Molnupiravir Use Among Patients with COVID-19 in Real-World Settings: A Systematic Literature Review.

INTRODUCTION: Molnupiravir (MOV) is an oral antiviral for the treatment of individuals with mild-to-moderate COVID-19 and at high risk of progression to severe disease. Our objective was to conduct a systematic literature review (SLR) of evidence on the effectiveness of MOV in reducing the risk of severe COVID-19 outcomes in real-world outpatient settings. METHODS: The SLR was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses 2020 guidelines and using pre-determined population, intervention, comparison, outcome, time, and study design inclusion criteria. Eligible studies were published between January 1, 2021, and March 10, 2023, and evaluated the real-world effectiveness of MOV compared to no treatment in reducing the risk of severe COVID-19 outcomes among outpatients ≥ 18 years of age with a laboratory-confirmed diagnosis of SARS-CoV-2 infection. RESULTS: Nine studies from five countries were included in the review. The size of the MOV-treated group ranged from 359 to 7818 individuals. Omicron variants of SARS-CoV-2 were dominant in all study periods. Most studies noted differences in the baseline characteristics of the MOV-treated and untreated control groups, with the treated groups generally being older and with more comorbidities. Eight studies reported that treatment with MOV was associated with a significantly reduced risk of at least one severe COVID-19 outcome in at least one age group, with greater benefits consistently observed among older age groups. CONCLUSIONS: In this SLR study, treatment with MOV was effective in reducing the risk of severe outcomes from COVID-19 caused by Omicron variants, especially for older individuals. Differences in the ages and baseline comorbidities of the MOV-treated and control groups may have led to underestimation of the effectiveness of MOV in many observational studies. Real-world studies published to date thus provide additional evidence supporting the continued benefits of MOV in non-hospitalized adults with COVID-19.

COVID-19 continues to be a major source of morbidity and mortality. Throughout the pandemic, many countries authorized various therapies for the treatment of individuals presenting with mild-to-moderate COVID-19 and at high risk of progression to severe disease. Some of these therapies have since been rendered ineffective due to the emergence of Omicron variants in late 2021. The objective of the current study was to conduct a systematic literature review to assess real-world evidence on the effectiveness of molnupiravir, including effectiveness against COVID-19 caused by Omicron variants, to supplement the findings of the MOVe-OUT clinical trial and further inform on the potential clinical benefit and utility of this antiviral agent. Nine studies were included in the systematic literature review. We found that treatment with molnupiravir was effective in reducing the risk of severe outcomes from COVID-19 caused by Omicron variants, especially for older individuals. Differences in the ages and baseline comorbidities of the molnupiravir-treated and control groups may have led to underestimation of the effectiveness of molnupiravir in many observational studies. In summary, real-world effectiveness studies provide additional evidence supporting the continued benefits of molnupiravir in non-hospitalized adults with COVID-19.

Risk of fall or fracture with concomitant use of prescription opioids and other medications in osteoarthritis patients.

BACKGROUND: Osteoarthritis (OA) patients taking prescription opioids for pain are at increased risk of fall or fracture, and the concomitant use of interacting drugs may further increase the risk of these events. AIMS: To identify prescription opioid-related medication combinations associated with fall or fracture. MATERIALS & METHODS: We conducted a case-crossover-based screening of two administrative claims databases spanning 2003 through 2021. OA patients were aged 40 years or older with at least 365 days of continuous enrollment and 90 days of continuous prescription opioid use before their first eligible fall or fracture event. The primary analysis quantified the odds ratio (OR) between fall and non-opioid medications dispensed in the 90 days before the fall date after adjustment for prescription opioid dosage and confounding using a case-time-control design. A secondary analogous analysis evaluated medications associated with fracture. The false discovery rate (FDR) was used to account for multiple testing. RESULTS: We identified 41 693 OA patients who experienced a fall and 24 891 OA patients who experienced a fracture after at least 90 days of continuous opioid therapy. Top non-opioid medications by ascending p-value with OR > 1 for fall were meloxicam (OR 1.22, FDR = 0.08), metoprolol (OR 1.06, FDR >0.99), and celecoxib (OR 1.13, FDR > 0.99). Top non-opioid medications for fracture were losartan (OR 1.20, FDR = 0.80), alprazolam (OR 1.14, FDR > 0.99), and duloxetine (OR 1.12, FDR = 0.97). CONCLUSION: Clinicians may seek to monitor patients who are co-prescribed drugs that act on the central nervous system, especially in individuals with OA.

