Publications by authors named "Nazleen F Khan"

12 Publications

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Coprescription of Opioids With Other Medications and Risk of Opioid Overdose.

Clin Pharmacol Ther 2021 May 28. Epub 2021 May 28.

Division of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA.

Polypharmacy is common among patients taking prescription opioids long-term, and the codispensing of interacting medications may further increase opioid overdose risk. To identify nonopioid medications that may increase opioid overdose risk in this population, we conducted a case-crossover-based screening of electronic claims data from IBM MarketScan and Optum Clinformatics Data Mart spanning 2003 through 2019. Eligible patients were 18 years of age or older and had at least 180 days of continuous enrollment and 90 days of prescription opioid use immediately before an opioid overdose resulting in an emergency room visit or hospitalization. The main analysis quantified the odds ratio (OR) between opioid overdose and each nonopioid medication dispensed in the 90 days immediately before the opioid overdose date after adjustment for prescription opioid dosage and benzodiazepine codispensing. Additional analyses restricted to patients without cancer diagnoses and individuals who used only oxycodone for 90 days immediately before the opioid overdose date. The false discovery rate (FDR) was used to account for multiple testing. We identified 24,866 individuals who experienced opioid overdose. Baclofen (OR 1.56; FDR < 0.01; 95% confidence interval (CI), 1.29 to 1.89), lorazepam (OR 1.53; FDR < 0.01; 95% CI, 1.25 to 1.88), and gabapentin (OR 1.16; FDR = 0.09; 95% CI, 1.04 to 1.28), among other nonopioid medications, were associated with opioid overdose. Similar patterns were observed in noncancer patients and individuals who used only oxycodone. Interventions may focus on prescribing safer alternatives when a potential for interaction exists.
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http://dx.doi.org/10.1002/cpt.2314DOI Listing
May 2021

Association of Opioid Overdose With Opioid Prescriptions to Family Members.

JAMA Intern Med 2019 Sep;179(9):1186-1192

Division of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts.

Importance: Prescription opioid misuse is a public health problem that leads to overdose. Although existing interventions focus on limiting prescribing to patients at high risk, individuals may still access prescription opioids dispensed to family members.

Objective: To determine whether opioid prescriptions to family members were associated with overdose for individuals who themselves did not have an opioid prescription.

Design, Setting, And Participants: We conducted a 1:4 matched case-control study using health care utilization data from 2004 through 2015 from a large US commercial insurance company. Eligible individuals were required to have at least 12 months of continuous enrollment and 1 or more family members in the database. Individuals who experienced overdose were identified by their first opioid overdose after the baseline period and matched to control participants by time in the database, calendar time, age, sex, and number of individuals in the family unit. Both groups were restricted to individuals with no prior opioid dispensing of their own. Data analysis was conducted from January 2018 to August 2018.

Exposures: Any prior opioid dispensing to a family member, total morphine milligram equivalents dispensed to family members, and the type of opioid product dispensed.

Main Outcomes And Measures: Individual odds of opioid overdose resulting in an emergency department visit or hospitalization were the primary end point. The primary analysis evaluated the odds of overdose among individuals whose family members had been dispensed an opioid. Sensitivity analyses examined the odds stratified by age and timing relative to the dispensing of opioids to family members.

Results: A total of 2303 individuals who experienced opioid overdose and 9212 matched control individuals were identified. The mean (SD) age was 23.2 (18.1) years; 1158 affected individuals and 4632 control individuals (50.3%) were female. The mean (SD) time in the database before an overdose case was 3.2 (3.3) years. Prior opioid dispensing to family members was associated with individual overdose (odds ratio [OR], 2.89 [95% CI, 2.59-3.23]). There was a significant dose-response association between increasing amounts of opioids dispensed to family members and odds of overdose (>0-<50 morphine milligram equivalents per day: OR, 2.71 [95% CI, 2.42-3.03]; 50-<90 morphine milligram equivalents per day: OR, 7.80 [95% CI, 3.63-16.78]; ≥90 morphine milligram equivalents per day: OR, 15.08 [95% CI, 8.66-26.27]).

