Publications by authors named "Katsiaryna Bykov"

40 Publications

Prevalence of avoidable and bias-inflicting methodological pitfalls in real-world studies of medication safety and effectiveness.

Clin Pharmacol Ther 2021 Jul 14. Epub 2021 Jul 14.

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

Many real-word evidence (RWE) studies that utilize existing healthcare data to evaluate treatment effects incur substantial, but avoidable bias from methodologically flawed study design; however, the extent of preventable methodological pitfalls in current RWE is unknown. To characterize the prevalence of avoidable methodological pitfalls with potential for bias in published claims-based studies of medication safety or effectiveness, we conducted an English-language search of PubMed for articles published from January 1, 2010 to May 20, 2019 and randomly selected 75 studies (10 case-control and 65 cohort studies) that evaluated safety or effectiveness of cardiovascular, diabetes, or osteoporosis medications using US health insurance claims. General and methodological study characteristics were extracted independently by two reviewers and potential for bias was assessed across 9 bias domains. Nearly all studies (95%) had at least one avoidable methodological issue known to incur bias and 81% had potentially at least one of the four issues considered major due to their potential to undermine study validity: time-related bias (57%), potential for depletion of outcome-susceptible individuals (44%), inappropriate adjustment for postbaseline variables (41%), or potential for reverse causation (39%). Median number of major issues per study was 2 (interquartile range [IQR], 1 to 3) and was lower in cohort studies with a new-user, active-comparator design (median 1, IQR 0 to1) than in studies of prevalent users and a non-user comparator (median 3, IQR 3 to 4). Recognizing and avoiding known methodological study design pitfalls could substantially improve the utility of RWE and confidence in its validity.
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http://dx.doi.org/10.1002/cpt.2364DOI Listing
July 2021

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

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

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

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

A Multi-modal Approach to Evaluate the Impact of Risk Evaluation and Mitigation Strategy (REMS) Programs.

Drug Saf 2021 Jul 27;44(7):743-751. Epub 2021 Apr 27.

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

Introduction: 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.

Objective: 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.

Methods: 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.

Conclusions: 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.
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http://dx.doi.org/10.1007/s40264-021-01070-2DOI Listing
July 2021

Association of Gabapentinoids With the Risk of Opioid-Related Adverse Events in Surgical Patients in the United States.

JAMA Netw Open 2020 12 1;3(12):e2031647. Epub 2020 Dec 1.

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

Importance: The use of gabapentinoids in multimodal postoperative analgesia is increasing; however, when coadministered with opioids, these drugs may potentiate central nervous system and respiratory depression.

Objective: To evaluate the association between perioperative coadministration of gabapentinoids and opioids with inpatient opioid-related adverse events in surgical patients.

Design, Setting, And Participants: This cohort study used propensity score trimming, stratification, and weighting of adults admitted for a major surgery between October 2007 and December 2017 who were treated with opioids on the day of surgery and included in the Premier Research database. Data analysis was conducted from February to April 2020.

Exposure: Gabapentinoids (gabapentin or pregabalin) coadministered with opioids starting the day of surgery vs opioid therapy without gabapentinoids.

Main Outcomes And Measures: Primary outcome was opioid overdose. Secondary outcomes included respiratory complications, unspecified adverse effects of opioid use, and a composite of these 3 outcomes. Patients were followed up for as long as 30 days from the day of surgery until deviation from the initial treatment regimen or discharge.

Results: Gabapentinoids with opioids were administered to 892 484 of 5 547 667 eligible admissions (16.1%; mean [SD] age, 63.5 [11.8] years; 353 315 [39.6%] men). Among the 4 655 183 patients who received opioids only, the mean (SD) age was 63.7 (14.7) years, and 1 913 284 (41.1%) were men. Overall, 441 overdose events were identified, with absolute risks of 1.4 per 10 000 patients with gabapentinoid exposure and 0.7 per 10 000 patients receiving opioids only. Following propensity score trimming, the cohort included 737 383 patients exposed to gabapentinoids and 3 002 480 patients receiving opioids only. The primary analysis yielded the adjusted hazard ratio of 1.95 (95% CI, 1.49-2.55), and the number needed to treat for an additional overdose to occur was 16 914 patients (95% CI, 11 556-31 537 patients). Adjusted hazard ratios for secondary outcomes were 1.68 (95% CI, 1.59-1.78) for respiratory complications, 1.77 (95% CI, 1.61-1.93) for unspecified adverse effects of opioids, and 1.70 (95% CI, 1.62-1.79) for the composite outcome. The results were consistent across sensitivity analyses and subgroups identified by key clinical factors.

Conclusions And Relevance: In this real-world cohort study of patients who underwent major surgery, concomitant use of gabapentinoids with opioids was associated with increased risk of opioid overdose and other opioid-related adverse events; however, the absolute risk of adverse events was low.
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http://dx.doi.org/10.1001/jamanetworkopen.2020.31647DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7772715PMC
December 2020

Postoperative inpatient utilization of opioid and opioid-sparing analgesics in the United States hospitals, 2007-2017.

Pharmacoepidemiol Drug Saf 2021 03 5;30(3):390-394. Epub 2021 Jan 5.

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

Purpose: To evaluate recent trends in inpatient postoperative utilization of opioid and non-opioid analgesics in US hospitals.

