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The importance and implications of comparator selection in pharmacoepidemiologic research.

ABSTRACT: Purpose of review:Pharmacoepidemiologic studies employing large databases are critical to evaluating the effectiveness and safety of drug exposures in large and diverse populations. Because treatment is not randomized, researchers must select a relevant comparison group for the treatment of interest. The comparator group can consist of individuals initiating: (1) a similarly indicated treatment (active comparator), (2) a treatment used for a different indication (inactive comparator) or (3) no particular treatment (non-initiators). Herein we review recent literature and describe considerations and implications of comparator selection in pharmacoepidemiologic studies. Recent findings:Comparator selection depends on the scientific question and feasibility constraints. Because pharmacoepidemiologic studies rely on the choice to initiate or not initiate a specific treatment, rather than randomization, they are at-risk for confounding related to the comparator choice including: by indication, disease severity and frailty. We describe forms of confounding specific to pharmacoepidemiologic studies and discuss each comparator along with informative examples and a case study. We provide commentary on potential issues relevant to comparator selection in each study, highlighting the importance of understanding the population in whom the treatment is given and how patient characteristics are associated with the outcome. Summary:Advanced statistical techniques may be insufficient for reducing confounding in observational studies. Evaluating the extent to which comparator selection may mitigate or induce systematic bias is a critical component of pharmacoepidemiologic studies.

SUBMITTER: D'Arcy M

PROVIDER: S-EPMC6338470 | biostudies-literature | 2018 Sep

REPOSITORIES: biostudies-literature

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The importance and implications of comparator selection in pharmacoepidemiologic research.

D'Arcy Monica M Stürmer Til T Lund Jennifer L JL

Current epidemiology reports 20180706 3

<h4>Purpose of review</h4>Pharmacoepidemiologic studies employing large databases are critical to evaluating the effectiveness and safety of drug exposures in large and diverse populations. Because treatment is not randomized, researchers must select a relevant comparison group for the treatment of interest. The comparator group can consist of individuals initiating: (1) a similarly indicated treatment (active comparator), (2) a treatment used for a different indication (inactive comparator) or ...[more]

PMID: 30666285

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Project description:BackgroundComparator selection is an important consideration in the design of observational research studies that evaluate potential associations between drug therapies and adverse event risks. It can affect the validity of observational study results, and potentially impact data interpretation, regulatory decision making, and patient medication access.ObjectiveThe aim of this study was to assess the impact of comparator selection bias using two real-world case studies evaluating an increased rate of acute myocardial infarction (AMI).MethodsData from the Truven Health Analytics MarketScan® electronic medical claims database were used to conduct two retrospective observational cohort studies, utilizing a cohort new-user design, comparing AMI risk between testosterone replacement therapy (TRT) and phosphodiesterase-5 inhibitors (PDE5is) in men treated for hypogonadism, and triptans versus other prescribed acute treatments for migraine in adults. All patients were enrolled continuously in a health plan (no enrollment gap > 31 consecutive days) for ≥ 1 year before index. Baseline period was defined as 365 days prior to index. Exposure was defined by prescription and outcome of interest was defined as occurrence of AMI. Using Cox proportional hazard models, primary analysis for the TRT cohort compared AMI risk between propensity score (PS)-matched TRT-treated and untreated patients; secondary analysis evaluated risk between PS-matched TRT-treated and PDE5i-treated patients. For the triptan cohort, primary analysis compared AMI/ischemic stroke risk between PS-matched triptan-treated and opiate-treated patients; secondary analysis evaluated risk between PS-matched triptan-treated and nonsteroidal anti-inflammatory drug (NSAID)-treated patients and PS-matched non-prescription-treated migraine patients and general patients.ResultsNo significant association between TRT and AMI was observed among TRT-treated (N = 198,528, mean age 52.4 ± 11.4 years) versus PDE5i-treated men (N = 198,528, mean age 52.3 ± 11.5 years) overall (adjusted hazard ratio [aHR] 1.01; 95% CI 0.95-1.07; p = 0.80). Among patients with prior cardiovascular disease (CVD), risk of AMI was significantly increased for TRT-treated versus PDE5i-treated patients (aHR 1.13; 95% CI 1.03-1.25). The triptan study included three comparisons (triptans [N = 436,642] vs prescription NSAIDs [N = 334,152], opiates [N = 55,234], and untreated migraine [N = 1,168,212]), and a positive control (untreated vs general non-migraine patients [N = 11,735,009]). Analyses of MI risk in migraine patients prescribed triptans versus NSAIDs/opiates had mixed results: the point estimate ranged from 0.33 to 0.84 depending on chosen study window.ConclusionsCardiovascular outcomes were not worse in hypogonadism patients with TRT versus PDE5i; however, a potential association with AMI was found in patients with prior CVD receiving TRT versus PDE5i. Findings pointed to a pseudo-protective effect of triptans versus untreated migraine patients or those potentially older and less healthy patients exposed to prescription NSAIDs or opiates. Triptan users should not be compared with those using other anti-migraine prescriptions when evaluating cardiovascular outcomes in migraine patients. Presence of high cardiovascular risks may contribute to channeling bias-healthier subjects being selected to receive treatment-highlighting the importance of choosing comparators wisely in observational studies.

