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Calculation of Sample Size in Survival Trials: The Impact of Informative Noncompliance

Qi Jiang, Steven Snapinn and Boris Iglewicz
Biometrics
Vol. 60, No. 3 (Sep., 2004), pp. 800-806
Stable URL: http://www.jstor.org/stable/3695403
Page Count: 7
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Calculation of Sample Size in Survival Trials: The Impact of Informative Noncompliance
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Abstract

Sample size calculations for survival trials typically include an adjustment to account for the expected rate of noncompliance, or discontinuation from study medication. Existing sample size methods assume that when patients discontinue, they do so independently of their risk of an endpoint; that is, that noncompliance is noninformative. However, this assumption is not always true, as we illustrate using results from a published clinical trial database. In this article, we introduce a modified version of the method proposed by Lakatos (1988, Biometrics 44, 229-241) that can be used to calculate sample size under informative noncompliance. This method is based on the concept of two subpopulations: one with high rates of endpoint and discontinuation and another with low rates. Using this new method, we show that failure to consider the impact of informative noncompliance can lead to a considerably underpowered study.

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