Statistical and Operational Issues Arising in an Interim Analysis When the Study Will Continue
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Copyright 0 1999 Drug Information Association Inc.
STATISTICAL AND OPERATIONAL ISSUES ARISING IN AN INTERIM ANALYSIS WHEN THE STUDY WILL CONTINUE WILLIAM HUSTER,PHD, AARTISHAH,PHD, GARYKAISER,PHD, WILL DERE,MD, AND RICHARD DIMARCHI,PHD Eli Lilly and Company, Indianapolis. Indiana
Guidelines for conducting interim analyses in clinical trials sponsored by thepharmaceutical industry have been recently published (1). Usually, the clinical trial will terminate or the design will change when the interirn analysis shows outstanding efficacy results. There are situations, however; where the interim analysis shows outstanding efficacy results and yet the study continues, for example. when regulatory requirements in the United States and Europe differ concerning study duration. A ca.se study is presented which describes the statistical and operational issues encountered while performing a two-year interim analysis of a three-year registration study when the study was to continue to the three-year timepoint with the same design regardless of the outcome of the interim analysis. The statistician plays a central role in developing and implementing the strategy to effectively resolve these issues. Key Words: Interim analysis; Type I error; Operational bias; Pharmaceutical trial, Statistical adjustment
INTRODUCTION GUIDELINES FOR conducting interim analyses in clinical trials sponsored by the pharmaceutical industry have recently been published (1). Interim analysis is defined in the guidelines using the “blinding test,” which specifies that any analysis, summary, or inspection of unblinded trial data prior to the end of the trial constitutes an interim
Presented at the DIA 34th Annual Meeting “Thinking Globally: Product Development, Registration, and Marketing in the New Millennium,” June 7-11. 1998, Boston, Massachusetts. Reprint address: William J. Huster. PhD. Lilly Corporate Center, DC2244, Eli Lilly and Company, Indianapolis. IN 46285.
analysis. Interim analysis may lead to bias which is defined in this paper as the effect of any factor or combination of factors resulting in inferences which systematically lead to incorrect conclusions about the treatment effect. In particular, interim analysis may lead to inflation of the Type I error rate and to the introduction of operational bias (2). Many papers have been written on methods for controlling the Type I error rate, for example, see Jennison and Turnbull (3) for a review of the literature. Operational bias arises when information from the interim analysis becomes available to those who can influence the study. This type of bias is difficult to measure and must be minimized by the pharmaceutical company (drug sponsor) through the use of standard operating procedures and data monitoring boards.
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W. Hirster, A. Shah. G. Kaiser. W. Dere, and R. DiMorchi
Usually, the clinical trial will terminate or the design will change (eg, open-label extension) when the interim analy
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