BACKGROUND: Drug interactions, particularly those involving warfarin, are a major clinical and public health problem. Minimizing serious bleeding caused by anticoagulants is a recent major focus of the United States (US) Department of Health and Human Services. This study quantified the risk of gastrointestinal bleeding (GIB) and intracranial hemorrhage (ICH) among concomitant users of warfarin and individual antihyperlipidemics.
METHODS: The authors conducted a high-dimensional propensity score-adjusted cohort study of new concomitant users of warfarin and an antihyperlipidemic, among US Medicaid beneficiaries from five states during 1999-2011. Exposure was defined by concomitant use of warfarin plus one of eight antihyperlipidemics. The primary outcome measure was a composite of GIB/ICH within the first 30days of concomitant use. As a secondary outcome measure, GIB/ICH was examined within the first 180days of concomitant use.
RESULTS: Among 236,691 persons newly-exposed to warfarin and an antihyperlipidemic, the crude incidence of GIB/ICH was 13.2 (95% confidence interval 12.7 to 13.8) per 100person-years. Users were predominantly older, female, and Caucasian. Adjusted hazard ratios (aHRs) for warfarin and individual statins were consistent with no association. Warfarin+gemfibrozil was associated with an 80% increased risk of GIB/ICH within the first month of concomitant use (aHR=1.8, 1.4 to 2.4). Warfarin+fenofibrate was associated with a similar increased risk (aHR=1.8, 1.2 to 2.7), yet with an onset during the second month of concomitant use.
CONCLUSIONS: Among warfarin-treated persons, the use of fibrates-but not statins-increases the risk of hospital presentation for GIB/ICH.
Clopidogrel is a pro-drug that requires activation by the cytochrome P450 (CYP) enzyme system. Patients receiving clopidogrel are often treated with selective serotonin reuptake inhibitors (SSRIs) for co-existing depression. SSRIs that inhibit the CYP2C19 enzyme have the potential to reduce the effectiveness of clopidogrel. Using 5 US databases (1998 to 2013), we conducted a cohort study of adults who initiated clopidogrel while being treated with either an SSRI that inhibits CYP2C19 (fluoxetine and fluvoxamine) or a noninhibiting SSRI. Patients were matched by propensity score and followed for as long as they were exposed to both clopidogrel and the index SSRI group (primary analysis) or for 180 days after clopidogrel initiation (sensitivity analysis). Outcomes included a composite ischemic event (myocardial infarction, ischemic stroke, or a revascularization procedure) and a composite major bleeding event (gastrointestinal bleed or hemorrhagic stroke). The final propensity score-matched cohort comprised 9,281 clopidogrel initiators on CYP2C19-inhibiting SSRIs and 44,278 clopidogrel initiators on a noninhibiting SSRIs. Compared with those treated with a noninhibiting SSRI, patients on a CYP2C19-inhibiting SSRI had an increased risk of ischemic events (hazard ratio [HR] 1.12; 95% confidence interval [CI] 1.01 to 1.24), which was more pronounced in patients ≥65 years (HR 1.22; 95% CI 1.00 to 1.48). The HR for major bleeding was 0.76 (95% CI 0.50 to 1.17). In conclusion, the findings from this large, population-based study suggest that being treated with a CYP2C19-inhibiting SSRI when initiating clopidogrel may be associated with slight decrease in effectiveness of clopidogrel.
WHAT IS KNOWN AND OBJECTIVE: Pharmacy claims are commonly used to assess medication adherence. It is unclear how different approaches to handling hospitalizations compare to the gold standard of using outpatient and inpatient drug data. This study aimed to compare the impact of different approaches to handling hospitalizations on medication adherence estimation in administrative claims data.
