Search

Background and ObjectivesThe 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.MethodsWe 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.ResultsWeighted 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.DiscussionConcomitant 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.

ImportanceClinical guidelines on chronic obstructive pulmonary disease (COPD) recommend inhalers containing long-acting muscarinic antagonists (LAMAs) and long-acting β-agonists (LABAs) over inhalers containing inhaled corticosteroids (ICSs) and LABAs. However, data from randomized clinical trials comparing these combination inhalers (LAMA-LABAs vs ICS-LABAs) have been conflicting and raised concerns of generalizability.ObjectiveTo assess whether LAMA-LABA therapy is associated with reduced COPD exacerbations and pneumonia hospitalizations compared with ICS-LABA therapy in routine clinical practice.Design, Setting, and ParticipantsThis was a 1:1 propensity score–matched cohort study using Optum’s Clinformatics Data Mart, a large commercial insurance–claims database. Patients must have had a diagnosis of COPD and filled a new prescription for a combination LAMA-LABA or ICS-LABA inhaler between January 1, 2014, and December 31, 2019. Patients younger than 40 years were excluded, as were those with a prior diagnosis of asthma. The current analysis was performed from February 2021 to March 2023.ExposuresCombination LAMA-LABA inhalers (aclidinium-formoterol, glycopyrronium-formoterol, glycopyrronium-indacaterol, tiotropium-olodaterol, or umeclidinium-vilanterol) and combination ICS-LABA inhalers (budesonide-formoterol, fluticasone-salmeterol, fluticasone-vilanterol, or mometasone-formoterol).Main OutcomeThe primary effectiveness outcome was first moderate or severe COPD exacerbation, and the primary safety outcome was first pneumonia hospitalization. Propensity score matching was used to control for confounding between the 2 groups. Logistic regression analysis was used to estimate propensity scores. Hazard ratios (HRs) and 95% CIs were estimated using Cox proportional hazards models stratified on matched pairs.ResultsAmong 137 833 patients (mean [SD] age, 70.2 [9.9] years; 69 530 [50.4%] female) (107 004 new ICS-LABA users and 30 829 new LAMA-LABA users), 30 216 matched pairs were identified for the primary analysis. Compared with ICS-LABA use, LAMA-LABA use was associated with an 8% reduction in the rate of first moderate or severe COPD exacerbation (HR, 0.92; 95% CI, 0.89-0.96) and a 20% reduction in the rate of first pneumonia hospitalization (HR, 0.80; 95% CI, 0.75-0.86). These findings were robust across a range of prespecified subgroup and sensitivity analyses.ConclusionIn this cohort study, LAMA-LABA therapy was associated with improved clinical outcomes compared with ICS-LABA therapy, suggesting that LAMA-LABA therapy should be preferred for patients with COPD.

The high-dimensional propensity score (HDPS) is a semi-automated procedure for confounder identification, prioritisation and adjustment in large healthcare databases that requires investigators to specify data dimensions, prioritisation strategy and tuning parameters. In practice, reporting of these decisions is inconsistent and this can undermine the transparency, and reproducibility of results obtained. We illustrate reporting tools, graphical displays and sensitivity analyses to increase transparency and facilitate evaluation of the robustness of analyses involving HDPS.Using a study from the UK Clinical Practice Research Datalink that implemented HDPS we demonstrate the application of the proposed recommendations.We identify seven considerations surrounding the implementation of HDPS, such as the identification of data dimensions, method for code prioritisation and number of variables selected. Graphical diagnostic tools include assessing the balance of key confounders before and after adjusting for empirically selected HDPS covariates and the identification of potentially influential covariates. Sensitivity analyses include varying the number of covariates selected and assessing the impact of covariates behaving empirically as instrumental variables. In our example, results were robust to both the number of covariates selected and the inclusion of potentially influential covariates. Furthermore, our HDPS models achieved good balance in key confounders.The data-adaptive approach of HDPS and the resulting benefits have led to its popularity as a method for confounder adjustment in pharmacoepidemiological studies. Reporting of HDPS analyses in practice may be improved by the considerations and tools proposed here to increase the transparency and reproducibility of study results.

We sought to develop and prospectively validate a dynamic model that incorporates changes in biomarkers to predict rapid clinical deterioration in patients hospitalized for COVID-19.We established a retrospective cohort of hospitalized patients aged ≥18 years with laboratory-confirmed COVID-19 using electronic health records (EHR) from a large integrated care delivery network in Massachusetts including40 facilities from March to November 2020. A total of 71 factors, including time-varying vital signs and laboratory findings during hospitalization were screened. We used elastic net regression and tree-based scan statistics for variable selection to predict rapid deterioration, defined as progression by two levels of a published severity scale in the next 24 h. The development cohort included the first 70% of patients identified chronologically in calendar time; the latter 30% served as the validation cohort. A cut-off point was estimated to alert clinicians of high risk of imminent clinical deterioration.Overall, 3706 patients (2587 in the development and 1119 in the validation cohort) met the eligibility criteria with a median of 6 days of follow-up. Twenty-four variables were selected in the final model, including 16 dynamic changes of laboratory results or vital signs. Area under the ROC curve was 0.81 (95% CI, 0.79-0.82) in the development set and 0.74 (95% CI, 0.71-0.78) in the validation set. The model was well calibrated (slope = 0.84 and intercept = -0.07 on the calibration plot in the validation set). The estimated cut-off point, with a positive predictive value of 83%, was 0.78.Our prospectively validated dynamic prognostic model demonstrated temporal generalizability in a rapidly evolving pandemic and can be used to inform day-to-day treatment and resource allocation decisions based on dynamic changes in biophysiological factors.

Objective Medication nonadherence is linked to worsened clinical outcomes and increased costs. Existing system-level adherence interventions rely on insurer claims for patient identification and outcome measurement, yet suffer from incomplete capture and lags in data acquisition. Data from pharmacies regarding prescription filling, captured in retail dispensing, may be more efficient. Data sources Pharmacy fill and insurer claims data. Study design We compared adherence measured using pharmacy fill data to adherence using insurer claims data, expressed as proportion of days covered (PDC) over 12 months. Agreement was evaluated using correlation/validation metrics. We also explored the relationship between adherence in both sources and disease control using prediction modeling. Data extraction methods Large pragmatic trial of cardiometabolic disease in an integrated delivery network. Principal findings Among 1113 patients, adherence was higher in pharmacy fill (mean = 50.0%) versus claims data (mean = 47.4%), although they had moderately high correlation (R = 0.57, 95% CI: 0.53-0.61) with most patients (86.9%) being similarly classified as adherent or nonadherent. Sensitivity and specificity of pharmacy fill versus claims data were high (0.89, 95% CI: 0.86-0.91 and 0.80, 95% CI: 0.75-0.85). Pharmacy fill-based PDC predicted better disease control slightly more than claims-based PDC, although the difference was nonsignificant. Conclusions Pharmacy fill data may be an alternative to insurer claims for adherence measurement.

