Abstract:
:Large health care databases are used extensively for pharmacoepidemiologic studies. Unique methodological issues arise when applying self-controlled designs (i.e., using within-person comparisons) for active surveillance of newly marketed drugs. We use 3 examples to illustrate bias related to population-level exposure time trends when using outcome-indexed self-controlled (i.e., case-crossover) designs for active surveillance and evaluate the ability of the case-time-control design to adjust for bias from population-level exposure time trends. We mimicked active surveillance by conducting sequential analyses after market entry for 3 medications and outcomes (valdecoxib for myocardial infarction (MI), aripiprazole for MI, and telithromycin for acute liver failure) using Medicaid Analytic eXtracts (from all 50 US states, 2000-2006). The case-crossover exposure odds ratio (EOR) in the months immediately following valdecoxib market entry implausibly suggested a 12-fold higher risk of MI during exposed time relative to unexposed time; among age-, sex-, and time-matched controls, the corresponding EOR of 4.5 indicated strong population-level exposure time trends. Over subsequent monitoring periods, case-crossover EORs rapidly dropped to 1.4. Adjustment for bias from population-level exposure time trends with the case-time-control analysis resulted in more consistent associations between valdecoxib and MI across sequential monitoring periods. Similar results were observed in each example. Strong population-level exposure time trends can bias case-crossover studies conducted among "first-wave" users of newly marketed medications. Suggested strategies can help assess and adjust for population-level exposure time trends.
journal_name
Am J Epidemioljournal_title
American journal of epidemiologyauthors
Wang SV,Schneeweiss S,Maclure M,Gagne JJdoi
10.1093/aje/kwu162subject
Has Abstractpub_date
2014-09-15 00:00:00pages
636-44issue
6eissn
0002-9262issn
1476-6256pii
kwu162journal_volume
180pub_type
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