Motivating sample sizes in adaptive Phase I trials via Bayesian posterior credible intervals.

ABSTRACT: In contrast with typical Phase III clinical trials, there is little existing methodology for determining the appropriate numbers of patients to enroll in adaptive Phase I trials. And, as stated by Dennis Lindley in a more general context, "[t]he simple practical question of 'What size of sample should I take' is often posed to a statistician, and it is a question that is embarrassingly difficult to answer." Historically, simulation has been the primary option for determining sample sizes for adaptive Phase I trials, and although useful, can be problematic and time-consuming when a sample size is needed relatively quickly. We propose a computationally fast and simple approach that uses Beta distributions to approximate the posterior distributions of DLT rates of each dose and determines an

SUBMITTER: Braun TM 

PROVIDER: S-EPMC9109046 | biostudies-literature | 2018 Sep

REPOSITORIES: biostudies-literature