Conclusions And Relevance: In this analysis, opioid prescriptions to family members were associated with overdose among individuals who do not receive opioid prescriptions. Interventions may focus on expanding access to opioid antagonists, locking prescription opioids in the home, and providing greater patient education to limit fatal overdose among family members.
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http://dx.doi.org/10.1001/jamainternmed.2019.1064DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6593630PMC
September 2019

Comparative effectiveness of generic and brand-name medication use: A database study of US health insurance claims.

PLoS Med 2019 03 13;16(3):e1002763. Epub 2019 Mar 13.

Division of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts, United States of America.

Background: To the extent that outcomes are mediated through negative perceptions of generics (the nocebo effect), observational studies comparing brand-name and generic drugs are susceptible to bias favoring the brand-name drugs. We used authorized generic (AG) products, which are identical in composition and appearance to brand-name products but are marketed as generics, as a control group to address this bias in an evaluation aiming to compare the effectiveness of generic versus brand medications.

Methods And Findings: For commercial health insurance enrollees from the US, administrative claims data were derived from 2 databases: (1) Optum Clinformatics Data Mart (years: 2004-2013) and (2) Truven MarketScan (years: 2003-2015). For a total of 8 drug products, the following groups were compared using a cohort study design: (1) patients switching from brand-name products to AGs versus generics, and patients initiating treatment with AGs versus generics, where AG use proxied brand-name use, addressing negative perception bias, and (2) patients initiating generic versus brand-name products (bias-prone direct comparison) and patients initiating AG versus brand-name products (negative control). Using Cox proportional hazards regression after 1:1 propensity-score matching, we compared a composite cardiovascular endpoint (for amlodipine, amlodipine-benazepril, and quinapril), non-vertebral fracture (for alendronate and calcitonin), psychiatric hospitalization rate (for sertraline and escitalopram), and insulin initiation (for glipizide) between the groups. Inverse variance meta-analytic methods were used to pool adjusted hazard ratios (HRs) for each comparison between the 2 databases. Across 8 products, 2,264,774 matched pairs of patients were included in the comparisons of AGs versus generics. A majority (12 out of 16) of the clinical endpoint estimates showed similar outcomes between AGs and generics. Among the other 4 estimates that did have significantly different outcomes, 3 suggested improved outcomes with generics and 1 favored AGs (patients switching from amlodipine brand-name: HR [95% CI] 0.92 [0.88-0.97]). The comparison between generic and brand-name initiators involved 1,313,161 matched pairs, and no differences in outcomes were noted for alendronate, calcitonin, glipizide, or quinapril. We observed a lower risk of the composite cardiovascular endpoint with generics versus brand-name products for amlodipine and amlodipine-benazepril (HR [95% CI]: 0.91 [0.84-0.99] and 0.84 [0.76-0.94], respectively). For escitalopram and sertraline, we observed higher rates of psychiatric hospitalizations with generics (HR [95% CI]: 1.05 [1.01-1.10] and 1.07 [1.01-1.14], respectively). The negative control comparisons also indicated potentially higher rates of similar magnitude with AG compared to brand-name initiation for escitalopram and sertraline (HR [95% CI]: 1.06 [0.98-1.13] and 1.11 [1.05-1.18], respectively), suggesting that the differences observed between brand and generic users in these outcomes are likely explained by either residual confounding or generic perception bias. Limitations of this study include potential residual confounding due to the unavailability of certain clinical parameters in administrative claims data and the inability to evaluate surrogate outcomes, such as immediate changes in blood pressure, upon switching from brand products to generics.

Conclusions: In this study, we observed that use of generics was associated with comparable clinical outcomes to use of brand-name products. These results could help in promoting educational interventions aimed at increasing patient and provider confidence in the ability of generic medicines to manage chronic diseases.
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http://dx.doi.org/10.1371/journal.pmed.1002763DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6415809PMC
March 2019

Implementation of a Health Plan Program for Switching From Analogue to Human Insulin and Glycemic Control Among Medicare Beneficiaries With Type 2 Diabetes.

JAMA 2019 01;321(4):374-384

Program On Regulation, Therapeutics, And Law, Division of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts.

Importance: Prices for newer analogue insulin products have increased. Lower-cost human insulin may be effective for many patients with type 2 diabetes.

Objective: To evaluate the association between implementation of a health plan-based intervention of switching patients from analogue to human insulin and glycemic control.

