MS.

To understand trends in payments for neurologic drugs, Dr. de Havenon and colleagues analyzed Medicare Part D claims filed from 2013 to 2017. The payments include costs paid by Medicare, the patient, government subsidies, and other third-party payers.

In addition to examining more current Medicare Part D data than previous studies, the current analysis examined all medications prescribed by neurologists that consistently remained branded or generic during the 5-year study period, said Dr. de Havenon. This approach resulted in a large number of claims and a large total cost.

To calculate the percentage change in annual payment claims, the researchers used 2013 prices as a reference point. They identified drugs named in 2013 claims and classified them as generic, brand-name only, or brand-name with generic equivalent. Researchers also divided the drugs by neurologic subspecialty.

The analysis included 520 drugs, all of which were available in each year of the study period. Of these drugs, 322 were generic, 61 were brand-name only, and 137 were brand-name with a generic equivalent. There were 90.7 million total claims.

Results showed total payments amounted to $26.65 billion. Yearly total payments increased from $4.05 billion in 2013 to $6.09 billion in 2017, representing a 50.4% increase, even after adjusting for inflation. Total claims increased by 7.6% – from 17.1 million in 2013 to 18.4 million in 2017.

From 2013 to 2017, claim payments increased by 0.6% for generic drugs, 42.4% for brand-name only drugs, and 45% for brand-name drugs with generic equivalents. The proportion of claims increased from 81.9% to 88% for generic drugs and from 4.9% to 6.2% for brand-name only drugs.

However, the proportion of claims for brand-name drugs with generic equivalents decreased from 13.3% to 5.8%.
 

Treatment barrier

Neuroimmunologic drugs, most of which were prescribed for MS, had exceptional cost, the researchers noted. These drugs accounted for more than 50% of payments but only 4.3% of claims. Claim payment for these drugs increased by 46.9% during the study period, from $3,337 to $4,902.

When neuroimmunologic drugs were removed from the analysis there was still significant increase in claim payments for brand-name only drugs (50.4%) and brand-name drugs with generic equivalents (45.6%).

Although neuroimmunologic medicines, including monoclonal antibodies, are more expensive to produce, this factor alone does not explain their exceptional cost, said Dr. de Havenon. “The high cost of brand-name drugs in this speciality is likely because the market bears it,” he added. “In other words, MS is a disabling disease and the medications work, so historically the Centers for Medicare & Medicaid Services have been willing to tolerate the high cost of these primarily brand-name medications.”

Several countries have controlled drug costs by negotiating with pharmaceutical companies and through legislation, Dr. de Havenon noted.

“My intent with this article was to raise awareness on the topic, which I struggle with frequently as a clinician. I know I want my patients to have a medication, but the cost prevents it,” he said.
 

‘Unfettered’ price-setting

Commenting on the findings, Robert J. Fox, MD, vice chair for research at the Neurological Institute of the Cleveland Clinic, said the study “brings into clear light” what neurologists, particularly those who treat MS, have long suspected but did not really know. These neurologists “are typically distanced from the payment aspects of the medications they prescribe,” said Dr. Fox, who was not involved with the research.

Although a particular strength of the study was its comprehensiveness, the researchers excluded infusion claims – which account for a large portion of total patient care costs for many disorders, he noted.

Drugs for MS historically have been expensive, ostensibly because of their high cost of development. In addition, the large and continued price increase that occurs long after these drugs have been approved remains unexplained, said Dr. Fox.

He noted that the study findings might not directly affect clinical practice because neurologists will continue prescribing medications they think are best for their patients. “Instead, I think this is a lesson to lawmakers about the massive error in the Medicare Modernization Act of 2003, where the federal government was prohibited from negotiating drug prices. If the seller is unfettered in setting a price, then no one should be surprised when the price rises,” Dr. Fox said.

Because many new drugs and new generic formulations for treating MS have become available during the past year, “repeating these types of economic studies for the period 2020-2025 will help us understand if generic competition – as well as new laws if they are passed – alter price,” he concluded.

The study was funded by the American Academy of Neurology, which publishes Neurology. Dr. de Havenon has received clinical research funding from AMAG Pharmaceuticals and Regeneron Pharmaceuticals. Dr. Fox receives consulting fees from many pharmaceutical companies involved in the development of therapies for MS.

A version of this article first appeared on Medscape.com.

Medicare payments for branded neurologic drugs jumped 50% over a 5-year period, while claims for these medications increased by just 8%, new research shows. Results of the retrospective study also showed that most of the increased costs for these agents were due to rising costs for neuroimmunology drugs, mainly for those used to treat multiple sclerosis (MS).

“The same brand name medication in 2017 cost approximately 50% more than in 2013,” said Adam de Havenon, MD, assistant professor of neurology, University of Utah, Salt Lake City.

“An analogy would be if you bought an iPhone 5 in 2013 for $500, and then in 2017, you were asked to pay $750 for the exact same iPhone 5,” Dr. de Havenon added.

The study findings were published online March 10 in the journal Neurology.
 

$26 billion in payments

Both neurologists and patients are concerned about the high cost of prescription drugs for neurologic diseases, and Medicare Part D data indicate that these drugs are the most expensive component of neurologic care, the researchers noted. In addition, out-of-pocket costs have increased significantly for patients with neurologic disease such as Parkinson’s disease, epilepsy, and MS.

To understand trends in payments for neurologic drugs, Dr. de Havenon and colleagues analyzed Medicare Part D claims filed from 2013 to 2017. The payments include costs paid by Medicare, the patient, government subsidies, and other third-party payers.

In addition to examining more current Medicare Part D data than previous studies, the current analysis examined all medications prescribed by neurologists that consistently remained branded or generic during the 5-year study period, said Dr. de Havenon. This approach resulted in a large number of claims and a large total cost.

To calculate the percentage change in annual payment claims, the researchers used 2013 prices as a reference point. They identified drugs named in 2013 claims and classified them as generic, brand-name only, or brand-name with generic equivalent. Researchers also divided the drugs by neurologic subspecialty.

The analysis included 520 drugs, all of which were available in each year of the study period. Of these drugs, 322 were generic, 61 were brand-name only, and 137 were brand-name with a generic equivalent. There were 90.7 million total claims.

Results showed total payments amounted to $26.65 billion. Yearly total payments increased from $4.05 billion in 2013 to $6.09 billion in 2017, representing a 50.4% increase, even after adjusting for inflation. Total claims increased by 7.6% – from 17.1 million in 2013 to 18.4 million in 2017.

From 2013 to 2017, claim payments increased by 0.6% for generic drugs, 42.4% for brand-name only drugs, and 45% for brand-name drugs with generic equivalents. The proportion of claims increased from 81.9% to 88% for generic drugs and from 4.9% to 6.2% for brand-name only drugs.

However, the proportion of claims for brand-name drugs with generic equivalents decreased from 13.3% to 5.8%.
 

Treatment barrier

Neuroimmunologic drugs, most of which were prescribed for MS, had exceptional cost, the researchers noted. These drugs accounted for more than 50% of payments but only 4.3% of claims. Claim payment for these drugs increased by 46.9% during the study period, from $3,337 to $4,902.

When neuroimmunologic drugs were removed from the analysis there was still significant increase in claim payments for brand-name only drugs (50.4%) and brand-name drugs with generic equivalents (45.6%).

Although neuroimmunologic medicines, including monoclonal antibodies, are more expensive to produce, this factor alone does not explain their exceptional cost, said Dr. de Havenon. “The high cost of brand-name drugs in this speciality is likely because the market bears it,” he added. “In other words, MS is a disabling disease and the medications work, so historically the Centers for Medicare & Medicaid Services have been willing to tolerate the high cost of these primarily brand-name medications.”

Several countries have controlled drug costs by negotiating with pharmaceutical companies and through legislation, Dr. de Havenon noted.

“My intent with this article was to raise awareness on the topic, which I struggle with frequently as a clinician. I know I want my patients to have a medication, but the cost prevents it,” he said.
 

‘Unfettered’ price-setting

Commenting on the findings, Robert J. Fox, MD, vice chair for research at the Neurological Institute of the Cleveland Clinic, said the study “brings into clear light” what neurologists, particularly those who treat MS, have long suspected but did not really know. These neurologists “are typically distanced from the payment aspects of the medications they prescribe,” said Dr. Fox, who was not involved with the research.

Although a particular strength of the study was its comprehensiveness, the researchers excluded infusion claims – which account for a large portion of total patient care costs for many disorders, he noted.

Drugs for MS historically have been expensive, ostensibly because of their high cost of development. In addition, the large and continued price increase that occurs long after these drugs have been approved remains unexplained, said Dr. Fox.

He noted that the study findings might not directly affect clinical practice because neurologists will continue prescribing medications they think are best for their patients. “Instead, I think this is a lesson to lawmakers about the massive error in the Medicare Modernization Act of 2003, where the federal government was prohibited from negotiating drug prices. If the seller is unfettered in setting a price, then no one should be surprised when the price rises,” Dr. Fox said.

Because many new drugs and new generic formulations for treating MS have become available during the past year, “repeating these types of economic studies for the period 2020-2025 will help us understand if generic competition – as well as new laws if they are passed – alter price,” he concluded.

The study was funded by the American Academy of Neurology, which publishes Neurology. Dr. de Havenon has received clinical research funding from AMAG Pharmaceuticals and Regeneron Pharmaceuticals. Dr. Fox receives consulting fees from many pharmaceutical companies involved in the development of therapies for MS.

A version of this article first appeared on Medscape.com.

Medicare payments for branded neurologic drugs jumped 50% over a 5-year period, while claims for these medications increased by just 8%, new research shows. Results of the retrospective study also showed that most of the increased costs for these agents were due to rising costs for neuroimmunology drugs, mainly for those used to treat multiple sclerosis (MS).

“The same brand name medication in 2017 cost approximately 50% more than in 2013,” said Adam de Havenon, MD, assistant professor of neurology, University of Utah, Salt Lake City.

“An analogy would be if you bought an iPhone 5 in 2013 for $500, and then in 2017, you were asked to pay $750 for the exact same iPhone 5,” Dr. de Havenon added.

The study findings were published online March 10 in the journal Neurology.
 

$26 billion in payments

Both neurologists and patients are concerned about the high cost of prescription drugs for neurologic diseases, and Medicare Part D data indicate that these drugs are the most expensive component of neurologic care, the researchers noted. In addition, out-of-pocket costs have increased significantly for patients with neurologic disease such as Parkinson’s disease, epilepsy, and MS.

To understand trends in payments for neurologic drugs, Dr. de Havenon and colleagues analyzed Medicare Part D claims filed from 2013 to 2017. The payments include costs paid by Medicare, the patient, government subsidies, and other third-party payers.

In addition to examining more current Medicare Part D data than previous studies, the current analysis examined all medications prescribed by neurologists that consistently remained branded or generic during the 5-year study period, said Dr. de Havenon. This approach resulted in a large number of claims and a large total cost.

To calculate the percentage change in annual payment claims, the researchers used 2013 prices as a reference point. They identified drugs named in 2013 claims and classified them as generic, brand-name only, or brand-name with generic equivalent. Researchers also divided the drugs by neurologic subspecialty.

The analysis included 520 drugs, all of which were available in each year of the study period. Of these drugs, 322 were generic, 61 were brand-name only, and 137 were brand-name with a generic equivalent. There were 90.7 million total claims.

Results showed total payments amounted to $26.65 billion. Yearly total payments increased from $4.05 billion in 2013 to $6.09 billion in 2017, representing a 50.4% increase, even after adjusting for inflation. Total claims increased by 7.6% – from 17.1 million in 2013 to 18.4 million in 2017.

From 2013 to 2017, claim payments increased by 0.6% for generic drugs, 42.4% for brand-name only drugs, and 45% for brand-name drugs with generic equivalents. The proportion of claims increased from 81.9% to 88% for generic drugs and from 4.9% to 6.2% for brand-name only drugs.

However, the proportion of claims for brand-name drugs with generic equivalents decreased from 13.3% to 5.8%.
 

Treatment barrier

Neuroimmunologic drugs, most of which were prescribed for MS, had exceptional cost, the researchers noted. These drugs accounted for more than 50% of payments but only 4.3% of claims. Claim payment for these drugs increased by 46.9% during the study period, from $3,337 to $4,902.

When neuroimmunologic drugs were removed from the analysis there was still significant increase in claim payments for brand-name only drugs (50.4%) and brand-name drugs with generic equivalents (45.6%).

Although neuroimmunologic medicines, including monoclonal antibodies, are more expensive to produce, this factor alone does not explain their exceptional cost, said Dr. de Havenon. “The high cost of brand-name drugs in this speciality is likely because the market bears it,” he added. “In other words, MS is a disabling disease and the medications work, so historically the Centers for Medicare & Medicaid Services have been willing to tolerate the high cost of these primarily brand-name medications.”

Several countries have controlled drug costs by negotiating with pharmaceutical companies and through legislation, Dr. de Havenon noted.

“My intent with this article was to raise awareness on the topic, which I struggle with frequently as a clinician. I know I want my patients to have a medication, but the cost prevents it,” he said.
 

‘Unfettered’ price-setting

Commenting on the findings, Robert J. Fox, MD, vice chair for research at the Neurological Institute of the Cleveland Clinic, said the study “brings into clear light” what neurologists, particularly those who treat MS, have long suspected but did not really know. These neurologists “are typically distanced from the payment aspects of the medications they prescribe,” said Dr. Fox, who was not involved with the research.

Although a particular strength of the study was its comprehensiveness, the researchers excluded infusion claims – which account for a large portion of total patient care costs for many disorders, he noted.

Drugs for MS historically have been expensive, ostensibly because of their high cost of development. In addition, the large and continued price increase that occurs long after these drugs have been approved remains unexplained, said Dr. Fox.

He noted that the study findings might not directly affect clinical practice because neurologists will continue prescribing medications they think are best for their patients. “Instead, I think this is a lesson to lawmakers about the massive error in the Medicare Modernization Act of 2003, where the federal government was prohibited from negotiating drug prices. If the seller is unfettered in setting a price, then no one should be surprised when the price rises,” Dr. Fox said.

Because many new drugs and new generic formulations for treating MS have become available during the past year, “repeating these types of economic studies for the period 2020-2025 will help us understand if generic competition – as well as new laws if they are passed – alter price,” he concluded.

The study was funded by the American Academy of Neurology, which publishes Neurology. Dr. de Havenon has received clinical research funding from AMAG Pharmaceuticals and Regeneron Pharmaceuticals. Dr. Fox receives consulting fees from many pharmaceutical companies involved in the development of therapies for MS.

A version of this article first appeared on Medscape.com.

Results from a phase 2 placebo-controlled trial of the investigational antiamyloid drug donanemab show that the novel agent met the primary outcome of slowing cognitive decline in patients with early symptomatic Alzheimer’s disease (AD). 

Results from the TRAILBLAZER-ALZ trial were presented at the 2021 International Conference on Alzheimer’s and Parkinson’s Diseases (AD/PD) and were simultaneously published online March 13 in the New England Journal of Medicine.

As previously reported by Medscape Medical News, topline results showed that donanemab slowed cognitive decline by 32% on the Integrated AD Rating Scale (iADRS) from baseline to 76 weeks relative to placebo.

The newly released detailed findings showed that “the use of donanemab resulted in a better composite score for cognition and for the ability to perform activities of daily living than placebo at 76 weeks, although results for secondary outcomes were mixed,” the investigators, with first author Mark A. Mintun, MD, an employee of Eli Lilly, reported.   

Results revealed improvement in scores on the Clinical Dementia Rating Scale-Sum of Boxes (CDR-SB) and the 13-item cognitive subscale of the AD Assessment Scale (ADAS-Cog13), but the differences between the two treatment groups were not significant. In addition, score changes on the AD Cooperative Study–Instrumental Activities of Daily Inventory (ADCS-iADL) and the Mini-Mental State Examination (MMSE) were not “substantial.”