Methods: Using Premier Research database (October 2007-September 2017), we identified adults who were hospitalized for inpatient surgical procedures (N = 6 068 133). For each month, we calculated proportion of patients admitted that month who were administered (1) opioids, (2) acetaminophen, (3) non-steroidal anti-inflammatory drugs (NSADs), and (4) gabapentinoids (gabapentin or pregabalin) during the postoperative period, defined as inpatient postoperative days 1-7, unless discharged earlier. For patients administered opioids, we estimated total and average daily postoperative opioid dose in morphine milligram equivalents (MMEs). Monthly measures were standardized to the distribution of surgeries and the length of postoperative stay within each surgery during the last year of available data.

Results: Overall, 90.8% of patients were administered opioids postoperatively; mean total postoperative dose was 304 MMEs (median 130). Both the frequency and the amount of opioids administered remained stable over 2007-2017. Postoperative use of acetaminophen increased from mean standardized monthly prevalence of 78% in 2007-2008 to 85% in 2017, while the use of NSAIDs remained stable at a standardized mean of 37%. The use of gabapentinoids increased from below 10% in 2007-2008 to the mean standardized monthly prevalence of 23% in 2017.

Conclusion: Despite growing awareness of risks associated with postoperative opioid use, we observed no change in postoperative utilization of opioids in US hospitals. Increasing the use of non-opioid pain management approaches could constitute an important target in our efforts to curtail US opioid epidemic.
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http://dx.doi.org/10.1002/pds.5187DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7854478PMC
March 2021

Drug-Drug Interaction Surveillance Study: Comparing Self-Controlled Designs in Five Empirical Examples in Real-World Data.

Clin Pharmacol Ther 2021 May 17;109(5):1353-1360. Epub 2020 Dec 17.

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

Self-controlled designs, specifically the case-crossover (CCO) and the self-controlled case series (SCCS), are increasingly utilized to generate real-world evidence (RWE) on drug-drug interactions (DDIs). Although these designs share the advantages and limitations of within-individual comparison, they also have design-specific assumptions. It is not known to what extent the differences in assumptions lead to different results in RWE DDI analyses. Using a nationwide US commercial healthcare insurance database (2006-2016), we compared the CCO and SCCS designs, as they are implemented in DDI studies, within five DDI-outcome examples: (1) simvastatin + clarithromycin and muscle-related toxicity; (2) atorvastatin + valsartan, and muscle-related toxicity; and (3-5) dabigatran + P-glycoprotein inhibitor (clarithromycin, amiodarone, and verapamil) and bleeding. Analyses were conducted within person-time exposed to the object drug (statins and dabigatran) and adjusted for bias associated with the inhibiting drugs via control groups of individuals unexposed to the object drug. The designs yielded similar estimates in most examples, with SCCS displaying better statistical efficiency. With both designs, results varied across sensitivity analyses, particularly in CCO analyses with small number of exposed individuals. Analyses in controls revealed substantial bias that may be differential across DDI-exposed and control individuals. Thus, both designs showed no association between amiodarone or verapamil and bleeding in dabigatran-exposed but revealed strong positive associations in controls. Overall, bias adjustment via a control group had a larger impact on results than the choice of a design, highlighting the importance and challenges of appropriate control group selection for adequate bias control in self-controlled analyses of DDIs.
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http://dx.doi.org/10.1002/cpt.2119DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8058240PMC
May 2021

Association of Fluoroquinolones With the Risk of Aortic Aneurysm or Aortic Dissection.

JAMA Intern Med 2020 Dec;180(12):1596-1605

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

Importance: Previous observational studies have suggested that fluoroquinolones are associated with aortic aneurysm or dissection, but these studies may be subject to confounding by indication or surveillance bias.

Objective: To assess the association of fluoroquinolones with risk of aortic aneurysm or aortic dissection (AA/AD) while accounting for potential confounding by fluoroquinolone indication and bias owing to differential surveillance.

Design, Setting, And Participants: In an observational cohort study using a US commercial claims database, 2 pairwise 1:1 propensity score-matched cohorts were identified: patients aged 50 years or older with a diagnosis of pneumonia 3 days or less before initiating treatment with a fluoroquinolone or azithromycin and patients aged 50 years or older with a urinary tract infection (UTI) diagnosis 3 days or less before initiating a fluoroquinolone or combined trimethoprim and sulfamethoxazole. Hazard ratios (HRs) and 95% CIs were estimated controlling for 85 baseline confounders. In a secondary analysis, patients receiving fluoroquinolones were compared with those receiving amoxicillin, both with and without considering baseline aortic imaging, to address differences in detection of AA/AD before antibiotic use. Data on patients within the database from January 1, 2003, through September 30, 2015, were analyzed. Data analysis was conducted from July 23, 2019, to July 6, 2020.

Main Outcomes And Measures: Hospitalization for AA/AD occurring within 60 days following treatment initiation.

Results: After propensity score matching, patient characteristics were well balanced, with 279 554 patients (mean [SD] age, 63.66 [10.93] years; 149 976 women [53.6%]) in the pneumonia cohort and 948 364 patients (mean [SD] age, 62.06 [10.33] years; 823 667 women [86.9%]) in the UTI cohort. Initiators of fluoroquinolones (n = 139 772 pairs in the pneumonia cohort and n = 474 182 pairs in the UTI cohort) had an increased rate of AA/AD compared with initiators of azithromycin (HR, 2.57; 95% CI, 1.36-4.86; incidence, 0.03% for fluoroquinolones vs 0.01% for azithromycin) but no increased rate compared with initiators of combined trimethoprim and sulfamethoxazole (HR, 0.99; 95% CI, 0.62-1.57; incidence, <0.01% in both UTI groups). Secondary analysis using amoxicillin as a comparator (n = 3 976 162 pairs) produced results consistent with those from earlier studies (HR, 1.54; 95% CI, 1.33-1.79; incidence, <0.01% in both groups). Requiring baseline imaging in this cohort (n = 542 649 pairs) to address surveillance bias attenuated the increased rate (HR, 1.13; 95% CI, 0.96-1.33; incidence, 0.06% for fluoroquinolones vs 0.05% for amoxicillin).

