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Activity Number: 44
Type: Contributed
Date/Time: Sunday, July 31, 2016 : 2:00 PM to 3:50 PM
Sponsor: Section on Medical Devices and Diagnostics
Abstract #319901
Title: Incorporation of Historical Information in Bayesian Analysis of Crossover Medical Device Clinical Trials
Author(s): Youssef Toubouti* and Xiwei Chen
Companies: Johnson & Johnson Vision Care and Johnson & Johnson Vision Care
Keywords: Bayesian ; Borrowing ; Clinical Trials ; Crossover ; Medical Device ; Power Priors
Abstract:

In medical device, good historical data are often available prior to the start of a study and can be formally incorporated into Bayesian analysis. In this paper, we investigate the use of the power priors (Ibrahim and Chen, 2000) in Bayesian hierarchical models applied to data from crossover trials. Power prior enables historical borrowing by discounting the historical likelihood to a certain power to accommodate heterogeneity between trials. However, in practice, we may be uncertain about the degree to which the historical data will agree with the current study. In such cases, probable values of the power parameter should be determined by the data. Three approaches are presented including those using (i) a hyperprior for the power parameter; (ii) a joint power prior; and (iii) an extended model that directly parameterize the similarity of the current and historical data. How key parameters affect borrowing behavior and key issues involved in each method are demonstrated. Applications of power prior historical borrowing as well as no borrowing are illustrated with real data from a crossover contact lens trial using SAS.


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

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