Sample size requirements in trials using repeated measurements and the impact of trial design.

<bold>Objective: </bold>Sample size calculations for clinical trials generally use expected changes between groups, and variances obtained from the literature. However, this approach neglects the impact of differences in trial design. We studied the effects of variations in trial design on the required sample size. <bold>Methods: </bold>Data were used from the METEOR (Measuring Effects on Intima-Media Thickness: an Evaluation of Rosuvastatin) trial in which carotid intima-media thickness (CIMT) measurements were performed twice at baseline, at 6, 12 and 18 months, and twice at the end of 2-year study treatment. A sample size formula for continuous outcome measures that incorporates between- and within-individual variance components was used to evaluate the impact of differences in the length of follow-up, and the number of CIMT examinations. <bold>Results: </bold>Trial designs with a shorter duration of follow-up have increased within-individual variance and require larger sample sizes to detect the same treatment effect. Reduction in the number of examinations within a trial with a given duration, i.e. by using single rather than duplicate baseline and end-of-study scans or by not performing intermediate scans, also increased the required sample size to maintain the same power. <bold>Conclusion: </bold>A longer trial duration and/or more frequent examinations within a trial which has repeated measures of an outcome variable substantially increase study power and reduce the required sample size. In situations where the costs of recruiting, retaining and examining individual participants are known, the sample size, study length and number of examinations can be balanced to optimize the trial design relative to costs or other study objectives. [ABSTRACT FROM AUTHOR]