Trends in the Use of Oral Anticoagulants for Adults With Venous Thromboembolism in the US, 2010-2020.

Importance: The introduction of direct oral anticoagulants (DOACs) has transformed the treatment of venous thromboembolism (VTE). Large health care databases offer valuable insight into how oral anticoagulants (OACs) are used in clinical practice and may aid in understanding reasons for changes in therapy. Objectives: To evaluate prescribing patterns of OACs for patients with VTE and identify clinical events that precede treatment changes. Design, Setting, and Participants: This retrospective cohort study used data from a public (Medicare fee-for-service) and a commercial (IBM MarketScan) health insurance database on 298 609 patients initiating OACs within 90 days of index VTE hospitalization from January 1, 2009, to December 31, 2020. Statistical analysis was conducted from April to August 2022. Exposures: Warfarin and the DOACs rivaroxaban, apixaban, dabigatran, and edoxaban. Main Outcomes and Measures: Characteristics of patients initiating different OACs, along with trends over time of patients initiating OACs, were compared. Time receiving continuous anticoagulant therapy, patterns of anticoagulant discontinuation (treatment gap of ≥30 days), and treatment switches were assessed. Clinical events in the 30 days preceding treatment modifications were identified. Results: A total of 203 378 individuals with Medicare (mean [SD] age, 76.9 [7.6] years; 122 554 women [60.3%]) and 95 231 with commercial insurance (mean [SD] age, 57.6 [15.8] years; 47 139 women [49.5%]) were included (N = 298 609). Warfarin was the most frequent OAC prescribed (163 044 [54.6%]), followed by rivaroxaban (66 882 [22.3%]) and apixaban (65 997 [22.1%]). The proportion of patients initiating DOACs increased from 0% in 2010 to 86.8% (22 420 of 25 817) in 2019 for patients with Medicare and 92.1% (4012 of 4357) in 2020 for commercially insured patients. Patients with chronic kidney disease were more likely to initiate warfarin (35 561 [11.9%]) or apixaban (16 294 [5.5%]) than rivaroxaban (10 136 [3.4%]), and those with a history of bleeding were more likely to initiate apixaban (5424 [1.8%]) than rivaroxaban (3007 [1.0%]). Overall, patients received persistent OAC treatment for approximately 6 months (Medicare: median, 175 days [IQR, 76-327 days]; commercial insurance: median, 168 days [IQR, 83-279 days]). A total of 33 011 patients (11.1%) switched anticoagulant therapy within a year. Switching to another anticoagulant was preceded most frequently by codes for a VTE diagnostic procedure (27.2% of all switchers [8983 of 33 011]). Conclusions and Relevance: This cohort study using data from 2 US health insurance databases suggests that most patients with VTE continued oral anticoagulant treatment for approximately 6 months. Clinical reasons for modifying anticoagulant therapy were identified in one-third of patients. Identifying reasons for treatment modification is crucial for generating valid evidence on drug safety and effectiveness.

Comparative Risk of Opioid Overdose With Concomitant Use of Prescription Opioids and Skeletal Muscle Relaxants.

