Literature DB >> 22461073

A new statistical decision rule for single-arm phase II oncology trials.

Yiyi Chen1, Zunqiu Chen2, Motomi Mori2.   

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 webpage http://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.
© The Author(s) 2012.

Entities:  

Keywords:  Transitional decision; oncology trials; phase II clinical trials; testing confidence value; “Go/No Go” decision

Mesh:

Year:  2012        PMID: 22461073     DOI: 10.1177/0962280212442584

Source DB:  PubMed          Journal:  Stat Methods Med Res        ISSN: 0962-2802            Impact factor:   3.021


  1 in total

1.  Bayesian probability of success for clinical trials using historical data.

Authors:  Joseph G Ibrahim; Ming-Hui Chen; Mani Lakshminarayanan; Guanghan F Liu; Joseph F Heyse
Journal:  Stat Med       Date:  2014-10-23       Impact factor: 2.373

  1 in total

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