title: Bayesian design of noninferiority trials for medical devices using historical data.
abstract: We develop a new Bayesian approach of sample size determination (SSD) for the design of noninferiority clinical trials. We extend the fitting and sampling priors of Wang and Gelfand (2002, Statistical Science 17, 193-208) to Bayesian SSD with a focus on controlling the type I error and power. Historical data are incorporated via a hierarchical modeling approach as well as the power prior approach of Ibrahim and Chen (2000, Statistical Science 15, 46-60). Various properties of the proposed Bayesian SSD methodology are examined and a simulation-based computational algorithm is developed. The proposed methodology is applied to the design of a noninferiority medical device clinical trial with historical data from previous trials.
authors.affiliation: Department of Statistics, University of Connecticut, 215 Glenbrook Road, Storrs, Connecticut 06269, USA. mhchen@stat.uconn.edu
authors.forename: Ming-Hui
authors.initials: MH
authors.lastname: Chen
authors.forename: Joseph G
authors.initials: JG
authors.lastname: Ibrahim
authors.forename: Peter
authors.initials: P
authors.lastname: Lam
authors.forename: Alan
authors.initials: A
authors.lastname: Yu
authors.forename: Yuanye
authors.initials: Y
authors.lastname: Zhang
mesh_terms: D001499:Bayes Theorem; D001699:Biometry / Q000379:methods; D002986:Clinical Trials as Topic / Q000592:standards*; D003198:Computer Simulation; D003627:Data Interpretation, Statistical; D004864:Equipment and Supplies / Q000592:standards*; D006801:Humans; D015233:Models, Statistical; D012107:Research Design / Q000592:standards*; D018401:Sample Size