Preservation of Type I error for partially-unblinded sample size re-estimation

Music City Center 

Sample size re-estimation (SSR) at an interim analysis allows for adjustments based on accrued data. Here, we propose an approach that uses partially unblinded SSR methods for binary and continuous outcomes. Although this approach has operational unblinding, its partial use of unblinded information for SSR does not include the interim effect size, hence the term "partially unblinded." Through proof-of-concept and simulation studies, we demonstrate that these adjustments can be made without compromising the Type I error rate. We also investigate different mathematical expressions for SSR under different variance scenarios: homogeneity, heterogeneity and a combination of both. Of particular interest is the third form of dual variance, the use of which for binary outcomes has additional clarifications, and for which we derive an analogous form for continuous outcomes. We show that the corresponding mathematical expressions for the dual variance method are a compromise between those for variance homogeneity and heterogeneity, resulting in sample size estimates that are bounded between those produced by the other expressions, and extend their applicability to adaptive trial design.

Adaptive design

Interim analysis

Sample size adjustment

Type I error preservation

Unequal treatment allocation

Variance heterogeneity 

Biopharmaceutical Section