Data-dependent interim analyses are a useful tool in confirmatory Phase III or IV clinical research. In particular, redesigning the sample size in an interim analysis based on the results observed to date considerably improves the power of the trial since the best available information at the time is used for the sample size adjustment. In recent years, several methods were proposed that enable a flexible design through the use of adaptive interim analyses while maintaining the type I error rate. In this article, these methods are briefly reviewed. We recommend a strategy that copes well with the demands of practice. Examples illustrate the use of multistage adaptive designs that make it possible to calculate confidence intervals and bias adjusted point estimates.
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