Design, Setting, And Participants: A retrospective cohort study using population-level interrupted times series analysis of members participating in a Medicare Advantage and prescription drug plan operating in 4 US states. Participants were prescribed insulin between January 1, 2014, and December 31, 2016 (median follow-up, 729 days). The intervention began in February 2015 and was expanded to the entire health plan system by June 2015.

Exposures: Implementation of a health plan program to switch patients from analogue to human insulin.

Main Outcomes And Measures: The primary outcome was the change in mean hemoglobin A1c (HbA1c) levels estimated over three 12-month periods: preintervention (baseline) in 2014, intervention in 2015, and postintervention in 2016. Secondary outcomes included rates of serious hypoglycemia or hyperglycemia using ICD-9-CM and ICD-10-CM diagnostic codes.

Results: Over 3 years, 14 635 members (mean [SD] age: 72.5 [9.8] years; 51% women; 93% with type 2 diabetes) filled 221 866 insulin prescriptions. The mean HbA1c was 8.46% (95% CI, 8.40%-8.52%) at baseline and decreased at a rate of -0.02% (95% CI, -0.03% to -0.01%; P <.001) per month before the intervention. There was an association between the start of the intervention and an overall HbA1c level increase of 0.14% (95% CI, 0.05%-0.23%; P = .003) and slope change of 0.02% (95% CI, 0.01%-0.03%; P < .001). After the completion of the intervention, there were no significant differences in changes in the level (0.08% [95% CI, -0.01% to 0.17%]) or slope (<0.001% [95% CI, -0.008% to 0.010%]) of mean HbA1c compared with the intervention period (P = .09 and P = 0.81, respectively). For serious hypoglycemic events, there was no significant association between the start of the intervention and a level (2.66/1000 person-years [95% CI, -3.82 to 9.13]; P = .41) or slope change (-0.66/1000 person-years [95% CI, -1.59 to 0.27]; P = .16). The level (1.64/1000 person-years [95% CI, -4.83 to 8.11]; P = .61) and slope (-0.23/1000 person-years [95% CI, -1.17 to 0.70]; P = .61) changes in the postintervention period were not significantly different compared with the intervention period. The baseline rate of serious hyperglycemia was 22.33 per 1000 person-years (95% CI, 12.70-31.97). For the rate of serious hyperglycemic events, there was no significant association between the start of the intervention and a level (4.23/1000 person-years [95% CI, -8.62 to 17.08]; P = .51) or slope (-0.51/1000 person-years [95% CI, -2.37 to 1.34]; P = .58) change.

Conclusions And Relevance: Among Medicare beneficiaries with type 2 diabetes, implementation of a health plan program that involved switching patients from analogue to human insulin was associated with a small increase in population-level HbA1c.
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http://dx.doi.org/10.1001/jama.2018.21364DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6439763PMC
January 2019

Quantifying Social Reinforcement Among Family Members on Adherence to Medications for Chronic Conditions: a US-Based Retrospective Cohort Study.

J Gen Intern Med 2019 06 7;34(6):855-861. Epub 2018 Nov 7.

Center for Healthcare Delivery Sciences and Division of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.

Background: More than 50% of patients are non-adherent to medications, often without an easily identifiable reason to clinicians. No study has quantified the extent to which health behaviors like medication-taking are correlated within families using national or routinely collected data for a range of conditions.

Objective: To examine how an individual's health behaviors are influenced by those of their family members, particularly in adherence to medications for chronic conditions.

Design: Retrospective cohort study.

Patients: Using claims from a large nationwide insurer, we identified patients initiating medications for one of five chronic conditions with a family member who also recently filled one of these medications.

Main Measures: The primary exposure was whether family members were fully adherent (defined as a proportion of days covered ≥ 80%) before the patient's date of initiation. The outcome of interest was whether patients were fully adherent in the 12 months after initiation. Baseline demographic and clinical characteristics were also measured before initiation. We used multivariable modified Poisson regression to examine the association between prior family adherence and subsequent patient adherence.

Key Results: Among 254,144 patients, rates of full adherence among patients whose family members were and were not fully adherent were 37.3% and 26.9%, respectively (adjusted relative risk [aRR] 1.29, 95%CI 1.28-1.31). The association was stronger when both used cardiometabolic medications (aRR 1.35, 95%CI 1.32-1.37). Similarly, patients were also 38% more likely to be adherent if they and their family members used a medication for the same condition (aRR 1.38, 95%CI 1.35-1.40).

