JSM 2004 - Toronto

Abstract #301071

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Activity Number: 333
Type: Topic Contributed
Date/Time: Wednesday, August 11, 2004 : 10:30 AM to 12:20 PM
Sponsor: Section on Bayesian Statistical Science
Abstract - #301071
Title: Bayesian Screening Tool for Clinical Safety Data
Author(s): Jayanti Gupta*+ and Saurabh Mukhopadhyay
Companies: Merck & Co., Inc. and Merck & Co., Inc.
Address: , Rahway, NJ, 07065,
Keywords: Bayesian ; clinical trials ; hierarchical models
Abstract:

Developing a unified screening tool to compare adverse experiences among treatment groups that occur in clinical trials is of considerable interest. Since Aes occur within body systems, it is also of interest to see if particular body systems are of more concern than others with respect to the treatments being tested. Bayesian hierarchical mixed models in the manner outlined by Berry (2002) holds promise, as it accommodates simultaneous estimation of several Aes occurring in the same body system. However, different choices of model development exist and their relative long-term performance needs to be examined. Different choices of hierarchical models will be studied through simulations, and methods will be proposed to provide consistent and long-term support to analyze safety data.

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