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.

In the United States, brand-name prescription drugs remain expensive until market exclusivity ends and lower-cost generics become available. Delayed generic drug uptake may increase spending and worsen medication adherence and patient outcomes. We assessed recent trends and factors associated with generic uptake.Among 227 drugs facing new generic competition from 2012 to 2017, we used a national claims database to measure generic uptake in the first and second year after generic entry, defined as the proportion of claims for a generic version of the drug. Using linear regression, we evaluated associations between generic uptake and key drug characteristics.Mean generic uptake was 66.1% (standard deviation 22.1%) in the first year and 82.7% (standard deviation 21.6%) in the second year after generic entry. From 2012 to 2017 generic uptake decreased 4.3% per year in the first year (95% confidence interval, 2.8%-5.8%, P.001) and 3.2%/year in the second year (95% confidence interval, 1.2%-5.1%). Generic uptake was lower for injected than oral drugs in the first year (38.5% vs 70.0%, P.001) and second year (50.3% vs 86.9%, P.001). In the second year, generic uptake was higher among drugs with an authorized generic (86.1 vs 80.1%, P = .045) and those with ≥3 generic competitors (87.7% vs 78.6%, P = .055).Early generic uptake decreased over the past several years. This trend may adversely affect patients and increase prescription drug spending. Policies are needed to encourage generic competition, particularly among injected drugs administered in a hospital or clinic setting.

Since 2007, the US Food and Drug Administration has had the authority to require risk evaluation and mitigation strategy (REMS) programs for certain medications with serious safety concerns to help ensure the benefits of the medication outweigh its risks. Such programs can include requirements for patient monitoring, restrictions on dispensing or administration, and physician and pharmacy training and certification. However, there has been only scattered evidence on the impact of REMS programs on informed decision making, medication access, or patient outcomes. The objective of this article was to describe a study that researchers at Brigham and Women’s Hospital and Harvard Medical School will conduct in partnership with the Food and Drug Administration’s Office of Surveillance and Epidemiology to investigate systematically how REMS programs have operated in practice. Investigations include health insurance claims-based analyses to understand patterns of drug use, adherence to safety requirements, and patient outcomes under REMS programs; surveys and interviews to understand physician and patient experiences with REMS; and REMS program material-based and interview-based analyses to understand the effectiveness of risk communication in REMS programs. These research activities will evaluate the performance of REMS programs, provide information on the benefits and burdens to patients and healthcare providers, and generate recommendations for actionable steps to improve REMS programs overall.

In patients with atrial fibrillation, incomplete adherence to anticoagulants increases risk of stroke. Non-warfarin oral anticoagulants (NOACs) are expensive; we evaluated whether higher copayments are associated with lower NOAC adherence.Using a national claims database of commercially-insured patients, we performed a cohort study of patients with atrial fibrillation who newly initiated a NOAC from 2012 to 2018. Patients were stratified into low ($35), medium ($35-$59), or high (≥$60) copayments and propensity-score weighted based on demographics, insurance characteristics, comorbidities, prior health care utilization, calendar year, and the NOAC received. Follow-up was 1 year, with censoring for switching to a different anticoagulant, undergoing an ablation procedure, disenrolling from the insurance plan, or death. The primary outcome was adherence, measured by proportion of days covered (PDC). Secondary outcomes included NOAC discontinuation (no refill for 30 days after the end of NOAC supply) and switching anticoagulants. We compared PDC using a Kruskal-Wallis test and rates of discontinuation and switching using Cox proportional hazards models.After weighting patients across the 3 copayment groups, the effective sample size was 17,558 patients, with balance across 50 clinical and demographic covariates (standardized differences0.1). Mean age was 62 years, 29% of patients were female, and apixaban (43%), and rivaroxaban (38%) were the most common NOACs. Higher copayments were associated with lower adherence (P.001), with a PDC of 0.82 (Interquartile range [IQR] 0.36-0.98) among those with high copayments, 0.85 (IQR 0.41-0.98) among those with medium copayments, and 0.88 (IQR 0.41-0.99) among those with low copayments. Compared to patients with low copayments, patients with high copayments had higher rates of discontinuation (hazard ratio [HR] 1.13, 95% confidence interval [CI] 1.08-1.19; P.001).Among atrial fibrillation patients newly initiating NOACs, higher copayments in commercial insurance were associated with lower adherence and higher rates of discontinuation in the first year. Policies to lower or limit cost-sharing of important medications may lead to improved adherence and better outcomes among patients receiving NOACs.

Purpose There is an urgent need for treatments that prevent or delay development to advanced age-related macular degeneration (AMD). Drugs already on the market for other conditions could affect progression to neovascular AMD (nAMD). If identified, these drugs could provide insights for drug development targets. The objective of this study was to use a novel data mining method that can simultaneously evaluate thousands of correlated hypotheses, while adjusting for multiple testing, to screen for associations between drugs and delayed progression to nAMD. Design We applied a nested case-control study to administrative insurance claims data to identify cases with nAMD and risk-set sampled controls that were 1:4 variable ratio matched on age, gender, and recent healthcare use. Participants The study population included cases with nAMD and risk set matched controls. Methods We used a tree-based scanning method to evaluate associations between hierarchical classifications of drugs that patients were exposed to within 6 months, 7 to 24 months, or ever before their index date. The index date was the date of first nAMD diagnosis in cases. Risk-set sampled controls were assigned the same index date as the case to which they were matched. The study was implemented using Medicare data from New Jersey and Pennsylvania, and national data from IBM MarketScan Research Database. We set an a priori threshold for statistical alerting at P ≤ 0.01 and focused on associations with large magnitude (relative risks ≥ 2.0). Main Outcome Measures Progression to nAMD. Results Of approximately 4000 generic drugs and drug classes evaluated, the method detected 19 distinct drug exposures with statistically significant, large relative risks indicating that cases were less frequently exposed than controls. These included (1) drugs with prior evidence for a causal relationship (e.g., megestrol); (2) drugs without prior evidence for a causal relationship, but potentially worth further exploration (e.g., donepezil, epoetin alfa); (3) drugs with alternative biologic explanations for the association (e.g., sevelamer); and (4) drugs that may have resulted in statistical alerts due to their correlation with drugs that alerted for other reasons. Conclusions This exploratory drug-screening study identified several potential targets for follow-up studies to further evaluate and determine if they may prevent or delay progression to advanced AMD.

