gms | German Medical Science

In the planning phase of a clinical trial with counts as primary outcomes, such as relapses in Multiple Sclerosis (MS), there is uncertainty with regard to the nuisance parameters (e.g. overall event rate, the dispersion parameter) which need to be specified for sample size estimation. For this reason the application of adaptive designs with blinded sample size reestimation (BSSR) are attractive (Cook et al. 2009 [1], Friede and Schmidli 2010 [2]). After a comparison of existing methods we consider in this presentation a modified version of the maximum likelihood method for BSSR for negative binomial data proposed by Friede and Schmidli (2010) [3]. The method works well in terms of sample size distribution and power, if the assumed clinically effect is equal to the true effect. We compare the BSSR approach to an unblinded procedure in situations where an uncertainty about the assumed effect size exists. For practically relevant scenarios we make recommendations when application of the blinded or unblinded procedure are indicated. In addition, results for unbalanced designs previously not considered are shown in a simulation study. The methods are illustrated by a study in Relapsing Remitting MS.