Conclusions: Adherence among family members appeared to be highly correlated, suggesting positive reinforcement by family or the sharing of unmeasured behaviors or characteristics associated with better adherence. Regardless, information about prior adherence among family members from routinely collected data could potentially inform adherence prediction or intervention efforts.
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http://dx.doi.org/10.1007/s11606-018-4654-9DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6544705PMC
June 2019

Effect of a Remotely Delivered Tailored Multicomponent Approach to Enhance Medication Taking for Patients With Hyperlipidemia, Hypertension, and Diabetes: The STIC2IT Cluster Randomized Clinical Trial.

JAMA Intern Med 2018 09;178(9):1182-1189

Division of General Internal Medicine and Department of Health Care Policy, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts.

Importance: Approximately half of patients with chronic conditions are nonadherent to prescribed medications, and interventions have been only modestly effective.

Objective: To evaluate the effect of a remotely delivered multicomponent behaviorally tailored intervention on adherence to medications for hyperlipidemia, hypertension, and diabetes.

Design, Setting, And Participants: Two-arm pragmatic cluster randomized controlled trial at a multispecialty group practice including participants 18 to 85 years old with suboptimal hyperlipidemia, hypertension, or diabetes disease control, and who were nonadherent to prescribed medications for these conditions.

Interventions: Usual care or a multicomponent intervention using telephone-delivered behavioral interviewing by trained clinical pharmacists, text messaging, pillboxes, and mailed progress reports. The intervention was tailored to individual barriers and level of activation.

Main Outcomes And Measures: The primary outcome was medication adherence from pharmacy claims data. Secondary outcomes were disease control based on achieved levels of low-density lipoprotein cholesterol, systolic blood pressure, and hemoglobin A1c from electronic health records, and health care resource use from claims data. Outcomes were evaluated using intention-to-treat principles and multiple imputation for missing values.

Results: Fourteen practice sites with 4078 participants had a mean (SD) age of 59.8 (11.6) years; 45.1% were female. Seven sites were each randomized to intervention or usual care. The intervention resulted in a 4.7% (95% CI, 3.0%-6.4%) improvement in adherence vs usual care but no difference in the odds of achieving good disease control for at least 1 (odds ratio [OR], 1.10; 95% CI, 0.94-1.28) or all eligible conditions (OR, 1.05; 95% CI, 0.91-1.22), hospitalization (OR, 1.02; 95% CI, 0.78-1.34), or having a physician office visit (OR, 1.11; 95% CI, 0.91-1.36). However, intervention participants were significantly less likely to have an emergency department visit (OR, 0.62; 95% CI, 0.45-0.85). In as-treated analyses, the intervention was associated with a 10.4% (95% CI, 8.2%-12.5%) increase in adherence, a significant increase in patients achieving disease control for at least 1 eligible condition (OR, 1.24; 95% CI, 1.03-1.50), and nonsignificantly improved disease control for all eligible conditions (OR, 1.18; 95% CI, 0.99-1.41).

Conclusions And Relevance: A remotely delivered multicomponent behaviorally tailored intervention resulted in a statistically significant increase in medication adherence but did not change clinical outcomes. Future work should focus on identifying which groups derive the most clinical benefit from adherence improvement efforts.

Trial Registration: ClinicalTrials.gov identifier: NCT02512276.
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http://dx.doi.org/10.1001/jamainternmed.2018.3189DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6142966PMC
September 2018

Effect of Lawyer-Submitted Reports on Signals of Disproportional Reporting in the Food and Drug Administration's Adverse Event Reporting System.

Drug Saf 2019 01;42(1):85-93

Division of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, 1620 Tremont Street, Suite 3030, Boston, MA, 02120, USA.

Introduction: Lawyer-submitted reports may have unintended consequences on safety signal detection in spontaneous adverse event reporting systems.

Objective: Our objective was to assess the impact of lawyer-submitted reports primarily for one adverse event (AE) on the ability to detect a signal of disproportional reporting for another AE for the same drug in the US FDA Adverse Event Reporting System (FAERS).

