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Bayesian Design of Superiority Trials: Methods and Applications.

Wenlin YuanMing-Hui ChenJohn Zhong
Published in: Statistics in biopharmaceutical research (2022)
In this paper, we lay out the basic elements of Bayesian sample size determination (SSD) for the Bayesian design of a two-arm superiority clinical trial. We develop a flowchart of the Bayesian SSD that highlights the critical components of a Bayesian design and provides a practically useful roadmap for designing a Bayesian clinical trial in real world applications. We empirically examine the amount of borrowing, the choice of noninformative priors, and the impact of model misspecification on the Bayesian type I error and power. A formal and statistically rigorous formulation of conditional borrowing within the decision rule framework is developed. Moreover, by extending the partial borrowing power priors, a new borrowing-by-parts power prior for incorporating historical data is proposed. Computational algorithms are also developed to calculate the Bayesian type I error and power. Extensive simulation studies are carried out to explore the operating characteristics of the proposed Bayesian design of a superiority trial.
Keyphrases
  • clinical trial
  • randomized controlled trial
  • study protocol
  • phase ii
  • phase iii
  • machine learning
  • high resolution
  • artificial intelligence
  • open label