Sample Size Adjustment for Clinical Trial with Multiple

• Activity Number: 606
• Type: Topic Contributed
• Date/Time: Thursday, August 2, 2012 : 8:30 AM to 10:20 AM
• Sponsor: Biopharmaceutical Section
• Author(s): Yi Tsong*+ and Anna Sun and Seung-Ho Kang
• Companies: FDA/CDER and University of Maryland Baltimore County and Yonsei University
• Keywords: Sample size ; multiple comparisons ; thorough QT trials ; QT prolongation testing ; Assay sensitivity test

Abstract

A thorough QT trial is typically designed to test for two sets of hypotheses. The primary set of hypotheses is for demonstrating that the test treatment will not prolong the QT interval. The second set of hypotheses is to demonstrate the assay sensitivity of the positive control treatment in the study population. Both analyses require multiple comparisons by testing the treatment difference measured repeatedly at multiple selected time points. For the prolongation testing, it involves the union-intersection test that leads to the reduction of power of the prolongation test. The assay sensitivity analysis is carried out using the intersection-union test that leads to the inflation of the family-wise type I error rate and requires type I error rate adjustment to control it. The conventional sample size calculation for thorough QT studies are usually based on simulation with a multivariate normal distribution model. These simulation results are limited for generalization to various advanced and adaptive designs of TQT trials. We propose a sample size determination approach using a power equation based on multivariate normal distribution but adjusted for multiple comparisons.