Methods: FAERS reports from January 2004 to September 2015 were used to estimate yearly cumulative proportional reporting ratios (PRRs) for three known drug-AE pairs-isotretinoin-birth defects, atorvastatin-rhabdomyolysis, and rosuvastatin-rhabdomyolysis-with and without lawyer-submitted reports. Isotretinoin and atorvastatin have been the subject of high-profile tort litigation regarding other AEs. A lower bound of the 95% confidence interval (CI) of one or more based on three or more reports defined a signal.

Results: Cumulative PRRs met signaling criteria in all analyses. For isotretinoin, lawyer-submitted reports increased PRRs for birth defects before 2008, with the largest increase in 2006 (2.9 [95% CI 2.4-3.5] to 3.3 [95% CI 2.8-3.9]); lawyer-submitted reports decreased PRRs for birth defects after 2011, with the largest decrease in 2013 (2.2 [95% CI 2.0-2.5] to 1.9 [95% CI 1.7-2.1]). For atorvastatin, lawyer-submitted reports reduced PRRs for rhabdomyolysis after 2013, with the largest decrease in 2015 (18.0 [95% CI 17.1-19.1] to 15.4 [95% CI 14.5-16.2]). Lawyer-submitted reports had little impact on PRRs for rosuvastatin and rhabdomyolysis.

Conclusions: Inclusion of lawyer-submitted reports in FAERS did not meaningfully distort known safety signals for two drugs subject to high-profile tort litigation for other AEs.
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http://dx.doi.org/10.1007/s40264-018-0703-xDOI Listing
January 2019

Differences in rates of switchbacks after switching from branded to authorized generic and branded to generic drug products: cohort study.

BMJ 2018 Apr 3;361:k1180. Epub 2018 Apr 3.

Division of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA 02120, USA.

Objectives: To compare rates of switchbacks to branded drug products for patients switched from branded to authorized generic drug products, which have the same active ingredients, appearance, and excipients as the branded product, with patients switched from branded to generic drug products, which have the same active ingredients as the branded product but may differ in appearance and excipients.

Design: Observational cohort study.

Setting: Private (a large commercial health plan) and public (Medicaid) insurance programs in the US.

Participants: Beneficiaries of a large US commercial health insurer between 2004 and 2013 (primary cohort) and Medicaid beneficiaries between 2000 and 2010 (replication cohort).

Main Outcome Measures: Patients taking branded products for one of the study drugs (alendronate tablets, amlodipine tablets, amlodipine-benazepril capsules, calcitonin salmon nasal spray, escitalopram tablets, glipizide extended release tablets, quinapril tablets, and sertraline tablets) were identified when they switched to an authorized generic or a generic drug product after the date of market entry of generic drug products. These patients were followed for switchbacks to the branded drug product in the year after their switch to an authorized generic or a generic drug product. Cox proportional hazard models were used to estimate hazard ratios and 95% confidence intervals after adjusting for demographics, including age, sex, and calendar year. Inverse variance meta-analysis was used to pool adjusted hazard ratios across all drug products.

Results: A total of 94 909 patients switched from branded to authorized generic drug products and 116 017 patients switched from branded to generic drug products and contributed to the switchback analysis. Unadjusted incidence rates of switchback varied across drug products, ranging from a low of 3.8 per 100 person years (for alendronate tablets) to a high of 17.8 per 100 person years (for amlodipine-benazepril capsules), with an overall rate of 8.2 per 100 person years across all drug products. Adjusted switchback rates were consistently lower for patients who switched from branded to authorized generic drug products compared with branded to generic drug products in the primary cohort (pooled hazard ratio 0.72, 95% confidence interval 0.64 to 0.81). Similar results (0.75, 0.62 to 0.91) were observed in the replication cohort.

Conclusion: Switching from branded to authorized generic drug products was associated with lower switchback rates compared with switching from branded to generic drug products.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5881140PMC
http://dx.doi.org/10.1136/bmj.k1180DOI Listing
April 2018

Adaptive design clinical trials: a review of the literature and ClinicalTrials.gov.

BMJ Open 2018 02 10;8(2):e018320. Epub 2018 Feb 10.

Program on Regulation, Therapeutics, and Law (PORTAL), Division of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts, USA.

Objectives: This review investigates characteristics of implemented adaptive design clinical trials and provides examples of regulatory experience with such trials.

