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Interim analysis of continuous long‐term endpoints in clinical trials with longitudinal outcomes
Author(s) -
Galbraith Sally,
Marschner Ian C.
Publication year - 2003
Publication title -
statistics in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.996
H-Index - 183
eISSN - 1097-0258
pISSN - 0277-6715
DOI - 10.1002/sim.1311
Subject(s) - interim analysis , interim , time point , term (time) , statistics , covariance , multivariate statistics , missing data , clinical trial , econometrics , clinical endpoint , mathematics , computer science , medicine , philosophy , physics , archaeology , quantum mechanics , history , aesthetics
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 © 2003 John Wiley & Sons, Ltd.