Conclusions And Relevance: The findings of this nationwide cohort study of adults with pneumonia or UTI suggest an increased relative rate of AA/AD associated with fluoroquinolones within the pneumonia cohort but not within the UTI cohort. In both cohorts, the absolute rate of AA/AD appeared to be low (<0.1%). The increased relative rate observed in the pneumonia cohort may be due to residual confounding or surveillance bias.
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http://dx.doi.org/10.1001/jamainternmed.2020.4199DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7489402PMC
December 2020

Bias in case-crossover studies of medications due to persistent use: A simulation study.

Pharmacoepidemiol Drug Saf 2020 09 16;29(9):1079-1085. Epub 2020 Jun 16.

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

Purpose: The case-crossover design is increasingly used to evaluate the effects of chronic medications; however, as traditionally implemented in pharmacoepidemiology, with referent period preceding the outcome, it may lead to bias in the presence of persistent exposures. We aimed to evaluate the extent and magnitude of bias in case-crossover analyses of chronic and persistent exposures, using simulations.

Methods: We simulated cohorts with either 30-day, 180-day, or 2-year exposure duration; and with varying degrees of persistence (10%, 30%, 50%, 70%, or 90% of patients not stopping exposure). We evaluated all scenarios under the null and the scenario with 30% persistence under varying exposure effects (odds ratios of 0.25 to 4.0). Cohorts were analyzed using conditional logistic regression that compared the odds of exposure on the outcome day to the odds of exposure on a referent day 30 days prior to the outcome. We further implemented the case-time-control design to evaluate its ability to adjust for bias from persistence.

Results: Case-crossover analyses produced unbiased estimates across all scenarios without persistent users, regardless of exposure duration. In scenarios where some patients persisted on treatment, case-crossover analyses resulted in upward bias, which increased with increasing proportion of persistent users, but did not vary substantially in relation to the magnitude of the true effect. Case-time-control analyses removed bias in all scenarios.

Conclusions: Investigators should be aware of bias due to treatment persistence in unidirectional case-crossover analyses of chronic medications, which can be remedied with a control group of similarly persistent noncases.
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http://dx.doi.org/10.1002/pds.5031DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7501161PMC
September 2020

Trends in Utilization of Prescribed Controlled Substances in US Commercially Insured Adults, 2004-2019.

JAMA Intern Med 2020 07;180(7):1006-1008

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

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http://dx.doi.org/10.1001/jamainternmed.2020.0989DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7171580PMC
July 2020

Response to "The Self-Controlled Case Series Design as a Viable Alternative to Studying Clinically Relevant Drug Interactions".

Clin Pharmacol Ther 2020 02 21;107(2):323. Epub 2019 Oct 21.

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

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http://dx.doi.org/10.1002/cpt.1630DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7015272PMC
February 2020

Comparison of Self-controlled Designs for Evaluating Outcomes of Drug-Drug Interactions: Simulation Study.

Epidemiology 2019 11;30(6):861-866

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

Background: Self-controlled designs, both case-crossover and self-controlled case series, are well suited for evaluating outcomes of drug-drug interactions in electronic healthcare data. Their comparative performance in this context, however, is unknown.

Methods: We simulated cohorts of patients exposed to two drugs: a chronic drug (object) and a short-term drug (precipitant) with an associated interaction of 2.0 on the odds ratio scale. We analyzed cohorts using case-crossover and self-controlled case series designs evaluating exposure to the precipitant drug within person-time exposed to the object drug. Scenarios evaluated violations of key design assumptions: (1) time-varying, within-person confounding; (2) time trend in precipitant drug exposure prevalence; (3) nontransient precipitant exposure; and (4) event-dependent object drug discontinuation.

Results: Case-crossover analysis produced biased estimates when 30% of patients persisted on the precipitant drug (estimated OR 2.85) and when the use of the precipitant drug was increasing in simulated cohorts (estimated OR 2.56). Self-controlled case series produced biased estimates when patients discontinued the object drug following the occurrence of an outcome (estimated incidence ratio [IR] of 2.09 [50% of patients stopping therapy] and 2.22 [90%]). Both designs yielded similarly biased estimates in the presence of time-varying, within-person confounding.

Conclusion: In settings with independent or rare outcomes and no substantial event-dependent censoring (<50%), self-controlled case series may be preferable to case-crossover design for evaluating outcomes of drug-drug interactions. With frequent event-dependent drug discontinuation, a case-crossover design may be preferable provided there are no time-related trends in drug exposure.
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http://dx.doi.org/10.1097/EDE.0000000000001087DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6768702PMC
November 2019

Glucose-lowering medications and the risk of cancer: A methodological review of studies based on real-world data.

Diabetes Obes Metab 2019 09 29;21(9):2029-2038. Epub 2019 May 29.

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

Aim: To review the methodology of observational studies examining the association between glucose-lowering medications and cancer to identify the most common methodological challenges and sources of bias.

Methods: We searched PubMed systematically to identify observational studies on glucose-lowering medications and cancer published between January 2000 and January 2016. We assessed the design and analytical methods used in each study, with a focus on their ability to achieve study validity, and further evaluated the prevalence of major methodological choices over time.

