Bayesian optimal phase II designs with dual‐criterion decision making

The conventional phase II trial design paradigm is to make the go/no‐go decision based on the hypothesis testing framework. Statistical significance itself alone, however, may not be sufficient to establish that the drug is clinically effective enough to warrant confirmatory phase III trials. We pro...

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Bibliographic Details
Published in:Pharmaceutical statistics : the journal of the pharmaceutical industry 2023-07, Vol.22 (4), p.605-618
Main Authors: Zhao, Yujie, Li, Daniel, Liu, Rong, Yuan, Ying
Format: Article
Language:English
Subjects:
Bayes Theorem
Bayesian adaptive design
Clinical decision making
Clinical Trials, Phase II as Topic
Computer Simulation
Decision Making
go/consider/no‐go decision
Humans
Hypothesis testing
optimal design
phase II trials
Research Design
Sample Size
Statistical significance
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Summary:The conventional phase II trial design paradigm is to make the go/no‐go decision based on the hypothesis testing framework. Statistical significance itself alone, however, may not be sufficient to establish that the drug is clinically effective enough to warrant confirmatory phase III trials. We propose the Bayesian optimal phase II trial design with dual‐criterion decision making (BOP2‐DC), which incorporates both statistical significance and clinical relevance into decision making. Based on the posterior probability that the treatment effect reaches the lower reference value (statistical significance) and the clinically meaningful value (clinical significance), BOP2‐DC allows for go/consider/no‐go decisions, rather than a binary go/no‐go decision. BOP2‐DC is highly flexible and accommodates various types of endpoints, including binary, continuous, time‐to‐event, multiple, and coprimary endpoints, in single‐arm and randomized trials. The decision rule of BOP2‐DC is optimized to maximize the probability of a go decision when the treatment is effective or minimize the expected sample size when the treatment is futile. Simulation studies show that the BOP2‐DC design yields desirable operating characteristics. The software to implement BOP2‐DC is freely available at www.trialdesign.org.
ISSN:1539-1604
1539-1612
DOI:10.1002/pst.2296