Premium
Approaches to handling data when a phase II trial deviates from the pre‐specified Simon's two‐stage design
Author(s) -
Wu Yujun,
Shih Weichung J.
Publication year - 2008
Publication title -
statistics in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.996
H-Index - 183
eISSN - 1097-0258
pISSN - 0277-6715
DOI - 10.1002/sim.3426
Subject(s) - minimax , computer science , sample size determination , stage (stratigraphy) , sample (material) , event (particle physics) , phase (matter) , research design , statistics , operations research , mathematics , mathematical optimization , paleontology , chemistry , physics , organic chemistry , chromatography , quantum mechanics , biology
Simon's ‘optimal’ and ‘minimax’ two‐stage designs are common methods for conducting phase IIA studies investigating new cancer therapies. However, these designs are rather rigid in their settings because of the pre‐specified rejection rules and fixed sample sizes at each stage. In practice, we often encounter the problem that a study is unable to adhere to the event number and sample sizes of the original two‐stage design. In this paper, we consider some approaches in handling situations where deviations or interruptions from the original Simon's two‐stage design occur because recruitment of patients is slower than expected. We consider four scenarios and use conditional probabilities to address the issues commonly inquired by the scientific review board. We also discuss how to report p ‐values in these situations. Copyright © 2008 John Wiley & Sons, Ltd.