Results: Of 155 studies evaluated, only 26% implemented a new-user design, 41% used an active comparator, 33% implemented a lag or latency period, and 51% adjusted for diabetes duration. Potential for immortal person-time bias was identified in 63% of the studies; 55% of the studies adjusted for variables measured during the follow-up without appropriate statistical methods. Aside from a decreasing trend in adjusting for variables measured during the follow-up, we observed no trends in methodological choices over time.

Conclusions: The prevalence of well-known design and analysis flaws that may lead to biased results remains high among observational studies on glucose-lowering medications and cancer, limiting the conclusions that can be drawn from these studies. Avoiding known pitfalls could substantially improve the quality and validity of real-world evidence in this field.
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http://dx.doi.org/10.1111/dom.13766DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6684441PMC
September 2019

A Case-Crossover-Based Screening Approach to Identifying Clinically Relevant Drug-Drug Interactions in Electronic Healthcare Data.

Clin Pharmacol Ther 2019 07 18;106(1):238-244. Epub 2019 Mar 18.

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

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.
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http://dx.doi.org/10.1002/cpt.1376DOI Listing
July 2019

The Case-Crossover Design for Drug-Drug Interactions: Considerations for Implementation.

Epidemiology 2019 03;30(2):204-211

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

Background: The case-crossover design may be useful for evaluating the clinical impact of drug-drug interactions in electronic healthcare data; however, experience with the design in this context is limited.

Methods: Using US healthcare claims data (1994-2013), we evaluated two examples of interacting drugs with prior evidence of harm: (1) cytochrome P450 (CYP)3A4-metabolized statins + clarithromycin or erythromycin and rhabdomyolysis; and (2) clopidogrel + fluoxetine or fluvoxamine and ischemic events. We conducted case-crossover analyses with (1) a three-parameter model with a product term and a six-parameter saturated model that distinguished initiation order of the two drugs; and (2) with or without active comparators.

Results: In the statin example, the three-parameter model produced estimates consistent with prior evidence with the active comparator (product term odds ratio [OR] = 2.05, 95% confidence interval [CI] = 1.00, 4.23) and without (OR = 1.99, 95% CI = 1.04, 3.81). In the clopidogrel example, this model produced results opposite of expectation (OR = 0.78, 95% = 0.68, 0.89), but closer to what was observed in prior studies when active comparator was used (OR = 1.03, 95% CI = 0.90, 1.19). The saturated model revealed heterogeneity of estimates across strata and considerable confounding; strata with concordant clopidogrel exposure likely produced the least biased estimates.

Conclusion: The three-parameter model assumes a common drug-drug interaction effect, whereas the saturated model is useful for identifying potential effect heterogeneity or differential confounding across strata. Restriction to certain strata or use of an active comparator may be necessary in the presence of within-person confounding.
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http://dx.doi.org/10.1097/EDE.0000000000000944DOI Listing
March 2019

Impact of a Metoprolol Extended Release Shortage on Post-Myocardial Infarction β-Blocker Utilization, Adherence, and Rehospitalization.

Circ Cardiovasc Qual Outcomes 2018 10;11(10):e004096

Division of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA (K.B., J.J.G., B.W., N.K.C.).

Background: Shortages of chronic medications are an increasingly common problem, yet little is known about their impact on drug utilization and clinical outcomes. We evaluated the population-level impact of metoprolol extended release shortage that occurred in the United States in 2009 to 2010.

Methods And Results: We conducted a population-based, time series analysis of 38 914 patients (mean age, 60 years; 69% men) discharged after hospitalization for myocardial infarction (MI) between January 2006 and November 2012 in a large commercial insurance database. The shortage period was defined as February 2009 to June 2010. Data before September 2008 was defined as preshortage period and data after June 2010 as postshortage period. Outcomes were proportion of patients who filled any long- or short-acting β-blocker within 30 days of discharge, adherence to β-blockers within the first year of therapy among patients who initiated β-blockers, and rates of 1-year rehospitalization for MI or unstable angina. Post-MI statin utilization and adherence were evaluated as control outcomes. During the preshortage period, 70% of patient filled a β-blocker, mean monthly adherence was 76%, and the average monthly rate of rehospitalization was 6.5 events per 100 person-years, as compared with β-blocker use of 62%, average adherence of 70%, and rehospitalization rate of 5.6 events per 100 person-years during the shortage. After accounting for the baseline (preshortage) trends, the shortage was associated with significant monthly reductions in postdischarge β-blocker use (-0.57% of patients [95% CI, -0.90 to -0.24] per month) and an immediate decrease in adherence (-4.58% days covered [95% CI, -6.12 to -3.04]). No negative impact on rates of rehospitalization, post-MI statin utilization, or statin adherence was observed. β-Blocker utilization began to increase after the resolution of the shortage.

Conclusions: The nationwide metoprolol extended release shortage in the United States was associated with fewer patients receiving any long- or short-acting β-blocker post-MI and lower adherence to β-blocker therapy for those who did receive it, but did not appear to appreciably affect clinical outcomes at the population level.
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http://dx.doi.org/10.1161/CIRCOUTCOMES.117.004096DOI Listing
October 2018

Use of Bypassing Agents and Risk of Thromboembolic Events in Patients with Haemophilia and Inhibitors.

Thromb Haemost 2017 12 6;117(12):2267-2273. Epub 2017 Dec 6.

