title: Practical midcourse sample size modification in clinical trials.
abstract: Power calculations are very important in the planning of a well-designed clinical trial. Sometimes there is limited information available before the trial, making it highly desirable to adjust the sample size after seeing actual trial data. Indeed, there has been a recent proliferation of papers promising great flexibility in midcourse correction of sample size and other design features, such as choice of primary endpoint. We point out the difficulty in accurately estimating the treatment effect midway through a trial, and we encourage the use of a simple, conservative approach whereby sample size can be increased but not decreased from what was originally planned. We show how to compute the p value and confidence interval for this two-stage procedure. If the original sample size is maintained, analysis of the data is the same as for a fixed sample procedure.
authors.affiliation: National Heart, Lung, and Blood Institute, Bethesda, MD, USA. ProschaM@nhlbi.nih.gov
authors.forename: Michael A
authors.initials: MA
authors.lastname: Proschan
authors.forename: Qing
authors.initials: Q
authors.lastname: Liu
authors.forename: Sally
authors.initials: S
authors.lastname: Hunsberger
mesh_terms: D001499:Bayes Theorem; D002986:Clinical Trials as Topic / Q000706:statistics & numerical data*; D016001:Confidence Intervals; D003627:Data Interpretation, Statistical; D006801:Humans; D012107:Research Design; D018401:Sample Size