Risk evaluation and mitigation strategy (REMS) programs are intended to improve safe use of US Food and Drug Administration-approved drugs. However, controversy exists over whether they consistently accomplish this goal. We aimed to assess how initiation of the erythropoiesis stimulating agents (ESAs) darbepoetin alfa and epoetin alfa changed following implementation and enforcement (following a 1-year post-implementation grace period) of a prominent REMS program warning physicians against use in cancer patients with hemoglobin above 10 g/dL. Using claims data from a large US commercial insurance company, we conducted interrupted time-series analyses of darbepoetin alfa and epoetin alfa initiation among adult cancer patients in the 12 months before REMS program implementation, after REMS program implementation, and after REMS program enforcement. We also evaluated differences in inappropriate initiation (hemoglobin tests all above 10 g/dL in the prior month) between the periods. In total, we identified 3456 darbepoetin alfa initiators and 2632 epoetin alfa initiators. Over the study period, the monthly number of initiators per 100,000 patients with cancer fell from 119 to 32 for darbepoetin alfa and from 82 to 34 for epoetin alfa. However, non-significant post-REMS program implementation level and slope changes per 100,000 adult patients with cancer were observed for darbepoetin alfa (level 0.03 [95% confidence interval (CI) −14.98 to 15.05]; slope 1.94 [95% CI −0.22 to 4.10]) and epoetin alfa (level −4.10 [95% CI −16.85 to 8.65]; slope −0.52 [95% CI −2.35 to 1.32]). Non-significant post-REMS program enforcement level and slope changes were also seen for both drugs (darbepoetin alfa level 1.58 [95% CI −0.58 to 3.74, slope −0.28 [95% CI −15.29 to 14.73]; epoetin alfa level 1.58 (95% CI −0.26 to 3.42], slope 5.74 [95% CI −7.01 to 18.49]). Finally, non-significant changes in inappropriate darbepoetin alfa (60% vs. 53% vs. 57%, p = 0.68) and epoetin alfa (53% vs. 53% vs. 46%, p = 0.41) initiation were observed between the three study periods. REMS program implementation and enforcement were not associated with significant changes in ESA initiation, adding to concerns over the degree to which certain REMS programs enhance patient safety.

Background Treatment decisions for Coronavirus Disease 2019 (COVID-19) depend on disease severity, but the prescribing pattern by severity and drivers of therapeutic choices remain unclear. Objectives The objectives of the study were to evaluate pharmacological treatment patterns by COVID-19 severity and identify the determinants of prescribing for COVID-19. Methods Using electronic health record data from a large Massachusetts-based healthcare system, we identified all patients aged ≥ 18 years hospitalized with laboratory-confirmed COVID-19 from 1 March to 24 May, 2020. We defined five levels of COVID-19 severity at hospital admission: (1) hospitalized but not requiring supplemental oxygen; (2–4) hospitalized and requiring oxygen ≤ 2, 3–4, and ≥ 5 L per minute, respectively; and (5) intubated or admitted to an intensive care unit. We assessed the medications used to treat COVID-19 or as supportive care during hospitalization. Results Among 2821 patients hospitalized for COVID-19, we found inpatient mortality increased by severity from 5% for level 1 to 23% for level 5. As compared to patients with severity level 1, those with severity level 5 were 3.53 times (95% confidence interval 2.73–4.57) more likely to receive a medication used to treat COVID-19. Other predictors of treatment were fever, low oxygen saturation, presence of co-morbidities, and elevated inflammatory biomarkers. The use of most COVID-19 relevant medications has dropped substantially while the use of remdesivir and therapeutic anticoagulants has increased over the study period. Conclusions Careful consideration of disease severity and other determinants of COVID-19 drug use is necessary for appropriate conduct and interpretation of non-randomized studies evaluating outcomes of COVID-19 treatments. Electronic supplementary material The online version of this article (10.1007/s40265-020-01424-7) contains supplementary material, which is available to authorized users.

BACKGROUND: Less than half of patients with cardiometabolic disease consistently take prescribed medications. While health insurers and some delivery organizations use claims to measure adherence, most clinicians do not have access during routine interactions. Self-reported scales exist, but their practical utility is often limited by length or cost. By contrast, the accuracy of a new 3-item self-reported measure has been demonstrated in individuals with HIV. We evaluated its concordance with claims-based adherence measures in cardiometabolic disease. METHODS: We used data from a recently-completed pragmatic trial of patients with cardiometabolic conditions. After 12 months of follow-up, intervention subjects were mailed a survey with the 3-item measure that queries about medication use in the prior 30 days. Responses were linearly transformed and averaged. Adherence was also measured in claims in Month 12 and Months 1–12 of the trial using proportion of days covered (PDC) metrics. We compared validation metrics for non-adherence for self-report (average

Supplemental Digital Content is available in the text., We use simulated data to examine the consequences of depletion of susceptibles for hazard ratio (HR) estimators based on a propensity score (PS). First, we show that the depletion of susceptibles attenuates marginal HRs toward the null by amounts that increase with the incidence of the outcome, the variance of susceptibility, and the impact of susceptibility on the outcome. If susceptibility is binary then the Bross bias multiplier, originally intended to quantify bias in a risk ratio from a binary confounder, also quantifies the ratio of the instantaneous marginal HR to the conditional HR as susceptibles are depleted differentially. Second, we show how HR estimates that are conditioned on a PS tend to be between the true conditional and marginal HRs, closer to the conditional HR if treatment status is strongly associated with susceptibility and closer to the marginal HR if treatment status is weakly associated with susceptibility. We show that associations of susceptibility with the PS matter to the marginal HR in the treated (ATT) though not to the marginal HR in the entire cohort (ATE). Third, we show how the PS can be updated periodically to reduce depletion-of-susceptibles bias in conditional estimators. Although marginal estimators can hit their ATE or ATT targets consistently without updating the PS, we show how their targets themselves can be misleading as they are attenuated toward the null. Finally, we discuss implications for the interpretation of HRs and their relevance to underlying scientific and clinical questions. See video Abstract: http://links.lww.com/EDE/B727.