However, the donanemab group did show an 85-centiloid greater reduction in amyloid plaque level at 76 weeks, as shown on PET, compared with the placebo group.
 

Proof of concept?

The humanized antibody donanemab, which was previously known as LY3002813, targets a modified form of deposited amyloid-beta (A-beta) peptide called N3pG.

The randomized, placebo-controlled, double-blind TRAILBLAZER-ALZ trial, which was described as a “phase 2 proof of concept trial” in the AD/PD program, was conducted at 56 sites in the United States and Canada and included 257 patients between the ages of 60 and 85 years (52% were women). PET confirmed tau and amyloid deposition in all participants.

The active treatment group (n = 131) was randomly assigned to receive donanemab 700 mg for three doses; after that, treatment was bumped up to 1,400 mg. Both the donanemab and placebo groups (n = 126) received treatment intravenously every 4 weeks for up to 72 weeks.

Participants also underwent F-florbetapir and F-flortaucipir PET scans at various timepoints and completed a slew of cognitive tests.

The study’s primary outcome measure was change between baseline and 76 weeks post treatment on composite score for cognition, as measured by the iADRS. The iADRS combines the ADAS-Cog13 and the ADCS-iADL.

This measure ranges from 0 to 144, with lower scores associated with greater cognitive impairment. Both treatment groups had an iADRS score of 106 at baseline.
 

More research needed

Results showed that the score change from baseline on the iADRS was –6.86 for the active treatment group vs –10.06 for the placebo group (group difference, 3.2; 95% confidence interval [CI], 0.12-6.27; P = .04). Although significant, “the trial was powered to show a 6-point difference,” which was not met, the investigators note.

Differences in score changes from baseline to 76 weeks for the treatment vs. placebo groups on the following secondary outcome measures were:

• CDR-SB: –0.36 (95% CI, –0.83 to –0.12).
• ADAS-Cog13: –1.86 (95% CI, –3.63 to –0.09).
• ADCS-iADL: 1.21 (95% CI, –0.77 to 3.2).
• MMSE: 0.64 (95% CI, –0.4 to 1.67).

The CDR-SB was designated as the first secondary outcome, and because it did not show a significant between-group difference, “the hierarchy failed and no definite conclusions can be drawn from data regarding the differences between groups in the change in the ADAS-Cog13,” the investigators wrote.

In addition, the differences in scores on the latter two secondary outcomes were not “substantial,” they reported.

However, at 76 weeks, the donanemab group showed a reduction of 84.13 centiloids in amyloid plaque level vs. an increase of 0.93 centiloids in the placebo group (between-group difference, 85.06 centiloids). At 24 weeks, the active-treatment group had a 67.83-centiloids greater reduction vs. the placebo group.

In addition, 40%, 59.8%, and 67.8% of the donanemab group achieved “amyloid-negative status” at 24, 52, and 76 weeks, respectively. Amyloid-negative status was defined as an amyloid plaque level of less than 24.1 centiloids.

Total incidence of death or serious adverse events did not differ significantly between the groups. However, the donanemab group had significantly more reports of ARIA-E compared with the placebo group (26.7% vs. 0.8%).

Overall, the researchers noted that more trials of longer duration with larger patient numbers are warranted “to further determine the efficacy and safety of donanemab” in AD.
 

Positive signal?

In a statement, Maria Carrillo, PhD, chief science officer for the Alzheimer’s Association, said the organization “is encouraged by this promising data.

“It is the first phase 2 Alzheimer’s trial to show positive results on a primary outcome measure related to memory and thinking,” Dr. Carrillo said. However, “more work needs to be done on this experimental drug therapy.”

Dr. Carrillo noted that because the trial was moderately sized and only 180 participants completed the study, “we look forward to the results of a second, larger phase 2 trial of this drug.”

Still, she added, there were several “novel and innovative aspects” in the way the study was conducted noting that it showcases the evolution of AD research.

“I’m hopeful for the future,” Dr. Carrillo said.

Also commenting on the results, Howard Fillit, MD, neuroscientist and founding executive director and chief science officer of the Alzheimer’s Drug Discovery Foundation, said the study showed “the pharmacology works” and that the drug did what it was supposed to do in terms of removing A-beta plaque.

“It also gave us a signal in a relatively small phase 2 study that there might be a modest cognitive benefit,” said Dr. Fillit, who was not involved with the research.

He noted that although the rate of decline slowing was statistically significant it remains to be seen whether this is clinically meaningful, particularly in light of the fact that the secondary outcome results were mixed.  

“Basically, it was a positive study that probably needs to be followed by another, much larger study to get us to really see the benefit,” Dr. Fillit said.

Dr. Mintun is an employee of Eli Lilly, which funded the study. Dr. Carrillo and Dr. Fillit have reported no relevant financial relationships.

A version of this article first appeared on Medscape.com.

Results from a phase 2 placebo-controlled trial of the investigational antiamyloid drug donanemab show that the novel agent met the primary outcome of slowing cognitive decline in patients with early symptomatic Alzheimer’s disease (AD). 

Results from the TRAILBLAZER-ALZ trial were presented at the 2021 International Conference on Alzheimer’s and Parkinson’s Diseases (AD/PD) and were simultaneously published online March 13 in the New England Journal of Medicine.

As previously reported by Medscape Medical News, topline results showed that donanemab slowed cognitive decline by 32% on the Integrated AD Rating Scale (iADRS) from baseline to 76 weeks relative to placebo.

The newly released detailed findings showed that “the use of donanemab resulted in a better composite score for cognition and for the ability to perform activities of daily living than placebo at 76 weeks, although results for secondary outcomes were mixed,” the investigators, with first author Mark A. Mintun, MD, an employee of Eli Lilly, reported.   

Results revealed improvement in scores on the Clinical Dementia Rating Scale-Sum of Boxes (CDR-SB) and the 13-item cognitive subscale of the AD Assessment Scale (ADAS-Cog13), but the differences between the two treatment groups were not significant. In addition, score changes on the AD Cooperative Study–Instrumental Activities of Daily Inventory (ADCS-iADL) and the Mini-Mental State Examination (MMSE) were not “substantial.”

However, the donanemab group did show an 85-centiloid greater reduction in amyloid plaque level at 76 weeks, as shown on PET, compared with the placebo group.
 

Proof of concept?

The humanized antibody donanemab, which was previously known as LY3002813, targets a modified form of deposited amyloid-beta (A-beta) peptide called N3pG.

The randomized, placebo-controlled, double-blind TRAILBLAZER-ALZ trial, which was described as a “phase 2 proof of concept trial” in the AD/PD program, was conducted at 56 sites in the United States and Canada and included 257 patients between the ages of 60 and 85 years (52% were women). PET confirmed tau and amyloid deposition in all participants.

The active treatment group (n = 131) was randomly assigned to receive donanemab 700 mg for three doses; after that, treatment was bumped up to 1,400 mg. Both the donanemab and placebo groups (n = 126) received treatment intravenously every 4 weeks for up to 72 weeks.

Participants also underwent F-florbetapir and F-flortaucipir PET scans at various timepoints and completed a slew of cognitive tests.

The study’s primary outcome measure was change between baseline and 76 weeks post treatment on composite score for cognition, as measured by the iADRS. The iADRS combines the ADAS-Cog13 and the ADCS-iADL.

This measure ranges from 0 to 144, with lower scores associated with greater cognitive impairment. Both treatment groups had an iADRS score of 106 at baseline.
 

More research needed

Results showed that the score change from baseline on the iADRS was –6.86 for the active treatment group vs –10.06 for the placebo group (group difference, 3.2; 95% confidence interval [CI], 0.12-6.27; P = .04). Although significant, “the trial was powered to show a 6-point difference,” which was not met, the investigators note.

Differences in score changes from baseline to 76 weeks for the treatment vs. placebo groups on the following secondary outcome measures were:

• CDR-SB: –0.36 (95% CI, –0.83 to –0.12).
• ADAS-Cog13: –1.86 (95% CI, –3.63 to –0.09).
• ADCS-iADL: 1.21 (95% CI, –0.77 to 3.2).
• MMSE: 0.64 (95% CI, –0.4 to 1.67).

The CDR-SB was designated as the first secondary outcome, and because it did not show a significant between-group difference, “the hierarchy failed and no definite conclusions can be drawn from data regarding the differences between groups in the change in the ADAS-Cog13,” the investigators wrote.

In addition, the differences in scores on the latter two secondary outcomes were not “substantial,” they reported.

However, at 76 weeks, the donanemab group showed a reduction of 84.13 centiloids in amyloid plaque level vs. an increase of 0.93 centiloids in the placebo group (between-group difference, 85.06 centiloids). At 24 weeks, the active-treatment group had a 67.83-centiloids greater reduction vs. the placebo group.

In addition, 40%, 59.8%, and 67.8% of the donanemab group achieved “amyloid-negative status” at 24, 52, and 76 weeks, respectively. Amyloid-negative status was defined as an amyloid plaque level of less than 24.1 centiloids.

Total incidence of death or serious adverse events did not differ significantly between the groups. However, the donanemab group had significantly more reports of ARIA-E compared with the placebo group (26.7% vs. 0.8%).

Overall, the researchers noted that more trials of longer duration with larger patient numbers are warranted “to further determine the efficacy and safety of donanemab” in AD.
 

Positive signal?

In a statement, Maria Carrillo, PhD, chief science officer for the Alzheimer’s Association, said the organization “is encouraged by this promising data.

“It is the first phase 2 Alzheimer’s trial to show positive results on a primary outcome measure related to memory and thinking,” Dr. Carrillo said. However, “more work needs to be done on this experimental drug therapy.”

Dr. Carrillo noted that because the trial was moderately sized and only 180 participants completed the study, “we look forward to the results of a second, larger phase 2 trial of this drug.”

Still, she added, there were several “novel and innovative aspects” in the way the study was conducted noting that it showcases the evolution of AD research.

“I’m hopeful for the future,” Dr. Carrillo said.

Also commenting on the results, Howard Fillit, MD, neuroscientist and founding executive director and chief science officer of the Alzheimer’s Drug Discovery Foundation, said the study showed “the pharmacology works” and that the drug did what it was supposed to do in terms of removing A-beta plaque.

“It also gave us a signal in a relatively small phase 2 study that there might be a modest cognitive benefit,” said Dr. Fillit, who was not involved with the research.

He noted that although the rate of decline slowing was statistically significant it remains to be seen whether this is clinically meaningful, particularly in light of the fact that the secondary outcome results were mixed.  

“Basically, it was a positive study that probably needs to be followed by another, much larger study to get us to really see the benefit,” Dr. Fillit said.

Dr. Mintun is an employee of Eli Lilly, which funded the study. Dr. Carrillo and Dr. Fillit have reported no relevant financial relationships.

A version of this article first appeared on Medscape.com.

Results from a phase 2 placebo-controlled trial of the investigational antiamyloid drug donanemab show that the novel agent met the primary outcome of slowing cognitive decline in patients with early symptomatic Alzheimer’s disease (AD). 

Results from the TRAILBLAZER-ALZ trial were presented at the 2021 International Conference on Alzheimer’s and Parkinson’s Diseases (AD/PD) and were simultaneously published online March 13 in the New England Journal of Medicine.

As previously reported by Medscape Medical News, topline results showed that donanemab slowed cognitive decline by 32% on the Integrated AD Rating Scale (iADRS) from baseline to 76 weeks relative to placebo.

The newly released detailed findings showed that “the use of donanemab resulted in a better composite score for cognition and for the ability to perform activities of daily living than placebo at 76 weeks, although results for secondary outcomes were mixed,” the investigators, with first author Mark A. Mintun, MD, an employee of Eli Lilly, reported.   

Results revealed improvement in scores on the Clinical Dementia Rating Scale-Sum of Boxes (CDR-SB) and the 13-item cognitive subscale of the AD Assessment Scale (ADAS-Cog13), but the differences between the two treatment groups were not significant. In addition, score changes on the AD Cooperative Study–Instrumental Activities of Daily Inventory (ADCS-iADL) and the Mini-Mental State Examination (MMSE) were not “substantial.”

However, the donanemab group did show an 85-centiloid greater reduction in amyloid plaque level at 76 weeks, as shown on PET, compared with the placebo group.
 

Proof of concept?

The humanized antibody donanemab, which was previously known as LY3002813, targets a modified form of deposited amyloid-beta (A-beta) peptide called N3pG.

The randomized, placebo-controlled, double-blind TRAILBLAZER-ALZ trial, which was described as a “phase 2 proof of concept trial” in the AD/PD program, was conducted at 56 sites in the United States and Canada and included 257 patients between the ages of 60 and 85 years (52% were women). PET confirmed tau and amyloid deposition in all participants.

The active treatment group (n = 131) was randomly assigned to receive donanemab 700 mg for three doses; after that, treatment was bumped up to 1,400 mg. Both the donanemab and placebo groups (n = 126) received treatment intravenously every 4 weeks for up to 72 weeks.

Participants also underwent F-florbetapir and F-flortaucipir PET scans at various timepoints and completed a slew of cognitive tests.

The study’s primary outcome measure was change between baseline and 76 weeks post treatment on composite score for cognition, as measured by the iADRS. The iADRS combines the ADAS-Cog13 and the ADCS-iADL.

This measure ranges from 0 to 144, with lower scores associated with greater cognitive impairment. Both treatment groups had an iADRS score of 106 at baseline.
 

More research needed

Results showed that the score change from baseline on the iADRS was –6.86 for the active treatment group vs –10.06 for the placebo group (group difference, 3.2; 95% confidence interval [CI], 0.12-6.27; P = .04). Although significant, “the trial was powered to show a 6-point difference,” which was not met, the investigators note.

Differences in score changes from baseline to 76 weeks for the treatment vs. placebo groups on the following secondary outcome measures were:

• CDR-SB: –0.36 (95% CI, –0.83 to –0.12).
• ADAS-Cog13: –1.86 (95% CI, –3.63 to –0.09).
• ADCS-iADL: 1.21 (95% CI, –0.77 to 3.2).
• MMSE: 0.64 (95% CI, –0.4 to 1.67).

The CDR-SB was designated as the first secondary outcome, and because it did not show a significant between-group difference, “the hierarchy failed and no definite conclusions can be drawn from data regarding the differences between groups in the change in the ADAS-Cog13,” the investigators wrote.

In addition, the differences in scores on the latter two secondary outcomes were not “substantial,” they reported.

However, at 76 weeks, the donanemab group showed a reduction of 84.13 centiloids in amyloid plaque level vs. an increase of 0.93 centiloids in the placebo group (between-group difference, 85.06 centiloids). At 24 weeks, the active-treatment group had a 67.83-centiloids greater reduction vs. the placebo group.

In addition, 40%, 59.8%, and 67.8% of the donanemab group achieved “amyloid-negative status” at 24, 52, and 76 weeks, respectively. Amyloid-negative status was defined as an amyloid plaque level of less than 24.1 centiloids.

Total incidence of death or serious adverse events did not differ significantly between the groups. However, the donanemab group had significantly more reports of ARIA-E compared with the placebo group (26.7% vs. 0.8%).

Overall, the researchers noted that more trials of longer duration with larger patient numbers are warranted “to further determine the efficacy and safety of donanemab” in AD.
 

Positive signal?

In a statement, Maria Carrillo, PhD, chief science officer for the Alzheimer’s Association, said the organization “is encouraged by this promising data.

“It is the first phase 2 Alzheimer’s trial to show positive results on a primary outcome measure related to memory and thinking,” Dr. Carrillo said. However, “more work needs to be done on this experimental drug therapy.”

