A Novel Bayesian Approach to Assessing the Risk of QT Prolongation

• Activity Number: 62
• Type: Topic Contributed
• Date/Time: Sunday, August 1, 2010 : 4:00 PM to 5:50 PM
• Sponsor: Biopharmaceutical Section
• Author(s): Suraj Anand*+ and Sujit Kumar Ghosh
• Companies: Novartis Pharmaceuticals Corporation and North Carolina State University
• Keywords: TQT study ; ICH E14 ; Bayesian approach ; mean QTc

Abstract

The standard way of analyzing a TQT study is to construct a 90% two-sided confidence interval (CI), for the difference in baseline-corrected mean QTc between drug and placebo at each time point, and to conclude non-inferiority if the upper limit for each CI is less than 10 ms. The intent of the ICH E14 guidelines is to establish that the mean effect of the drug is less than 5 ms and the standard approach may not be well suited to achieve this goal. We propose a Bayesian approach to address this problem, keeping in line with the intent of the ICH E14 guidelines, by directly calculating the probability that the mean effect of the drug is no larger than 5 ms, thereby, providing a direct measure of evidence of whether the drug prolongs mean QTc beyond 5 ms. We assess the performance of our proposed approach using simulated data, discuss its advantages, and illustrate it using a real dataset.