Project description:PURPOSE:To provide an overview of altmetrics, including their potential benefits and limitations, how they may be obtained, and their role in assessing pharmacoepidemiologic research impact. METHODS:Our review was informed by compiling relevant literature identified through searching multiple health research databases (PubMed, Embase, and CIHNAHL) and grey literature sources (websites, blogs, and reports). We demonstrate how pharmacoepidemiologists, in particular, may use altmetrics to understand scholarly impact and knowledge translation by providing a case study of a drug-safety study conducted by the Canadian Network of Observational Drug Effect Studies. RESULTS:A common approach to measuring research impact is the use of citation-based metrics, such as an article's citation count or a journal's impact factor. "Alternative" metrics, or altmetrics, are increasingly supported as a complementary measure of research uptake in the age of social media. Altmetrics are nontraditional indicators that capture a diverse set of traceable, online research-related artifacts including peer-reviewed publications and other research outputs (software, datasets, blogs, videos, posters, policy documents, presentations, social media posts, wiki entries, etc). CONCLUSION:Compared with traditional citation-based metrics, altmetrics take a more holistic view of research impact, attempting to capture the activity and engagement of both scholarly and nonscholarly communities. Despite the limited theoretical underpinnings, possible commercial influence, potential for gaming and manipulation, and numerous data quality-related issues, altmetrics are promising as a supplement to more traditional citation-based metrics because they can ingest and process a larger set of data points related to the flow and reach of scholarly communication from an expanded pool of stakeholders. Unlike citation-based metrics, altmetrics are not inherently rooted in the research publication process, which includes peer review; it is unclear to what extent they should be used for research evaluation.

Project description:Pediatric populations continue to be understudied in clinical drug trials despite the increasing use of pharmacotherapy in children, particularly with psychotropic drugs. Most pertinent to the clinical selection of drug interventions are trials directly comparing drugs against other drugs. The aim was to measure the prevalence of active drug comparators in neuropsychiatric drug trials in children and identify the effects of funding source on comparator selection. We analyzed the selection of drugs and drug comparisons in clinical trials registered between January 2006 and May 2012. Completed and ongoing interventional trials examining treatments for six neuropsychiatric conditions in children were included. Networks of drug comparisons for each condition were constructed using information about the trial study arms. Of 421 eligible trial registrations, 228 (63,699 participants) were drug trials addressing ADHD (106 trials), autism spectrum disorders (47), unipolar depression (16), seizure disorders (38), migraines and other headaches (15), or schizophrenia (11). Active drug comparators were used in only 11.0% of drug trials while 44.7% used a placebo control and 44.3% no drug or placebo comparator. Even among conditions with well-established pharmacotherapeutic options, almost all drug interventions were compared to a placebo. Active comparisons were more common among trials without industry funding (17% vs. 8%, p=0.04). Trials with industry funding differed from non-industry trials in terms of the drugs studied and the comparators selected. For 73% (61/84) of drugs and 90% (19/21) of unique comparisons, trials were funded exclusively by either industry or non-industry. We found that industry and non-industry differed when choosing comparators and active drug comparators were rare for both groups. This gap in pediatric research activity limits the evidence available to clinicians treating children and suggests a need to reassess the design and funding of pediatric trials in order to optimize the information derived from pediatric participation in clinical trials.

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The importance and implications of comparator selection in pharmacoepidemiologic research.

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The importance and implications of comparator selection in pharmacoepidemiologic research.

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