Dr. Carrillo noted that because the trial was moderately sized and only 180 participants completed the study, “we look forward to the results of a second, larger phase 2 trial of this drug.”

Still, she added, there were several “novel and innovative aspects” in the way the study was conducted noting that it showcases the evolution of AD research.

“I’m hopeful for the future,” Dr. Carrillo said.

Also commenting on the results, Howard Fillit, MD, neuroscientist and founding executive director and chief science officer of the Alzheimer’s Drug Discovery Foundation, said the study showed “the pharmacology works” and that the drug did what it was supposed to do in terms of removing A-beta plaque.

“It also gave us a signal in a relatively small phase 2 study that there might be a modest cognitive benefit,” said Dr. Fillit, who was not involved with the research.

He noted that although the rate of decline slowing was statistically significant it remains to be seen whether this is clinically meaningful, particularly in light of the fact that the secondary outcome results were mixed.  

“Basically, it was a positive study that probably needs to be followed by another, much larger study to get us to really see the benefit,” Dr. Fillit said.

Dr. Mintun is an employee of Eli Lilly, which funded the study. Dr. Carrillo and Dr. Fillit have reported no relevant financial relationships.

A version of this article first appeared on Medscape.com.

COVID-19 vaccines are safe and effective for patients taking osteoporosis medications, according to joint guidance from six endocrine and osteoporosis societies and foundations.

They noted, though, that some timing modifications with certain medications should be considered to help distinguish between adverse events from the medication versus the vaccine.

The American Society for Bone and Mineral Research “is an international organization, so we brought together our sister societies that have a vested interested in bone health. Vaccination is happening worldwide, and we wanted to present a united front and united recommendations about how to handle osteoporosis medications appropriately during vaccination,” said Suzanne Jan De Beur, MD, who is president of ASBMR and an associate professor of medicine at Johns Hopkins University, Baltimore.

There has been quite a lot of concern from the community about vaccine and medications, from both physicians and patients wondering whether treatments and vaccines should occur in a certain order, and whether there should be a time gap between the two, said Dr. Jan De Beur. “There was a dearth of information about the best practices for osteoporosis treatment management during vaccination, and we didn’t want people missing their opportunity for a vaccine, and we also didn’t want them unnecessarily delaying their osteoporosis treatment.”

There is no evidence that osteoporosis therapies affect the risk or severity of COVID-19 disease, nor do they appear to change the disease course. Osteoporosis itself does not appear associated with increased risk of infection or severe outcomes, so patients with osteoporosis do not need to be prioritized for vaccination based on that condition alone.

There is no evidence that osteoporosis therapies affect the safety or efficacy of vaccination, but given that vaccine availability is currently inconsistent, patients may need to make temporary changes to their osteoporosis regimens to ensure they can receive vaccine when it is available, such as ensuring a delay between medication and vaccination injections.

A key reason for a delay between injectable or infusion medications and a vaccine is to distinguish between adverse events that could occur, so that an adverse reaction to vaccine isn’t mistaken for an adverse reaction to a drug. Nevertheless, the real world is messy. Dr. Jan De Beur noted a recent patient who arrived at her clinic for an injectable treatment who had just received a COVID-19 vaccination that morning. “We decided to put the injection in the other arm, rather than reschedule the person and put them through the risk of coming back. We could distinguish between injection-site reactions, at least,” she said.

copyright DesignPics/Thinkstock

No changes should be made to general bone health therapies, such as calcium and vitamin D supplementation, weight-bearing exercises, and maintenance of a balanced diet.

The guidance includes some recommendations for specific osteoporosis medications.

• Oral bisphosphonates: Alendronate, risedronate, and ibandronate should be continued.
• Intravenous bisphosphonates: a 7-day interval (4-day minimum) is recommended between intravenous bisphosphonate (zoledronic acid and ibandronate) infusion and COVID-19 vaccination in order to distinguish potential autoimmune or inflammatory reactions that could be attributable to either intravenous bisphosphonate or the vaccine.
• Denosumab: There should be a 4- to 7-day delay between denosumab infusion and COVID-19 vaccination to account for injection-site reactions. Another option is to have denosumab injected into the contralateral arm or another site like the abdomen or upper thigh, if spacing the injections is not possible. In any case, denosumab injections should be performed within 7 months of the previous dose.
• Teriparatide and abaloparatide should be continued.
• Romosozumab: There should be a 4- to 7-day delay between a romosozumab injection and COVID-19 vaccine, or romosozumab can be injected in the abdomen (with the exception of a 2-inch area around the naval) or thigh if spacing is not possible.
• Raloxifene should be continued in patients receiving COVID-19 vaccination.

Guidance signatories include ASBMR, the American Association of Clinical Endocrinology, the Endocrine Society, the European Calcified Tissue Society, the National Osteoporosis Foundation, and the International Osteoporosis Foundation.

Dr. Jan De Beur has no relevant financial disclosures.

COVID-19 vaccines are safe and effective for patients taking osteoporosis medications, according to joint guidance from six endocrine and osteoporosis societies and foundations.

They noted, though, that some timing modifications with certain medications should be considered to help distinguish between adverse events from the medication versus the vaccine.

The American Society for Bone and Mineral Research “is an international organization, so we brought together our sister societies that have a vested interested in bone health. Vaccination is happening worldwide, and we wanted to present a united front and united recommendations about how to handle osteoporosis medications appropriately during vaccination,” said Suzanne Jan De Beur, MD, who is president of ASBMR and an associate professor of medicine at Johns Hopkins University, Baltimore.

There has been quite a lot of concern from the community about vaccine and medications, from both physicians and patients wondering whether treatments and vaccines should occur in a certain order, and whether there should be a time gap between the two, said Dr. Jan De Beur. “There was a dearth of information about the best practices for osteoporosis treatment management during vaccination, and we didn’t want people missing their opportunity for a vaccine, and we also didn’t want them unnecessarily delaying their osteoporosis treatment.”

There is no evidence that osteoporosis therapies affect the risk or severity of COVID-19 disease, nor do they appear to change the disease course. Osteoporosis itself does not appear associated with increased risk of infection or severe outcomes, so patients with osteoporosis do not need to be prioritized for vaccination based on that condition alone.

There is no evidence that osteoporosis therapies affect the safety or efficacy of vaccination, but given that vaccine availability is currently inconsistent, patients may need to make temporary changes to their osteoporosis regimens to ensure they can receive vaccine when it is available, such as ensuring a delay between medication and vaccination injections.

A key reason for a delay between injectable or infusion medications and a vaccine is to distinguish between adverse events that could occur, so that an adverse reaction to vaccine isn’t mistaken for an adverse reaction to a drug. Nevertheless, the real world is messy. Dr. Jan De Beur noted a recent patient who arrived at her clinic for an injectable treatment who had just received a COVID-19 vaccination that morning. “We decided to put the injection in the other arm, rather than reschedule the person and put them through the risk of coming back. We could distinguish between injection-site reactions, at least,” she said.

copyright DesignPics/Thinkstock

No changes should be made to general bone health therapies, such as calcium and vitamin D supplementation, weight-bearing exercises, and maintenance of a balanced diet.

The guidance includes some recommendations for specific osteoporosis medications.

• Oral bisphosphonates: Alendronate, risedronate, and ibandronate should be continued.
• Intravenous bisphosphonates: a 7-day interval (4-day minimum) is recommended between intravenous bisphosphonate (zoledronic acid and ibandronate) infusion and COVID-19 vaccination in order to distinguish potential autoimmune or inflammatory reactions that could be attributable to either intravenous bisphosphonate or the vaccine.
• Denosumab: There should be a 4- to 7-day delay between denosumab infusion and COVID-19 vaccination to account for injection-site reactions. Another option is to have denosumab injected into the contralateral arm or another site like the abdomen or upper thigh, if spacing the injections is not possible. In any case, denosumab injections should be performed within 7 months of the previous dose.
• Teriparatide and abaloparatide should be continued.
• Romosozumab: There should be a 4- to 7-day delay between a romosozumab injection and COVID-19 vaccine, or romosozumab can be injected in the abdomen (with the exception of a 2-inch area around the naval) or thigh if spacing is not possible.
• Raloxifene should be continued in patients receiving COVID-19 vaccination.

Guidance signatories include ASBMR, the American Association of Clinical Endocrinology, the Endocrine Society, the European Calcified Tissue Society, the National Osteoporosis Foundation, and the International Osteoporosis Foundation.

Dr. Jan De Beur has no relevant financial disclosures.

COVID-19 vaccines are safe and effective for patients taking osteoporosis medications, according to joint guidance from six endocrine and osteoporosis societies and foundations.

They noted, though, that some timing modifications with certain medications should be considered to help distinguish between adverse events from the medication versus the vaccine.

The American Society for Bone and Mineral Research “is an international organization, so we brought together our sister societies that have a vested interested in bone health. Vaccination is happening worldwide, and we wanted to present a united front and united recommendations about how to handle osteoporosis medications appropriately during vaccination,” said Suzanne Jan De Beur, MD, who is president of ASBMR and an associate professor of medicine at Johns Hopkins University, Baltimore.

There has been quite a lot of concern from the community about vaccine and medications, from both physicians and patients wondering whether treatments and vaccines should occur in a certain order, and whether there should be a time gap between the two, said Dr. Jan De Beur. “There was a dearth of information about the best practices for osteoporosis treatment management during vaccination, and we didn’t want people missing their opportunity for a vaccine, and we also didn’t want them unnecessarily delaying their osteoporosis treatment.”

There is no evidence that osteoporosis therapies affect the risk or severity of COVID-19 disease, nor do they appear to change the disease course. Osteoporosis itself does not appear associated with increased risk of infection or severe outcomes, so patients with osteoporosis do not need to be prioritized for vaccination based on that condition alone.

There is no evidence that osteoporosis therapies affect the safety or efficacy of vaccination, but given that vaccine availability is currently inconsistent, patients may need to make temporary changes to their osteoporosis regimens to ensure they can receive vaccine when it is available, such as ensuring a delay between medication and vaccination injections.

A key reason for a delay between injectable or infusion medications and a vaccine is to distinguish between adverse events that could occur, so that an adverse reaction to vaccine isn’t mistaken for an adverse reaction to a drug. Nevertheless, the real world is messy. Dr. Jan De Beur noted a recent patient who arrived at her clinic for an injectable treatment who had just received a COVID-19 vaccination that morning. “We decided to put the injection in the other arm, rather than reschedule the person and put them through the risk of coming back. We could distinguish between injection-site reactions, at least,” she said.

copyright DesignPics/Thinkstock

No changes should be made to general bone health therapies, such as calcium and vitamin D supplementation, weight-bearing exercises, and maintenance of a balanced diet.

The guidance includes some recommendations for specific osteoporosis medications.

• Oral bisphosphonates: Alendronate, risedronate, and ibandronate should be continued.
• Intravenous bisphosphonates: a 7-day interval (4-day minimum) is recommended between intravenous bisphosphonate (zoledronic acid and ibandronate) infusion and COVID-19 vaccination in order to distinguish potential autoimmune or inflammatory reactions that could be attributable to either intravenous bisphosphonate or the vaccine.
• Denosumab: There should be a 4- to 7-day delay between denosumab infusion and COVID-19 vaccination to account for injection-site reactions. Another option is to have denosumab injected into the contralateral arm or another site like the abdomen or upper thigh, if spacing the injections is not possible. In any case, denosumab injections should be performed within 7 months of the previous dose.
• Teriparatide and abaloparatide should be continued.
• Romosozumab: There should be a 4- to 7-day delay between a romosozumab injection and COVID-19 vaccine, or romosozumab can be injected in the abdomen (with the exception of a 2-inch area around the naval) or thigh if spacing is not possible.
• Raloxifene should be continued in patients receiving COVID-19 vaccination.

Guidance signatories include ASBMR, the American Association of Clinical Endocrinology, the Endocrine Society, the European Calcified Tissue Society, the National Osteoporosis Foundation, and the International Osteoporosis Foundation.

Dr. Jan De Beur has no relevant financial disclosures.

Evaluation of oral antineoplastic agent (OAN) adherence patterns have identified correlations between nonadherence or over-adherence and poorer disease-related outcomes. Multiple studies have focused on imatinib use in chronic myeloid leukemia (CML) due to its continuous, long-term use. A study by Ganesan and colleagues found that nonadherence to imatinib showed a significant decrease in 5-year event-free survival between 76.7% of adherent participants compared with 59.8% of nonadherent participants.¹ This study found that 44% of patients who were adherent to imatinib achieved complete cytogenetic response vs only 26% of patients who were nonadherent. In another study of imatinib for CML, major molecular response (MMR) was strongly correlated with adherence and no patients with adherence < 80% were able to achieve MMR.² Similarly, in studies of tamoxifen for breast cancer, < 80% adherence resulted in a 10% decrease in survival when compared to those who were more adherent.^3,4

In addition to the clinical implications of nonadherence, there can be a significant cost associated with suboptimal use of these medications. The price of a single dose of OAN medication may cost as much as $440.⁵

The benefits of multidisciplinary care teams have been identified in many studies.^6,7 While studies are limited in oncology, pharmacists provide vital contributions to the oncology multidisciplinary team when managing OANs as these health care professionals have expert knowledge of the medications, potential adverse events (AEs), and necessary monitoring parameters.⁸ In one study, patients seen by the pharmacist-led oral chemotherapy management program experienced improved clinical outcomes and response to therapy when compared with preintervention patients (early molecular response, 88.9% vs 54.8%, P = .01; major molecular response, 83.3% vs 57.6%, P = .06).⁹ During the study, 318 AEs were reported, leading to 235 pharmacist interventions to ameliorate AEs and improve adherence.

The primary objective of this study was to measure the impact of a pharmacist-driven OAN renewal clinic on medication adherence. The secondary objective was to estimate cost-savings of this new service.

Methods

Prior to July 2014, several limitations were identified related to OAN prescribing and monitoring at the Richard L. Roudebush Veterans Affairs Medical Center in Indianapolis, Indiana (RLRVAMC). The prescription ordering process relied primarily on the patient to initiate refills, rather than the prescriber OAN prescriptions also lacked consistency for number of refills or quantities dispensed. Furthermore, ordering of antineoplastic products was not limited to hematology/oncology providers. Patients were identified with significant supply on hand at the time of medication discontinuation, creating concerns for medication waste, tolerability, and nonadherence.

As a result, opportunities were identified to improve the prescribing process, recommended monitoring, toxicity and tolerability evaluation, medication reconciliation, and medication adherence. In July of 2014, the RLRVAMC adopted a new chemotherapy order entry system capable of restricting prescriptions to hematology/oncology providers and limiting dispensed quantities and refill amounts. A comprehensive pharmacist driven OAN renewal clinic was implemented on September 1, 2014 with the goal of improving long-term adherence and tolerability, in addition to minimizing medication waste.

Study Design and Setting

This was a pre/post retrospective cohort, quality improvement study of patients enrolled in the RLRVAMC OAN pharmacist renewal clinic. The study was deemed exempt from institutional review board (IRB) by the US Department of Veterans Affairs (VA) Research and Development Department.

Study Population

Patients were included in the preimplementation group if they had received at least 2 prescriptions of an eligible OAN. Therapy for the preimplementation group was required to be a monthly duration > 21 days and between the dates of September 1, 2013 and August 31, 2014. Patients were included in the postimplementation group if they had received at least 2 prescriptions of the studied OANs between September 1, 2014 and January 31, 2015. Patients were excluded if they had filled < 2 prescriptions of OAN; were managed by a non-VA oncologist or hematologist; or received an OAN other than those listed in Table 1.