Objectives To better understand patients' and pharmacists' preferences for and experiences with changes in pill appearance (size, shape, color, and markings). Study design Cross-sectional. Methods We conducted independent national surveys of patients 50 years and older taking generic drugs for depression, diabetes, epilepsy, HIV, hyperlipidemia, or hypertension and of licensed pharmacists practicing in chain, franchise, or independent pharmacies. Responses were collected between January and April 2016. Results Of 1000 patient respondents (30% response rate), most reported experiencing changes in pill appearance (51%) and preferred to be notified about them (82%), but less than half recalled being notified (verbally: 36%; via sticker: 45%). Among patients who reported experiencing a change, 12% reported stopping their medication or using it less frequently. Of 710 pharmacist respondents (33% response rate), many reported changes in pill appearance occurring frequently in their pharmacies (47% reported that changes occurred 6 or more times per month) and more than three-fourths reported notifying patients about them often (verbally: 88%; via sticker: 77%). Conclusions Our findings reveal opportunities to improve patients' experiences with pill appearance changes through better notification practices and patient education.

Using nationwide Danish registries, we conducted a population-based case-crossover study evaluating the association between switching from a vitamin K antagonist (VKA) to a direct oral anticoagulant (DOAC), and vice versa, and 30-day risks of bleeding and arterial thromboembolism in patients with atrial fibrillation (AF). The case-crossover population was identified among oral anticoagulant users during 2011–2018 (n = 123,217) as patients with AF with 1) a case-defining outcome and 2) an anticoagulant switch during the 180 days preceding the outcome. Odds ratios were estimated using conditional logistic regression by comparing the occurrence of switching during the 30-day window immediately preceding the outcome to that in reference windows in the same individual 60–180 days before the outcome. The case-crossover populations for switching from VKA to DOAC and DOAC to VKA comprised 1,382 and 287 case patients, respectively. Switching from VKA to DOAC, but not from DOAC to VKA, was associated with an increased short-term risk of bleeding (odds ratio = 1.42; 95% confidence intervals: 1.13, 1.79, and 1.06; and 0.64, 1.75, respectively) and ischemic stroke (odds ratio = 1.74; 95% confidence intervals: 1.21, 2.51, and 0.92; and 0.46, 1.83, respectively). Our findings suggest that switching from VKA to DOAC is an intermittent risk factor of bleeding and ischemic stroke in patients with AF.

Sulfonylureas are commonly used to treat type 2 diabetes mellitus. Despite awareness of their effects on cardiac physiology, a knowledge gap exists regarding their effects on cardiovascular events in real-world populations. Prior studies reported sulfonylurea-associated cardiovascular death but not serious arrhythmogenic endpoints like sudden cardiac arrest (SCA) or ventricular arrhythmia (VA). We assessed the comparative real-world risk of SCA/VA among users of second-generation sulfonylureas: glimepiride, glyburide, and glipizide. We conducted two incident user cohort studies using five-state Medicaid claims (1999–2012) and Optum Clinformatics commercial claims (2000–2016). Outcomes were SCA/VA events precipitating hospital presentation. We used Cox proportional hazards models, adjusted for high-dimensional propensity scores, to generate adjusted hazard ratios (aHR). We identified 624,406 and 491,940 sulfonylurea users, and 714 and 385 SCA/VA events, in Medicaid and Optum, respectively. Dataset-specific associations with SCA/VA for both glimepiride and glyburide (vs. glipizide) were on opposite sides of and could not exclude the null (glimepiride: aHRMedicaid 1.17, 95% CI 0.96–1.42; aHROptum 0.84, 0.65–1.08; glyburide: aHRMedicaid 0.87, 0.74–1.03; aHROptum 1.11, 0.86–1.42). Database differences in data availability, populations, and documentation completeness may have contributed to the incongruous results. Emphasis should be placed on assessing potential causes of discrepancies between conflicting studies evaluating the same research question.

Outcomes-based contracts tie rebates and discounts for expensive drugs to outcomes. The objective was to estimate the utility of outcomes-based contracts for diabetes medications using real-world data and to identify methodologic limitations of this approach.A population-based cohort study of adults newly prescribed a medication for diabetes with a publicly announced outcomes-based contract (ie, exenatide microspheres ["exenatide"], dulaglutide, or sitagliptin) was conducted. The comparison group included patients receiving canagliflozin or glipizide. The primary outcome was announced in the outcomes-based contract: the percentage of adults with a follow-up hemoglobin A1C8% up to 1 year later. Secondary outcomes included the percentage of patients diagnosed with hypoglycemia and the cost of a 1-month supply.Thousands of adults newly filled prescriptions for exenatide (n = 5079), dulaglutide (n = 6966), sitagliptin (n = 40 752), canagliflozin (n = 16 404), or glipizide (n = 59 985). The percentage of adults subsequently achieving a hemoglobin A1C below 8% ranged from 83% (dulaglutide, sitagliptin) to 71% (canagliflozin). The rate of hypoglycemia was 25 per 1000 person-years for exenatide, 37 per 1000 person-years for dulaglutide, 28 per 1000 person-years for sitagliptin, 18 per 1000 person-years for canagliflozin, and 34 per 1000 person-years for glipizide. The cash price for a 1-month supply was $847 for exenatide, $859 for dulaglutide, $550 for sitagliptin, $608 for canagliflozin, and $14 for glipizide.Outcomes-based pricing of diabetes medications has the potential to lower the cost of medications, but using outcomes such as hemoglobin A1C may not be clinically meaningful because similar changes in A1C can be achieved with generic medications at a far lower cost.

