Blinded sample size recalculation in clinical trials incorporating historical data

Abstract

Recruiting sufficient patients within an acceptable time horizon is an issue for most clinical trials and is especially challenging in the field of rare diseases. It is therefore an attractive option to include historical data from previous (pilot) trials in the current study thus reducing the recruitment burden. In clinical trials with binary endpoint, the required sample size does not only depend on the type I error rate, the power, and the treatment group difference but additionally on the overall event rate. However, there is usually some uncertainty in the planning phase about the value of this nuisance parameter. We present methods for blinded sample size recalculation in the setting of two-arm superiority trials with historical control data where the overall rate is estimated mid-course and the sample size is recalculated accordingly. The operating characteristics of the method are investigated in terms of actual type I error rate, power, and expected sample size. Application is illustrated with a clinical trial example in patients with systemic sclerosis, a rare connective tissue disorder.