Accounting for Pilot Study Uncertainty in Sample Size Determination of Randomized Controlled Trials. (3rd April 2021)

• Record Type: Journal Article
• Authors: Shi, Yaru; Liu, Fang; Li, Se; Chen, Jie
• Is Part Of: Statistics in biopharmaceutical research. Volume 13:Number 2(2021)
• Page Start: 192
• Page End: 202
• Publication Date: 2021-04-03
• Subjects: Effect size -- Expected power -- Minimum total sample size -- Pilot studies -- Sampling variability -- Total cost; Pharmacy -- Statistical methods -- Periodicals; Pharmaceutical biotechnology -- Statistical methods -- Periodicals; Biopharmaceutics -- Periodicals; Biometry -- Periodicals; Pharmacy -- Statistical methods; Periodicals; 615.190727
• DOI: 10.1080/19466315.2020.1831951
• Languages: English
• ISSNs: 1946-6315

Abstract

Abstract: A confirmatory randomized controlled trial can be severely underpowered if the variability and/or effect size estimated from a small-scale pilot study is not taken into account in the sample size calculation. This article reviews and summarizes four existing methods and proposes five new approaches, namely a tolerance probability (TP) based approach and four expected power (EP) based approaches. While the TP-based approach takes into account only sampling variability, the four EP-based approaches incorporate both sampling variability and effect size estimates from external pilot studies. Formulas for power and sample size determination of the proposed approaches are first derived for normally distributed response variables and then extended to binary and time-to-event outcome variables. Simulations are conducted to compare the performance of the proposed methods with two existing methods in terms of sample size inflation and total costs (assuming a fixed cost ratio per subject between external pilot and confirmatory trials). The proposed methods are illustrated in two examples, one with binary endpoint and another with time-to-event endpoint, in terms of study sample size and power. Finally, some recommendations are made based on the degree of uncertainty of sampling variance and effect size and the performance of the methods.