STUDY OBJECTIVE: Inhaled long-acting bronchodilators are commonly used as maintenance therapy in chronic obstructive pulmonary disease (COPD). We compared the risk of cardiovascular and cerebrovascular events among patients with COPD treated with inhaled long-acting bronchodilator monotherapy and combination therapy.
DESIGN: Retrospective cohort study.
SETTINGS: A population-based health care database from Taiwan.
PATIENTS: Individuals with COPD who initiated long-acting muscarinic antagonists (LAMAs) alone, long-acting β-2 agonists (LABA) alone, and LABA and LAMA in combination between 2001 and 2010.
MEASUREMENTS AND MAIN RESULTS: We used Cox regression models to compare a composite cardiovascular outcome, defined as hospitalization for acute myocardial infarction, congestive heart failure, and cerebrovascular diseases among the three treatment groups, adjusting for potential confounders. Among a cohort of 3458 study-eligible patients, we identified 505 composite cardiovascular events during 10,590 patient-years of follow-up. In the primary analysis which considered first exposure carried forward, LABA alone and LAMA alone were associated with similar risks of the composite outcome (hazard ratio [HR] 1.09; 95% confidence interval [CI] 0.87-1.37). The HR comparing LABA and LAMA in combination with LAMA alone was 1.13 (95% CI 0.60-2.13) and to LABA alone was 1.03 (95% CI 0.55-1.92). The secondary analysis in which we allowed patients to reenter the cohort upon treatment change yielded similar results, but with slightly higher HRs comparing LABA and LAMA in combination with LAMA alone (HR 1.26, 95% CI 0.74-2.15) and to LABA alone (HR 1.31, 95% CI 0.80-2.13).
CONCLUSIONS: Our results suggest similar cardiovascular and cerebrovascular safety of LABA and LAMA when agents are used alone. Additional studies are needed to rule out potential risk associated with inhaled long-acting bronchodilator combination therapy.
We conducted high-dimensional propensity score-adjusted cohort studies to examine whether thiazolidinedione use with a statin or fibrate was associated with an increased risk of severe hypoglycemia. We found that concomitant therapy with a thiazolidinedione+fibrate was associated with a generally delayed increased risk of severe hypoglycemia.
Previous studies have compared calipers for propensity score (PS) matching, but none have considered calipers for matching on the disease risk score (DRS). We used Medicare claims data to perform 3 cohort studies of medication initiators: a study of raloxifene versus alendronate in 1-year nonvertebral fracture risk, a study of cyclooxygenase 2 inhibitors versus nonselective nonsteroidal antiinflammatory medications in 6-month gastrointestinal bleeding, and a study of simvastatin + ezetimibe versus simvastatin alone in 6-month cardiovascular outcomes. The study periods for each cohort were 1998 through 2005, 1999 through 2002, and 2004 through 2005, respectively. In each cohort, we calculated 1) a DRS, 2) a prognostic PS which included the DRS as the independent variable in a PS model, and 3) the PS for each patient. We then nearest-neighbor matched on each score in a variable ratio and a fixed ratio within 8 calipers based on the standard deviation of the logit and the natural score scale. When variable ratio matching on the DRS, a caliper of 0.05 on the natural scale performed poorly when the outcome was rare. The prognostic PS did not appear to offer any consistent practical benefits over matching on the DRS directly. In general, logit-based calipers or calipers smaller than 0.05 on the natural scale performed well when DRS matching in all examples.
OBJECTIVE: To compare confounding adjustment by high-dimensional propensity scores (hdPSs) and historically developed high-dimensional disease risk scores (hdDRSs) in three comparative study examples of newly marketed medications: (1) dabigatran vs. warfarin on major hemorrhage; (2) on death; and (3) cyclooxygenase-2 inhibitors vs. nonselective nonsteroidal anti-inflammatory drugs on gastrointestinal bleeds.
STUDY DESIGN AND SETTING: In each example, we constructed a concurrent cohort of new and old drug initiators using US claims databases. In historical cohorts of old drug initiators, we developed hdDRS models including investigator-specified plus empirically identified variables and using principal component analysis and lasso regression for dimension reduction. We applied the models to the concurrent cohorts to obtain predicted outcome probabilities, which we used for confounding adjustment. We compared the resulting estimates to those from hdPS.
