Evaluation of the US Food and Drug Administration Sentinel Analysis Tools Using a Comparator with a Different Indication: Comparing the Rates of Gastrointestinal Bleeding in Warfarin and Statin Users
The US Food and Drug Administration’s Sentinel System was established to monitor safety of regulated medical products. Sentinel investigators identified known associations between drugs and adverse events to test reusable analytic tools developed for Sentinel. This test case used a comparator with a different indication.
We tested the ability of Sentinel’s reusable analytic tools to identify the known association between warfarin and gastrointestinal bleeding (GIB). Statins, expected to have no effect on GIB, were the comparator. We further explored the impact of analytic features, including matching ratio and stratifying Cox regression analyses, on matched pairs.
This evaluation included data from 14 Sentinel Data Partners. New users of warfarin and statins, aged 18 years and older, who had not received other anticoagulants or had recent GIB were matched on propensity score using 1:1 and 1:n variable ratio matching, matching statin users with warfarin users to estimate the average treatment effect in warfarin-treated patients. We compared the risk of GIB using Cox proportional hazards regression, following patients for the duration of their observed continuous treatment or until a GIB. For the 1:1 matched cohort, we conducted analyses with and without stratification on matched pair. The variable ratio matched cohort analysis was stratified on the matched set.
We identified 141,398 new users of warfarin and 2,275,694 new users of statins. In analyses stratified on matched pair/set, the hazard ratios (HR) for GIB in warfarin users compared with statin users were 2.78 (95% confidence interval [CI] 2.36–3.28) in the 1:1 matched cohort and 3.10 (95% CI 2.76–3.49) in the variable ratio matched cohort. The HR was lower in the analysis of the 1:1 matched cohort not stratified by matched pair (2.22, 95% CI 1.97–2.49), and highest early in treatment. Follow-up for warfarin users tended to be shorter than for statin users.
This study identified the expected GIB risk with warfarin compared with statins using an analytic tool developed for Sentinel. Our findings suggest that comparators with different indications may be useful in surveillance in select circumstances. Finally, in the presence of differential censoring, stratification by matched pair may reduce the potential for bias in Cox regression analyses.
The authors would like to thank Patrick Archdeacon, MD, for his contributions in planning the study, and Zilu Zhang, MS, for assistance with analyses. The authors would also like to gratefully acknowledge the contributions of the following organizations that provided data used in the analysis: Aetna, Blue Bell, PA; Blue Cross Blue Shield of Massachusetts, Boston, MA; Harvard Pilgrim Health Care Institute, Boston, MA; HealthCore, Inc., Translational Research for Affordability and Quality, Alexandria, VA; HealthPartners Institute (formerly Health Partners Research Foundation), Minneapolis, MN; Humana, Inc., Comprehensive Health Insights, Miramar, FL; Kaiser Permanente Colorado Institute for Health Research, Denver, CO; Kaiser Permanente Center for Health Research Hawai’i, Honolulu, HI; Kaiser Permanente Mid-Atlantic States, Mid-Atlantic Permanente Research Institute, Rockville, MD; Kaiser Permanente Northern California, Division of Research, Oakland, CA; Kaiser Permanente Northwest Center for Health Research, Portland, OR; Kaiser Permanente Washington Health Research Institute (formerly Group Health Research Institute), Seattle, WA; Marshfield Clinic Research Institute, Marshfield, WI; Meyers Primary Care Institute, Worcester, MA; OptumInsight Life Sciences Inc., Boston, MA; Vanderbilt University Medical Center, Department of Health Policy, Nashville, TN, which is indebted to the Tennessee Division of TennCare of the Department of Finance and Administration, which provided data.
Compliance with Ethical Standards
The Sentinel System is sponsored by the US FDA and funded by the FDA through the Department of Health and Human Services (HHS) Contract Number HHSF223201400030I. This study was supported under Mini-Sentinel Contract Numbers HHSF223200910006I/HHSF22301008T.
Conflicts of Interest
Ryan Carnahan, Joshua Gagne, Charles Leonard, Sengwee Toh, Candace Fuller, Sean Hennessy, Laura Hou, Noelle Cocoros, Genna Panucci, Tiffany Woodworth, Austin Cosgrove, Aarthi Iyer, and Elizabeth Chrischilles report no conflicts of interest. Christian Hampp works for the FDA, which funded the study.
- 3.Sentinel Distributed Database and Common Data Model. Available at: https://www.sentinelinitiative.org/sentinel/data/distributed-database-common-data-model. Accessed 19 Nov 2018.
- 4.Sentinel surveillance tools, routine querying system. Available at: https://www.sentinelinitiative.org/sentinel/surveillance-tools/routine-querying-tools/routine-querying-system. Accessed 12 Mar 2018.
- 7.Carnahan RM, Kuntz JL, Wang SV, et al. Evaluation of the US Food and Drug Administration sentinel analysis tools in confirming previously observed drug-outcome associations: the case of clindamycin and Clostridium difficile infection. Pharmacoepidemiol Drug Saf. 2018;27(7):731–9.CrossRefGoogle Scholar
- 8.Iowa Health Fact Book: Alzheimer’s Disease Mortality. Available at: http://iowahealthfactbook.org/factbook/#/aspects/data/Other%20Mortality/Alzheimer’s%20Disease%20Mortality/0. Accessed 24 Jan 2018.
- 10.Johnsen SP, Sorensen HT, Mellemkjoer L, et al. Hospitalisation for upper gastrointestinal bleeding associated with use of oral anticoagulants. Thromb Haemost. 2001;86(2):563–8.Google Scholar
- 20.Huitfeldt A, Hernan MA, Kalager M, Robins JM. Comparative effectiveness research using observational data: active comparators to emulate target trials with inactive comparators. EGEMS (Wash DC). 2016;4(1):1234.Google Scholar
- 37.Binswanger I, Blatchford P, Smiley-Mcdonald H, Ellis C. NDI-DCRP data linking task final report. 2014.Google Scholar