Adaptive two-stage test procedures to find the best treatment in clinical trials
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.
Year of publication: |
2005
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Authors: | Bischoff, Wolfgang ; Miller, Frank |
Published in: |
Biometrika. - Biometrika Trust, ISSN 0006-3444. - Vol. 92.2005, 1, p. 197-212
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Publisher: |
Biometrika Trust |
Saved in:
Online Resource
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