Application of sample size re-estimation within the “promising zone” framework in adaptive design clinical trials

doi:10.3969/j.issn.1006-7795.2025.02.004

Abstract

Abstract: The “promising zone” is a method used to analyze interim data from adaptive design clinical trials in an unblinded state. It allows for the adjustment of sample size based on interim results to enhance the trial's probability of success or minimize investment in unnecessary sample size. Mehta and Pocock proposed rules for increasing sample size based on interim analysis results using the concept of the “promising zone” (MP design). Furthermore, combination of the MP design with group sequential design can set up early stopping boundaries in trials, allowing for a reduction in sample size under favorable or unfavorable zone. The combination test (CT) design further optimizes the framework of the “promising zone”, by considering sample size and conditional power in combination to achieve the highest conditional power with the smallest sample size. This review summarizes the principles of the “promising zone”, introduces the method of determining the “promising zone” and re-estimating sample size, and further illustrates the feasibility of this method in clinical trials with a practical case.

Key words: promising zone, sample size re-estimate, adaptive design, interim analysis, conditional power

CLC Number:

Yang Xiao, Xia Xue, Zhou Quan, Hao Yunyi, Wang Anxin. Application of sample size re-estimation within the “promising zone” framework in adaptive design clinical trials[J]. Journal of Capital Medical University, 2025, 46(2): 197-201.

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