title: Extended likelihood ratio test-based methods for signal detection in a drug class with application to FDA's adverse event reporting system database.
abstract: A likelihood ratio test, recently developed for the detection of signals of adverse events for a drug of interest in the FDA Adverse Events Reporting System database, is extended to detect signals of adverse events simultaneously for all the drugs in a drug class. The extended likelihood ratio test methods, based on Poisson model (Ext-LRT) and zero-inflated Poisson model (Ext-ZIP-LRT), are discussed and are analytically shown, like the likelihood ratio test method, to control the type-I error and false discovery rate. Simulation studies are performed to evaluate the performance characteristics of Ext-LRT and Ext-ZIP-LRT. The proposed methods are applied to the Gadolinium drug class in FAERS database. An in-house likelihood ratio test tool, incorporating the Ext-LRT methodology, is being developed in the Food and Drug Administration.
authors.affiliation: 1 Division of Biometrics VII, Office of Biostatistics, MD, USA.
authors.forename: Yueqin
authors.initials: Y
authors.lastname: Zhao
authors.affiliation: 2 Department of Statistics, University of Missouri, Columbia, MO,USA.
authors.forename: Min
authors.initials: M
authors.lastname: Yi
authors.affiliation: 3 Office of Biostatistics, MD, USA.
authors.forename: Ram C
authors.initials: RC
authors.lastname: Tiwari
mesh_terms: D016907:Adverse Drug Reaction Reporting Systems / Q000706:statistics & numerical data*; D056808:Biostatistics / Q000379:methods; D003198:Computer Simulation; D062313:Databases, Pharmaceutical / Q000706:statistics & numerical data; D064420:Drug-Related Side Effects and Adverse Reactions; D006801:Humans; D016013:Likelihood Functions; D016012:Poisson Distribution; D059629:Signal-To-Noise Ratio; D014481:United States; D014486:United States Food and Drug Administration
keywords: Likelihood ratio; false discovery rate; sensitivity; zero-inflated Poisson