Data Collection

For all patients in both the pre- and postimplementation cohorts, a standardized data collection tool was used to collect the following via electronic health record review by a PGY2 oncology resident: age, race, gender, oral antineoplastic agent, refill dates, days’ supply, estimated unit cost per dose cancer diagnosis, distance from the RLRVAMC, copay status, presence of hospitalizations/ED visits/dosage reductions, discontinuation rates, reasons for discontinuation, and total number of current prescriptions. The presence or absence of dosage reductions were collected to identify concerns for tolerability, but only the original dose for the preimplementation group and dosage at time of clinic enrollment for the postimplementation group was included in the analysis.

Outcomes and Statistical Analyses

The primary outcome was medication adherence defined as the median medication possession ratio (MPR) before and after implementation of the clinic. Secondary outcomes included the proportion of patients who were adherent from before implementation to after and estimated cost-savings of this clinic after implementation. MPR was used to estimate medication adherence by taking the cumulative day supply of medication on hand divided by the number of days on therapy.¹² Number of days on therapy was determined by taking the difference on the start date of the new medication regimen and the discontinuation date of the same regimen. Patients were grouped by adherence into one of the following categories: < 0.8, 0.8 to 0.89, 0.9 to 1, and > 1.1. Patients were considered adherent if they reported taking ≥ 90% (MPR ≥ 0.9) of prescribed doses, adopted from the study by Anderson and colleagues.¹² A patient with an MPR > 1, likely due to filling prior to the anticipated refill date, was considered 100% adherent (MPR = 1). If a patient switched OAN during the study, both agents were included as separate entities.

A conservative estimate of cost-savings was made by multiplying the RLRVAMC cost per unit of medication at time of initial prescription fill by the number of units taken each day multiplied by the total days’ supply on hand at time of therapy discontinuation. Patients with an MPR < 1 at time of therapy discontinuation were assumed to have zero remaining units on hand and zero cost savings was estimated. Waste, for purposes of cost-savings, was calculated for all MPR values > 1. Additional supply anticipated to be on hand from dose reductions was not included in the estimated cost of unused medication.

Descriptive statistics compared demographic characteristics between the pre- and postimplementation groups. MPR data were not normally distributed, which required the use of nonparametric Mann-Whitney U tests to compare pre- and postMPRs. Pearson χ² compared the proportion of adherent patients between groups while descriptive statistics were used to estimate cost savings. Significance was determined based on a P value < .05. IBM SPSS Statistics software was used for all statistical analyses. As this was a complete sample of all eligible subjects, no sample size calculation was performed.

Results

In the preimplementation period, 246 patients received an OAN and 61 patients received an OAN in the postimplementation period (Figure 1). Of the 246 patients in the preimplementation period, 98 were eligible and included in the preimplementation group. Similarly, of the 61 patients in the postimplementation period, 35 patients met inclusion criteria for the postimplementation group. The study population was predominantly male with an average age of approximately 70 years in both groups (Table 3). More than 70% of the population in each group was White. No statistically significant differences between groups were identified. The most commonly prescribed OAN in the preimplementation group were abiraterone, imatinib, and enzalutamide (Table 3). In the postimplementation group, the most commonly prescribed agents were abiraterone, imatinib, pazopanib, and dasatinib. No significant differences were observed in prescribing of individual agents between the pre- and postimplementation groups or other characteristics that may affect adherence including patient copay status, number of concomitant medications, and driving distance from the RLRVAMC.

Thirty-six (36.7%) patients in the preimplementation group were considered nonadherent (MPR < 0.9) and 18 (18.4%) had an MPR < 0.8. Fifteen (15.3%) patients in the preimplementation clinic were considered overadherent (MPR > 1.1). Forty-seven (47.9%) patients in the preimplementation group were considered adherent (MPR 0.9 - 1.1) while all 35 (100%) patients in the postimplementation group were considered adherent (MPR 0.9 - 1.1). No non- or overadherent patients were identified in the postimplementation group (Figure 2). The median MPR for all patients in the preimplementation group was 0.94 compared with 1.06 (P < .001) in the postimplementation group.

Discussion

OANs are widely used therapies, with more than 25 million doses administered per year in the United States alone.¹² The use of these agents will continue to grow as more targeted agents become available and patients request more convenient treatment options. The role for hematology/oncology clinical pharmacy services must adapt to this increased usage of OANs, including increasing pharmacist involvement in medication education, adherence and tolerability assessments, and proactive drug interaction monitoring.However, additional research is needed to determine optimal management strategies.

Our study aimed to compare OAN adherence among patients at a tertiary care VA hospital before and after implementation of a renewal clinic. The preimplementation population had a median MPR of 0.94 compared with 1.06 in the postimplementation group (P < .001). Although an ideal MPR is 1.0, we aimed for a slightly higher MPR to allow a supply buffer in the event of prescription delivery delays, as more than 90% of prescriptions are mailed to patients from a regional mail-order pharmacy. Importantly, the median MPRs do not adequately convey the impact from this clinic. The proportion of patients who were considered adherent to OANs increased from 47.9% in the preimplementation to 100% in the postimplementation period. These finding suggest that the clinical pharmacist role to assess and encourage adherence through monitoring tolerability of these OANs improved the overall medication taking experience of these patients.

Upon initial evaluation of adherence pre- and postimplementation, median adherence rates in both groups appeared to be above goal at 0.94 and 1.06 respectively. Patients in the postimplementation group intentionally received a 5- to 7-day supply buffer to account for potential prescription delivery delays due to holidays and inclement weather. This would indicate that the patients in the postimplementation group would have 15% oversupply due to the 5-day supply buffer. After correcting for patients with confounding reasons for excess (dose reductions, breaks in treatment, etc.), the median MPR in the prerefill clinic group decreased to 0.9 and the MPR in the postrefill clinic group increased slightly to 1.08. Although the median adherence rate in both the pre- and postimplementation groups were above goal of 0.90, 36% of the patients in the preimplementation group were considered nonadherent (MPR < 0.9) compared with no patients in the postimplementation group. Therefore, our intervention to improve patient adherence appeared to be beneficial at our institution.

In addition to improving adherence, one of the goals of the renewal clinic was to minimize excess supply at the time of therapy discontinuation. This was accomplished by aligning medication fills with medical visits and objective monitoring, as well as limiting supply to no more than 30 days. Of the patients in the postimplementation group, only 1 patient had remaining medication at the time of therapy discontinuation compared with 14 patients in the preimplementation group. The estimated cost savings from excess supply was $36,335. Limiting the amount of unused supply not only saves money for the patient and the institution, but also decreases opportunity for improper hazardous waste disposal and unnecessary exposure of hazardous materials to others.

Our results show the pharmacist intervention in the coordination of renewals improved adherence, minimized medication waste, and saved money. The cost of pharmacist time participating in the refill clinic was not calculated. Each visit was completed in approximately 5 minutes, with subsequent documentation and coordination taking an additional 5 to 10 minutes. During the launch of this service, the oncology pharmacy resident provided all coverage of the clinic. Oversite of the resident was provided by hematology/oncology clinical pharmacy specialists. We have continued to utilize pharmacy resident coverage since that time to meet education needs and keep the estimated cost per visit low. Another option in the case that pharmacy residents are not available would be utilization of a pharmacy technician, intern, or professional student to conduct the adherence and tolerability phone assessments. Our escalation protocol allows intervention by clinical pharmacy specialist and/or other health care providers when necessary. Trainees have only required basic training on how to use the protocol.

Limitations

Due to this study’s retrospective design, an inherent limitation is dependence on prescriber and refill records for documentation of initiation and discontinuation dates. Therefore, only the association of impact of pharmacist intervention on medication adherence can be determined as opposed to causation. We did not take into account discrepancies in day supply secondary to ‘held’ therapies, dose reductions, or doses supplied during an inpatient admission, which may alter estimates of MPR and cost-savings data. Patients in the postimplementation group intentionally received a 5 to 7-day supply buffer to account for potential prescription delivery delays due to holidays and inclement weather. This would indicate that the patients in the postimplementation group would have 15% oversupply due to the 5-day supply buffer, thereby skewing MPR values. This study did not account for cost avoidance resulting from early identification and management of toxicity. Finally, the postimplementation data only spans 4 months and a longer duration of time is needed to more accurately determine sustainability of renewal clinic interventions and provide comprehensive evaluation of cost-avoidance.

Conclusion

Implementation of an OAN renewal clinic was associated with an increase in MPR, improved proportion of patients considered adherent, and an estimated $36,335 cost-savings. However, prospective evaluation and a longer study duration are needed to determine causality of improved adherence and cost-savings associated with a pharmacist-driven OAN renewal clinic.

Evaluation of oral antineoplastic agent (OAN) adherence patterns have identified correlations between nonadherence or over-adherence and poorer disease-related outcomes. Multiple studies have focused on imatinib use in chronic myeloid leukemia (CML) due to its continuous, long-term use. A study by Ganesan and colleagues found that nonadherence to imatinib showed a significant decrease in 5-year event-free survival between 76.7% of adherent participants compared with 59.8% of nonadherent participants.¹ This study found that 44% of patients who were adherent to imatinib achieved complete cytogenetic response vs only 26% of patients who were nonadherent. In another study of imatinib for CML, major molecular response (MMR) was strongly correlated with adherence and no patients with adherence < 80% were able to achieve MMR.² Similarly, in studies of tamoxifen for breast cancer, < 80% adherence resulted in a 10% decrease in survival when compared to those who were more adherent.^3,4

In addition to the clinical implications of nonadherence, there can be a significant cost associated with suboptimal use of these medications. The price of a single dose of OAN medication may cost as much as $440.⁵

The benefits of multidisciplinary care teams have been identified in many studies.^6,7 While studies are limited in oncology, pharmacists provide vital contributions to the oncology multidisciplinary team when managing OANs as these health care professionals have expert knowledge of the medications, potential adverse events (AEs), and necessary monitoring parameters.⁸ In one study, patients seen by the pharmacist-led oral chemotherapy management program experienced improved clinical outcomes and response to therapy when compared with preintervention patients (early molecular response, 88.9% vs 54.8%, P = .01; major molecular response, 83.3% vs 57.6%, P = .06).⁹ During the study, 318 AEs were reported, leading to 235 pharmacist interventions to ameliorate AEs and improve adherence.

The primary objective of this study was to measure the impact of a pharmacist-driven OAN renewal clinic on medication adherence. The secondary objective was to estimate cost-savings of this new service.

Methods

Prior to July 2014, several limitations were identified related to OAN prescribing and monitoring at the Richard L. Roudebush Veterans Affairs Medical Center in Indianapolis, Indiana (RLRVAMC). The prescription ordering process relied primarily on the patient to initiate refills, rather than the prescriber OAN prescriptions also lacked consistency for number of refills or quantities dispensed. Furthermore, ordering of antineoplastic products was not limited to hematology/oncology providers. Patients were identified with significant supply on hand at the time of medication discontinuation, creating concerns for medication waste, tolerability, and nonadherence.

As a result, opportunities were identified to improve the prescribing process, recommended monitoring, toxicity and tolerability evaluation, medication reconciliation, and medication adherence. In July of 2014, the RLRVAMC adopted a new chemotherapy order entry system capable of restricting prescriptions to hematology/oncology providers and limiting dispensed quantities and refill amounts. A comprehensive pharmacist driven OAN renewal clinic was implemented on September 1, 2014 with the goal of improving long-term adherence and tolerability, in addition to minimizing medication waste.

Study Design and Setting

This was a pre/post retrospective cohort, quality improvement study of patients enrolled in the RLRVAMC OAN pharmacist renewal clinic. The study was deemed exempt from institutional review board (IRB) by the US Department of Veterans Affairs (VA) Research and Development Department.

Study Population

Patients were included in the preimplementation group if they had received at least 2 prescriptions of an eligible OAN. Therapy for the preimplementation group was required to be a monthly duration > 21 days and between the dates of September 1, 2013 and August 31, 2014. Patients were included in the postimplementation group if they had received at least 2 prescriptions of the studied OANs between September 1, 2014 and January 31, 2015. Patients were excluded if they had filled < 2 prescriptions of OAN; were managed by a non-VA oncologist or hematologist; or received an OAN other than those listed in Table 1.

Data Collection

For all patients in both the pre- and postimplementation cohorts, a standardized data collection tool was used to collect the following via electronic health record review by a PGY2 oncology resident: age, race, gender, oral antineoplastic agent, refill dates, days’ supply, estimated unit cost per dose cancer diagnosis, distance from the RLRVAMC, copay status, presence of hospitalizations/ED visits/dosage reductions, discontinuation rates, reasons for discontinuation, and total number of current prescriptions. The presence or absence of dosage reductions were collected to identify concerns for tolerability, but only the original dose for the preimplementation group and dosage at time of clinic enrollment for the postimplementation group was included in the analysis.

Outcomes and Statistical Analyses

The primary outcome was medication adherence defined as the median medication possession ratio (MPR) before and after implementation of the clinic. Secondary outcomes included the proportion of patients who were adherent from before implementation to after and estimated cost-savings of this clinic after implementation. MPR was used to estimate medication adherence by taking the cumulative day supply of medication on hand divided by the number of days on therapy.¹² Number of days on therapy was determined by taking the difference on the start date of the new medication regimen and the discontinuation date of the same regimen. Patients were grouped by adherence into one of the following categories: < 0.8, 0.8 to 0.89, 0.9 to 1, and > 1.1. Patients were considered adherent if they reported taking ≥ 90% (MPR ≥ 0.9) of prescribed doses, adopted from the study by Anderson and colleagues.¹² A patient with an MPR > 1, likely due to filling prior to the anticipated refill date, was considered 100% adherent (MPR = 1). If a patient switched OAN during the study, both agents were included as separate entities.

A conservative estimate of cost-savings was made by multiplying the RLRVAMC cost per unit of medication at time of initial prescription fill by the number of units taken each day multiplied by the total days’ supply on hand at time of therapy discontinuation. Patients with an MPR < 1 at time of therapy discontinuation were assumed to have zero remaining units on hand and zero cost savings was estimated. Waste, for purposes of cost-savings, was calculated for all MPR values > 1. Additional supply anticipated to be on hand from dose reductions was not included in the estimated cost of unused medication.

Descriptive statistics compared demographic characteristics between the pre- and postimplementation groups. MPR data were not normally distributed, which required the use of nonparametric Mann-Whitney U tests to compare pre- and postMPRs. Pearson χ² compared the proportion of adherent patients between groups while descriptive statistics were used to estimate cost savings. Significance was determined based on a P value < .05. IBM SPSS Statistics software was used for all statistical analyses. As this was a complete sample of all eligible subjects, no sample size calculation was performed.

Results

In the preimplementation period, 246 patients received an OAN and 61 patients received an OAN in the postimplementation period (Figure 1). Of the 246 patients in the preimplementation period, 98 were eligible and included in the preimplementation group. Similarly, of the 61 patients in the postimplementation period, 35 patients met inclusion criteria for the postimplementation group. The study population was predominantly male with an average age of approximately 70 years in both groups (Table 3). More than 70% of the population in each group was White. No statistically significant differences between groups were identified. The most commonly prescribed OAN in the preimplementation group were abiraterone, imatinib, and enzalutamide (Table 3). In the postimplementation group, the most commonly prescribed agents were abiraterone, imatinib, pazopanib, and dasatinib. No significant differences were observed in prescribing of individual agents between the pre- and postimplementation groups or other characteristics that may affect adherence including patient copay status, number of concomitant medications, and driving distance from the RLRVAMC.

Thirty-six (36.7%) patients in the preimplementation group were considered nonadherent (MPR < 0.9) and 18 (18.4%) had an MPR < 0.8. Fifteen (15.3%) patients in the preimplementation clinic were considered overadherent (MPR > 1.1). Forty-seven (47.9%) patients in the preimplementation group were considered adherent (MPR 0.9 - 1.1) while all 35 (100%) patients in the postimplementation group were considered adherent (MPR 0.9 - 1.1). No non- or overadherent patients were identified in the postimplementation group (Figure 2). The median MPR for all patients in the preimplementation group was 0.94 compared with 1.06 (P < .001) in the postimplementation group.