RESULTS: The crude odds ratio (OR) comparing dabigatran to warfarin was 0.52 (95% confidence interval: 0.37-0.72) for hemorrhage and 0.38 (0.26-0.55) for death. Decile stratification yielded an OR of 0.64 (0.46-0.90) for hemorrhage using hdDRS vs. 0.70 (0.49-1.02) for hdPS. ORs for death were 0.69 (0.45-1.06) and 0.73 (0.48-1.10), respectively. The relative performance of hdDRS in the cyclooxygenase-2 inhibitors example was similar.
CONCLUSION: hdDRS achieved similar or better confounding adjustment compared to conventional regression approach but worked slightly less well than hdPS.
BACKGROUND: Multivariable confounder adjustment in comparative studies of newly marketed drugs can be limited by small numbers of exposed patients and even fewer outcomes. Disease risk scores (DRSs) developed in historical comparator drug users before the new drug entered the market may improve adjustment. However, in a high dimensional data setting, empirical selection of hundreds of potential confounders and modeling of DRS even in the historical cohort can lead to over-fitting and reduced predictive performance in the study cohort. We propose the use of combinations of dimension reduction and shrinkage methods to overcome this problem, and compared the performances of these modeling strategies for implementing high dimensional (hd) DRSs from historical data in two empirical study examples of newly marketed drugs versus comparator drugs after the new drugs' market entry-dabigatran versus warfarin for the outcome of major hemorrhagic events and cyclooxygenase-2 inhibitor (coxibs) versus nonselective non-steroidal anti-inflammatory drugs (nsNSAIDs) for gastrointestinal bleeds.
RESULTS: Historical hdDRSs that included predefined and empirical outcome predictors with dimension reduction (principal component analysis; PCA) and shrinkage (lasso and ridge regression) approaches had higher c-statistics (0.66 for the PCA model, 0.64 for the PCA + ridge and 0.65 for the PCA + lasso models in the warfarin users) than an unreduced model (c-statistic, 0.54) in the dabigatran example. The odds ratio (OR) from PCA + lasso hdDRS-stratification [OR, 0.64; 95 % confidence interval (CI) 0.46-0.90] was closer to the benchmark estimate (0.93) from a randomized trial than the model without empirical predictors (OR, 0.58; 95 % CI 0.41-0.81). In the coxibs example, c-statistics of the hdDRSs in the nsNSAID initiators were 0.66 for the PCA model, 0.67 for the PCA + ridge model, and 0.67 for the PCA + lasso model; these were higher than for the unreduced model (c-statistic, 0.45), and comparable to the demographics + risk score model (c-statistic, 0.67).
CONCLUSIONS: hdDRSs using historical data with dimension reduction and shrinkage was feasible, and improved confounding adjustment in two studies of newly marketed medications.
The aim of this study was to examine the risk of early discontinuation of metformin as a proxy for intolerance, associated with use of drugs known to inhibit transporters involved in metformin distribution. We analysed all incident users of metformin in Denmark between 2000 and 2012 (n = 132,221) and in a cohort of US patients (n = 296,903). Risk of early discontinuation of metformin was assessed using adjusted logistic regression for 28 drugs putatively inhibiting metformin transporters and four negative controls. Increased odds ratio of early discontinuation of metformin was only associated with codeine, an inhibitor of organic cation transporter 1 in both cohorts [adjusted odds ratio (OR) in Danish cohort (95% CI): 1.13 (1.02-1.26), adjusted OR in American cohort (95% CI): 1.32 (1.19-1.47)]. The remaining drugs were not associated with increased odds ratio of early discontinuation and, surprisingly, four drugs were associated with a decreased risk. These findings indicate that codeine use may be associated with risk of early discontinuation of metformin and could be used as a basis for further investigation.
IMPORTANCE: In November 2011, the cholesterol level-lowering medication atorvastatin calcium became available in the United States as a generic drug. However, only a single generic form (from a manufacturer that qualified for market exclusivity by challenging several of Pfizer's patents) and an authorized generic form (a brand-name drug sold as a generic) were available for the first 180 days.
