title: Statistical analysis methods for QT/QTc prolongation.
abstract: Prolonged QT interval is associated with life-threatening arrhythmias. Regulatory authorities have paid special attention to investigating the drug-induced delay of cardiac repolarization. Studies aimed at evaluating QT prolongation have become a routine part of safety packages across the pharmaceutical industry. However, the assessment of QT interval prolongation on the surface electrocardiogram is complicated by the fact that many factors influence the duration of the QT interval, among which heart rate plays a predominant role. Some widely used corrections of the QT interval for varying heart rate are known to be inadequate. Many alternatives have been proposed in the literature. Using information obtained from Eli Lilly thorough QT studies, we examine the performance of several approaches to the analysis of QT changes, including subject-specific (individual) QT corrections and model-based QT analysis methods. The simulation results indicate that the mixed-effects modeling approach proposed in this paper is more powerful than the other methods, all of which are commonly used in QT studies.
authors.affiliation: Thousand Oaks, California, USA.
authors.forename: Haijun
authors.initials: H
authors.lastname: Ma
authors.forename: Brian
authors.initials: B
authors.lastname: Smith
authors.forename: Alex
authors.initials: A
authors.lastname: Dmitrienko
mesh_terms: D003627:Data Interpretation, Statistical; D004345:Drug Industry; D004562:Electrocardiography / Q000592:standards*; D017408:Guidelines as Topic; D006339:Heart Rate / Q000187:drug effects / Q000502:physiology; D006801:Humans; D007391:International Cooperation; D008133:Long QT Syndrome / Q000139:chemically induced / Q000175:diagnosis / Q000503:physiopathology; D015233:Models, Statistical; D016032:Randomized Controlled Trials as Topic / Q000706:statistics & numerical data*