Background The low cost of thiazolidinediones makes them a potentially valuable therapeutic option for the > 300 million economically disadvantaged persons worldwide with type 2 diabetes mellitus. Differential selectivity of thiazolidinediones for peroxisome proliferator-activated receptors in the myocardium may lead to disparate arrhythmogenic effects. We examined real-world effects of thiazolidinediones on outpatient-originating sudden cardiac arrest (SCA) and ventricular arrhythmia (VA). Methods We conducted population-based high-dimensional propensity score-matched cohort studies in five Medicaid programs (California, Florida, New York, Ohio, Pennsylvania | 1999–2012) and a commercial health insurance plan (Optum Clinformatics | 2000–2016). We defined exposure based on incident rosiglitazone or pioglitazone dispensings; the latter served as an active comparator. We controlled for confounding by matching exposure groups on propensity score, informed by baseline covariates identified via a data adaptive approach. We ascertained SCA/VA outcomes precipitating hospital presentation using a validated, diagnosis-based algorithm. We generated marginal hazard ratios (HRs) via Cox proportional hazards regression that accounted for clustering within matched pairs. We prespecified Medicaid and Optum findings as primary and secondary, respectively; the latter served as a conceptual replication dataset. Results The adjusted HR for SCA/VA among rosiglitazone (vs. pioglitazone) users was 0.91 (0.75–1.10) in Medicaid and 0.88 (0.61–1.28) in Optum. Among Medicaid but not Optum enrollees, we found treatment effect heterogeneity by sex (adjusted HRs = 0.71 [0.54–0.93] and 1.16 [0.89–1.52] in men and women respectively, interaction term p-value = 0.01). Conclusions Rosiglitazone and pioglitazone appear to be associated with similar risks of SCA/VA.

Objective To evaluate the association between initiation of fluoroquinolones and hospital admission or emergency department visit for suicidality. Design Population based cohort study. Setting IBM MarketScan database, USA. Participants 2 756 268 adults (≥18 years) who initiated an oral fluoroquinolone (ciprofloxacin, levofloxacin, moxifloxacin, gemifloxacin, ofloxacin, gatifloxacin, norfloxacin, lomefloxacin, besifloxacin) or comparator antibiotic (January 2003 to September 2015) and had at least six months of continuous health plan enrollment and a diagnosis of pneumonia or urinary tract infection (UTI) three days or less before the drug initiation date. Comparator antibiotics were azithromycin in the pneumonia cohort and trimethoprim-sulfamethoxazole in the UTI cohort. Participants were matched 1:1 within each cohort on a propensity score, calculated from a multivariable logistic regression model that included 57 baseline covariates. Main outcomes measure Primary outcome was hospital admission or emergency department visit for suicidal ideation or self-harm within 60 days after treatment initiation. Cox proportional hazard models were used to estimate hazard ratios and 95% confidence intervals. Results The pneumonia cohort included 551 042 individuals, and the UTI cohort included 2 205 526 individuals. During the 60 day follow-up, 181 events were observed in the pneumonia cohort and 966 in the UTI cohort. The adjusted hazard ratios for fluoroquinolones were 1.01 (95% confidence interval 0.76 to 1.36) versus azithromycin in the pneumonia cohort and 1.03 (0.91 to 1.17) versus trimethoprim-sulfamethoxazole in the UTI cohort. Results were consistent across sensitivity analyses and subgroups of sex, age, or history of mental illnesses. Conclusion Initiation of fluoroquinolones was not associated with a substantially increased risk of admission to hospital or emergency department visits for suicidality compared with azithromycin or trimethoprim-sulfamethoxazole.

Background The role of differing levels of frailty in the choice of oral anticoagulants for older adults with atrial fibrillation (AF) is unclear. Objective To examine the outcomes of direct oral anticoagulants (DOACs) versus warfarin by frailty levels. Design 1:1 propensity score-matched analysis of Medicare data, 2010 to 2017. Setting Community. Patients Medicare beneficiaries with AF who initiated use of dabigatran, rivaroxaban, apixaban, or warfarin. Measurements Composite end point of death, ischemic stroke, or major bleeding by frailty levels, defined by a claims-based frailty index. Results In the dabigatran-warfarin cohort (n = 158 730; median follow-up, 72 days), the event rate per 1000 person-years was 63.5 for dabigatran initiators and 65.6 for warfarin initiators (hazard ratio [HR], 0.98 [95% CI, 0.92 to 1.05]; rate difference [RD], -2.2 [CI, -6.5 to 2.1]). For nonfrail, prefrail, and frail persons, HRs were 0.81 (CI, 0.68 to 0.97), 0.98 (CI, 0.90 to 1.08), and 1.09 (CI, 0.96 to 1.23), respectively. In the rivaroxaban-warfarin cohort (n = 275 944; median follow-up, 82 days), the event rate per 1000 person-years was 77.8 for rivaroxaban initiators and 83.7 for warfarin initiators (HR, 0.98 [CI, 0.94 to 1.02]; RD, -5.9 [CI, -9.4 to -2.4]). For nonfrail, prefrail, and frail persons, HRs were 0.88 (CI, 0.77 to 0.99), 1.04 (CI, 0.98 to 1.10), and 0.96 (CI, 0.89 to 1.04), respectively. In the apixaban-warfarin cohort (n = 218 738; median follow-up, 84 days), the event rate per 1000 person-years was 60.1 for apixaban initiators and 92.3 for warfarin initiators (HR, 0.68 [CI, 0.65 to 0.72]; RD, -32.2 [CI, -36.1 to -28.3]). For nonfrail, prefrail, and frail persons, HRs were 0.61 (CI, 0.52 to 0.71), 0.66 (CI, 0.61 to 0.70), and 0.73 (CI, 0.67 to 0.80), respectively. Limitations Residual confounding and lack of clinical frailty assessment. Conclusion For older adults with AF, apixaban was associated with lower rates of adverse events across all frailty levels. Dabigatran and rivaroxaban were associated with lower event rates only among nonfrail patients. Primary funding source National Institute on Aging.

This pharmacoepidemiology study uses insurance claims data to compare generic substitutions for drugs with vs without manufacturer copayment coupons in California vs surrounding states in the year before and after a January 2018 California ban on coupons intended to incentivize use of more expensive brand-name medication.

Purpose Consensus is needed on conceptual foundations, terminology and relationships among the various self‐controlled “trigger” study designs that control for time‐invariant confounding factors and target the association between transient exposures (potential triggers) and abrupt outcomes. The International Society for Pharmacoepidemiology (ISPE) funded a working group of ISPE members to develop guidance material for the application and reporting of self‐controlled study designs, similar to Standards of Reporting Observational Epidemiology (STROBE). This first paper focuses on navigation between the types of self‐controlled designs to permit a foundational understanding with guiding principles. Methods We leveraged a systematic review of applications of these designs, that we term Self‐controlled Crossover Observational PharmacoEpidemiologic (SCOPE) studies. Starting from first principles and using case examples, we reviewed outcome‐anchored (case‐crossover [CCO], case‐time control [CTC], case‐case‐time control [CCTC]) and exposure‐anchored (self‐controlled case‐series [SCCS]) study designs. Results Key methodological features related to exposure, outcome and time‐related concerns were clarified, and a common language and worksheet to facilitate the design of SCOPE studies is introduced. Conclusions Consensus on conceptual foundations, terminology and relationships among SCOPE designs will facilitate understanding and critical appraisal of published studies, as well as help in the design, analysis and review of new SCOPE studies. This manuscript is endorsed by ISPE.