OBJECTIVE: To describe trends in the prescribing of generic atorvastatin after expiration of market exclusivity for the brand-name medication and the effect on patients' out-of-pocket spending.
DESIGN, SETTING, AND PARTICIPANTS: A US population-based study used commercial claims data from the Optum Clinformatics research database (UnitedHealth Group) from December 1, 2010, to May 31, 2013. Participants were 1 968 709 adults with commercial insurance who had been prescribed 1 or more statins (13 285 223 statin prescriptions). An interrupted times series model was used to examine the effect of limited and full generic competition on brand-name and generic atorvastatin prescriptions. Data were analyzed from December 1, 2010, to May 31, 2013.
EXPOSURES: Prescription of brand-name atorvastatin, generic atorvastatin, and authorized generic atorvastatin were distinguished using National Drug Codes.
MAIN OUTCOMES AND MEASURES: Total number of prescriptions dispensed per month and out-of-pocket expenditures for a typical 30-day supply of 20-mg atorvastatin during the periods of brand-name availability only, limited generic competition (lasting 180 days after market exclusivity ended), and full generic competition.
RESULTS: Of the 1 968 709 beneficiaries, 1 483 066 (58.8% male and 41.2% female; mean [SD] age, 55.6 [10.2] years) received a prescription for a single statin and were included in the analysis. The introduction of the first generic competitor was associated with a reduction in monthly brand-name atorvastatin fills by 20 896 prescriptions (level change, P = .001), an 18.1% change compared with the month preceding loss of exclusivity. Full generic competition reduced brand-name fills by 54 944 prescriptions (level change, P < .001), a 47.6% change relative to the month preceding loss of exclusivity. During the first 180 days of generic competition, no meaningful difference in monthly out-of-pocket spending was found between brand-name (median, $16.98; interquartile range [IQR], $8.76-$48.66) and generic (median, $19.98; IQR, $7.50-$54.90) atorvastatin. After full generic competition, estimated monthly out-of-pocket spending for generic atorvastatin (median $5.10; IQR, $3.36-$19.98) or authorized generic atorvastatin (median, $5.52; IQR, $3.48-$19.98) was substantially lower than that for brand-name atorvastatin (median, $30.00; IQR, $15.00-$91.38).
CONCLUSIONS AND RELEVANCE: Among patients with commercial health insurance, delays in generic uptake and high levels of out-of-pocket spending during the first 180 days after atorvastatin lost market exclusivity slowed changes in drug prescribing and decreases in patients' out-of-pocket costs.
PURPOSE: We present a systematic screening for identifying associations between prescribed drugs and cancer risk using the high quality Danish nationwide health registries.
METHODS: We identified all patients (cases) with incident cancer in Denmark during 2000-2012 (n=278,485) and matched each case to 10 controls. Complete prescription histories since 1995 were extracted. Applying a two-phased case-control approach, we first identified drug classes or single drugs associated with an increased or decreased risk of 99 different cancer types, and further evaluated potential associations by examining specificity and dose-response patterns.
FINDINGS: 22,125 drug-cancer pairs underwent evaluation in the first phase. Of 4561 initial signals (i.e., drug-cancer associations), 3541 (78%) failed to meet requirements for dose-response patterns and specificity, leaving 1020 eligible signals. Of these, 510 signals involved the use of single drugs, and 33% (166 signals) and 67% (344 signals) suggested a reduced or an increased cancer risk, respectively. While a large proportion of the signals were attributable to the underlying conditions being treated, our algorithm successfully identified well-established associations, as well as several new signals that deserve further investigation.
CONCLUSION: Our results provide the basis for future targeted studies of single associations to capture novel carcinogenic or chemopreventive effects of prescription drugs.
