1. Sample Size Reassessment and Hypothesis Testing in Adaptive Survival Trials
- Author
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Magirr, Dominic, Jaki, Thomas, Koenig, Franz, and Posch, Martin
- Subjects
Drug Research and Development ,Decision Making ,Test Statistics ,Cancer Treatment ,Normal Distribution ,lcsh:Medicine ,Fluid Mechanics ,Research and Analysis Methods ,Continuum Mechanics ,Mathematical and Statistical Techniques ,Cognition ,Medicine and Health Sciences ,Humans ,Clinical Trials ,Statistical Methods ,Clinical Trials (Cancer Treatment) ,lcsh:Science ,Statistical Data ,Pharmacology ,Stochastic Processes ,Clinical Trials as Topic ,Physics ,lcsh:R ,Biology and Life Sciences ,Classical Mechanics ,Fluid Dynamics ,Probability Theory ,Probability Distribution ,Survival Analysis ,Oncology ,Sample Size ,Physical Sciences ,Brownian Motion ,Cognitive Science ,lcsh:Q ,Clinical Medicine ,Safety Studies ,Mathematics ,Statistics (Mathematics) ,Research Article ,Neuroscience ,Follow-Up Studies - Abstract
Mid-study design modifications are becoming increasingly accepted in confirmatory clinical trials, so long as appropriate methods are applied such that error rates are controlled. It is therefore unfortunate that the important case of time-to-event endpoints is not easily handled by the standard theory. We analyze current methods that allow design modifications to be based on the full interim data, i.e., not only the observed event times but also secondary endpoint and safety data from patients who are yet to have an event. We show that the final test statistic may ignore a substantial subset of the observed event times. An alternative test incorporating all event times is found, where a conservative assumption must be made in order to guarantee type I error control. We examine the power of this approach using the example of a clinical trial comparing two cancer therapies.
- Published
- 2016