Design: Review of adaptive design clinical trials in EMBASE, PubMed, Cochrane Registry of Controlled Clinical Trials, Web of Science and ClinicalTrials.gov. Phase I and seamless Phase I/II trials were excluded. Variables extracted from trials included basic study characteristics, adaptive design features, size and use of independent data monitoring committees (DMCs) and blinded interim analyses. We also examined use of the adaptive trials in new drug submissions to the Food and Drug Administration (FDA) and European Medicines Agency (EMA) and recorded regulators' experiences with adaptive designs.

Results: 142 studies met inclusion criteria. There has been a recent growth in publicly reported use of adaptive designs among researchers around the world. The most frequently appearing types of adaptations were seamless Phase II/III (57%), group sequential (21%), biomarker adaptive (20%), and adaptive dose-finding designs (16%). About one-third (32%) of trials reported an independent DMC, while 6% reported blinded interim analysis. We found that 9% of adaptive trials were used for FDA product approval consideration, and 12% were used for EMA product approval consideration. International regulators had mixed experiences with adaptive trials. Many product applications with adaptive trials had extensive correspondence between drug sponsors and regulators regarding the adaptive designs, in some cases with regulators requiring revisions or alterations to research designs.

Conclusions: Wider use of adaptive designs will necessitate new drug application sponsors to engage with regulatory scientists during planning and conduct of the trials. Investigators need to more consistently report protections intended to preserve confidentiality and minimise potential operational bias during interim analysis.
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http://dx.doi.org/10.1136/bmjopen-2017-018320DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5829673PMC
February 2018

Effect of Reminder Devices on Medication Adherence: The REMIND Randomized Clinical Trial.

JAMA Intern Med 2017 05;177(5):624-631

Division of Pharmacoepidemiology and Pharmacoeconomics, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts.

Importance: Forgetfulness is a major contributor to nonadherence to chronic disease medications and could be addressed with medication reminder devices.

Objective: To compare the effect of 3 low-cost reminder devices on medication adherence.

Design, Setting, And Participants: This 4-arm, block-randomized clinical trial involved 53 480 enrollees of CVS Caremark, a pharmacy benefit manager, across the United States. Eligible participants were aged 18 to 64 years and taking 1 to 3 oral medications for long-term use. Participants had to be suboptimally adherent to all of their prescribed therapies (with a medication possession ratio of 30% to 80%) in the 12 months before randomization. Participants were stratified on the basis of the medications they were using at randomization: medications for cardiovascular or other nondepression chronic conditions (the chronic disease stratum) and antidepressants (the antidepressant stratum). In each stratum, randomization occurred within blocks defined by whether all of the patient's targeted medications were dosed once daily. Patients were randomized to receive in the mail a pill bottle strip with toggles, digital timer cap, or standard pillbox. The control group received neither notification nor a device. Data were collected from February 12, 2013, through March 21, 2015, and data analyses were on the intention-to-treat population.

Main Outcomes And Measures: The primary outcome was optimal adherence (medication possession ratio ≥80%) to all eligible medications among patients in the chronic disease stratum during 12 months of follow-up, ascertained using pharmacy claims data. Secondary outcomes included optimal adherence to cardiovascular medications among patients in the chronic disease stratum as well as optimal adherence to antidepressants.

Results: Of the 53 480 participants, mean (SD) age was 45 (12) years and 56% were female. In the primary analysis, 15.5% of patients in the chronic disease stratum assigned to the standard pillbox, 15.1% assigned to the digital timer cap, 16.3% assigned to the pill bottle strip with toggles, and 15.1% assigned to the control arm were optimally adherent to their prescribed treatments during follow-up. There was no statistically significant difference in the odds of optimal adherence between the control and any of the devices (standard pillbox: odds ratio [OR], 1.03 [95% CI, 0.95-1.13]; digital timer cap: OR, 1.00 [95% CI, 0.92-1.09]; and pill bottle strip with toggles: OR, 0.94 [95% CI, 0.85-1.04]). In direct comparisons, the odds of optimal adherence were higher with a standard pillbox than with the pill bottle strip (OR, 1.10 [95% CI, 1.00-1.21]). Secondary analyses yielded similar results.

