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Mixed-effects Poisson regression analysis of adverse event reports: The relationship between antidepressants and suicide

Authors

  • Robert D. Gibbons,

    Corresponding author
    1. Center for Health Statistics, University of Illinois at Chicago, Rooms 455–457 (MC 912), 1601 W. Taylor, Chicago, IL 60612, U.S.A.
    • Center for Health Statistics, University of Illinois at Chicago, 1601 W. Taylor, Chicago, IL 60614, U.S.A.
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  • Eisuke Segawa,

    1. Center for Health Statistics, University of Illinois at Chicago, Rooms 455–457 (MC 912), 1601 W. Taylor, Chicago, IL 60612, U.S.A.
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  • George Karabatsos,

    1. Department of Education, University of Illinois at Chicago, (MC 147), 1040 W. Harrison St., Chicago, IL 60607, U.S.A.
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  • Anup K. Amatya,

    1. Center for Health Statistics, University of Illinois at Chicago, Rooms 455–457 (MC 912), 1601 W. Taylor, Chicago, IL 60612, U.S.A.
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  • Dulal K. Bhaumik,

    1. Center for Health Statistics, University of Illinois at Chicago, Rooms 455–457 (MC 912), 1601 W. Taylor, Chicago, IL 60612, U.S.A.
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  • C. Hendricks Brown,

    1. Center for Health Statistics, University of Illinois at Chicago, Rooms 455–457 (MC 912), 1601 W. Taylor, Chicago, IL 60612, U.S.A.
    2. Prevention Science and Methodology Group, Department of Epidemiology and Biostatistics, College of Public Health MDC-56, University of South Florida, 13201 Bruce B Downs Blvd, Tampa, FL 33612, U.S.A.
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  • Kush Kapur,

    1. Center for Health Statistics, University of Illinois at Chicago, Rooms 455–457 (MC 912), 1601 W. Taylor, Chicago, IL 60612, U.S.A.
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  • Sue M. Marcus,

    1. Center for Health Statistics, University of Illinois at Chicago, Rooms 455–457 (MC 912), 1601 W. Taylor, Chicago, IL 60612, U.S.A.
    2. Department of Psychiatry, Mount Sinai School of Medicine, One Gustave L. Levy Place, P.O. Box 1230, New York, NY 10029, U.S.A.
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  • Kwan Hur,

    1. Center for Health Statistics, University of Illinois at Chicago, Rooms 455–457 (MC 912), 1601 W. Taylor, Chicago, IL 60612, U.S.A.
    2. Cooporate Studies Program Coordinating Center, Hines VA Hospital, Hines, IL 60141, U.S.A.
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  • J. John Mann

    1. Department of Molecular Imaging and Neuropathology, New York State Psychiatric Institute, 1051 Riverside Drive, New York, NY 10032, U.S.A.
    2. Department of Psychiatry, Columbia University College of Physicians & Surgeons, 1051 Riverside Drive, New York, NY 10032, U.S.A.
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Abstract

A new statistical methodology is developed for the analysis of spontaneous adverse event (AE) reports from post-marketing drug surveillance data. The method involves both empirical Bayes (EB) and fully Bayes estimation of rate multipliers for each drug within a class of drugs, for a particular AE, based on a mixed-effects Poisson regression model. Both parametric and semiparametric models for the random-effect distribution are examined. The method is applied to data from Food and Drug Administration (FDA)'s Adverse Event Reporting System (AERS) on the relationship between antidepressants and suicide. We obtain point estimates and 95 per cent confidence (posterior) intervals for the rate multiplier for each drug (e.g. antidepressants), which can be used to determine whether a particular drug has an increased risk of association with a particular AE (e.g. suicide). Confidence (posterior) intervals that do not include 1.0 provide evidence for either significant protective or harmful associations of the drug and the adverse effect. We also examine EB, parametric Bayes, and semiparametric Bayes estimators of the rate multipliers and associated confidence (posterior) intervals. Results of our analysis of the FDA AERS data revealed that newer antidepressants are associated with lower rates of suicide adverse event reports compared with older antidepressants. We recommend improvements to the existing AERS system, which are likely to improve its public health value as an early warning system. Copyright © 2008 John Wiley & Sons, Ltd.

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