METHODS: We identified β-blocker initiators after myocardial infarction (MI) and statin initiators regardless of hospitalization histories in the population-based, Taiwan database, which includes outpatient and inpatient drug claims data. Adherence to β-blockers or to statins during a 365-day follow-up period was estimated in outpatient pharmacy claims using the proportion of days covered (PDC) in three ways: ignoring hospitalizations (PDC1); subtracting hospitalized days from the denominator (PDC2); and assuming drug use on all hospitalized days (PDC3). We compared these to an approach that incorporated inpatient drug use (PDC4). We also used a hypothetical example to examine variations across approaches in several scenarios, such as increasing hospitalized days.
RESULTS AND DISCUSSION: Mean 365-day PDC was 74% among 1729 post-MI β-blocker initiators (range: 73.1%-74.9%) and 44% among 69 435 statins initiators (range: 43.5%-44.0%), which varied little across approaches. Differences across approaches increased with increasing number of hospitalized days. For patients hospitalized for >28 days, mean difference across approaches was >15%. PDC3 consistently yielded the highest value and PDC1 the lowest.
WHAT IS NEW AND CONCLUSIONS: On average, different approaches to handling hospitalizations lead to similar adherence estimates to the gold standard of incorporating inpatient drug use. When patients have many hospitalization days during follow-up, the choice of approach should be tailored to the specific setting.
BACKGROUND: Propensity score matching is a commonly used tool. However, its use in settings with more than two treatment groups has been less frequent. We examined the performance of a recently developed propensity score weighting method in the three-treatment group setting.
METHODS: The matching weight method is an extension of inverse probability of treatment weighting (IPTW) that reweights both exposed and unexposed groups to emulate a propensity score matched population. Matching weights can generalize to multiple treatment groups. The performance of matching weights in the three-group setting was compared via simulation to three-way 1:1:1 propensity score matching and IPTW. We also applied these methods to an empirical example that compared the safety of three analgesics.
RESULTS: Matching weights had similar bias, but better mean squared error (MSE) compared with three-way matching in all scenarios. The benefits were more pronounced in scenarios with a rare outcome, unequally sized treatment groups, or poor covariate overlap. IPTW's performance was highly dependent on covariate overlap. In the empirical example, matching weights achieved the best balance for 24 out of 35 covariates. Hazard ratios were numerically similar to matching. However, the confidence intervals were narrower for matching weights.
CONCLUSIONS: Matching weights demonstrated improved performance over three-way matching in terms of MSE, particularly in simulation scenarios where finding matched subjects was difficult. Given its natural extension to settings with even more than three groups, we recommend matching weights for comparing outcomes across multiple treatment groups, particularly in settings with rare outcomes or unequal exposure distributions. See video abstract at, http://links.lww.com/EDE/B188.
AIM: Laboratory test (lab) results may be useful to detect incident diabetes in electronic health record and claims-based studies.
RESEARCH DESIGN & METHODS: Using the Mini-Sentinel distributed database, we assessed the value of lab results added to diagnosis codes and dispensing claims to identify incident diabetes.
RESULTS: Inclusion of lab results increased the number of diabetes outcomes identified by 21%. In settings where capture of lab results was relatively complete, the absence of lab results was associated with implausibly low rates of the outcome.
CONCLUSION: Lab results can increase sensitivity of algorithms for detecting diabetes, and missing lab results are associated with much lower rates of diabetes ascertainment regardless of algorithm. Patterns of missing lab results may identify ascertainment bias.
OBJECTIVE: We sought to examine rates of clinical outcomes among patients before and after market introduction of generic versions of five drugs approved using product-specific equivalence determinations.
METHODS: We used data from a large national insurer to identify patients who initiated a study (acarbose tablets, salmon calcitonin nasal spray, enoxaparin injection, vancomycin capsules, venlafaxine extended-release tablets) or control drug (nateglinide, glimepiride, alendronate, fondaparinux, metronidazole, sertraline, paroxetine) in each calendar month between 2003 and 2012 and to determine rates of claims-based proxies for lack of effectiveness outcomes following initiation. We used segmented time-series analyses to evaluate level (short-term) and slope (longer-term) changes in outcomes upon introduction of a generic study or control drug.
