Evaluation of dependent variable, time effect, covariates, and covariation structure in concentration-QTc modeling: A simulation study
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Published on: June 24, 2019
Dalong Patrick Huang1, Shan Xiao2, Qianyu Dang1
1US Food and Drug Administration, Office of Biostatics, Office of Translational Sciences, Center for Drug Evaluation and Research, Silver Spring, MD, USA.
Abstract:
The revised ICH E14 Question and Answer (R3) document issued in December 2015 enables pharmaceutical companies to use concentration-QTc (C-QTc) modeling as the primary analysis for assessing QTc prolongation risk of new drugs. A new approach by including the time effect into the current C-QTc model is introduced. Through a simulation study, we evaluated performances of different C-QTc modeling with different dependent variables, covariates, and covariance structures. This simulation study shows that C-QTc models with ΔQTc being dependent variable without time effect inflate false negative rate and that fitting C-QTc models with different dependent variables, covariates, and covariance structures impacts the control of false negative and false positive rates. Appropriate C-QTc modeling strategies with good control of false negative rate and false positive rate are recommended.
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