Sample Size Calculations for Crossover Thorough QT Studies: Satisfaction of Regulatory Threshold and Assay Sensitivity

Abstract

The cost for conducting a “thorough QT/QTc study” is substantial and an unsuccessful outcome of the study can be detrimental to the safety profile of the drug, so sample size calculations play a very important role in ensuring adequate power for a thorough QT study. Current literature offers some help in designing such studies, but these methods have limitations and mostly apply only in the context of linear mixed models with compound symmetry covariance structure. It is not evident that such models can satisfactorily be employed to represent all kinds of QTc data, and the existing literature inadequately addresses whether there is a change in sample size and power for more general covariance structures for the linear mixed models. We assess the use of some of the existing methods to design a thorough QT study through data arising from a GlaxoSmithKline (GSK)-conducted thorough QT study, and explore newer models for sample size calculation. We also provide a new method to calculate the sample size required to detect assay sensitivity with adequate power.

Key Words:

• Correlation structure
• ICH E14
• Monte Carlo simulation
• Power and sample size
• QTc prolongation
• Thorough QT/QTc study

Notes

∗Results for hill, steady state, and constant mean difference structures.

∗Results for constant, hill, and steady state mean difference structures.

∗Results for constant, hill, and steady state mean difference structures.

∗Results for constant, hill, and steady state mean difference structures.