RESULTS: Among study drugs, we observed three increases (one with p < 0.05) and three decreases (two with p < 0.05) in the level of outcome rates. All changes in slope indicated decreases in outcomes from the brand-only to the generic period; four had p < 0.05. For control drugs, we observed positive level changes for eight of nine drug-outcome pairs; two had p < 0.05. We observed negative slope changes for eight out of nine pairs; six had p < 0.05. We observed a significant increase in level change following the introduction of generic bupropion versions that were later found to be not bioequivalent (p < 0.01).
CONCLUSIONS: We did not find evidence that introduction of generic drugs approved using product-specific therapeutic equivalence determinations was associated with worse clinical outcomes than those among initiators of the brand-name versions of the same products. We observed similar patterns for control drugs.
BACKGROUND: Many countries lack fully functional pharmacovigilance programs, and public budgets allocated to pharmacovigilance in industrialized countries remain low due to resource constraints and competing priorities.
OBJECTIVE: Using 3 case examples, we sought to estimate the public health and economic benefits resulting from public investment in active pharmacovigilance programs to detect adverse drug effects.
RESEARCH DESIGN: We assessed 3 examples in which early signals of safety hazards were not adequately recognized, resulting in continued exposure of a large number of patients to these drugs when safer and effective alternative treatments were available. The drug examples studied were rofecoxib, cerivastatin, and troglitazone. Using an individual patient simulation model and the health care system perspective, we estimated the potential costs that could have been averted by early systematic detection of safety hazards through the implementation of active surveillance programs.
RESULTS: We found that earlier drug withdrawal made possible by active safety surveillance would most likely have resulted in savings in direct medical costs of $773-$884 million for rofecoxib, $3-$10 million for cerivastatin, and $38-$63 million for troglitazone in the United States through the prevention of adverse events. By contrast, the yearly public investment in Food and Drug Administration initiated population-based pharmacovigilance activities in the United States is about $42.5 million at present.
CONCLUSION: These examples illustrate a critical and economically justifiable role for active adverse effect surveillance in protecting the health of the public.
INTRODUCTION: The identification of upper gastrointestinal (UGI) bleeding and perforated ulcers in claims data typically relies on inpatient diagnoses. The use of hemoglobin laboratory results might increase the detection of UGI events that do not lead to hospitalization.
OBJECTIVES: Our objective was to evaluate whether hemoglobin results increase UGI outcome identification in electronic databases, using non-steroidal anti-inflammatory drugs (NSAIDs) as a test case.
METHODS: From three data partner sites within the Mini-Sentinel Distributed Database, we identified NSAID initiators aged ≥18 years between 2008 and 2013. Numbers of events and risks within 30 days after NSAID initiation were calculated for four mutually exclusive outcomes: (1) inpatient UGI diagnosis of bleeding or gastric ulcer (standard claims-based definition without laboratory results); (2) non-inpatient UGI diagnosis AND ≥3 g/dl hemoglobin decrease; (3) ≥3 g/dl hemoglobin decrease without UGI diagnosis in any clinical setting; (4) non-inpatient UGI diagnosis, without ≥3 g/dl hemoglobin decrease.
RESULTS: We identified 2,289,772 NSAID initiators across three sites. Overall, 45.3% had one or more hemoglobin result available within 365 days before or 30 days after NSAID initiation; only 6.8% had results before and after. Of 7637 potential outcomes identified, outcome 1 accounted for 21.7%, outcome 2 for 0.8%, outcome 3 for 34.3%, and outcome 4 for 43.3%. Potential cases identified by outcome 3 were largely not suggestive of UGI events. Outcomes 1, 2, and 4 had similar distributions of specific UGI diagnoses.
CONCLUSIONS: Using available hemoglobin result values combined with non-inpatient UGI diagnoses identified few additional UGI cases. Non-inpatient UGI diagnostic codes may increase outcome detection but would require validation.