Sequential analysis is used in clinical trials and postmarket drug safety surveillance to prospectively monitor efficacy and safety to quickly detect benefits and problems, while taking the multiple testing of repeated analyses into account. When there are multiple outcomes, each one may be given a weight corresponding to its severity. This paper introduces an exact sequential analysis procedure for multiple weighted binomial end points; the analysis incorporates a drug’s combined benefit and safety profile. It works with a variety of alpha spending functions for continuous, group, or mixed group-continuous sequential analysis. The binomial probabilities may vary over time and do not need to be known a priori. The new method was implemented in the free R Sequential package for both one- and two-tailed sequential analysis. An example is given examining myocardial infarction and major bleeding events in patients who initiated non-steroidal antiinflammatory drugs.

Patients taking non-vitamin K antagonist oral anticoagulants (NOACs) such as dabigatran, rivaroxaban, and apixaban have reported experiencing angioedema in randomized trials and routine care. The aim of this study was to quantify the association between NOACs and angioedema relative to warfarin among routinely treated patients with atrial fibrillation in a cohort study. We also compared warfarin users with non-users in a case-crossover study. We utilized a cohort design that drew eligible patients from the Truven Health MarketScan Commercial database, the Optum© Clinformatics® Data Mart, and Medicare. Within each database, we compared the 6-month relative rate of angioedema among new users of NOACs (dabigatran, rivaroxaban, apixaban) and new users of warfarin. We estimated hazard ratios (HRs) and 95% confidence intervals (CIs) after adjusting for confounders using propensity score stratification, and meta-analyzed the database-specific HRs using a random-effects model. We also estimated an odds ratio (OR) for the association between warfarin and angioedema using a case-crossover design, a self-controlled design that controls for time-invariant confounders. In the cohort study, we observed 249 incident angioedema events among 267,681 NOAC initiators and 281,143 warfarin initiators across all databases. The meta-analyzed HR for angioedema comparing any NOAC versus warfarin was 0.98 (95% CI 0.76–1.27). In the case-crossover design, the OR for the association between warfarin and angioedema was 0.91 (95% CI 0.68–1.21) based on 431 cases. Our estimates were inconsistent with substantial short-term relative increases in the rate of angioedema associated with oral anticoagulant therapy.

Purpose As more biosimilars become available in the United States, postapproval noninterventional studies describing biosimilar switching and comparing effectiveness and/or safety between switchers and nonswitchers will play a key role in generating real-world evidence to inform clinical practices and policy decisions. Ensuring sound methodology is critical for making valid inferences from these studies. Methods The Biologics and Biosimilars Collective Intelligence Consortium (BBCIC) convened a workgroup consisting of academic researchers, industry scientists, and practicing clinicians to establish best practice recommendations for the conduct of noninterventional studies of biosimilar and reference biologic switching. The workgroup members participated in eight teleconferences between August 2017 and February 2018 to discuss specific topics and build consensus. Results This report provides workgroup recommendations covering five main considerations relating to noninterventional studies describing reference biologic to biosimilar switching and comparing reference biologic to biosimilars for safety and effectiveness in the presence of switching at treatment initiation and during follow-up: (a) selecting appropriate data sources from a range of available options including insurance claims, electronic health records, and registries; (b) study designs; (c) outcomes of interest including health care utilization and clinical endpoints; (d) analytic approaches including propensity scores, disease risk scores, and instrumental variables; and (e) special considerations including avoiding designs that ignore history of biologic use, avoiding immortal time bias, exposure misclassification, and accounting for postindex switching. Conclusion Recommendations provided in this report provide a framework that may be helpful in designing and critically evaluating postapproval noninterventional studies involving reference biologic to biosimilar switching.

PURPOSE Bootstrapping can account for uncertainty in propensity score (PS) estimation and matching processes in 1:1 PS-matched cohort studies. While theory suggests that the classical bootstrap can fail to produce proper coverage, practical impact of this theoretical limitation in settings typical to pharmacoepidemiology is not well studied. METHODS In a plasmode-based simulation study, we compared performance of the standard parametric approach, which ignores uncertainty in PS estimation and matching, with two bootstrapping methods. The first method only accounted for uncertainty introduced during the matching process (the observation resampling approach). The second method accounted for uncertainty introduced during both PS estimation and matching processes (the PS reestimation approach). Variance was estimated based on percentile and empirical standard errors, and treatment effect estimation was based on median and mean of the estimated treatment effects across 1000 bootstrap resamples. Two treatment prevalence scenarios (5% and 29%) across two treatment effect scenarios (hazard ratio of 1.0 and 2.0) were evaluated in 500 simulated cohorts of 10 000 patients each. RESULTS We observed that 95% confidence intervals from the bootstrapping approaches but not the standard approach, resulted in inaccurate coverage rates (98%-100% for the observation resampling approach, 99%-100% for the PS reestimation approach, and 95%-96% for standard approach). Treatment effect estimation based on bootstrapping approaches resulted in lower bias than the standard approach (less than 1.4% vs 4.1%) at 5% treatment prevalence; however, the performance was equivalent at 29% treatment prevalence. CONCLUSION Use of bootstrapping led to variance overestimation and inconsistent coverage, while coverage remained more consistent with parametric estimation.

A retrospective cohort study, supplemented with a nested case-control study, was performed using two administrative databases from commercial health plans in the United States to compare the incidence of pancreatic and thyroid cancer among users of exenatide versus other antidiabetic drugs (OADs). Patients with type 2 diabetes who initiated exenatide or OADs between 1 June 2005 and 30 June 2015 were included. Pancreatic and thyroid cancers were identified using chart-validated algorithms in the cohort study. Cases in the nested case-control study were chart-confirmed pancreatic or thyroid cancers, and controls were sampled using risk-set sampling. The time-fixed analyses comparing 33 629 exenatide initiators with 49 317 propensity-score-matched OAD initiators yielded hazard ratios of 0.76 (95% confidence interval [CI] 0.47-1.21) for pancreatic cancer and 1.46 (95% CI 0.98-2.19) for thyroid cancer. Results in the time-dependent analyses by cumulative duration or dose were similar. Nested case-control analyses yielded rate ratios of 0.61 (95%CI, 0.37-1.00) for pancreatic cancer and 0.89 (95% CI, 0.64-1.24) for thyroid cancer. This observational study suggested exenatide use was not associated with an increased risk of pancreatic or thyroid cancer.

