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Sentinel Modular Program for Propensity Score–Matched Cohort Analyses: Application to Glyburide, Glipizide, and Serious Hypoglycemia

Zhou, Meijiaa; Wang, Shirley V.b; Leonard, Charles E.a; Gagne, Joshua J.b; Fuller, Candacec; Hampp, Christiand; Archdeacon, Patrickd; Toh, Sengweec; Iyer, Aarthic; Woodworth, Tiffany Siuc; Cavagnaro, Elizabethc; Panozzo, Catherine A.c; Axtman, Sophiac; Carnahan, Ryan M.e; Chrischilles, Elizabeth A.e; Hennessy, Seana

doi: 10.1097/EDE.0000000000000709
Methods
Video Abstract

Sentinel is a program sponsored by the US Food and Drug Administration to monitor the safety of medical products. We conducted a cohort assessment to evaluate the ability of the Sentinel Propensity Score Matching Tool to reproduce in an expedited fashion the known association between glyburide (vs. glipizide) and serious hypoglycemia. Thirteen data partners who contribute to the Sentinel Distributed Database participated in this analysis. A pretested and customizable analytic program was run at each individual site. De-identified summary results from each data partner were returned and aggregated at the Sentinel Operations Center. We identified a total of 198,550 and 379,507 new users of glyburide and glipizide, respectively. The incidence of emergency department visits and hospital admissions for serious hypoglycemia was 19 per 1000 person-years (95% confidence interval = 17.9, 19.7) for glyburide users and 22 (21.6, 22.7) for glipizide users. In cohorts matched by propensity score based on predefined variables, the hazard ratio (HR) for glyburide was 1.36 (1.24, 1.49) versus glipizide. In cohorts matched on a high-dimensional propensity score based on empirically selected variables, for which the program ran to completion in five data partners, the HR was 1.49 (1.31, 1.70). In cohorts matched on propensity scores based on both predefined and empirically selected variables via the high-dimensional propensity score algorithm (the same five data partners), the HR was 1.51 (1.32, 1.71). These findings are consistent with the literature, and demonstrate the ability of the Sentinel Propensity Score Matching Tool to reproduce this known association in an expedited fashion.

See video abstract at, http://links.lww.com/EDE/B275.

From the aCenter for Pharmacoepidemiology Research and Training, Center for Clinical Epidemiology and Biostatistics, Department of Biostatistics and Epidemiology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA; bDivision of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA; cDepartment of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA; dCenter for Drug Evaluation and Research, US Food and Drug Administration, Silver Spring, MD; and eDepartment of Epidemiology, College of Public Health, University of Iowa, Iowa City, IA.

Submitted March 22, 2016; accepted June 30, 2017.

Statement about availability of data and code for replication: Sentinel uses a distributed data approach in which data partners (DPs) maintain physical and operational control over electronic health data in their existing environments after transforming their data into a common data model. This analysis utilized the Sentinel distributed database and standardized data querying tools. Code for Sentinel standardized data querying tools, query specifications, and related documentation are shared via the Sentinel website, which allows for transparency and potential replicability of this study on other data sources. Due to its distributed nature, Sentinel generally does not save, maintain, or post individual-level datasets. Sentinel DPs update data at varying intervals and retain a limited number of iterations of their historical data, which may affect replication of this assessment.

The Mini-Sentinel program is funded by the Food and Drug Administration through contract HHSF223200910006I from the US Department of Health and Human Services.

During the conduct of this study, S.V.W. was funded by Agency for Healthcare Research and Quality (AHRQ) grant number R00HS022193, an investigator initiated grant to Brigham and Women’s Hospital from Novartis for unrelated work and contracts to Brigham and Women’s Hospital from Sentinel. S.V.W. is a paid consultant to Aetion, a software company for unrelated work. J.J.G. has received salary support from grants from Novartis Pharmaceuticals Corporation and Eli Lilly and Company to Brigham and Women’s Hospital and is a consultant to Aetion, Inc. and to Optum, Inc., all for unrelated work. J.J.G. has received salary support from contracts to Brigham and Women’s Hospital for work related to Sentinel. The other authors report no conflicts of interest.

Supplemental digital content is available through direct URL citations in the HTML and PDF versions of this article (www.epidem.com).

Correspondence: Sean Hennessy, Department of Biostatistics and Epidemiology, University of Pennsylvania Perelman School of Medicine, 423 Guardian Drive/803 Blockley Hall, Philadelphia, PA 19104. E-mail: hennessy@upenn.edu.

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