Journal
STATISTICS IN MEDICINE
Volume 22, Issue 11, Pages 1787-1805Publisher
JOHN WILEY & SONS LTD
DOI: 10.1002/sim.1311
Keywords
clinical trials; interim analysis; longitudinal data; missing data; repeated measures; sequential methods
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This paper discusses interim analysis for clinical trials where the primary endpoint is observed at a specific long-term follow-up time, but where repeated measures of the same outcome are also taken at earlier times. Methods are considered for improving the efficiency with which the long-term treatment difference is estimated, making use of information from shorter-term follow-up times. This approach to interim analysis has previously been studied for binary endpoints assessed at two time points during follow-up. Here we adapt and extend this methodology to include continuous endpoints assessed at an arbitrary number of follow-up times, making use of methods for analysing multivariate normal data subject to monotone missingness and unstructured mean and covariance relationships. The magnitude of efficiency gains obtained by using short-term measurements is considered, as well as how these gains depend on the number and timing of the short-term measurements. Sequential analysis of treatment differences is discussed, including the extent to which efficiency gains translate into reductions in the expected duration of a sequentially monitored trial. The methods are illustrated on a data set involving a ;placebo-controlled comparison of longitudinal cholesterol measurements. Copyright (C) 2003 John Wiley Sons, Ltd.
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