BACKGROUND AND OBJECTIVES: The concomitant use of prescription opioids and skeletal muscle relaxants has been associated with opioid overdose, but little data exist on the head-to-head safety of these drug combinations. The objective of this study was to compare the risk of opioid overdose among patients on long-term opioid therapy who concurrently initiate skeletal muscle relaxants. METHODS: We conducted an active comparator cohort study spanning 2000 to 2019 using healthcare utilization data from 4 US commercial and public insurance databases. Individuals were required to have at least 180 days of continuous enrollment and at least 90 days of continuous prescription opioid use immediately before and on the date of skeletal muscle relaxant initiation. Exposures were the concomitant use of prescription opioids and skeletal muscle relaxants, and the main outcome was the hazard ratio (HR) and bootstrapped 95% CI of opioid overdose resulting in an emergency department visit or hospitalization. The primary analysis quantified opioid overdose risk across 7 prescription opioid-skeletal muscle relaxant therapies and a negative control outcome (sepsis) to assess potential confounding by unmeasured illicit opioid use. Secondary analyses evaluated two-group and five-group comparisons in patients with similar baseline characteristics; individuals without previous recorded substance abuse; and subgroups stratified by baseline opioid dosage, benzodiazepine codispensing, and oxycodone or hydrocodone use. RESULTS: Weighted HR of opioid overdose relative to cyclobenzaprine was 2.52 (95% CI 1.29-4.90) for baclofen; 1.64 (95% CI 0.81-3.34) for carisoprodol; 1.14 (95% CI 0.53-2.46) for chlorzoxazone/orphenadrine; 0.46 (95% CI 0.17-1.24) for metaxalone; 1.00 (95% CI 0.45-2.20) for methocarbamol; and 1.07 (95% CI 0.49-2.33) for tizanidine in the 30-day intention-to-treat analysis. Findings were similar in the as-treated analysis, 2-group and 5-group comparisons, and patients without previous recorded substance abuse. None of the therapies relative to cyclobenzaprine were associated with sepsis, and no subgroups indicated an increased risk of opioid overdose. DISCUSSION: Concomitant use of prescription opioids and baclofen relative to cyclobenzaprine is associated with opioid overdose. Clinical interventions may focus on prescribing alternatives in the same drug class or providing access to opioid antagonists if treatment with both medications is necessary for pain management.

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

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.

Clarithromycin use and the risk of mortality and cardiovascular events: A systematic review and meta-analysis.

BACKGROUND: Although studies reported increased cardiovascular (CV) risks in patients treated with macrolides, the risks remain controversial among clarithromycin (CLR) users. We aimed to summarize the association between CLR use and the risks of mortality and CV events. METHODS: We searched PubMed, EMBASE, Web of Science, and the Cochrane Library for randomized controlled trials (RCTs) and observational studies with population exposed to CLR published until December 31st, 2018. These studies reported either all-cause mortality (primary outcome) or CV adverse events (secondary outcomes) based on multivariate models. Effect measures were synthesized by study design and follow-up duration (long-term, ≥ 1 year; short-term, ≤ 3 months; and immediate, ≤ 2 weeks). This study has been registered on PROSPERO (ID: CRD42018089605). RESULTS: This meta-analysis included 13 studies (3 RCTs and 10 observational studies) and 8,351,815 subjects (1,124,672 cases and 7,227,143 controls). Overall, CLR use was not associated with increased long-term all-cause mortality (pooled rate ratio RR = 1.09, 95% CI = 0.91-1.32), either among patients with or without comorbidities of cardiovascular diseases. Comparing CLR users to placebo, there is no additional risks of cardiac mortality (pooled RR = 1.03, 95% CI = 0.53-2.01), acute myocardial infarction (pooled RR = 1.29, 95% CI = 0.98-1.68), and arrhythmia (pooled RR = 0.90, 95% CI = 0.62-1.32). CONCLUSIONS: Our findings suggested no significant association between CLR use and subsequent long-term all-cause mortality, regardless having comorbidity of cardiovascular diseases or not. Further RCTs investigating the short-term CV risks of CLR use compared to alternative antibiotics are warranted, particularly in high-risk populations.

Association of Opioid Overdose With Opioid Prescriptions to Family Members.

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.

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

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.

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

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.

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

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.

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

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.

Using Previous Medication Adherence to Predict Future Adherence.

