John G Connolly1, Shirley V Wang1, Candace C Fuller2, Sengwee Toh2, Catherine A Panozzo2, Noelle Cocoros2, Meijia Zhou3,4, Joshua J Gagne1, Judith C Maro2. 1. Division of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School Boston, MA. 2. Department of Population Medicine, Harvard Pilgrim Health Care Institute and Harvard Medical School, Boston, MA. 3. Center for Clinical Epidemiology and Biostatistics, Pereleman School of Medicine at the University of Pennsylvania, Philadelphia, PA. 4. Center for Pharmacoepidemiology Research and Training, University of Pennsylvania Pereleman School of Medicine, Philadelphia, PA.
Abstract
PURPOSE OF REVIEW: An important component of the Food and Drug Administration's Sentinel Initiative is the active post-market risk identification and analysis (ARIA) system, which utilizes semi-automated, parameterized computer programs to implement propensity-score adjusted and self-controlled risk interval designs to conduct targeted surveillance of medical products in the Sentinel Distributed Database. In this manuscript, we review literature relevant to the development of these programs and describe their application within the Sentinel Initiative. RECENT FINDINGS: These quality-checked and publicly available tools have been successfully used to conduct rapid, replicable, and targeted safety analyses of several medical products. In addition to speed and reproducibility, use of semi-automated tools allows investigators to focus on decisions regarding key methodological parameters. We also identified challenges associated with the use of these methods in distributed and prospective datasets like the Sentinel Distributed Database, namely uncertainty regarding the optimal approach to estimating propensity scores in dynamic data among data partners of heterogeneous size. SUMMARY: Future research should focus on the methodological challenges raised by these applications as well as developing new modular programs for targeted surveillance of medical products.
PURPOSE OF REVIEW: An important component of the Food and Drug Administration's Sentinel Initiative is the active post-market risk identification and analysis (ARIA) system, which utilizes semi-automated, parameterized computer programs to implement propensity-score adjusted and self-controlled risk interval designs to conduct targeted surveillance of medical products in the Sentinel Distributed Database. In this manuscript, we review literature relevant to the development of these programs and describe their application within the Sentinel Initiative. RECENT FINDINGS: These quality-checked and publicly available tools have been successfully used to conduct rapid, replicable, and targeted safety analyses of several medical products. In addition to speed and reproducibility, use of semi-automated tools allows investigators to focus on decisions regarding key methodological parameters. We also identified challenges associated with the use of these methods in distributed and prospective datasets like the Sentinel Distributed Database, namely uncertainty regarding the optimal approach to estimating propensity scores in dynamic data among data partners of heterogeneous size. SUMMARY: Future research should focus on the methodological challenges raised by these applications as well as developing new modular programs for targeted surveillance of medical products.
Entities:
Keywords:
ARIA; Sentinel; drug safety; pharmacoepidemiology; surveillance; targeted
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