Sample Size Calculations in Thorough QT Studies

Abstract

An analysis of QTc data collected in four thorough QT studies conducted at Eli Lilly and Company was performed to estimate the variability of the QTc interval and to calculate the variance components related to time-to-time, day-to-day variability, etc. The results were used to develop a sample size calculation framework that enables clinical trial researchers to account for key features of their thorough QT studies, including study design (parallel and crossover designs), number of ECG replicates, number of post-baseline ECG recordings, and subject population (based on subject gender and age). The sample size calculation framework is illustrated using several popular study designs.

Key Words:

• QT interval
• Sample size
• Thorough QT study
• Variability

ACKNOWLEDGMENTS

The authors would like to thank Dr. Craig Mallinckrodt, of Eli Lilly and Company, for his careful review of this manuscript and his helpful comments. The authors would also like to thank Dr. Jingyuan Wang and Ms. Grace Li, of Eli Lilly and Company, for data support and helpful comments.

Notes

∗Based on the variance components shown in Table 3.

^∗∗Based on the variance components shown in Table 2.

Note: The treatment difference between the test drug and placebo is defined as follows: Definition A1, the direct comparison at t _k ; Definition A2, the comparison based on change from the pre-dose time point t ₀ to post-dose time point t _k ; Definition B1, the comparison based on a time-matched difference between t _k on Day 0 and t _k on Day 1; Definition B2, the comparison based on a two-stage structure: the change from t ₀ to t _k on Days 0 and 1 is computed first, and then the difference between them is calculated.

Note: The treatment difference between the test drug and placebo is defined as follows: Definition A1, the direct comparison at t _k ; Definition A2, the comparison based on change from the pre-dose time point t ₀ to post-dose time point t _k ; Definition B1, the comparison based on a time-matched difference between t _k on Day 0 and t _k on Day 1; Definition B2, the comparison based on a two-stage structure: the change from t ₀ to t _k on Days 0 and 1 is computed first, and then the difference between them is calculated.

Note: The treatment difference between the test drug and placebo is defined as follows: Definition A1, the direct comparison at t _k ; Definition A2, the comparison based on change from the pre-dose time point t ₀ to post-dose time point t _k ; Definition B1, the comparison based on a time-matched the difference between t _k on Day 0 and t _k on Day 1; Definition B2, the comparison based on a two-stage structure: the change from t ₀ to t _k on Days 0 and 1 is computed first and then difference between them is calculated. The configuration of true mean treatment differences is defined as follows: Configuration 1, the treatment effect is constant over time; Configuration 2, the treatment effect is present only at one time point; Configuration 3, the treatment effect increases and decreases over time.

Note: The treatment difference between the test drug and placebo is defined as follows: Definition D1, the comparison based on a time-matched difference between t _k on Day 0 and t _k on Day d; Definition D2, the comparison based on a two-stage structure: the change from t ₀ to t _k on Days 0 and d is computed first and then the difference between them is calculated. The configuration of true mean treatment differences is defined as follows: Configuration 1, the treatment effect is constant over time; Configuration 2, the treatment effect is present only at one time point; Configuration 3, the treatment effect increases and decreases over time.