Conclusions And Relevance: Low-cost reminder devices did not improve adherence among nonadherent patients who were taking up to 3 medications to treat common chronic conditions. The devices may have been more effective if coupled with interventions to ensure consistent use or if targeted to individuals with an even higher risk of nonadherence.

Trial Registration: clinicaltrials.gov Identifier: NCT02015806.
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http://dx.doi.org/10.1001/jamainternmed.2016.9627DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5470369PMC
May 2017

Strength of evidence for labeled dosing recommendations in renal impairment.

Clin Trials 2017 Apr 25;14(2):219-221. Epub 2016 Oct 25.

Division of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.

Background/aims: Renally excreted medications often require dose adjustment in patients with kidney impairment. While drug development and approval in the United States are typically based on several Phase I and II studies and one or more larger Phase III randomized trials, the basis for labeled dosing recommendations for patients with renal impairment is less well known. In response, we aimed to quantify the level of evidence used to recommend labeled dosing adjustments for newly approved drugs in patients with renal impairment.

Methods: We reviewed publicly available drug labels and approval packages for new molecular entities approved in the United States between 2012 and 2014. The sample was restricted to 29 renally excreted new molecular entities that were not granted orphan drug status. We extracted data regarding approved indications, normal dosing, dosing adjustments for patients with mild (estimated glomerular filtration rate >60 mL/min/1.73 m), moderate (estimated glomerular filtration rate 30-<60 mL/min/1.73 m), and severe (estimated glomerular filtration rate <30 mL/min/1.73 m) renal impairment, characteristics of studies used to justify dosing adjustments, and numbers of subjects in each study.

Results: In all, 14 of 29 (48%) new molecular entities had labels that recommended dosing adjustments for patients with mild, moderate, and/or severe renal impairment. Among these 14 new molecular entities, 4 (29%) used only pharmacokinetic studies to justify the recommendations, with no examination of clinical outcomes for patients with renal impairment. Where data were available, the median number of patients with renal impairment evaluated in studies used for dosing adjustment was 34 (range, 4-5976). Of the 15 new molecular entities with no recommended dosing adjustments for this population, 2 (13%) did not report assessing the effects of renal impairment.

Conclusion: Nearly half of newly approved renally excreted drugs include dosing adjustments for kidney impairment on the label, but the recommendations are usually based on very small numbers of patients and often utilize pharmacokinetic studies alone. More research is needed to understand the benefits and risks of new drugs in patients with renal impairment.
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http://dx.doi.org/10.1177/1740774516673818DOI Listing
April 2017

Rationale and design of the Study of a Tele-pharmacy Intervention for Chronic diseases to Improve Treatment adherence (STIC2IT): A cluster-randomized pragmatic trial.

Am Heart J 2016 Oct 8;180:90-7. Epub 2016 Aug 8.

Division of General Internal Medicine and Department of Health Care Policy, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.

Background: Approximately half of patients with chronic cardiometabolic conditions are nonadherent with their prescribed medications. Interventions to improve adherence have been only modestly effective because they often address single barriers to adherence, intervene at single points in time, or are imprecisely targeted to patients who may not need adherence assistance.

Objective: To evaluate the effect of a multicomponent, behaviorally tailored pharmacist-based intervention to improve adherence to medications for diabetes, hypertension, and hyperlipidemia.

Trial Design: The STIC2IT trial is a cluster-randomized pragmatic trial testing the impact of a pharmacist-led multicomponent intervention that uses behavioral interviewing, text messaging, mailed progress reports, and video visits. Targeted patients are those who are nonadherent to glucose-lowering, antihypertensive, or statin medications and who also have evidence of poor disease control. The intervention is tailored to patients' individual health barriers and their level of health activation. We cluster-randomized 14 practice sites of a large multispecialty group practice to receive either the pharmacist-based intervention or usual care. STIC2IT has enrolled 4,076 patients who will be followed up for 12months after randomization. The trial's primary outcome is medication adherence, assessed using pharmacy claims data. Secondary outcomes are disease control and health care resource utilization.

Conclusion: This trial will determine whether a technologically enabled, behaviorally targeted pharmacist-based intervention results in improved adherence and disease control. If effective, this strategy could be a scalable method of offering tailored adherence support to those with the greatest clinical need.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5053099PMC
http://dx.doi.org/10.1016/j.ahj.2016.07.017DOI Listing
October 2016
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