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Adaptive two-stage test procedures to find the best treatment in clinical trials

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  • Wolfgang Bischoff
  • Frank Miller

Abstract

A main objective in clinical trials is to find the best treatment in a given finite class of competing treatments and then to show superiority of this treatment against a control treatment. The traditional procedure estimates the best treatment in a first trial. Then in an independent second trial superiority of this treatment, estimated as best in the first trial, is to be shown against the control treatment by a size α test. In this paper we investigate these two trials of this traditional procedure as a two-stage test procedure. Additionally we introduce competing two-stage group-sequential test procedures. Then we derive formulae for the expected number of patients. These formulae depend on unknown parameters. When we have a prior for the unknown parameters we can determine the two-stage test procedure of size α and power β that is optimal, in that it needs a minimal number of observations. The results are illustrated by a numerical example, which indicates the superiority of the group-sequential procedures. Copyright 2005, Oxford University Press.

Suggested Citation

  • Wolfgang Bischoff & Frank Miller, 2005. "Adaptive two-stage test procedures to find the best treatment in clinical trials," Biometrika, Biometrika Trust, vol. 92(1), pages 197-212, March.
    • Handle: RePEc:oup:biomet:v:92:y:2005:i:1:p:197-212
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    File URL: http://hdl.handle.net/10.1093/biomet/92.1.197
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    Cited by:

    1. Ying Kuen Cheung, 2008. "Simple Sequential Boundaries for Treatment Selection in Multi‐Armed Randomized Clinical Trials with a Control," Biometrics, The International Biometric Society, vol. 64(3), pages 940-949, September.

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