A Decision Rule for Evaluating Several Independent Clinical Trials Collectively

Usually, in applying for market approval of a new drug, more than one similarly designed clinical trial is conducted to support efficacy claims. How to evaluate these trials collectively and assess the overall type I error of a decision rule can be a challenging statistical issue. In this paper, we...

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Bibliographic Details
Published in:Journal of biopharmaceutical statistics 2003-11, Vol.13 (4), p.621-628
Main Authors: Li, Qian H., Huque, Mohammad F.
Format: Article
Language:English
Subjects:
Clinical trials
Clinical Trials as Topic - methods
Clinical Trials as Topic - statistics & numerical data
Decision rules
Decision Support Techniques
Multiplicity
Overall hypotheses
Overall type I error
p-Value cut points
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Summary:Usually, in applying for market approval of a new drug, more than one similarly designed clinical trial is conducted to support efficacy claims. How to evaluate these trials collectively and assess the overall type I error of a decision rule can be a challenging statistical issue. In this paper, we propose a decision rule to collectively evaluate p-values from several similarly designed and independently conducted trials. A concept of overall hypotheses, which is essentially union or intersection combinations of individual trials' hypotheses, is used so that the overall type I error can be controlled at desired levels. We also discuss some important properties of the approach, including the selection of the overall type I error rates and power. Examples are presented.
ISSN:1054-3406
1520-5711
DOI:10.1081/BIP-120024198