A new statistical decision rule for single-arm phase II oncology trials. (February 2016)

• Record Type: Journal Article
• Authors: Chen, Yiyi; Chen, Zunqiu; Mori, Motomi
• Is Part Of: Statistical methods in medical research. Volume 25:Number 1(2016:Feb.)
• Page Start: 118
• Page End: 132
• Publication Date: 2016-02
• Subjects: Transitional decision -- "Go/No Go" decision -- testing confidence value -- phase II clinical trials -- oncology trials; Medicine -- Research -- Statistical methods -- Periodicals; Research -- Periodicals; Review Literature -- Periodicals; Statistics -- methods -- Periodicals; Médecine -- Recherche -- Méthodes statistiques -- Périodiques; 610.727
• DOI: 10.1177/0962280212442584
• Languages: English
• ISSNs: 0962-2802

Abstract

Most single-arm phase II clinical trials compare the efficacy of a new treatment with historical controls through statistical hypothesis testing. One major problem with such a comparison is that the efficacy of the historical control is treated as a known constant, whereas in reality, it is never precisely known. This partially explains why many "Go" decisions made in single-arm phase II trials are shown to be incorrect in phase III trials. In this paper, we propose a new decision rule for an improved transitional decision for single-arm phase II oncology clinical trials with binary endpoints. This new decision rule is jointly based on the p value and a new statistical index named the testing confidence value. The testing confidence value reflects the uncertainty associated with the null value in the hypothesis testing of single-arm trials. Simulations are used to evaluate the operating characteristics of the new decision rule in comparison with the traditional decision rule and a widely used Bayesian decision rule. The application of the new decision rule is illustrated using a clinical trial on marginally resectable pancreatic cancer. A webpagehttp://www.yiyichenbiostatistics.com/TCV.html is available for readers to interactively compute the testing confidence value and to find the suggested decision based on the new decision rule.