title: Mixed-effects Poisson regression analysis of adverse event reports: the relationship between antidepressants and suicide.
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.
authors.affiliation: Center for Health Statistics, University of Illinois at Chicago, 1601 W. Taylor, Chicago, IL 60612, U.S.A. rdgib@uic.edu
authors.forename: Robert D
authors.initials: RD
authors.lastname: Gibbons
authors.forename: Eisuke
authors.initials: E
authors.lastname: Segawa
authors.forename: George
authors.initials: G
authors.lastname: Karabatsos
authors.forename: Anup K
authors.initials: AK
authors.lastname: Amatya
authors.forename: Dulal K
authors.initials: DK
authors.lastname: Bhaumik
authors.forename: C Hendricks
authors.initials: CH
authors.lastname: Brown
authors.forename: Kush
authors.initials: K
authors.lastname: Kapur
authors.forename: Sue M
authors.initials: SM
authors.lastname: Marcus
authors.forename: Kwan
authors.initials: K
authors.lastname: Hur
authors.forename: J John
authors.initials: JJ
authors.lastname: Mann
mesh_terms: D000465:Algorithms; D000928:Antidepressive Agents / Q000009:adverse effects* / Q000627:therapeutic use; D019538:Health Care Surveys; D006801:Humans; D016012:Poisson Distribution; D011358:Product Surveillance, Postmarketing / Q000706:statistics & numerical data; D013405:Suicide / Q000523:psychology*
chemical_list: D000928:Antidepressive Agents