Discussion

OANs are widely used therapies, with more than 25 million doses administered per year in the United States alone.¹² The use of these agents will continue to grow as more targeted agents become available and patients request more convenient treatment options. The role for hematology/oncology clinical pharmacy services must adapt to this increased usage of OANs, including increasing pharmacist involvement in medication education, adherence and tolerability assessments, and proactive drug interaction monitoring.However, additional research is needed to determine optimal management strategies.

Our study aimed to compare OAN adherence among patients at a tertiary care VA hospital before and after implementation of a renewal clinic. The preimplementation population had a median MPR of 0.94 compared with 1.06 in the postimplementation group (P < .001). Although an ideal MPR is 1.0, we aimed for a slightly higher MPR to allow a supply buffer in the event of prescription delivery delays, as more than 90% of prescriptions are mailed to patients from a regional mail-order pharmacy. Importantly, the median MPRs do not adequately convey the impact from this clinic. The proportion of patients who were considered adherent to OANs increased from 47.9% in the preimplementation to 100% in the postimplementation period. These finding suggest that the clinical pharmacist role to assess and encourage adherence through monitoring tolerability of these OANs improved the overall medication taking experience of these patients.

Upon initial evaluation of adherence pre- and postimplementation, median adherence rates in both groups appeared to be above goal at 0.94 and 1.06 respectively. Patients in the postimplementation group intentionally received a 5- to 7-day supply buffer to account for potential prescription delivery delays due to holidays and inclement weather. This would indicate that the patients in the postimplementation group would have 15% oversupply due to the 5-day supply buffer. After correcting for patients with confounding reasons for excess (dose reductions, breaks in treatment, etc.), the median MPR in the prerefill clinic group decreased to 0.9 and the MPR in the postrefill clinic group increased slightly to 1.08. Although the median adherence rate in both the pre- and postimplementation groups were above goal of 0.90, 36% of the patients in the preimplementation group were considered nonadherent (MPR < 0.9) compared with no patients in the postimplementation group. Therefore, our intervention to improve patient adherence appeared to be beneficial at our institution.

In addition to improving adherence, one of the goals of the renewal clinic was to minimize excess supply at the time of therapy discontinuation. This was accomplished by aligning medication fills with medical visits and objective monitoring, as well as limiting supply to no more than 30 days. Of the patients in the postimplementation group, only 1 patient had remaining medication at the time of therapy discontinuation compared with 14 patients in the preimplementation group. The estimated cost savings from excess supply was $36,335. Limiting the amount of unused supply not only saves money for the patient and the institution, but also decreases opportunity for improper hazardous waste disposal and unnecessary exposure of hazardous materials to others.

Our results show the pharmacist intervention in the coordination of renewals improved adherence, minimized medication waste, and saved money. The cost of pharmacist time participating in the refill clinic was not calculated. Each visit was completed in approximately 5 minutes, with subsequent documentation and coordination taking an additional 5 to 10 minutes. During the launch of this service, the oncology pharmacy resident provided all coverage of the clinic. Oversite of the resident was provided by hematology/oncology clinical pharmacy specialists. We have continued to utilize pharmacy resident coverage since that time to meet education needs and keep the estimated cost per visit low. Another option in the case that pharmacy residents are not available would be utilization of a pharmacy technician, intern, or professional student to conduct the adherence and tolerability phone assessments. Our escalation protocol allows intervention by clinical pharmacy specialist and/or other health care providers when necessary. Trainees have only required basic training on how to use the protocol.

Limitations

Due to this study’s retrospective design, an inherent limitation is dependence on prescriber and refill records for documentation of initiation and discontinuation dates. Therefore, only the association of impact of pharmacist intervention on medication adherence can be determined as opposed to causation. We did not take into account discrepancies in day supply secondary to ‘held’ therapies, dose reductions, or doses supplied during an inpatient admission, which may alter estimates of MPR and cost-savings data. Patients in the postimplementation group intentionally received a 5 to 7-day supply buffer to account for potential prescription delivery delays due to holidays and inclement weather. This would indicate that the patients in the postimplementation group would have 15% oversupply due to the 5-day supply buffer, thereby skewing MPR values. This study did not account for cost avoidance resulting from early identification and management of toxicity. Finally, the postimplementation data only spans 4 months and a longer duration of time is needed to more accurately determine sustainability of renewal clinic interventions and provide comprehensive evaluation of cost-avoidance.

Conclusion

Implementation of an OAN renewal clinic was associated with an increase in MPR, improved proportion of patients considered adherent, and an estimated $36,335 cost-savings. However, prospective evaluation and a longer study duration are needed to determine causality of improved adherence and cost-savings associated with a pharmacist-driven OAN renewal clinic.

Evaluation of oral antineoplastic agent (OAN) adherence patterns have identified correlations between nonadherence or over-adherence and poorer disease-related outcomes. Multiple studies have focused on imatinib use in chronic myeloid leukemia (CML) due to its continuous, long-term use. A study by Ganesan and colleagues found that nonadherence to imatinib showed a significant decrease in 5-year event-free survival between 76.7% of adherent participants compared with 59.8% of nonadherent participants.¹ This study found that 44% of patients who were adherent to imatinib achieved complete cytogenetic response vs only 26% of patients who were nonadherent. In another study of imatinib for CML, major molecular response (MMR) was strongly correlated with adherence and no patients with adherence < 80% were able to achieve MMR.² Similarly, in studies of tamoxifen for breast cancer, < 80% adherence resulted in a 10% decrease in survival when compared to those who were more adherent.^3,4

In addition to the clinical implications of nonadherence, there can be a significant cost associated with suboptimal use of these medications. The price of a single dose of OAN medication may cost as much as $440.⁵

The benefits of multidisciplinary care teams have been identified in many studies.^6,7 While studies are limited in oncology, pharmacists provide vital contributions to the oncology multidisciplinary team when managing OANs as these health care professionals have expert knowledge of the medications, potential adverse events (AEs), and necessary monitoring parameters.⁸ In one study, patients seen by the pharmacist-led oral chemotherapy management program experienced improved clinical outcomes and response to therapy when compared with preintervention patients (early molecular response, 88.9% vs 54.8%, P = .01; major molecular response, 83.3% vs 57.6%, P = .06).⁹ During the study, 318 AEs were reported, leading to 235 pharmacist interventions to ameliorate AEs and improve adherence.

The primary objective of this study was to measure the impact of a pharmacist-driven OAN renewal clinic on medication adherence. The secondary objective was to estimate cost-savings of this new service.

Methods

Prior to July 2014, several limitations were identified related to OAN prescribing and monitoring at the Richard L. Roudebush Veterans Affairs Medical Center in Indianapolis, Indiana (RLRVAMC). The prescription ordering process relied primarily on the patient to initiate refills, rather than the prescriber OAN prescriptions also lacked consistency for number of refills or quantities dispensed. Furthermore, ordering of antineoplastic products was not limited to hematology/oncology providers. Patients were identified with significant supply on hand at the time of medication discontinuation, creating concerns for medication waste, tolerability, and nonadherence.

As a result, opportunities were identified to improve the prescribing process, recommended monitoring, toxicity and tolerability evaluation, medication reconciliation, and medication adherence. In July of 2014, the RLRVAMC adopted a new chemotherapy order entry system capable of restricting prescriptions to hematology/oncology providers and limiting dispensed quantities and refill amounts. A comprehensive pharmacist driven OAN renewal clinic was implemented on September 1, 2014 with the goal of improving long-term adherence and tolerability, in addition to minimizing medication waste.

Study Design and Setting

This was a pre/post retrospective cohort, quality improvement study of patients enrolled in the RLRVAMC OAN pharmacist renewal clinic. The study was deemed exempt from institutional review board (IRB) by the US Department of Veterans Affairs (VA) Research and Development Department.

Study Population

Patients were included in the preimplementation group if they had received at least 2 prescriptions of an eligible OAN. Therapy for the preimplementation group was required to be a monthly duration > 21 days and between the dates of September 1, 2013 and August 31, 2014. Patients were included in the postimplementation group if they had received at least 2 prescriptions of the studied OANs between September 1, 2014 and January 31, 2015. Patients were excluded if they had filled < 2 prescriptions of OAN; were managed by a non-VA oncologist or hematologist; or received an OAN other than those listed in Table 1.

Data Collection

For all patients in both the pre- and postimplementation cohorts, a standardized data collection tool was used to collect the following via electronic health record review by a PGY2 oncology resident: age, race, gender, oral antineoplastic agent, refill dates, days’ supply, estimated unit cost per dose cancer diagnosis, distance from the RLRVAMC, copay status, presence of hospitalizations/ED visits/dosage reductions, discontinuation rates, reasons for discontinuation, and total number of current prescriptions. The presence or absence of dosage reductions were collected to identify concerns for tolerability, but only the original dose for the preimplementation group and dosage at time of clinic enrollment for the postimplementation group was included in the analysis.

Outcomes and Statistical Analyses

The primary outcome was medication adherence defined as the median medication possession ratio (MPR) before and after implementation of the clinic. Secondary outcomes included the proportion of patients who were adherent from before implementation to after and estimated cost-savings of this clinic after implementation. MPR was used to estimate medication adherence by taking the cumulative day supply of medication on hand divided by the number of days on therapy.¹² Number of days on therapy was determined by taking the difference on the start date of the new medication regimen and the discontinuation date of the same regimen. Patients were grouped by adherence into one of the following categories: < 0.8, 0.8 to 0.89, 0.9 to 1, and > 1.1. Patients were considered adherent if they reported taking ≥ 90% (MPR ≥ 0.9) of prescribed doses, adopted from the study by Anderson and colleagues.¹² A patient with an MPR > 1, likely due to filling prior to the anticipated refill date, was considered 100% adherent (MPR = 1). If a patient switched OAN during the study, both agents were included as separate entities.

A conservative estimate of cost-savings was made by multiplying the RLRVAMC cost per unit of medication at time of initial prescription fill by the number of units taken each day multiplied by the total days’ supply on hand at time of therapy discontinuation. Patients with an MPR < 1 at time of therapy discontinuation were assumed to have zero remaining units on hand and zero cost savings was estimated. Waste, for purposes of cost-savings, was calculated for all MPR values > 1. Additional supply anticipated to be on hand from dose reductions was not included in the estimated cost of unused medication.

Descriptive statistics compared demographic characteristics between the pre- and postimplementation groups. MPR data were not normally distributed, which required the use of nonparametric Mann-Whitney U tests to compare pre- and postMPRs. Pearson χ² compared the proportion of adherent patients between groups while descriptive statistics were used to estimate cost savings. Significance was determined based on a P value < .05. IBM SPSS Statistics software was used for all statistical analyses. As this was a complete sample of all eligible subjects, no sample size calculation was performed.

Results

In the preimplementation period, 246 patients received an OAN and 61 patients received an OAN in the postimplementation period (Figure 1). Of the 246 patients in the preimplementation period, 98 were eligible and included in the preimplementation group. Similarly, of the 61 patients in the postimplementation period, 35 patients met inclusion criteria for the postimplementation group. The study population was predominantly male with an average age of approximately 70 years in both groups (Table 3). More than 70% of the population in each group was White. No statistically significant differences between groups were identified. The most commonly prescribed OAN in the preimplementation group were abiraterone, imatinib, and enzalutamide (Table 3). In the postimplementation group, the most commonly prescribed agents were abiraterone, imatinib, pazopanib, and dasatinib. No significant differences were observed in prescribing of individual agents between the pre- and postimplementation groups or other characteristics that may affect adherence including patient copay status, number of concomitant medications, and driving distance from the RLRVAMC.

Thirty-six (36.7%) patients in the preimplementation group were considered nonadherent (MPR < 0.9) and 18 (18.4%) had an MPR < 0.8. Fifteen (15.3%) patients in the preimplementation clinic were considered overadherent (MPR > 1.1). Forty-seven (47.9%) patients in the preimplementation group were considered adherent (MPR 0.9 - 1.1) while all 35 (100%) patients in the postimplementation group were considered adherent (MPR 0.9 - 1.1). No non- or overadherent patients were identified in the postimplementation group (Figure 2). The median MPR for all patients in the preimplementation group was 0.94 compared with 1.06 (P < .001) in the postimplementation group.

Discussion

OANs are widely used therapies, with more than 25 million doses administered per year in the United States alone.¹² The use of these agents will continue to grow as more targeted agents become available and patients request more convenient treatment options. The role for hematology/oncology clinical pharmacy services must adapt to this increased usage of OANs, including increasing pharmacist involvement in medication education, adherence and tolerability assessments, and proactive drug interaction monitoring.However, additional research is needed to determine optimal management strategies.

Our study aimed to compare OAN adherence among patients at a tertiary care VA hospital before and after implementation of a renewal clinic. The preimplementation population had a median MPR of 0.94 compared with 1.06 in the postimplementation group (P < .001). Although an ideal MPR is 1.0, we aimed for a slightly higher MPR to allow a supply buffer in the event of prescription delivery delays, as more than 90% of prescriptions are mailed to patients from a regional mail-order pharmacy. Importantly, the median MPRs do not adequately convey the impact from this clinic. The proportion of patients who were considered adherent to OANs increased from 47.9% in the preimplementation to 100% in the postimplementation period. These finding suggest that the clinical pharmacist role to assess and encourage adherence through monitoring tolerability of these OANs improved the overall medication taking experience of these patients.

Upon initial evaluation of adherence pre- and postimplementation, median adherence rates in both groups appeared to be above goal at 0.94 and 1.06 respectively. Patients in the postimplementation group intentionally received a 5- to 7-day supply buffer to account for potential prescription delivery delays due to holidays and inclement weather. This would indicate that the patients in the postimplementation group would have 15% oversupply due to the 5-day supply buffer. After correcting for patients with confounding reasons for excess (dose reductions, breaks in treatment, etc.), the median MPR in the prerefill clinic group decreased to 0.9 and the MPR in the postrefill clinic group increased slightly to 1.08. Although the median adherence rate in both the pre- and postimplementation groups were above goal of 0.90, 36% of the patients in the preimplementation group were considered nonadherent (MPR < 0.9) compared with no patients in the postimplementation group. Therefore, our intervention to improve patient adherence appeared to be beneficial at our institution.

In addition to improving adherence, one of the goals of the renewal clinic was to minimize excess supply at the time of therapy discontinuation. This was accomplished by aligning medication fills with medical visits and objective monitoring, as well as limiting supply to no more than 30 days. Of the patients in the postimplementation group, only 1 patient had remaining medication at the time of therapy discontinuation compared with 14 patients in the preimplementation group. The estimated cost savings from excess supply was $36,335. Limiting the amount of unused supply not only saves money for the patient and the institution, but also decreases opportunity for improper hazardous waste disposal and unnecessary exposure of hazardous materials to others.

Our results show the pharmacist intervention in the coordination of renewals improved adherence, minimized medication waste, and saved money. The cost of pharmacist time participating in the refill clinic was not calculated. Each visit was completed in approximately 5 minutes, with subsequent documentation and coordination taking an additional 5 to 10 minutes. During the launch of this service, the oncology pharmacy resident provided all coverage of the clinic. Oversite of the resident was provided by hematology/oncology clinical pharmacy specialists. We have continued to utilize pharmacy resident coverage since that time to meet education needs and keep the estimated cost per visit low. Another option in the case that pharmacy residents are not available would be utilization of a pharmacy technician, intern, or professional student to conduct the adherence and tolerability phone assessments. Our escalation protocol allows intervention by clinical pharmacy specialist and/or other health care providers when necessary. Trainees have only required basic training on how to use the protocol.

