Two-stage designs with small sample sizes

ABSTRACT

When applying group-sequential designs in clinical trials with normally distributed outcomes, approximate critical values are often applied. Here, normally distributed test statistics are assumed which, however, are in fact t-distributed. For small sample sizes, the approximation may lead to a serious inflation of the type I error rate. Recently, a method for computing the exact critical boundaries assuring type I error rate control was proposed and the critical boundaries for Pocock- and O’Brien-Fleming-like group-sequential designs were provided. For designs with one interim analysis, we present six alternative designs, which also control the type I error rate and in addition allow flexible design modifications. We compare the characteristics of these 6 two-stage designs. It is shown that considerable sample size savings can be achieved by including futility stopping and by optimizing the designs. Therefore, for clinical trials with small sample sizes as, for example, in the area of rare diseases, optimal two-stage designs with futility stopping may be a valuable alternative to classical group-sequential designs.

KEYWORDS:

• Adaptive designs
• group-sequential designs
• optimal designs
• rare diseases
• sample size

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This work was supported by the Deutsche Forschungsgemeinschaft (DFG) under Grants KI 708/4-2, KI 708/7-1, and RA 2347/4-2.