LINEARLY DIVERGENT TREATMENT EFFECTS IN CLINICAL-TRIALS WITH REPEATED-MEASURES - EFFICIENT ANALYSIS USING SUMMARY STATISTICS

In many randomized clinical trials with repeated measures of a respons e variable one anticipates a linear divergence over time in the differ ence between treatments, This paper explores how to make an efficient choice of analysis based on individual patient summary statistics. Wit h the objective of estimating the mean rate of treatment divergence th e simplest choice of summary statistic is the regression coefficient o f response on time for each subject (SLOPE). The gains in statistical efficiency imposed by adjusting for the observed pre-treatment levels, or even better the estimated intercepts, are clarified. In the proces s, we develop the optimal linear summary statistic for any repeated me asures design with assumed known covariance structure and shape of tru e mean treatment difference over time. Statistical power consideration s are explored and an example from an asthma trial is used to illustra te the main points. (C) 1997 by John Wiley & Sons, Ltd.