We sought to develop a semiautomated screening approach using electronic healthcare data to identify drug-drug interactions (DDIs) that result in clinical outcomes. Using a case-crossover design with 30-day hazard and referent windows, we evaluated codispensed drugs (potential precipitants) in 7,801 patients who experienced rhabdomyolysis while on cytochrome P450 (CYP)3A4-metabolized statins and in 15,147 who experienced bleeding while on dabigatran. Estimates of direct associations between precipitant drugs and outcomes were used to adjust for bias and precipitants' direct effects. The P values were adjusted for multiple testing using the false discovery rate (FDR). From among 460 drugs codispensed with statins, 1 drug (clarithromycin) generated an alert (adjusted odds ratio (OR) 5.83, FDR < 0.05). From among 485 drugs codispensed with dabigatran, 2 drugs (naproxen and enoxaparin, ORs 2.50 and 2.75; FDR < 0.05) generated an alert. All three signals reflected known pharmacologic interactions, confirming the potential of case-crossover-based approaches for DDI screening in electronic healthcare data.

Purpose Implementing a cohort study in longitudinal healthcare databases requires looking back over some covariate assessment period (CAP) preceding cohort entry to measure confounders. We used simulations to compare fixed-duration versus all-available CAPs for confounder adjustment in the presence of differences in available baseline time between exposure groups. Methods We simulated cohorts of 10 000 patients with binary variables for a single confounder, exposure, and outcome. Baseline time was simulated based on the observed distribution in a claims-based comparison of statin users versus nonusers. We compared bias after measuring confounders using fixed-duration and all-available CAPs, both when exposure groups had similar and discrepant amounts of available baseline time. Results When the comparison groups had similar amounts of baseline time, an all-available CAP was less biased than a fixed-duration CAP. When baseline time differed between comparison groups, the preferable CAP approach depended on the direction of confounding and which exposure group had higher covariate sensitivity. These findings were consistent in direction across sensitivity analyses. Conclusion In certain settings of differential available baseline time between exposure groups, the all-available CAP was more biased than the fixed-duration CAP. The relative directions and strengths of confounding and misclassification biases are an important consideration when choosing between a fixed-duration or all-available CAP, but they are often unknown. Therefore, we recommend comparing the amount of available baseline time between exposure groups. When there is a large discrepancy, despite appropriate design choices, we recommend a fixed-duration approach to avoid potential increases in bias because of differential data availability.

During 2017, opioids were associated with 47,600 deaths in the United States, approximately one third of which involved a prescription opioid (1). Amid concerns that overprescribing to patients with acute pain remains an essential factor underlying misuse, abuse, diversion, and unintentional overdose, several states have restricted opioid analgesic prescribing (2,3). To characterize patterns of opioid analgesic use for acute pain in primary care settings before the widespread implementation of limits on opioid prescribing (2,3), patients filling an opioid analgesic prescription for acute pain were identified from a 2014 database of commercial claims. Using a logistic generalized additive model, the probability of obtaining a refill was estimated as a function of the initial number of days supplied. Among 176,607 patients with a primary care visit associated with an acute pain complaint, 7.6% filled an opioid analgesic prescription. Among patients who received an initial 7-day supply, the probability of obtaining an opioid analgesic prescription refill for nine of 10 conditions was

The US Food and Drug Administration’s Sentinel System was established to monitor safety of regulated medical products. Sentinel investigators identified known associations between drugs and adverse events to test reusable analytic tools developed for Sentinel. This test case used a comparator with a different indication. We tested the ability of Sentinel’s reusable analytic tools to identify the known association between warfarin and gastrointestinal bleeding (GIB). Statins, expected to have no effect on GIB, were the comparator. We further explored the impact of analytic features, including matching ratio and stratifying Cox regression analyses, on matched pairs. This evaluation included data from 14 Sentinel Data Partners. New users of warfarin and statins, aged 18 years and older, who had not received other anticoagulants or had recent GIB were matched on propensity score using 1:1 and 1:n variable ratio matching, matching statin users with warfarin users to estimate the average treatment effect in warfarin-treated patients. We compared the risk of GIB using Cox proportional hazards regression, following patients for the duration of their observed continuous treatment or until a GIB. For the 1:1 matched cohort, we conducted analyses with and without stratification on matched pair. The variable ratio matched cohort analysis was stratified on the matched set. We identified 141,398 new users of warfarin and 2,275,694 new users of statins. In analyses stratified on matched pair/set, the hazard ratios (HR) for GIB in warfarin users compared with statin users were 2.78 (95% confidence interval [CI] 2.36–3.28) in the 1:1 matched cohort and 3.10 (95% CI 2.76–3.49) in the variable ratio matched cohort. The HR was lower in the analysis of the 1:1 matched cohort not stratified by matched pair (2.22, 95% CI 1.97–2.49), and highest early in treatment. Follow-up for warfarin users tended to be shorter than for statin users. This study identified the expected GIB risk with warfarin compared with statins using an analytic tool developed for Sentinel. Our findings suggest that comparators with different indications may be useful in surveillance in select circumstances. Finally, in the presence of differential censoring, stratification by matched pair may reduce the potential for bias in Cox regression analyses.

BACKGROUND: Generic versions of a drug can vary in appearance, which can impact adherence. OBJECTIVE: To assess the preferences, perceptions, and responses of patients who experienced a change in the appearance of a generic medication. DESIGN: Cross-sectional survey of patients from a large commercial health plan. PARTICIPANTS: Adults receiving generic versions of lisinopril, fluoxetine, lamotrigine, or simvastatin who experienced a change in the color or shape of their pills between March 2014 and November 2015. MAIN MEASURES: Likert-scale responses to questions concerning perceptions of generic drug safety and effectiveness, reliance on and preferences for pill appearance, and responses to pill appearance changes. Multivariable logistic regression-modeled predictors of seeking advice and adjusting use following a pill appearance change. KEY RESULTS: Of 814 respondents (response rate = 41%), 72% relied on pill appearance to ensure they took the correct medication. A similar percentage wanted their pills to remain the same color (72%), shape (71%), and size (75%) upon refill, but 58% would not have paid a $1 premium on a $5 co-pay to ensure such consistency. Most respondents (86%) wanted their pharmacists to notify them about pill appearance changes, but only 37% recalled such notification; 21% thought they received the wrong medication, and 8% adjusted medication use. Younger respondents (18–33 vs. 50–57 years) were more likely to seek advice (odds ratio [OR] = 1.91; 95% confidence interval [CI],1.02–3.59), and respondents with lower household income ( $100,000) were more likely to adjust medication use (OR = 3.40; 95% CI,1.09–10.67). CONCLUSIONS: Requiring uniform pill appearance may help increase adherence but presents challenges. Standardized pharmacy notification and education policies may be a more feasible short-term solution. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s11606-018-4791-1) contains supplementary material, which is available to authorized users.