Limitations

Due to this study’s retrospective design, an inherent limitation is dependence on prescriber and refill records for documentation of initiation and discontinuation dates. Therefore, only the association of impact of pharmacist intervention on medication adherence can be determined as opposed to causation. We did not take into account discrepancies in day supply secondary to ‘held’ therapies, dose reductions, or doses supplied during an inpatient admission, which may alter estimates of MPR and cost-savings data. Patients in the postimplementation group intentionally received a 5 to 7-day supply buffer to account for potential prescription delivery delays due to holidays and inclement weather. This would indicate that the patients in the postimplementation group would have 15% oversupply due to the 5-day supply buffer, thereby skewing MPR values. This study did not account for cost avoidance resulting from early identification and management of toxicity. Finally, the postimplementation data only spans 4 months and a longer duration of time is needed to more accurately determine sustainability of renewal clinic interventions and provide comprehensive evaluation of cost-avoidance.

Conclusion

Implementation of an OAN renewal clinic was associated with an increase in MPR, improved proportion of patients considered adherent, and an estimated $36,335 cost-savings. However, prospective evaluation and a longer study duration are needed to determine causality of improved adherence and cost-savings associated with a pharmacist-driven OAN renewal clinic.

More than 70% of Americans are overweight or obese and 1 in 10 has type 2 diabetes mellitus (T2DM). In the last 20 years, the prevalence of obesity and DM has each increased drastically according to the Centers for Disease Control and Prevention.^1,2 Thus, an increase in severe insulin-resistant DM is predicted. Severe insulin resistance occurs when insulin doses exceed 200 units per day or 2 units/kg per day.^3-5 Treating this condition demands large volumes of U-100 insulin and a high frequency of injections (usually 4-7 per day), which can lead to reduced patient adherence.^8-10 Likewise, large injected volumes are more painful and can lead to altered absorption.^3,9-11

U-500 insulin (500 units/mL) is 5 times more concentrated than U-100 insulin and has advantages in the management of severe insulin-resistant DM.^11-13 Its pharmacokinetic profile is unique, for the clinical effect can last for up to 24 hours.^4-6 U-500 can replace basal-bolus and other complex insulin regimens, offering convenient, effective glycemic control with 2 or 3 injections per day.^11,14-20 U-500 can also improve the quality of life and adherence compared with formulations that require more frequent injections.^7,14,21 Historically, only exceptional or “special” cases were treated with U-500, but demand for concentrated insulins has increased in the last decade as clinicians adjust their care for this growing patient population.¹⁷

The purpose of this study was to determine whether a population of subjects with severe insulin-resistant T2DM would benefit from the use of U-500 vs U-100 insulin regimens. The hypothesis was that this population would obtain equal or better glycemic control while achieving improved adherence. Other studies have demonstrated that U-500 yields improvements in glycemic control but also potentially increases hypoglycemic episodes.^15-18,22-24 To our knowledge, this study is the first to evaluate the clinical outcomes of subjects with severe insulin-resistant T2DM who changed from U-100 to U-500 vs subjects who remained on high-dose U-100 insulin.

Methods

This was a single-site, retrospective chart review of subjects with T2DM who attended the endocrinology specialty clinic at the James A. Haley Veterans’ Hospital (JAHVA) in Tampa, Florida, between July 2002 and June 2011. The study included a group of subjects using U-500 insulin and a comparison group using U-100 insulin. The study was approved by the JAHVA Research & Development Committee and by the University of South Florida Institutional Review Board.

Inclusion criteria included diagnosis of T2DM, body mass index (BMI) of more than 30, use of U-500 insulin, or > 200 units daily of U-100 insulin. Exclusion criteria included hypoglycemia unawareness, type 1 DM, and use of an insulin pump. A total of 142 subjects met the inclusion criteria (68 in the U-500 group and 74 in the U-100 group).

All study subjects had at least 1 DM education session. U-500 subjects used insulin vials and 1-mL volumetric hypodermal syringes. All U-500 prescriptions were issued electronically in units and volume (U-500 insulin was available exclusively in vials during the time frame from which data were collected). Subjects in the U-100 group used insulin vials or pen devices. Laboratory studies were processed in house by the institution using high-pressure liquid chromatography to determine hemoglobin A_1C (Hb A_1C) levels. All study subjects required at least 2 Hb A_1C measurements over the observed 12 months for inclusion.

Transition to U-500 Insulin

U-500 transition was considered routinely and presented as an option for patients requiring > 200 units of insulin daily. The transition criteria included adherence to medications, follow-up appointments, and glucose monitoring recommendations, and ability to learn and apply insulin self-adjustment instructions. All subjects were given an additional U-500 insulin education session before transition. The endocrinologist calculated all starting doses by reducing the total daily dose by 20%.

Data Collection

Data were collected using the automatic data mining tools within the JAHVA Computerized Patient Record System and confirmed individually by clinical staff. Demographic data included age, race, and sex. Other parameters were weight; BMI; Hb A_1C; estimated glomerular filtration rate (eGFR); duration of DM; use of metformin and other oral agents; total daily insulin dose; number of daily injections; prior history of atherosclerotic cardiovascular disease (ASCVD), including coronary artery disease (CAD), cerebrovascular accident (CVA), or peripheral vascular disease (PVD); occurrence of severe hypoglycemia (symptomatic hypoglycemia requiring treatment assistance from another individual) and of new cardiovascular events, classified as CAD, CVA, or PVD.

For the U-500 group, data were collected and analyzed for the 3 months before (baseline) and the 12 months after the initiation of concentrated insulin. For the U-100 group, data were collected and analyzed for the comparable 3 months before (baseline) and the 12 months after the first clinic visit in which the subject started using more than 200 units per day of U-100. Frequency of follow-up visits was individualized according to clinical needs.

Clinical Endpoints

Primary outcomes included changes in Hb A_1C from baseline to the following 12 months, and the occurrence of severe hypoglycemia. Secondary outcomes included the occurrence of new ASCVD events during the study, and changes in weight, BMI, and number of injections.

Statistical Analysis

A descriptive analysis was applied to the categorical variables using absolute and relative frequencies. For continuous variables, mean and SD, or median and interquartile range, according to the distribution were calculated. Differences in baseline characteristics between groups were determined using chi-square and t test.

The primary and secondary outcomes were assessed through univariate and multivariate general linear models. Multivariate models were used to compare differences in the variation of Hb A_1C over time. Data were incomplete for the Hb A_1C in 27 subjects, 6% of the dataset (Each subject had more than one variable or observation). Therefore, a multiple imputation was used to account for the incompleteness on Hb A_1C (value substitutions by the mean and by the prior Hb A_1C and models were balanced against the unaltered data). A P value of ≤ .05 was used to determine statistical significance. The statistical analyses were performed using IBM SPSS Statistics 21.

Results

Most patients were male (94%) of white race (86%), with a mean age of 57 years and comparable duration of DM (Table 1). Demographics were balanced between the groups, except for weight and BMI, both higher in the U-500 group (P < .001). Use of oral antidiabetic agents was not significantly different between groups, nor were comorbid conditions, with nearly 50% of subjects in each group affected by CKD and ASCVD, of which CAD was the most common (approximately 40% of both groups). Only about one-third of subjects used metformin and/or other oral agents, likely due to the high prevalence of CKD (contraindicating metformin) and high insulin requirements (due to correlation with β cell failure). A subgroup analysis of subjects on metformin did not demonstrate significant differences in risk of severe hypoglycemia or in Hb A_1C levels (data not shown).

Both groups had similar initial Hb A_1C baselines (> 9%) and both improved glycemic control during the study period. However, the Hb A_1C reduction was greater in the U-500 group (P= .034), 0.84% vs 0.56% for U-100 and the between-groups difference was 0.4%. (Figure 1, Tables 2 and 3).

The univariate general linear model shows a statistically significant difference in the levels of Hb A_1C within each treatment group, regardless of the imputation strategy. However, the differences were not significant when comparing postintervention Hb A_1C means between groups with unaltered data (P = .23), because the U-500 group Hb A_1C improvement gap narrowed at the end of study. In the multivariate analysis, irrespective of imputation method, the differences in Hb A_1C between group treated with U-100 and U-500 were statistically significant (Table 3).

Overall, more subjects in the U-500 group than in the U-100 group achieved Hb A_1C levels < 8.5% (56% vs 46%, respectively, P = .003) and the proportion of subjects achieving Hb A_1C levels < 7.5% doubled that of the U-100 group (26% vs 12%; Figure 2). Five subjects in the U-500 group experienced severe hypoglycemia, compared with 1 in the U-100 group (P = .08). The total daily insulin dose was significantly higher in the U-500 group (296 units daily) than in the U-100 group (209 units daily) (P < .001) (Table 2). Baseline weight and BMI differences were also significant for the U-500 and U-100 groups (P < .001). Weight gain of approximately 2 kg occurred in both groups, a change that was not statistically significant (P = .79)

Discussion

The purpose of the study was to compare subjects with obesity and T2DM using U-500 concentrated insulin with similarly matched subjects using U-100 insulin. Available studies using U-500 insulin, including prospective trials, have reported the experience after transitioning patients who “failed” U-100 regimens.^{13-16,18,21-24} This failure is a relative and transient condition that, in theory, could be improved with medical intervention and lifestyle changes. Such changes cannot be easily quantified in a clinical trial or retrospective study without a control group. This study was an attempt to fill this knowledge gap.

The U-500 intervention resulted in a 0.8% overall reduction in Hb A_1C and a significant 0.4% reduction compared to subjects using U-100. While both groups had improvement in Hb A_1C , U-500 was associated with superior reductions in Hb A_1C . This finding confirms prior assertions that U-500, compared with U-100, is associated with larger Hb A_1C improvement.^14-16

The preintervention and postintervention Hb A_1C means were > 8% in both groups. This finding suggests that lowering Hb A_1C is challenging, similar to published results demonstrating that Hb A_1C levels < 7% are achieved by fewer than one-third of U-500 users.^16-18 The explanation for this finding remains elusive, due to the methodologic limitations of a retrospective analysis. A possible explanation is the high prevalence of CKD and ASCVD among the study population, conditions which, according to guidelines justify less aggressive glycemic control efforts.²⁵ Multiple prior studies using retrospective data^8,13-16 and 2 prospective trials^18,22 demonstrated similar Hb A_1C reductions after failure of U-100 regimens.

In this study, U-500 resulted in a nominal increase in the risk of severe hypoglycemic episodes. A detailed review of the events found that most of these patients had preestablished CKD and ASCVD, and half of the subjects with sever hypoglycemic episodes had new vascular events during the study (Appendix). These findings suggest a possible correlation between CKD and ASCVD complications and the risk of severe hypoglycemic events. Pharmacokinetic profiles for U-500 have not been studied in subjects with CKD, but the clinical effect of CKD is likely prolonged by the expected reduction in insulin clearance. Similarly, the frailty associated with preexisting ASCVD, or the related polypharmacy, could be factors increasing the risk of hypoglycemia and deserve further study.

Most of the U-500 subjects used it twice daily in this study, which could have contributed to the higher hypoglycemia rate. In a prospective randomized trial Hood and colleagues reported a rate of symptomatic hypoglycemia exceeding 90% in the 2 study groups, and 8 subjects (of 325 total) had severe hypoglycemia during the 6-month observation. The group assigned to 2 daily injections had a significantly higher rate of hypoglycemic events compared with a group that had 3 injections per day.¹⁸ Additional studies are required to ascertain whether U-500, compared with specific U-100 regimens (basal-bolus vs premixed; human vs insulin analogs), results in a higher risk of severe hypoglycemia.

This study also investigated the incidence of new cardiovascular events, and no difference was found between the 2 groups. A longer observation would be required to better assess whether U-500 therapy can reduce the incidence of microvascular and macrovascular complications. The similar incidence of complications is further evidence of the similarity between the 2 studied groups. It was also reassuring to find that weight gains were small and nearly identical in both insulin groups.

Strengths and Limitations

This study has several limitations. Data about hospitalizations for congestive heart failure, amputations, progression of diabetic retinopathy, neuropathy, and nephropathy were not collected for this analysis. As both groups of subjects were relatively small, statistical power to assess outcomes is a concern. Retrospective chart reviews may also be affected by incomplete data collections and multiple biases. No data were available for other hypoglycemic episodes, especially to calculate the rate of the more common forms of hypoglycemia. The period of data analyzed spanned only about 15 months. A longer, longitudinal assessment of the differences between these 2 groups may yield more differences, and clearer results and conclusions. Moreover, the data set had aged before publication of this report; however, the authors think that the analysis and information remain highly clinically relevant. The uncommon use of U-500, and prominence as a “special case” insulin may also lead to a detection bias for severe hypoglycemia in the U-500 group. In contrast, lapses in documentation of hypoglycemia in subjects using U-100 could have occurred. Finally, the differences in total daily dose and body weight among groups were significant and may reflect on important physiologic differences between the 2 groups that may affect the reproducibility of our results.

Nevertheless, this study had notable strengths. Comparing U-500 insulin users with similar subjects using U-100 over a period of time provides head-to-head data with potentially important clinical utility. Also, we collected and analyzed a sizable number of clinically important variables, including cardiovascular risk factors, the occurrence of new cardiovascular events, and prevalence of renal disease. The use of linear regression and multivariate analysis using multiple models also strengthened the results. Previous studies compared the outcomes in subjects using U-500 insulin with only their historical selves.^{8,13-16,18,19,22-25} Therefore, these studies analyzed the data for preconversion and postconversion of U-500 only and consistently favored U-500. This design in a retrospective study cannot eliminate the selection and/or intervention biases, as the subjects of study had inevitably “failed” prior therapies. Similarly, there is no prospective clinical trial data comparing patients on U-500 with patients on high doses of U-100 insulin. Finally, the patients in our study had high rates of comorbidities, which may have increased the applicability of our results to those of “real-life” patients in the community. To our knowledge, no other study has attempted a similar study design approach either prospectively or retrospectively.

Conclusions

In this population of elderly veterans with severely insulin-resistant T2DM, with a high incidence of CKD and ASCVD, U-500 insulin was associated with significantly greater reductions in Hb A_1C than U-100 insulin-based regimens, while requiring fewer injections. No difference was noted in the incidence of new ASCVD events. More studies are needed to assess whether U-500 may increase the risk of severe hypoglycemic episodes.

Acknowledgments

The authors recognize the invaluable help provided by the editorial staff of University of South Florida IMpact, the Intramural Review to Support Research and Scientific Publication, and especially to Richard F. Lockey, MD, who has mentored us in this beautiful journey of scientific writing and for his editorial assistance. A portion of this study preliminary data was presented as an abstract at ENDO 2013, The Endocrine Society Annual meeting in San Francisco, CA, June 15-18, 2013.

Appendix. Severe Hypoglycemic Events

Subject 1: U-500 user, 61-year-old African American male. Hypoglycemia occurred during fasting and was associated with a seizure-like event 9 months after transition to concentrated insulin. He was taken by ambulance to a local hospital. No additional data were obtained. Hb A_1C was 8.2% in the month before the episode (lowest of the studied period) and increased to 9.1% in the last segment of the study.

Subject 2: U-500 user, 57-year-old white male. The severe hypoglycemic episode occurred approximately 8 months after transition. His Hb A_1C was 5.6% around the time of the event, the lowest of the studied period, and increased to 6.8% over the next 4 months. No other data were available.

Subject 3: U-500 user, 67-year-old white male. The event occurred at home in the morning while fasting, 3 months after transition. He was assisted by his family. Hb A_1C was 7.1% 10 weeks after the event and was 7% at the end of the studied period. He had a history of CKD and PVD.

