Bayesian adaptive two-stage design for determining person-time in Phase II clinical trials with Poisson data. Issue 9 (3rd July 2016)

• Record Type: Journal Article
• Authors: Hand, Austin L.; Scott, John A.; Young, Phil D.; Stamey, James D.; Young, Dean M.
• Is Part Of: Journal of applied statistics. Volume 43:Issue 9(2016)
• Page Start: 1625
• Page End: 1635
• Publication Date: 2016-07-03
• Subjects: Bayesian predictive distribution -- experimental efficacy -- conjugate prior -- count data -- Phase II clinical trials; 62P10 -- 62F15 -- 62F03; Statistics -- Periodicals; 519.5
• DOI: 10.1080/02664763.2015.1117588
• Languages: English
• ISSNs: 0266-4763

Abstract

ABSTRACT: Adaptive clinical trial designs can often improve drug-study efficiency by utilizing data obtained during the course of the trial. We present a novel Bayesian two-stage adaptive design for Phase II clinical trials with Poisson-distributed outcomes that allows for person-observation-time adjustments for early termination due to either futility or efficacy. Our design is motivated by the adaptive trial from [9 ], which uses binomial data. Although many frequentist and Bayesian two-stage adaptive designs for count data have been proposed in the literature, many designs do not allow for person-time adjustments after the first stage. This restriction limits flexibility in the study design. However, our proposed design allows for such flexibility by basing the second-stage person-time on the first-stage observed-count data. We demonstrate the implementation of our Bayesian predictive adaptive two-stage design using a hypothetical Phase II trial of Immune Globulin (Intravenous).