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The New England Journal of Statistics in Data Science


On Bayesian Sequential Clinical Trial Designs
Volume 2, Issue 1 (2024), pp. 136–151
Pub. online: 31 January 2023      Type: Methodology Article      Open accessOpen Access
Area: Cancer Research
Accepted
24 January 2023
Published
31 January 2023

Abstract

Clinical trials usually involve sequential patient entry. When designing a clinical trial, it is often desirable to include a provision for interim analyses of accumulating data with the potential for stopping the trial early. We review Bayesian sequential clinical trial designs based on posterior probabilities, posterior predictive probabilities, and decision-theoretic frameworks. A pertinent question is whether Bayesian sequential designs need to be adjusted for the planning of interim analyses. We answer this question from three perspectives: a frequentist-oriented perspective, a calibrated Bayesian perspective, and a subjective Bayesian perspective. We also provide new insights into the likelihood principle, which is commonly tied to statistical inference and decision making in sequential clinical trials. Some theoretical results are derived, and numerical studies are conducted to illustrate and assess these designs.

Supplementary material

 Supplementary Material
Supplementary Material to “On Bayesian Sequential Clinical Trial Designs”.

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Keywords
Adaptive design Interim analysis Likelihood principle Multiplicity Optional stopping Sequential hypothesis testing

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