Subject 4: U-500 user, 68-year-old white male. He presented with altered consciousness, hypoglycemia, and elevated troponin levels, which was later confirmed as a non-ST elevation myocardial infarction (NSTEMI), 7 months after transition. Hb A_1C during the events was 7.1% and was followed by a 9.3% level 9 weeks later. He had history of CKD and PVD.

Subject 5: U-500 user, 67-year-old white man. Hypoglycemia occurred 6 months after transition to U-500. Hb A_1C was 8.4% 2 months prior, and was followed by a 7% during the admission for severe hypoglycemia. 3 months later, his HbA1c rose to 8.2%. He had an extensive history of CAD and had a NSTEMI during the study period.

Subject 6: U-100 user, 65-year-old white man. He was found unconscious in the morning while fasting, 6 months after his first clinic visit. He had CKD and advanced ASCVD with prior CAD, PVD, and CVA. He had also had a recent CVA that had affected his movement and cognition.

More than 70% of Americans are overweight or obese and 1 in 10 has type 2 diabetes mellitus (T2DM). In the last 20 years, the prevalence of obesity and DM has each increased drastically according to the Centers for Disease Control and Prevention.^1,2 Thus, an increase in severe insulin-resistant DM is predicted. Severe insulin resistance occurs when insulin doses exceed 200 units per day or 2 units/kg per day.^3-5 Treating this condition demands large volumes of U-100 insulin and a high frequency of injections (usually 4-7 per day), which can lead to reduced patient adherence.^8-10 Likewise, large injected volumes are more painful and can lead to altered absorption.^3,9-11

U-500 insulin (500 units/mL) is 5 times more concentrated than U-100 insulin and has advantages in the management of severe insulin-resistant DM.^11-13 Its pharmacokinetic profile is unique, for the clinical effect can last for up to 24 hours.^4-6 U-500 can replace basal-bolus and other complex insulin regimens, offering convenient, effective glycemic control with 2 or 3 injections per day.^11,14-20 U-500 can also improve the quality of life and adherence compared with formulations that require more frequent injections.^7,14,21 Historically, only exceptional or “special” cases were treated with U-500, but demand for concentrated insulins has increased in the last decade as clinicians adjust their care for this growing patient population.¹⁷

The purpose of this study was to determine whether a population of subjects with severe insulin-resistant T2DM would benefit from the use of U-500 vs U-100 insulin regimens. The hypothesis was that this population would obtain equal or better glycemic control while achieving improved adherence. Other studies have demonstrated that U-500 yields improvements in glycemic control but also potentially increases hypoglycemic episodes.^15-18,22-24 To our knowledge, this study is the first to evaluate the clinical outcomes of subjects with severe insulin-resistant T2DM who changed from U-100 to U-500 vs subjects who remained on high-dose U-100 insulin.

Methods

This was a single-site, retrospective chart review of subjects with T2DM who attended the endocrinology specialty clinic at the James A. Haley Veterans’ Hospital (JAHVA) in Tampa, Florida, between July 2002 and June 2011. The study included a group of subjects using U-500 insulin and a comparison group using U-100 insulin. The study was approved by the JAHVA Research & Development Committee and by the University of South Florida Institutional Review Board.

Inclusion criteria included diagnosis of T2DM, body mass index (BMI) of more than 30, use of U-500 insulin, or > 200 units daily of U-100 insulin. Exclusion criteria included hypoglycemia unawareness, type 1 DM, and use of an insulin pump. A total of 142 subjects met the inclusion criteria (68 in the U-500 group and 74 in the U-100 group).

All study subjects had at least 1 DM education session. U-500 subjects used insulin vials and 1-mL volumetric hypodermal syringes. All U-500 prescriptions were issued electronically in units and volume (U-500 insulin was available exclusively in vials during the time frame from which data were collected). Subjects in the U-100 group used insulin vials or pen devices. Laboratory studies were processed in house by the institution using high-pressure liquid chromatography to determine hemoglobin A_1C (Hb A_1C) levels. All study subjects required at least 2 Hb A_1C measurements over the observed 12 months for inclusion.

Transition to U-500 Insulin

U-500 transition was considered routinely and presented as an option for patients requiring > 200 units of insulin daily. The transition criteria included adherence to medications, follow-up appointments, and glucose monitoring recommendations, and ability to learn and apply insulin self-adjustment instructions. All subjects were given an additional U-500 insulin education session before transition. The endocrinologist calculated all starting doses by reducing the total daily dose by 20%.

Data Collection

Data were collected using the automatic data mining tools within the JAHVA Computerized Patient Record System and confirmed individually by clinical staff. Demographic data included age, race, and sex. Other parameters were weight; BMI; Hb A_1C; estimated glomerular filtration rate (eGFR); duration of DM; use of metformin and other oral agents; total daily insulin dose; number of daily injections; prior history of atherosclerotic cardiovascular disease (ASCVD), including coronary artery disease (CAD), cerebrovascular accident (CVA), or peripheral vascular disease (PVD); occurrence of severe hypoglycemia (symptomatic hypoglycemia requiring treatment assistance from another individual) and of new cardiovascular events, classified as CAD, CVA, or PVD.

For the U-500 group, data were collected and analyzed for the 3 months before (baseline) and the 12 months after the initiation of concentrated insulin. For the U-100 group, data were collected and analyzed for the comparable 3 months before (baseline) and the 12 months after the first clinic visit in which the subject started using more than 200 units per day of U-100. Frequency of follow-up visits was individualized according to clinical needs.

Clinical Endpoints

Primary outcomes included changes in Hb A_1C from baseline to the following 12 months, and the occurrence of severe hypoglycemia. Secondary outcomes included the occurrence of new ASCVD events during the study, and changes in weight, BMI, and number of injections.

Statistical Analysis

A descriptive analysis was applied to the categorical variables using absolute and relative frequencies. For continuous variables, mean and SD, or median and interquartile range, according to the distribution were calculated. Differences in baseline characteristics between groups were determined using chi-square and t test.

The primary and secondary outcomes were assessed through univariate and multivariate general linear models. Multivariate models were used to compare differences in the variation of Hb A_1C over time. Data were incomplete for the Hb A_1C in 27 subjects, 6% of the dataset (Each subject had more than one variable or observation). Therefore, a multiple imputation was used to account for the incompleteness on Hb A_1C (value substitutions by the mean and by the prior Hb A_1C and models were balanced against the unaltered data). A P value of ≤ .05 was used to determine statistical significance. The statistical analyses were performed using IBM SPSS Statistics 21.

Results

Most patients were male (94%) of white race (86%), with a mean age of 57 years and comparable duration of DM (Table 1). Demographics were balanced between the groups, except for weight and BMI, both higher in the U-500 group (P < .001). Use of oral antidiabetic agents was not significantly different between groups, nor were comorbid conditions, with nearly 50% of subjects in each group affected by CKD and ASCVD, of which CAD was the most common (approximately 40% of both groups). Only about one-third of subjects used metformin and/or other oral agents, likely due to the high prevalence of CKD (contraindicating metformin) and high insulin requirements (due to correlation with β cell failure). A subgroup analysis of subjects on metformin did not demonstrate significant differences in risk of severe hypoglycemia or in Hb A_1C levels (data not shown).

Both groups had similar initial Hb A_1C baselines (> 9%) and both improved glycemic control during the study period. However, the Hb A_1C reduction was greater in the U-500 group (P= .034), 0.84% vs 0.56% for U-100 and the between-groups difference was 0.4%. (Figure 1, Tables 2 and 3).

The univariate general linear model shows a statistically significant difference in the levels of Hb A_1C within each treatment group, regardless of the imputation strategy. However, the differences were not significant when comparing postintervention Hb A_1C means between groups with unaltered data (P = .23), because the U-500 group Hb A_1C improvement gap narrowed at the end of study. In the multivariate analysis, irrespective of imputation method, the differences in Hb A_1C between group treated with U-100 and U-500 were statistically significant (Table 3).

Overall, more subjects in the U-500 group than in the U-100 group achieved Hb A_1C levels < 8.5% (56% vs 46%, respectively, P = .003) and the proportion of subjects achieving Hb A_1C levels < 7.5% doubled that of the U-100 group (26% vs 12%; Figure 2). Five subjects in the U-500 group experienced severe hypoglycemia, compared with 1 in the U-100 group (P = .08). The total daily insulin dose was significantly higher in the U-500 group (296 units daily) than in the U-100 group (209 units daily) (P < .001) (Table 2). Baseline weight and BMI differences were also significant for the U-500 and U-100 groups (P < .001). Weight gain of approximately 2 kg occurred in both groups, a change that was not statistically significant (P = .79)

Discussion

The purpose of the study was to compare subjects with obesity and T2DM using U-500 concentrated insulin with similarly matched subjects using U-100 insulin. Available studies using U-500 insulin, including prospective trials, have reported the experience after transitioning patients who “failed” U-100 regimens.^{13-16,18,21-24} This failure is a relative and transient condition that, in theory, could be improved with medical intervention and lifestyle changes. Such changes cannot be easily quantified in a clinical trial or retrospective study without a control group. This study was an attempt to fill this knowledge gap.

The U-500 intervention resulted in a 0.8% overall reduction in Hb A_1C and a significant 0.4% reduction compared to subjects using U-100. While both groups had improvement in Hb A_1C , U-500 was associated with superior reductions in Hb A_1C . This finding confirms prior assertions that U-500, compared with U-100, is associated with larger Hb A_1C improvement.^14-16

The preintervention and postintervention Hb A_1C means were > 8% in both groups. This finding suggests that lowering Hb A_1C is challenging, similar to published results demonstrating that Hb A_1C levels < 7% are achieved by fewer than one-third of U-500 users.^16-18 The explanation for this finding remains elusive, due to the methodologic limitations of a retrospective analysis. A possible explanation is the high prevalence of CKD and ASCVD among the study population, conditions which, according to guidelines justify less aggressive glycemic control efforts.²⁵ Multiple prior studies using retrospective data^8,13-16 and 2 prospective trials^18,22 demonstrated similar Hb A_1C reductions after failure of U-100 regimens.

In this study, U-500 resulted in a nominal increase in the risk of severe hypoglycemic episodes. A detailed review of the events found that most of these patients had preestablished CKD and ASCVD, and half of the subjects with sever hypoglycemic episodes had new vascular events during the study (Appendix). These findings suggest a possible correlation between CKD and ASCVD complications and the risk of severe hypoglycemic events. Pharmacokinetic profiles for U-500 have not been studied in subjects with CKD, but the clinical effect of CKD is likely prolonged by the expected reduction in insulin clearance. Similarly, the frailty associated with preexisting ASCVD, or the related polypharmacy, could be factors increasing the risk of hypoglycemia and deserve further study.

Most of the U-500 subjects used it twice daily in this study, which could have contributed to the higher hypoglycemia rate. In a prospective randomized trial Hood and colleagues reported a rate of symptomatic hypoglycemia exceeding 90% in the 2 study groups, and 8 subjects (of 325 total) had severe hypoglycemia during the 6-month observation. The group assigned to 2 daily injections had a significantly higher rate of hypoglycemic events compared with a group that had 3 injections per day.¹⁸ Additional studies are required to ascertain whether U-500, compared with specific U-100 regimens (basal-bolus vs premixed; human vs insulin analogs), results in a higher risk of severe hypoglycemia.

This study also investigated the incidence of new cardiovascular events, and no difference was found between the 2 groups. A longer observation would be required to better assess whether U-500 therapy can reduce the incidence of microvascular and macrovascular complications. The similar incidence of complications is further evidence of the similarity between the 2 studied groups. It was also reassuring to find that weight gains were small and nearly identical in both insulin groups.

Strengths and Limitations

This study has several limitations. Data about hospitalizations for congestive heart failure, amputations, progression of diabetic retinopathy, neuropathy, and nephropathy were not collected for this analysis. As both groups of subjects were relatively small, statistical power to assess outcomes is a concern. Retrospective chart reviews may also be affected by incomplete data collections and multiple biases. No data were available for other hypoglycemic episodes, especially to calculate the rate of the more common forms of hypoglycemia. The period of data analyzed spanned only about 15 months. A longer, longitudinal assessment of the differences between these 2 groups may yield more differences, and clearer results and conclusions. Moreover, the data set had aged before publication of this report; however, the authors think that the analysis and information remain highly clinically relevant. The uncommon use of U-500, and prominence as a “special case” insulin may also lead to a detection bias for severe hypoglycemia in the U-500 group. In contrast, lapses in documentation of hypoglycemia in subjects using U-100 could have occurred. Finally, the differences in total daily dose and body weight among groups were significant and may reflect on important physiologic differences between the 2 groups that may affect the reproducibility of our results.

Nevertheless, this study had notable strengths. Comparing U-500 insulin users with similar subjects using U-100 over a period of time provides head-to-head data with potentially important clinical utility. Also, we collected and analyzed a sizable number of clinically important variables, including cardiovascular risk factors, the occurrence of new cardiovascular events, and prevalence of renal disease. The use of linear regression and multivariate analysis using multiple models also strengthened the results. Previous studies compared the outcomes in subjects using U-500 insulin with only their historical selves.^{8,13-16,18,19,22-25} Therefore, these studies analyzed the data for preconversion and postconversion of U-500 only and consistently favored U-500. This design in a retrospective study cannot eliminate the selection and/or intervention biases, as the subjects of study had inevitably “failed” prior therapies. Similarly, there is no prospective clinical trial data comparing patients on U-500 with patients on high doses of U-100 insulin. Finally, the patients in our study had high rates of comorbidities, which may have increased the applicability of our results to those of “real-life” patients in the community. To our knowledge, no other study has attempted a similar study design approach either prospectively or retrospectively.

Conclusions

In this population of elderly veterans with severely insulin-resistant T2DM, with a high incidence of CKD and ASCVD, U-500 insulin was associated with significantly greater reductions in Hb A_1C than U-100 insulin-based regimens, while requiring fewer injections. No difference was noted in the incidence of new ASCVD events. More studies are needed to assess whether U-500 may increase the risk of severe hypoglycemic episodes.

Acknowledgments

The authors recognize the invaluable help provided by the editorial staff of University of South Florida IMpact, the Intramural Review to Support Research and Scientific Publication, and especially to Richard F. Lockey, MD, who has mentored us in this beautiful journey of scientific writing and for his editorial assistance. A portion of this study preliminary data was presented as an abstract at ENDO 2013, The Endocrine Society Annual meeting in San Francisco, CA, June 15-18, 2013.

Appendix. Severe Hypoglycemic Events

Subject 1: U-500 user, 61-year-old African American male. Hypoglycemia occurred during fasting and was associated with a seizure-like event 9 months after transition to concentrated insulin. He was taken by ambulance to a local hospital. No additional data were obtained. Hb A_1C was 8.2% in the month before the episode (lowest of the studied period) and increased to 9.1% in the last segment of the study.

Subject 2: U-500 user, 57-year-old white male. The severe hypoglycemic episode occurred approximately 8 months after transition. His Hb A_1C was 5.6% around the time of the event, the lowest of the studied period, and increased to 6.8% over the next 4 months. No other data were available.

Subject 3: U-500 user, 67-year-old white male. The event occurred at home in the morning while fasting, 3 months after transition. He was assisted by his family. Hb A_1C was 7.1% 10 weeks after the event and was 7% at the end of the studied period. He had a history of CKD and PVD.

Subject 4: U-500 user, 68-year-old white male. He presented with altered consciousness, hypoglycemia, and elevated troponin levels, which was later confirmed as a non-ST elevation myocardial infarction (NSTEMI), 7 months after transition. Hb A_1C during the events was 7.1% and was followed by a 9.3% level 9 weeks later. He had history of CKD and PVD.

Subject 5: U-500 user, 67-year-old white man. Hypoglycemia occurred 6 months after transition to U-500. Hb A_1C was 8.4% 2 months prior, and was followed by a 7% during the admission for severe hypoglycemia. 3 months later, his HbA1c rose to 8.2%. He had an extensive history of CAD and had a NSTEMI during the study period.

