title: Accounting for uncertainty in the historical response rate of the standard treatment in single-arm two-stage designs based on Bayesian power functions.
abstract: In phase II single-arm studies, the response rate of the experimental treatment is typically compared with a fixed target value that should ideally represent the true response rate for the standard of care therapy. Generally, this target value is estimated through previous data, but the inherent variability in the historical response rate is not taken into account. In this paper, we present a Bayesian procedure to construct single-arm two-stage designs that allows to incorporate uncertainty in the response rate of the standard treatment. In both stages, the sample size determination criterion is based on the concepts of conditional and predictive Bayesian power functions. Different kinds of prior distributions, which play different roles in the designs, are introduced, and some guidelines for their elicitation are described. Finally, some numerical results about the performance of the designs are provided and a real data example is illustrated. Copyright © 2016 John Wiley & Sons, Ltd.
authors.affiliation: Statistics Department, Carnegie Mellon University, Pittsburgh (PA), USA.
authors.forename: Francesca
authors.initials: F
authors.lastname: Matano
authors.affiliation: Department of Statistical Sciences, Sapienza University of Rome, Rome, Italy.
authors.forename: Valeria
authors.initials: V
authors.lastname: Sambucini
mesh_terms: D001499:Bayes Theorem; D017322:Clinical Trials, Phase II as Topic / Q000379:methods*; D017408:Guidelines as Topic; D006801:Humans; D012107:Research Design; D035501:Uncertainty
keywords: Bayesian power functions; analysis and design priors; phase II clinical trials; single-arm two-stage designs