Stopping a trial early – and then what? 8/9/12.

Statistics Collaborative, Inc., Washington, DC, USA

This article addresses a problem arising when a trial shows such strong evidence of benefit of the tested intervention that it stops early with an observed effect size for the experimental treatment that is statistically significantly better than the control. Within the classical frequentist framework of group sequential trials, the observed estimated effect size, the associated naïve confidence interval, and the p-value are all biased estimates of the true values. The bias is in the direction of the overestimation of the treatment effect, creation of narrower confidence intervals than appropriate, and a p-value that is too small.

Purpose To discuss methods for correcting the bias in observed effect sizes, confidence intervals, and p-values for trials stopped early and to show the extent to which such correction would have modified the conclusions of the Randomized Aldactone Evaluation Study (RALES). Read More