The impact of exposure model misspecification on signal detection in prospective pharmacovigilance

摘要

PurposePharmacovigilance monitors the safety of drugs after their approval and marketing. Timely detection of adverse effects is important. The true relationship between time-varying drug use and the adverse event risk is typically unknown. Yet, most current pharmacovigilance studies rely on arbitrarily chosen exposure metrics such as current exposure or use in the past 3months. The authors used simulations to assess the impact of a misspecified exposure model on the timeliness of adverse effect detection.