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

Patients with haemophilia and inhibitors to factors VIII or IX require bypassing therapy. The primary safety concern of bypassing agents is thromboembolism; however, the incidence of thromboembolic adverse events (TAEs) in haemophilia patients with inhibitors remains poorly characterized. The aim of this study was to assess the incidence of TAEs following exposure to bypassing agents in patients with haemophilia. Using U.S. Medicaid database (2000–2010), we identified a cohort of 719 males (mean age: 10 years at cohort entry) with haemophilia A or B and use of either recombinant factor VIIa (rFVIIa) or activated prothrombin complex concentrate (aPCC). Patients were followed up until loss of insurance eligibility, end of study period, or the first occurrence of TAE. Exposure was assessed on as-treated basis, and outcomes were adjudicated through review of healthcare claims. During the observation of a total of 2,823 person-years (py; mean follow-up: 3.9 years), 22 TAEs were identified, leading to incidence rates of 4.2 events (95% confidence interval [CI]: 1.8–8.3) per 1,000 unexposed py; 15.4 events (95% CI: 6.7–30.3) per 1,000 aPCC-exposed py; 18.2 events (95% CI: 8.3–34.6) per 1,000 rFVIIa-exposed py; and 29.7 events (95% CI: 6.1–86.7) per 1,000 py of concomitant exposure to both agents. The results were consistent across sensitivity analyses. In conclusion, we found no difference in the rate of TAEs across agents, but the data are compatible with a possibly increased rate associated with a combination therapy, highlighting the need for continuing safety monitoring through prospective registries or observational data.
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http://dx.doi.org/10.1160/TH17-05-0365DOI Listing
December 2017

Updating the Evidence of the Interaction Between Clopidogrel and CYP2C19-Inhibiting Selective Serotonin Reuptake Inhibitors: A Cohort Study and Meta-Analysis.

Drug Saf 2017 10;40(10):923-932

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

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.
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http://dx.doi.org/10.1007/s40264-017-0556-8DOI Listing
October 2017

Clinical Outcomes of Concomitant Use of Warfarin and Selective Serotonin Reuptake Inhibitors: A Multidatabase Observational Cohort Study.

J Clin Psychopharmacol 2017 Apr;37(2):200-209

From the *Division of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA; †Faculty of Pharmacy, National Yang-Ming University, Taipei, Taiwan; ‡Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA; and §Division of Pharmacy Practice and Science, College of Pharmacy, The Ohio State University, Columbus, OH.

Background: Patients treated with warfarin are often coprescribed selective serotonin reuptake inhibitors (SSRIs) for coexisting depression. Some SSRIs are potent CYP2C9 inhibitors that may increase warfarin plasma concentrations and the risk of bleeding. We aimed to examine the effect of the putative CYP2C9-mediated warfarin-SSRI interaction on clinical outcomes.

Methods: We conducted an observational cohort study among warfarin initiators who had a subsequent SSRI prescription in 5 US claims databases. Patients were followed for up to 180 days as long as they were exposed to both warfarin and their index SSRI groups. Cox regression models were used to estimate hazard ratios and 95% confidence intervals for bleeding events, ischemic or thromboembolic events, and mortality comparing patients treated with SSRIs that are potent CYP2C9 inhibitors (fluoxetine, fluvoxamine) with those treated with other SSRIs after propensity score matching.

Findings: The eligible cohort comprised 52,129 patients. Hazard ratios were 1.14 (95% confidence interval [CI], 0.94-1.38) for bleeding events, 1.03 (95% CI, 0.87-1.21) for ischemic or thromboembolic events, and 0.90 (95% CI, 0.72-1.14) for mortality. Results were consistent across individual component outcomes, different warfarin stabilization periods, and subgroup analyses.

Conclusions: Patients concomitantly treated with warfarin and SSRIs that are potent CYP2C9 inhibitors had comparable rates of bleeding events, ischemic or thromboembolic events, and mortality as did patients cotreated with warfarin and other SSRIs, although small but potentially meaningful effects on bleeding cannot be completely excluded. SSRI inhibition of CYP2C9 does not appear to affect major safety or effectiveness outcomes of warfarin treatment in clinical practice, where patients may be closely monitored.
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http://dx.doi.org/10.1097/JCP.0000000000000658DOI Listing
April 2017

Generating Evidence of Clinical Outcomes of Drug-Drug Interactions.

Drug Saf 2017 02;40(2):101-103

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

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http://dx.doi.org/10.1007/s40264-016-0496-8DOI Listing
February 2017

Impact of an Interaction Between Clopidogrel and Selective Serotonin Reuptake Inhibitors.

Am J Cardiol 2017 02 16;119(4):651-657. Epub 2016 Nov 16.

Division of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts; Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts.

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.
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http://dx.doi.org/10.1016/j.amjcard.2016.10.052DOI Listing
February 2017

Propensity Score Weighting Compared to Matching in a Study of Dabigatran and Warfarin.

Drug Saf 2017 02;40(2):169-181

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

Introduction: Comparing medications in observational settings requires differences in patient characteristics to be accounted for. Propensity score (PS) methods can address these differences, but PS weighting approaches may introduce bias.

Methods: Within a cohort study of anticoagulant initiators from October 2010 through to December 2012, PS values for dabigatran relative to warfarin were estimated, and study outcomes (stroke or major bleeding) among the cohort were identified. The PS was used to match initiators and results compared with those obtained using inverse probability of treatment weighting (IPTW) and standardized morbidity ratio (SMR) weighting. Hazard ratios (HRs) for study outcomes were estimated using a proportional hazards regression model.