Subject 6: U-100 user, 65-year-old white man. He was found unconscious in the morning while fasting, 6 months after his first clinic visit. He had CKD and advanced ASCVD with prior CAD, PVD, and CVA. He had also had a recent CVA that had affected his movement and cognition.

More than 70% of Americans are overweight or obese and 1 in 10 has type 2 diabetes mellitus (T2DM). In the last 20 years, the prevalence of obesity and DM has each increased drastically according to the Centers for Disease Control and Prevention.^1,2 Thus, an increase in severe insulin-resistant DM is predicted. Severe insulin resistance occurs when insulin doses exceed 200 units per day or 2 units/kg per day.^3-5 Treating this condition demands large volumes of U-100 insulin and a high frequency of injections (usually 4-7 per day), which can lead to reduced patient adherence.^8-10 Likewise, large injected volumes are more painful and can lead to altered absorption.^3,9-11

U-500 insulin (500 units/mL) is 5 times more concentrated than U-100 insulin and has advantages in the management of severe insulin-resistant DM.^11-13 Its pharmacokinetic profile is unique, for the clinical effect can last for up to 24 hours.^4-6 U-500 can replace basal-bolus and other complex insulin regimens, offering convenient, effective glycemic control with 2 or 3 injections per day.^11,14-20 U-500 can also improve the quality of life and adherence compared with formulations that require more frequent injections.^7,14,21 Historically, only exceptional or “special” cases were treated with U-500, but demand for concentrated insulins has increased in the last decade as clinicians adjust their care for this growing patient population.¹⁷

The purpose of this study was to determine whether a population of subjects with severe insulin-resistant T2DM would benefit from the use of U-500 vs U-100 insulin regimens. The hypothesis was that this population would obtain equal or better glycemic control while achieving improved adherence. Other studies have demonstrated that U-500 yields improvements in glycemic control but also potentially increases hypoglycemic episodes.^15-18,22-24 To our knowledge, this study is the first to evaluate the clinical outcomes of subjects with severe insulin-resistant T2DM who changed from U-100 to U-500 vs subjects who remained on high-dose U-100 insulin.

Methods

This was a single-site, retrospective chart review of subjects with T2DM who attended the endocrinology specialty clinic at the James A. Haley Veterans’ Hospital (JAHVA) in Tampa, Florida, between July 2002 and June 2011. The study included a group of subjects using U-500 insulin and a comparison group using U-100 insulin. The study was approved by the JAHVA Research & Development Committee and by the University of South Florida Institutional Review Board.

Inclusion criteria included diagnosis of T2DM, body mass index (BMI) of more than 30, use of U-500 insulin, or > 200 units daily of U-100 insulin. Exclusion criteria included hypoglycemia unawareness, type 1 DM, and use of an insulin pump. A total of 142 subjects met the inclusion criteria (68 in the U-500 group and 74 in the U-100 group).

All study subjects had at least 1 DM education session. U-500 subjects used insulin vials and 1-mL volumetric hypodermal syringes. All U-500 prescriptions were issued electronically in units and volume (U-500 insulin was available exclusively in vials during the time frame from which data were collected). Subjects in the U-100 group used insulin vials or pen devices. Laboratory studies were processed in house by the institution using high-pressure liquid chromatography to determine hemoglobin A_1C (Hb A_1C) levels. All study subjects required at least 2 Hb A_1C measurements over the observed 12 months for inclusion.

Transition to U-500 Insulin

U-500 transition was considered routinely and presented as an option for patients requiring > 200 units of insulin daily. The transition criteria included adherence to medications, follow-up appointments, and glucose monitoring recommendations, and ability to learn and apply insulin self-adjustment instructions. All subjects were given an additional U-500 insulin education session before transition. The endocrinologist calculated all starting doses by reducing the total daily dose by 20%.

Data Collection

Data were collected using the automatic data mining tools within the JAHVA Computerized Patient Record System and confirmed individually by clinical staff. Demographic data included age, race, and sex. Other parameters were weight; BMI; Hb A_1C; estimated glomerular filtration rate (eGFR); duration of DM; use of metformin and other oral agents; total daily insulin dose; number of daily injections; prior history of atherosclerotic cardiovascular disease (ASCVD), including coronary artery disease (CAD), cerebrovascular accident (CVA), or peripheral vascular disease (PVD); occurrence of severe hypoglycemia (symptomatic hypoglycemia requiring treatment assistance from another individual) and of new cardiovascular events, classified as CAD, CVA, or PVD.

For the U-500 group, data were collected and analyzed for the 3 months before (baseline) and the 12 months after the initiation of concentrated insulin. For the U-100 group, data were collected and analyzed for the comparable 3 months before (baseline) and the 12 months after the first clinic visit in which the subject started using more than 200 units per day of U-100. Frequency of follow-up visits was individualized according to clinical needs.

Clinical Endpoints

Primary outcomes included changes in Hb A_1C from baseline to the following 12 months, and the occurrence of severe hypoglycemia. Secondary outcomes included the occurrence of new ASCVD events during the study, and changes in weight, BMI, and number of injections.

Statistical Analysis

A descriptive analysis was applied to the categorical variables using absolute and relative frequencies. For continuous variables, mean and SD, or median and interquartile range, according to the distribution were calculated. Differences in baseline characteristics between groups were determined using chi-square and t test.

The primary and secondary outcomes were assessed through univariate and multivariate general linear models. Multivariate models were used to compare differences in the variation of Hb A_1C over time. Data were incomplete for the Hb A_1C in 27 subjects, 6% of the dataset (Each subject had more than one variable or observation). Therefore, a multiple imputation was used to account for the incompleteness on Hb A_1C (value substitutions by the mean and by the prior Hb A_1C and models were balanced against the unaltered data). A P value of ≤ .05 was used to determine statistical significance. The statistical analyses were performed using IBM SPSS Statistics 21.

Results

Most patients were male (94%) of white race (86%), with a mean age of 57 years and comparable duration of DM (Table 1). Demographics were balanced between the groups, except for weight and BMI, both higher in the U-500 group (P < .001). Use of oral antidiabetic agents was not significantly different between groups, nor were comorbid conditions, with nearly 50% of subjects in each group affected by CKD and ASCVD, of which CAD was the most common (approximately 40% of both groups). Only about one-third of subjects used metformin and/or other oral agents, likely due to the high prevalence of CKD (contraindicating metformin) and high insulin requirements (due to correlation with β cell failure). A subgroup analysis of subjects on metformin did not demonstrate significant differences in risk of severe hypoglycemia or in Hb A_1C levels (data not shown).

Both groups had similar initial Hb A_1C baselines (> 9%) and both improved glycemic control during the study period. However, the Hb A_1C reduction was greater in the U-500 group (P= .034), 0.84% vs 0.56% for U-100 and the between-groups difference was 0.4%. (Figure 1, Tables 2 and 3).

The univariate general linear model shows a statistically significant difference in the levels of Hb A_1C within each treatment group, regardless of the imputation strategy. However, the differences were not significant when comparing postintervention Hb A_1C means between groups with unaltered data (P = .23), because the U-500 group Hb A_1C improvement gap narrowed at the end of study. In the multivariate analysis, irrespective of imputation method, the differences in Hb A_1C between group treated with U-100 and U-500 were statistically significant (Table 3).

Overall, more subjects in the U-500 group than in the U-100 group achieved Hb A_1C levels < 8.5% (56% vs 46%, respectively, P = .003) and the proportion of subjects achieving Hb A_1C levels < 7.5% doubled that of the U-100 group (26% vs 12%; Figure 2). Five subjects in the U-500 group experienced severe hypoglycemia, compared with 1 in the U-100 group (P = .08). The total daily insulin dose was significantly higher in the U-500 group (296 units daily) than in the U-100 group (209 units daily) (P < .001) (Table 2). Baseline weight and BMI differences were also significant for the U-500 and U-100 groups (P < .001). Weight gain of approximately 2 kg occurred in both groups, a change that was not statistically significant (P = .79)

Discussion

The purpose of the study was to compare subjects with obesity and T2DM using U-500 concentrated insulin with similarly matched subjects using U-100 insulin. Available studies using U-500 insulin, including prospective trials, have reported the experience after transitioning patients who “failed” U-100 regimens.^{13-16,18,21-24} This failure is a relative and transient condition that, in theory, could be improved with medical intervention and lifestyle changes. Such changes cannot be easily quantified in a clinical trial or retrospective study without a control group. This study was an attempt to fill this knowledge gap.

The U-500 intervention resulted in a 0.8% overall reduction in Hb A_1C and a significant 0.4% reduction compared to subjects using U-100. While both groups had improvement in Hb A_1C , U-500 was associated with superior reductions in Hb A_1C . This finding confirms prior assertions that U-500, compared with U-100, is associated with larger Hb A_1C improvement.^14-16

The preintervention and postintervention Hb A_1C means were > 8% in both groups. This finding suggests that lowering Hb A_1C is challenging, similar to published results demonstrating that Hb A_1C levels < 7% are achieved by fewer than one-third of U-500 users.^16-18 The explanation for this finding remains elusive, due to the methodologic limitations of a retrospective analysis. A possible explanation is the high prevalence of CKD and ASCVD among the study population, conditions which, according to guidelines justify less aggressive glycemic control efforts.²⁵ Multiple prior studies using retrospective data^8,13-16 and 2 prospective trials^18,22 demonstrated similar Hb A_1C reductions after failure of U-100 regimens.

In this study, U-500 resulted in a nominal increase in the risk of severe hypoglycemic episodes. A detailed review of the events found that most of these patients had preestablished CKD and ASCVD, and half of the subjects with sever hypoglycemic episodes had new vascular events during the study (Appendix). These findings suggest a possible correlation between CKD and ASCVD complications and the risk of severe hypoglycemic events. Pharmacokinetic profiles for U-500 have not been studied in subjects with CKD, but the clinical effect of CKD is likely prolonged by the expected reduction in insulin clearance. Similarly, the frailty associated with preexisting ASCVD, or the related polypharmacy, could be factors increasing the risk of hypoglycemia and deserve further study.

Most of the U-500 subjects used it twice daily in this study, which could have contributed to the higher hypoglycemia rate. In a prospective randomized trial Hood and colleagues reported a rate of symptomatic hypoglycemia exceeding 90% in the 2 study groups, and 8 subjects (of 325 total) had severe hypoglycemia during the 6-month observation. The group assigned to 2 daily injections had a significantly higher rate of hypoglycemic events compared with a group that had 3 injections per day.¹⁸ Additional studies are required to ascertain whether U-500, compared with specific U-100 regimens (basal-bolus vs premixed; human vs insulin analogs), results in a higher risk of severe hypoglycemia.

This study also investigated the incidence of new cardiovascular events, and no difference was found between the 2 groups. A longer observation would be required to better assess whether U-500 therapy can reduce the incidence of microvascular and macrovascular complications. The similar incidence of complications is further evidence of the similarity between the 2 studied groups. It was also reassuring to find that weight gains were small and nearly identical in both insulin groups.

Strengths and Limitations

This study has several limitations. Data about hospitalizations for congestive heart failure, amputations, progression of diabetic retinopathy, neuropathy, and nephropathy were not collected for this analysis. As both groups of subjects were relatively small, statistical power to assess outcomes is a concern. Retrospective chart reviews may also be affected by incomplete data collections and multiple biases. No data were available for other hypoglycemic episodes, especially to calculate the rate of the more common forms of hypoglycemia. The period of data analyzed spanned only about 15 months. A longer, longitudinal assessment of the differences between these 2 groups may yield more differences, and clearer results and conclusions. Moreover, the data set had aged before publication of this report; however, the authors think that the analysis and information remain highly clinically relevant. The uncommon use of U-500, and prominence as a “special case” insulin may also lead to a detection bias for severe hypoglycemia in the U-500 group. In contrast, lapses in documentation of hypoglycemia in subjects using U-100 could have occurred. Finally, the differences in total daily dose and body weight among groups were significant and may reflect on important physiologic differences between the 2 groups that may affect the reproducibility of our results.

Nevertheless, this study had notable strengths. Comparing U-500 insulin users with similar subjects using U-100 over a period of time provides head-to-head data with potentially important clinical utility. Also, we collected and analyzed a sizable number of clinically important variables, including cardiovascular risk factors, the occurrence of new cardiovascular events, and prevalence of renal disease. The use of linear regression and multivariate analysis using multiple models also strengthened the results. Previous studies compared the outcomes in subjects using U-500 insulin with only their historical selves.^{8,13-16,18,19,22-25} Therefore, these studies analyzed the data for preconversion and postconversion of U-500 only and consistently favored U-500. This design in a retrospective study cannot eliminate the selection and/or intervention biases, as the subjects of study had inevitably “failed” prior therapies. Similarly, there is no prospective clinical trial data comparing patients on U-500 with patients on high doses of U-100 insulin. Finally, the patients in our study had high rates of comorbidities, which may have increased the applicability of our results to those of “real-life” patients in the community. To our knowledge, no other study has attempted a similar study design approach either prospectively or retrospectively.

Conclusions

In this population of elderly veterans with severely insulin-resistant T2DM, with a high incidence of CKD and ASCVD, U-500 insulin was associated with significantly greater reductions in Hb A_1C than U-100 insulin-based regimens, while requiring fewer injections. No difference was noted in the incidence of new ASCVD events. More studies are needed to assess whether U-500 may increase the risk of severe hypoglycemic episodes.

Acknowledgments

The authors recognize the invaluable help provided by the editorial staff of University of South Florida IMpact, the Intramural Review to Support Research and Scientific Publication, and especially to Richard F. Lockey, MD, who has mentored us in this beautiful journey of scientific writing and for his editorial assistance. A portion of this study preliminary data was presented as an abstract at ENDO 2013, The Endocrine Society Annual meeting in San Francisco, CA, June 15-18, 2013.

Appendix. Severe Hypoglycemic Events

Subject 1: U-500 user, 61-year-old African American male. Hypoglycemia occurred during fasting and was associated with a seizure-like event 9 months after transition to concentrated insulin. He was taken by ambulance to a local hospital. No additional data were obtained. Hb A_1C was 8.2% in the month before the episode (lowest of the studied period) and increased to 9.1% in the last segment of the study.

Subject 2: U-500 user, 57-year-old white male. The severe hypoglycemic episode occurred approximately 8 months after transition. His Hb A_1C was 5.6% around the time of the event, the lowest of the studied period, and increased to 6.8% over the next 4 months. No other data were available.

Subject 3: U-500 user, 67-year-old white male. The event occurred at home in the morning while fasting, 3 months after transition. He was assisted by his family. Hb A_1C was 7.1% 10 weeks after the event and was 7% at the end of the studied period. He had a history of CKD and PVD.

Subject 4: U-500 user, 68-year-old white male. He presented with altered consciousness, hypoglycemia, and elevated troponin levels, which was later confirmed as a non-ST elevation myocardial infarction (NSTEMI), 7 months after transition. Hb A_1C during the events was 7.1% and was followed by a 9.3% level 9 weeks later. He had history of CKD and PVD.

Subject 5: U-500 user, 67-year-old white man. Hypoglycemia occurred 6 months after transition to U-500. Hb A_1C was 8.4% 2 months prior, and was followed by a 7% during the admission for severe hypoglycemia. 3 months later, his HbA1c rose to 8.2%. He had an extensive history of CAD and had a NSTEMI during the study period.

Subject 6: U-100 user, 65-year-old white man. He was found unconscious in the morning while fasting, 6 months after his first clinic visit. He had CKD and advanced ASCVD with prior CAD, PVD, and CVA. He had also had a recent CVA that had affected his movement and cognition.