The approval of new oral disease-modifying drugs (DMDs), such as fingolimod, dimethyl fumarate (DMF), and teriflunamide, has considerably expanded treatment options for relapsing forms of multiple sclerosis (MS). However, data describing the use of these agents in routine clinical practice are limited.To describe time trends and identify factors associated with oral DMD treatment initiation and switching among individuals with MS.Using data from a large sample of commercially insured patients, we evaluated changes over time in the proportion of MS patients who initiated treatment with an oral DMD and who switched from an injectable DMD to an oral DMD between 2009 and 2014 in the United States. We evaluated predictors of oral DMD use using conditional logistic regression in 2 groups matched on calendar time: oral DMD initiators matched to injectable DMDs initiators and oral DMD switchers matched to those who switched to a second injectable DMD.Our cohort included 7,576 individuals who initiated a DMD and 1,342 who switched DMDs, of which oral DMDs accounted for 6% and 39%, respectively. Oral DMD initiation and switching steadily increased from 5% to 16% and 35% to 84%, respectively, between 2011 and 2014, with DMF being the most commonly used agent. Of the potential predictors with clinical significance, a recent neurologist consultation (OR = 1.60; 95% CI = 1.20-2.15) and emergency department visit (OR = 1.43; 95% CI = 1.01-2.01) were significantly associated with oral DMD initiation. History of depression was noted to be a potential predictor of oral DMD initiation; however, the estimate for this predictor did not reach statistical significance (OR = 1.35; 95% CI = 0.99-1.84). No clinically relevant factors measured in our data were associated with switching to an oral DMD.Oral DMDs were found to be routinely used as second-line treatment. However, we identified few factors predictive of oral DMD initiation or switching, which implies that their selection is driven by patient and/or physician preferences.This study was funded by CVS Caremark through an unrestricted research grant to Brigham and Women's Hospital. Shrank and Matlin were employees of, and shareholders in, CVS Health at the time of the study; they report no financial interests in products or services that are related to the subject of this study. Spettell is an employee of, and shareholder in, Aetna. Chitnis serves on clinical trial advisory boards for Novartis and Genzyme-Sanofi; has consulted for Bayer, Biogen Idec, Celgene, Novartis, Merck-Serono, and Genentech-Roche; and has received research support from NIH, National Multiple Sclerosis Society, Peabody Foundation, Consortium for MS Centers, Guthy Jackson Charitable Foundation, EMD-Serono, Novartis Biogen, and Verily. Desai reports receiving a research grant from Merck for unrelated work. Gagne is principal investigator of a research grant from Novartis Pharmaceuticals Corporation to the Brigham and Women's Hospital and has received grant support from Eli Lilly, all for unrelated work. He is also a consultant to Aetion and Optum. Minden reports grants from Biogen and other fees from Genentech, EMD Serano, Avanir, and Novartis, unrelated to this study. The other authors have no conflicts to report. This study was presented as a poster at the International Society for Pharmacoepidemiology 32nd Annual Meeting; August 25-28, 2016; Dublin, Ireland.

Adults with repaired coarctation of the aorta (CoA) suffer reduced long-term survival compared with the general population, in part due to coronary artery disease (CAD). There is conflicting evidence as to whether or not CoA is an independent risk factor for CAD. The primary aim was to determine if CoA is independently associated with premature myocardial infarction (MI) in the contemporary era. The secondary aim was to determine if CoA is independently associated with early coronary intervention. In a cross-sectional study using the National Inpatient Sample database from 2005 to 2014, we compared the age at MI and the age at coronary intervention (coronary artery bypass grafting or percutaneous coronary intervention, in the absence of MI diagnosis) in patients with and without CoA using weighted linear regression. Among 5,472,416 observations with a primary diagnosis of MI, 174 had a diagnosis of CoA. Patients with CoA had MI 7.2 years younger than those without CoA, after adjusting for potential confounders (95% CI -11.3, -3.1, p = 0.001). Among 3,631,718 patients without a diagnosis of MI who underwent coronary artery bypass grafting or percutaneous coronary intervention, 279 had a diagnosis of CoA. Patients with CoA who underwent coronary intervention were 15.6 years younger than those without CoA, after adjusting for potential confounders (95% CI -18.3, -12.9, p0.001). In conclusion, patients with CoA have MI at a slightly younger age and undergo coronary intervention at a significantly younger age than those without CoA in the contemporary era. Our findings support continued close surveillance for and treatment of modifiable risk factors for CAD.

Electronic health records (EHR) discontinuity, i.e., receiving care outside of the study EHR system, can lead to information bias in EHR-based real-world evidence (RWE) studies. An algorithm has been previously developed to identify patients with high EHR-continuity. We sought to assess whether applying this algorithm to patient selection for inclusion can reduce bias caused by data-discontinuity in 4 RWE examples. Among Medicare beneficiaries aged >=65 years from 2007 to 2014, we established four cohorts assessing drug effects on short-term or long-term outcomes, respectively. We linked claims data with two US EHR systems and calculated %bias of the multivariable-adjusted effect estimates based on only EHR vs. linked EHR-claims data since the linked data capture medical information recorded outside of the study EHR. Our study cohort included 77,288 patients in system 1 and 60,309 in system 2. We found the sub-cohort in the lowest quartile of EHR-continuity captured 72-81% of the short-term and only 21-31% of the long-term outcome events, leading to %bias of 6-99% for the short-term and 62-112% for the long-term outcome examples. This trend appeared to be more pronounced in the example using a non-user comparison rather than an active comparison. We did not find significant treatment effect heterogeneity by EHR-continuity for most subgroups across empirical examples. In EHR-based RWE studies, investigators may consider excluding patients with low algorithm-predicted EHR-continuity as the EHR data capture relatively few of their actual outcomes, and treatment effect estimates in these patients may be unreliable.