In a case-control study, matching on a disease risk score (DRS), which includes many confounders, should theoretically result in greater precision than matching on only a few confounders; however, this has not been investigated. We simulated 1,000 hypothetical cohorts with a binary exposure, a time-to-event outcome, and 13 covariates. Each cohort comprised 2 subcohorts of 10,000 patients each: a historical subcohort and a concurrent subcohort. DRS were estimated in the historical subcohorts and applied to the concurrent subcohorts. Nested case-control studies were conducted in the concurrent subcohorts using incidence density sampling with 2 strategies-matching on age and sex, with adjustment for additional confounders, and matching on DRS-followed by conditional logistic regression for 9 outcome-exposure incidence scenarios. In all scenarios, DRS matching yielded lower average standard errors and mean squared errors than did matching on age and sex. In 6 scenarios, DRS matching also resulted in greater empirical power. DRS matching resulted in less relative bias than did matching on age and sex at lower outcome incidences but more relative bias at higher incidences. Post-hoc analysis revealed that the effect of DRS model misspecification might be more pronounced at higher outcome incidences, resulting in higher relative bias. These results suggest that DRS matching might increase the statistical efficiency of case-control studies, particularly when the outcome is rare.
Studying the effect of chronic medication exposure by means of a case-crossover design may result in an upward-biased odds ratio. In this study, our aim was to assess the occurrence of this bias and to evaluate whether it is remedied by including a control group (the case-time-control design). Using Danish data resources from 1995-2012, we conducted case-crossover and case-time-control analyses for 3 medications (statins, insulin, and thyroxine) in relation to 3 outcomes (retinal detachment, wrist fracture, and ischemic stroke), all with assumed null associations. Controls were matched on age, sex, and index date, and exposure over the preceding 12 months was ascertained. For retinal detachment, the case-crossover odds ratio was 1.60 (95% confidence interval (CI): 1.42, 1.80) for statins, 1.40 (95% CI: 1.02, 1.92) for thyroxine, and 1.53 (95% CI: 1.04, 2.24) for insulin. Estimates for the retinal detachment controls were similar, leading to near-null case-time-control estimates for all 3 medication classes. For wrist fracture and stroke, the odds ratios were higher for cases than for controls, and case-time-control odds ratios were consistently above unity, thus implying significant residual bias. In case-crossover studies of medications, contamination by persistent users confers a moderate bias upward, which is partly remedied by using a control group. The optimal strategy for dealing with this problem is currently unknown.
A drug-drug interaction (DDI) occurs when one or more drugs affect the pharmacokinetics (the body's effect on the drug) and/or pharmacodynamics (the drug's effect on the body) of one or more other drugs. Pharmacoepidemiologic studies are the principal way of studying the health effects of potential DDIs. This article discusses aspects of pharmacoepidemiologic research designs that are particularly salient to the design and interpretation of pharmacoepidemiologic studies of DDIs.
BACKGROUND: Generic drugs are cost-effective versions of brand-name drugs approved by the Food and Drug Administration (FDA) following proof of pharmaceutical equivalence and bioequivalence. Generic drugs are widely prescribed by physicians, although there is disagreement over the clinical comparability of generic drugs to brand-name drugs within the physician community. The objective of this survey was to assess physicians' perceptions of generic drugs and the generic drug approval process.
METHODS AND FINDINGS: A survey was administered to a national sample of primary care internists and specialists between August 2014 and January 2015. In total, 1,152 physicians comprising of internists with no reported specialty certification and those with specialty certification in hematology, infectious diseases, and endocrinology were surveyed. The survey assessed physicians' perceptions of the FDA's generic drug approval process, as well as their experiences prescribing six generic drugs approved between 2008 and 2012 using product-specific approval pathways and selected comparator drugs. Among 718 respondents (62% response rate), a majority were comfortable with the FDA's process in ensuring the safety and effectiveness of generic drugs overall (91%) and with letting the FDA determine which tests were necessary to determine bioequivalence in a particular drug (92%). A minority (13-26%) still reported being uncomfortable prescribing generic drugs approved using product-specific pathways. Overall, few physicians heard reports of concerns about generic versions of the study drugs or their comparators, with no differences between the two groups. Physicians tended to hear about concerns about the safety or effectiveness of generic drugs from patients, pharmacists, and physician colleagues.