Results: There were 23,543 dabigatran and 50,288 warfarin initiators, and matching formed 19,189 pairs (81.5% of dabigatran initiators) which resulted in a pooled stroke HR of 0.77 (95% confidence interval [CI] 0.54-1.09), and a pooled major hemorrhage HR of 0.75 (95% CI 0.65-0.87). The IPTW results for stroke (HR = 0.00; 95% CI 0.00-0.56) and major hemorrhage (HR = 0.08; 95% CI 0.08-0.10) substantially differed, while the SMR-weighted results for stroke (HR = 0.65; 95% CI 0.42-1.03) and major hemorrhage (HR = 0.73; 95% CI 0.61-0.85) differed only slightly from matching.

Conclusions: In this example, different applications of the same PS led to substantially different results, a finding that was particularly apparent with IPTW, and this was remedied by truncating extreme weights. If IPTW is used, information regarding the weights applied along with sensitivity analyses could avoid misrepresentation of study results, and would enhance their interpretation.
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http://dx.doi.org/10.1007/s40264-016-0480-3DOI Listing
February 2017

Switching generic antiepileptic drug manufacturer not linked to seizures: A case-crossover study.

Neurology 2016 Oct 28;87(17):1796-1801. Epub 2016 Sep 28.

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

Objective: With more antiepileptic drugs (AED) becoming available in generic form, we estimated the risk of seizure-related events associated with refilling generic AEDs and the effect of switching between different manufacturers of the same generic drug.

Methods: We designed a population-based case-crossover study using the Medicaid Analytic eXtract and a US commercial health insurance database. We identified 83,001 generic AED users who experienced a seizure-related hospital admission or emergency room visit between 2000 and 2013 and assessed whether they received a refill of the same AED from the same manufacturer or a different manufacturer. Patients served as their own controls and conditional logistic regression was used to compare exposure to a refill during the hazard period, defined as days 2-36 preceding the seizure-related event, to exposure during the control period, defined as days 51-85 preceding the seizure-related event.

Results: Generic AED refilling was associated with an 8% increase in the odds of seizure-related events (odds ratio [OR] 1.08; 95% confidence interval [CI] 1.06-1.11). The OR following a switch to a different manufacturer of the same AED was 1.09 (95% CI 1.03-1.15); however, after adjusting for the process of refilling, there was no association between switching and seizure-related hospital visits (OR 1.00; 95% CI 0.94-1.07).

Conclusions: Among patients on a generic AED, refilling the same AED was associated with an elevated risk of seizure-related event; however, there was no additional risk from switching during that refill to a different manufacturer. Generic AEDs available to US patients, with Food and Drug Administration-validated bioequivalence, appear to be safe clinical choices.
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http://dx.doi.org/10.1212/WNL.0000000000003259DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5089522PMC
October 2016

Risk of mortality with concomitant use of tamoxifen and selective serotonin reuptake inhibitors: multi-database cohort study.

BMJ 2016 Sep 30;354:i5014. Epub 2016 Sep 30.

Division of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA 02120 Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA 02115

Objective:  To compare differences in mortality between women concomitantly treated with tamoxifen and selective serotonin reuptake inhibitors (SSRIs) that are potent inhibitors of the cytochrome-P450 2D6 enzyme (CYP2D6) versus tamoxifen and other SSRIs.

Design:  Population based cohort study.

Setting:  Five US databases covering individuals enrolled in private and public health insurance programs from 1995 to 2013.

Participants:  Two cohorts of women who started taking tamoxifen. In cohort 1, women started taking an SSRI during tamoxifen treatment. In cohort 2, women were already taking an SSRI when they started taking tamoxifen.

Main Outcome Measures:  All cause mortality in each cohort in women taking SSRIs that are potent inhibitors of CYP2D6 (paroxetine, fluoxetine) versus other SSRIs. Propensity scores were used to match exposure groups in a variable ratio fashion. Results were measured separately for each cohort and combined hazard ratios calculated from Cox regression models across the two cohorts with random effects meta-analysis.

Results:  There were 6067 and 8465 new users of tamoxifen in cohorts 1 and 2, respectively. Mean age was 55. A total of 991 and 1014 deaths occurred in cohorts 1 and 2 during a median follow-up of 2.2 (interquartile range 0.9-4.5) and 2.0 (0.8-3.9) years, respectively. The pooled hazard ratio for death for potent inhibitors (rate 58.6/1000 person years) compared with other SSRIs (rate 57.9/1000 person years) across cohorts 1 and 2 was 0.96 (95% confidence interval 0.88 to 1.06). Results were consistent across sensitivity analyses.

Conclusion:  Concomitant use of tamoxifen and potent CYP2D6 inhibiting SSRIs versus other SSRIs was not associated with an increased risk of death.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5044871PMC
http://dx.doi.org/10.1136/bmj.i5014DOI Listing
September 2016

Response to the Comment on Evaluating Cardiovascular Health Disparities Using Estimated Race/Ethnicity: A Validation Study.

Med Care 2016 10;54(10):965-6

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

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http://dx.doi.org/10.1097/MLR.0000000000000627DOI Listing
October 2016

Confounding of the association between statins and Parkinson disease: systematic review and meta-analysis.

Pharmacoepidemiol Drug Saf 2017 Mar 16;26(3):294-300. Epub 2016 Aug 16.

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

Purpose: Both statins and higher serum cholesterol have been reported to reduce to risk of Parkinson Disease (PD). Given the importance of adjusting for cholesterol levels when evaluating the effect of statins, we assessed whether the protective effect of statins would remain when adjustment for cholesterol is performed.

