An alternative to traditional sample size determination for small patient populations

The majority of phase III clinical trials use a 2-arm randomized controlled trial with 50% allocation between the control treatment and experimental treatment. The sample size calculated for these clinical trials normally guarantee a power of at least 80% for a certain type I error, usually 5%. However, these sample size calculations, do not typically take into account the total patient population that may benefit from the treatment investigated.

In this paper, we discuss two methods, which optimize the sample size of phase III clinical trial designs, to maximize the benefit to patients for the total patient population. We do this for trials that use a continuous endpoint, when the total patient population is small (i.e. for rare diseases). One approach uses a point estimate for the treatment effect to optimize the sample size and the second uses a distribution on the treatment effect in order to account for the uncertainty in the estimated treatment effect. Both one-stage and two-stage clinical trials, using three different stopping boundaries are investigated and compared, using efficacy and ethical measures.

A completed clinical trial in patients with anti-neutrophil cytoplasmic antibody (ANCA)-associated vasculitis is used to demonstrate the use of the method.