BACKGROUND: Medication nonadherence is a major public health problem. Identification of patients who are likely to be and not be adherent can guide targeted interventions and improve the design of comparative-effectiveness studies. OBJECTIVE: To evaluate multiple measures of patient previous medication adherence in light of predicting future statin adherence in a large U.S. administrative claims database. METHODS: We identified a cohort of patients newly initiating statins and measured their previous adherence to other chronic preventive medications during a 365-day baseline period, using metrics such as proportion of days covered (PDC), lack of second fills, and number of dispensations. We measured adherence to statins during the year after initiation, defining high adherence as PDC ≥ 80%. We built logistic regression models from different combinations of baseline variables and previous adherence measures to predict high adherence in a random 50% sample and tested their discrimination using concordance statistics (c-statistics) in the other 50%. We also assessed the association between previous adherence and subsequent statin high adherence by fitting a modified Poisson model from all relevant covariates plus previous mean PDC categorized as < 25%, 25%-79%, and ≥ 80%. RESULTS: Among 89,490 statin initiators identified, a prediction model including only demographic variables had a c-statistic of 0.578 (95% CI = 0.573-0.584). A model combining information on patient comorbidities, health care services utilization, and medication use resulted in a c-statistic of 0.665 (95% CI = 0.659-0.670). Models with each of the previous medication adherence measures as the only explanatory variable yielded c-statistics ranging between 0.533 (95% CI = 0.529-0.537) for lack of second fill and 0.666 (95% CI = 0.661-0.671) for maximum PDC. Adding mean PDC to the combined model yielded a c-statistic of 0.695 (95% CI = 0.690-0.700). Given a sensitivity of 75%, the predictor improved the specificity from 47.7% to 53.6%. Patients with previous mean PDC < 25% were half as likely to show high adherence to statins compared with those with previous mean PDC ≥ 80% (risk ratio = 0.49, 95% CI = 0.46-0.50). CONCLUSIONS: Including measures of previous medication adherence yields better prediction of future statin adherence than usual baseline clinical measures that are typically used in claims-based studies. DISCLOSURES: This study was funded by the Patient-Centered Outcomes Research Institute (ME-1309-06274). Kumamaru, Kohsaka, and Miyata are affiliated with the Department of Healthcare Quality Assessment at the University of Tokyo, which is a social collaboration department supported by National Clinical Database. The department was formerly supported by endowments from Johnson & Johnson K.K., Nipro, Teijin Pharma, Kaketsuken K.K., St. Jude Medical Japan, Novartis Pharma K.K., Taiho Pharmaceutical, W. L. Gore & Associates, Olympus Corporation, and Chugai Pharmaceutical. Gagne has received grants from Novartis Pharmaceuticals and Eli Lilly and Company to the Brigham and Women's Hospital for unrelated work. He is a consultant to Aetion, a software company, and to Optum. Choudhry has received grants from the National Heart, Lung, and Blood Institute, PhRMA Foundation, Merck, Sanofi, AstraZeneca, CVS, and MediSafe. Schneeweiss is consultant to WHISCON and Aetion, a software manufacturer of which he also owns equity. He is principal investigator of investigator-initiated grants to the Brigham and Women's Hospital from Bayer, Genentech, and Boehringer Ingelheim unrelated to the topic of this study. He does not receive personal fees from biopharmaceutical companies. No potential conflict of interest was reported by the other authors.

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.

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.

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

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.

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

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.

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

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.

Strength of evidence for labeled dosing recommendations in renal impairment.

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 m2), moderate (estimated glomerular filtration rate 30-<60 mL/min/1.73 m2), and severe (estimated glomerular filtration rate <30 mL/min/1.73 m2) 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.

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

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.

A survey of food allergen control practices in the U.S. food industry.

Despite awareness of the importance of food allergy as a public health issue, recalls and adverse reactions linked to undeclared allergens in foods continue to occur with high frequency. To reduce the overall incidence of such problems and to ensure that food-allergic consumers have the information they need to prevent adverse reactions, it is important to understand which allergen control practices are currently used by the food industry. Therefore, the U.S. Food and Drug Administration carried out directed inspections of registered food facilities in 2010 to obtain a broader understanding of industry allergen control practices in the United States. The results of these inspections show that allergen awareness and the use of allergen controls have increased greatly in the last decade, but that small facilities lag in implementing allergen controls.