Methods: We conducted a systematic review of epidemiologic studies that reported quantitative estimates of the association between statins and incident PD and were published through February 2016. Random-effects meta-analysis was used to assess the effect of statins on PD separately among the studies that adjusted for either cholesterol or hyperlipidemia and studies that did not.

Results: Ten eligible studies that evaluated the use of statins and incident PD were identified. Among the six studies that did not adjust for cholesterol, a protective effect of statins was observed (relative risk 0.75; 95% confidence intervals (CI) 0.60 to 0.92). Excluding studies with possible bias because of reverse causation or stratifying on study design did not affect the results. No protective effect was observed among the four studies that adjusted for either cholesterol of hyperlipidemia (relative risk 0.91; 95%CI 0.68 to 1.22). The effect estimate for studies that adjusted for cholesterol was 1.04 (95%CI 0.68 to 1.59) when a study with immortal time bias was excluded.

Conclusions: The apparent protective effect of statins on risk of PD is at least partially explained by confounding by statin indication. Immortal time bias and healthy user effects also could have contributed to biased results. Copyright © 2016 John Wiley & Sons, Ltd.
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http://dx.doi.org/10.1002/pds.4079DOI Listing
March 2017

Persistent opioid use following cesarean delivery: patterns and predictors among opioid-naïve women.

Am J Obstet Gynecol 2016 09 17;215(3):353.e1-353.e18. Epub 2016 Mar 17.

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

Background: The incidence of opioid-related death in women has increased 5-fold over the past decade. For many women, their initial opioid exposure will occur in the setting of routine medical care. Approximately 1 in 3 deliveries in the United States is by cesarean, and opioids are commonly prescribed for postsurgical pain management.

Objective: The objective of this study was to determine the risk that opioid-naïve women prescribed opioids after cesarean delivery will subsequently become consistent prescription opioid users in the year following delivery and to identify predictors for this behavior.

Study Design: We identified women in a database of commercial insurance beneficiaries who underwent cesarean delivery and who were opioid naïve in the year prior to delivery. To identify persistent users of opioids, we used trajectory models, which group together patients with similar patterns of medication filling during follow-up, based on patterns of opioid dispensing in the year following cesarean delivery. We then constructed a multivariable logistic regression model to identify independent risk factors for membership in the persistent user group.

Results: A total of 285 of 80,127 (0.36%, 95% confidence interval, 0.32-0.40), opioid-naïve women became persistent opioid users (identified using trajectory models based on monthly patterns of opioid dispensing) following cesarean delivery. Demographics and baseline comorbidity predicted such use with moderate discrimination (c statistic = 0.73). Significant predictors included a history of cocaine abuse (risk, 7.41%; adjusted odds ratio, 6.11, 95% confidence interval, 1.03-36.31) and other illicit substance abuse (2.36%; adjusted odds ratio, 2.78, 95% confidence interval, 1.12-6.91), tobacco use (1.45%; adjusted odds ratio, 3.04, 95% confidence interval, 2.03-4.55), back pain (0.69%; adjusted odds ratio, 1.74, 95% confidence interval, 1.33-2.29), migraines (0.91%; adjusted odds ratio, 2.14, 95% confidence interval, 1.58-2.90), antidepressant use (1.34%; adjusted odds ratio, 3.19, 95% confidence interval, 2.41-4.23), and benzodiazepine use (1.99%; adjusted odds ratio, 3.72, 95% confidence interval, 2.64-5.26) in the year prior to the cesarean delivery.

Conclusion: A very small proportion of opioid-naïve women (approximately 1 in 300) become persistent prescription opioid users following cesarean delivery. Preexisting psychiatric comorbidity, certain pain conditions, and substance use/abuse conditions identifiable at the time of initial opioid prescribing were predictors of persistent use.
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http://dx.doi.org/10.1016/j.ajog.2016.03.016DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5003640PMC
September 2016

Prospective Benefit-Risk Monitoring of New Drugs for Rapid Assessment of Net Favorability in Electronic Health Care Data.

Value Health 2015 Dec 21;18(8):1063-9. Epub 2015 Oct 21.

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

Background: Benefit-risk assessment (BRA) methods can combine measures of benefits and risks into a single value.

Objectives: To examine BRA metrics for prospective monitoring of new drugs in electronic health care data.

Methods: Using two electronic health care databases, we emulated prospective monitoring of three drugs (rofecoxib vs. nonselective nonsteroidal anti-inflammatory drugs, prasugrel vs. clopidogrel, and denosumab vs. bisphosphonates) using a sequential propensity score-matched cohort design. We applied four BRA metrics: number needed to treat and number needed to harm; incremental net benefit (INB) with maximum acceptable risk; INB with relative-value-adjusted life-years; and INB with quality-adjusted life-years (QALYs). We determined whether and when the bootstrapped 99% confidence interval (CI) for each metric excluded zero, indicating net favorability of one drug over the other.

Results: For rofecoxib, all four metrics yielded a negative value, suggesting net favorability of nonselective nonsteroidal anti-inflammatory drugs over rofecoxib, and the 99% CI for all but the number needed to treat and number needed to harm excluded the null during follow-up. For prasugrel, only the 99% CI for INB-QALY excluded the null, but trends in values over time were similar across the four metrics, suggesting overall net favorability of prasugrel versus clopidogrel. The 99% CI for INB-relative-value-adjusted life-years and INB-QALY excluded the null in the denosumab example, suggesting net favorability of denosumab over bisphosphonates.