BACKGROUND/AIMS: Renally excreted medications often require dose adjustment in patients with kidney impairment. While drug development and approval in the United States are typically based on several Phase I and II studies and one or more larger Phase III randomized trials, the basis for labeled dosing recommendations for patients with renal impairment is less well known. In response, we aimed to quantify the level of evidence used to recommend labeled dosing adjustments for newly approved drugs in patients with renal impairment.
METHODS: We reviewed publicly available drug labels and approval packages for new molecular entities approved in the United States between 2012 and 2014. The sample was restricted to 29 renally excreted new molecular entities that were not granted orphan drug status. We extracted data regarding approved indications, normal dosing, dosing adjustments for patients with mild (estimated glomerular filtration rate >60 mL/min/1.73 m), moderate (estimated glomerular filtration rate 30-<60 mL/min/1.73 m), and severe (estimated glomerular filtration rate <30 mL/min/1.73 m) renal impairment, characteristics of studies used to justify dosing adjustments, and numbers of subjects in each study.
RESULTS: In all, 14 of 29 (48%) new molecular entities had labels that recommended dosing adjustments for patients with mild, moderate, and/or severe renal impairment. Among these 14 new molecular entities, 4 (29%) used only pharmacokinetic studies to justify the recommendations, with no examination of clinical outcomes for patients with renal impairment. Where data were available, the median number of patients with renal impairment evaluated in studies used for dosing adjustment was 34 (range, 4-5976). Of the 15 new molecular entities with no recommended dosing adjustments for this population, 2 (13%) did not report assessing the effects of renal impairment.
CONCLUSION: Nearly half of newly approved renally excreted drugs include dosing adjustments for kidney impairment on the label, but the recommendations are usually based on very small numbers of patients and often utilize pharmacokinetic studies alone. More research is needed to understand the benefits and risks of new drugs in patients with renal impairment.
INTRODUCTION: We previously found that patients who initiate clopidogrel while treated with a cytochrome P450 (CYP) 2C19-inhibiting selective serotonin reuptake inhibitor (SSRI) have a higher risk of subsequent ischemic events than patients treated with other SSRIs. It is not known whether initiating an inhibiting SSRI while treated with clopidogrel will also increase risk of ischemic events.
OBJECTIVE: The aim of this study was to assess clinical outcomes following initiation of a CYP2C19-inhibiting SSRI versus initiation of other SSRIs among patients treated with clopidogrel and to update existing evidence on the clinical impact of clopidogrel-SSRI interaction.
METHODS: Using five US databases (1998-2013), we conducted a cohort study of clopidogrel initiators who encountered treatment with SSRI during their clopidogrel therapy. Patients were matched by propensity score (PS) and followed for as long as they were exposed to both clopidogrel and index SSRI group. Outcomes were a composite ischemic event (myocardial infarction, ischemic stroke, or a revascularization procedure, whichever came first) and a composite major bleeding event (gastrointestinal bleed or hemorrhagic stroke, whichever came first). Results were combined via random-effects meta-analysis with previous evidence from subjects initiating clopidogrel while on SSRI therapy.
RESULTS: The PS-matched cohort comprised 2346 clopidogrel users starting CYP2C19-inhibiting SSRI therapy and 16,115 starting other SSRIs (mean age 61 years; 59% female). Compared with those treated with a non-inhibiting SSRI, the hazard ratio (HR) for patients treated with a CYP2C19-inhibiting SSRI was 1.07 (95% confidence interval [CI] 0.82-1.40) for the ischemic outcome and 1.00 (95% CI 0.42-2.36) for bleeding. The pooled estimates were 1.11 (95% CI 1.01-1.22) for ischemic events and 0.80 (95% CI 0.55-1.18) for bleeding.
CONCLUSIONS: We observed similar estimates of association between the two studies. The updated evidence still indicates a small decrease in clopidogrel effectiveness associated with concomitant exposure to clopidogrel and CYP2C19-inhibiting SSRIs.