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Sample Size Reassessment and Hypothesis Testing in Adaptive Survival Trials

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  • Dominic Magirr
  • Thomas Jaki
  • Franz Koenig
  • Martin Posch

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.

Suggested Citation

  • Dominic Magirr & Thomas Jaki & Franz Koenig & Martin Posch, 2016. "Sample Size Reassessment and Hypothesis Testing in Adaptive Survival Trials," PLOS ONE, Public Library of Science, vol. 11(2), pages 1-14, February.
    • Handle: RePEc:plo:pone00:0146465
    DOI: 10.1371/journal.pone.0146465
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    References listed on IDEAS

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    1. Zhiwei Jiang & Ling Wang & Chanjuan Li & Jielai Xia & Hongxia Jia, 2012. "A Practical Simulation Method to Calculate Sample Size of Group Sequential Trials for Time-to-Event Data under Exponential and Weibull Distribution," PLOS ONE, Public Library of Science, vol. 7(9), pages 1-12, September.
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    Cited by:

    1. Nezameddin Faghih & Ebrahim Bonyadi & Lida Sarreshtehdari, 2021. "Comparison of the entrepreneurial motivation in different economic groups," Journal of Global Entrepreneurship Research, Springer;UNESCO Chair in Entrepreneurship, vol. 11(1), pages 29-39, December.

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