Conclusions: Prospective benefit-risk monitoring can be used to determine net favorability of a new drug in electronic health care data. In three examples, existing BRA metrics produced qualitatively similar results but differed with respect to alert generation.
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http://dx.doi.org/10.1016/j.jval.2015.08.011DOI Listing
December 2015

Comparison of Benefit-Risk Assessment Methods for Prospective Monitoring of Newly Marketed Drugs: A Simulation Study.

Value Health 2015 Dec 2;18(8):1057-62. Epub 2015 Nov 2.

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

Objectives: To compare benefit-risk assessment (BRA) methods for determining whether and when sufficient evidence exists to indicate that one drug is favorable over another in prospective monitoring.

Methods: We simulated prospective monitoring of a new drug (A) versus an alternative drug (B) with respect to two beneficial and three harmful outcomes. We generated data for 1000 iterations of six scenarios and applied four BRA metrics: number needed to treat and number needed to harm (NNT|NNH), incremental net benefit (INB) with maximum acceptable risk, INB with relative-value-adjusted life-years, and INB with quality-adjusted life-years. We determined the proportion of iterations in which the 99% confidence interval for each metric included and excluded the null and we calculated mean time to alerting.

Results: With no true difference in any outcome between drugs A and B, the proportion of iterations including the null was lowest for INB with relative-value-adjusted life-years (64%) and highest for INB with quality-adjusted life-years (76%). When drug A was more effective and the drugs were equally safe, all metrics indicated net favorability of A in more than 70% of the iterations. When drug A was safer than drug B, NNT|NNH had the highest proportion of iterations indicating net favorability of drug A (65%). Mean time to alerting was similar among methods across the six scenarios.

Conclusions: BRA metrics can be useful for identifying net favorability when applied to prospective monitoring of a new drug versus an alternative drug. INB-based approaches similarly outperform unweighted NNT|NNH approaches. Time to alerting was similar across approaches.
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http://dx.doi.org/10.1016/j.jval.2015.08.015DOI Listing
December 2015

Evaluating Cardiovascular Health Disparities Using Estimated Race/Ethnicity: A Validation Study.

Med Care 2015 Dec;53(12):1050-7

*Department of Medicine, Division of Pharmacoepidemiology and Pharmacoeconomics, Brigham and Women's Hospital, Harvard Medical School, Boston, MA †Aetna, Hartford, CT ‡Aetna, Blue Bell, PA §CVS/Caremark, Woonsocket, RI.

Background: Methods of estimating race/ethnicity using administrative data are increasingly used to examine and target disparities; however, there has been no validation of these methods using clinically relevant outcomes.

Objective: To evaluate the validity of the indirect method of race/ethnicity identification based on place of residence and surname for assessing clinically relevant outcomes.

Data Sources: A total of 2387 participants in the Post-MI Free Rx Event and Economic Evaluation (MI FREEE) trial who had both self-reported and Bayesian Improved Surname Geocoding method (BISG)-estimated race/ethnicity information available.

Study Design: We used tests of interaction to compare differences in the effect of providing full drug coverage for post-MI medications on adherence and rates of major vascular events or revascularization for white and nonwhite patients based upon self-reported and indirect racial/ethnic assignment.

Results: The impact of full coverage on clinical events differed substantially when based upon self-identified race (HR=0.97 for whites, HR=0.65 for nonwhites; interaction P-value=0.05); however, it did not differ among race/ethnicity groups classified using indirect methods (HR=0.87 for white and nonwhites; interaction P-value=0.83). The impact on adherence was the same for self-reported and BISG-estimated race/ethnicity for 2 of the 3 medication classes studied.

Conclusions: Quantitatively and qualitatively different results were obtained when indirectly estimated race/ethnicity was used, suggesting that these techniques may not accurately describe aspects of race/ethnicity related to actual health behaviors.
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http://dx.doi.org/10.1097/MLR.0000000000000438DOI Listing
December 2015

Thiazolidinediones and Parkinson Disease: A Cohort Study.

Am J Epidemiol 2015 Dec 22;182(11):936-44. Epub 2015 Oct 22.

Thiazolidinediones, a class of medications indicated for the treatment of type 2 diabetes mellitus, reduce inflammation and have been shown to provide a therapeutic benefit in animal models of Parkinson disease. We examined the association between treatment with thiazolidinediones and the onset of Parkinson disease in older individuals. We performed a cohort study of 29,397 Medicare patients enrolled in state pharmaceutical benefits programs who initiated treatment with thiazolidinediones or sulfonylureas during the years 1997 through 2005 and had no prior diagnosis of Parkinson disease. New users of thiazolidinediones were propensity score matched to new users of sulfonylureas and followed to determine whether they were diagnosed with Parkinson disease. We used Cox proportional hazards models to compare time to diagnosis of Parkinson disease in the propensity score-matched populations. To assess the association with duration of use, we performed several analyses that required longer continuous use of medications. In the primary analysis, thiazolidinedione users had a hazard ratio for a diagnosis of Parkinson disease of 1.09 (95% confidence interval: 0.71, 1.66) when compared with sulfonylurea users. Increasing the duration-of-use requirements to 10 months did not substantially change the association; the hazard ratios ranged from 1.00 (95% confidence interval: 0.49, 2.05) to 1.17 (95% confidence interval: 0.60, 2.25). Thiazolidinedione use was not associated with a longer time to diagnosis of Parkinson disease than was sulfonylurea use, regardless of duration of exposure.
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http://dx.doi.org/10.1093/aje/kwv109DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4655743PMC
December 2015
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