Bayesian optimal response-adaptive design for binary responses using stopping rule

Response-adaptive designs are used in phase III clinical trials to allocate a larger number of patients to the better treatment arm. Optimal designs are explored in the recent years in the context of response-adaptive designs, in the frequentist view point only. In the present paper, we propose some...

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Bibliographic Details
Published inStatistical methods in medical research Vol. 27; no. 3; p. 891
Main Authors Komaki, Fumiyasu, Biswas, Atanu
Format Journal Article
LanguageEnglish
Published England 01.03.2018
Subjects
Anti-HIV Agents - therapeutic use
Bayes Theorem
Biostatistics - methods
Clinical Trial Protocols as Topic
Clinical Trials, Phase III as Topic - statistics & numerical data
Computer Simulation
Early Termination of Clinical Trials - statistics & numerical data
Female
HIV Infections - complications
HIV Infections - prevention & control
HIV Infections - transmission
Humans
Infant, Newborn
Infectious Disease Transmission, Vertical - prevention & control
Pregnancy
Pregnancy Complications, Infectious - drug therapy
Zidovudine - therapeutic use
sequential design
Bayesian design
ethics
proportion of allocation
sample size
non-informative prior
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Summary:Response-adaptive designs are used in phase III clinical trials to allocate a larger number of patients to the better treatment arm. Optimal designs are explored in the recent years in the context of response-adaptive designs, in the frequentist view point only. In the present paper, we propose some response-adaptive designs for two treatments based on Bayesian prediction for phase III clinical trials. Some properties are studied and numerically compared with some existing competitors. A real data set is used to illustrate the applicability of the proposed methodology where we redesign the experiment using parameters derived from the data set.
ISSN:1477-0334
DOI:10.1177/0962280216647210