CONCLUSIONS: Physicians hold largely positive views of the FDA's generic drug approval process even when some questioned the performance of certain generic drugs in comparison to brand-name drugs. Better education about the generic drug approval process and standards may alleviate concerns among the physician community and support the delivery of cost-effective health care.
OBJECTIVE: To explore the association between unexpected potentially disruptive life events in a patient or family member that may challenge an individual's ability to take medications as prescribed and the discontinuation of evidence-based medications for common, chronic conditions. Understanding the relationship between medication adherence and life stressors, especially those that can be identified using administrative data, may help identify patients at risk of non-adherence.
DESIGN: Observational self-controlled case-crossover design.
SETTING: Individuals in a nationally representative US commercial health insurance database.
PARTICIPANTS: Adult individuals who initiated an oral hypoglycaemic, antihypertensive and/or statin and subsequently stopped the medication for ≥90 days.
MAIN OUTCOME MEASURE: Potentially disruptive life events among patients and their family members measured in the 30 days just before the medication was discontinued ('hazard period') compared with the 30 days before this period ('control period'). These events included personal injury, hospitalisation, emergency room visits, changes in insurance coverage, acute stress or acute anxiety.
RESULTS: Among the 326 519 patients meeting study criteria who discontinued their chronic disease medications, 88 896 (27.2%) experienced at least one potentially disruptive life event. Newly experiencing an injury (OR: 1.26, 95% CI 1.12 to 1.42), an emergency room visit (OR: 1.19, 95% CI 1.13 to 1.26) and acute stress (OR: 1.19, 95% CI 1.08 to 1.31) were associated with discontinuation. Life events among patients' family members did not appear to be associated with medication discontinuation or occurred less frequently just prior to discontinuation.
CONCLUSIONS: Potentially disruptive life events among individuals identified using routinely collected claims data are associated with discontinuation of chronic disease medications. Awareness of these events may help providers or payers identify patients at risk of non-adherence to maximise patient outcomes.
OBJECTIVES: To compare stratified event rates from randomized controlled trials with predicted event rates from models developed in observational data, and assess their ability to accurately capture observed rates of thromboembolism and major bleeding for patients treated with dabigatran or warfarin as part of routine care.
DESIGN: New initiator cohort study.
SETTING: Data from United Health (October 2009 to June 2013), a commercial healthcare claims database in the United States.
PARTICIPANTS: 21 934 adults with atrial fibrillation initiating dabigatran (150 mg dose only) or warfarin treatment as part of routine care.
MAIN OUTCOME MEASURES: Predicted annual rates of thromboembolism or major bleeding, based on estimates from randomized controlled trials, models developed in routine care patients, and baseline risk scores (CHADS2, CHA2DS2-VASc, and HAS-BLED). Thromboembolism was a composite outcome, including primary inpatient diagnosis codes for ischemic or ill defined stroke, transient ischemic attack, pulmonary embolism, deep vein thrombosis, and systemic embolism. Major bleeding was a composite outcome including codes occurring in an inpatient setting for hemorrhagic stroke; major upper, lower, or unspecified gastrointestinal bleed; and major urogenital or other bleed.
RESULTS: 6516 (30%) and 15 418 (70%) of patients initiated dabigatran and warfarin, respectively. Annual event rates per 100 patients were 1.7 for thromboembolism and 4.6 for major bleeding. For thromboembolism, calibration of estimates from randomized controlled trials was similar to calibration for model based predictions; however, trial estimates for major bleeding consistently underestimated the rate of bleeding among patients in routine care. Underestimation of bleeding rates was particularly pronounced in warfarin initiators with high HAS-BLED scores, where event rates were underestimated by up to 4.0 per 100 patient years. Harrell's c indices for discrimination for thromboembolism or major bleeding in dabigatran and warfarin initiators ranged between 0.59 and 0.66 for randomized controlled trial predictions, and between 0.52 and 0.70 for cross validated model based predictions.
CONCLUSION: Estimated rates of thromboembolism under dabigatran or warfarin treatment in randomized controlled trials were close to observed rates in routine care patients. However, rates of major bleeding were underestimated. Models developed in routine care patients can provide accurate, tailored estimates of risk and benefit under alternative treatment to enhance patient centered care.
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.