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Activity Number: 150 - Lead with Statistics in Medical Device Innovations and Beyond
Type: Topic Contributed
Date/Time: Monday, July 30, 2018 : 10:30 AM to 12:20 PM
Sponsor: Section on Medical Devices and Diagnostics
Abstract #329359 Presentation
Title: Bayesian Approach for Benefit-Risk Assessment with Examples
Author(s): Ram Tiwari*
Companies: Center for Devices and Radiologica Health, FDA
Keywords: Dirichlet Distribution; Dirichlet process; Power Prior; , Model Selection

An important aspect of the drug/device evaluation process is to have an integrated benefit-risk assessment to determine, using some quantitative measures, whether the benefit outweighs the risk for the target population. The subject-level benefit-risk response is a five-category random variable with cell counts following a multinomial distribution. Assuming that the cell probabilities follow a Dirichlet distribution, we develop a Bayesian approach for the longitudinal assessment of benefit-risk using the global measures proposed by Chuang-Stein et al. In a more generalized approach, a power prior is used through the likelihood function to discount the information from previous visits. For the subject-level benefit-risk assessment, the cell-probability of the subject, with respect to a reference category, is modeled, on the logarithmic scale, as a generalized linear model using a Dirichlet process as a prior. The model is applied to drug/device clinical trial datasets.

Authors who are presenting talks have a * after their name.

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