Abstract

Interim analysis of data accumulated in clinical trials is one aspect of the monitoring of the study progress. It is usually done to assess whether there are significant differences in efficacy between the experimental and control treatment groups, in interruption of a trial is the ethical consideration that subjects should not be exposed to an unsafe, inferior or ineffective treatment. Statistical methods suited for doing interim analysis, that allow to control the probability of incorrectly rejecting the null hypothesis of no treatment differences, are often not well understood by researchers. In this article we present an intuitive, non-mathematical explanation and review of the statistical methods for doing interim analysis in clinical trials along with an illustrative example of the application of the methods on a hypothetical dataset.