Statistical characterization of QT prolongation.
The appropriate assessment of QT prolongation remains controversial. We suggest that before the relative merits of various methods can be evaluated, we must state what we assume an assessment of QT prolongation should be about. As a general framework for the assessment of QT prolongation we propose that an assessment of "absolute" or "uncorrected" QT prolongation is properly carried out through a between-treatment (active versus placebo) comparison of the marginal distributions of QT data; an assessment of "heart rate corrected" QT prolongation is carried out through a between-treatment comparison of the conditional distributions of QT data (conditional on RR interval or heart rate). Under this general framework, conditional QT prolongation is, in general, a function of RR interval, and we discuss three possible summary characteristics for that function. We show how current procedures for the assessment of QT prolongation relate to the general approach (that is, to between-treatment contrasts of the marginal and conditional expectation of the QT interval), and to each other. It transpires that only the so-called "one-step procedure" can provide a complete characterization of conditional QT prolongation. We show that the "two-step procedure" with data-driven correction provides an unbiased estimate of expected conditional QT prolongation, which may, from a clinical point of view, be a more satisfactory characteristic than the conventional characteristic, QT prolongation at the reference RR interval. We strongly suggest that two-step procedures with fixed correction be abandoned in the analysis of thorough QT/QTc studies: Fixed correction is either redundant (when a drug has no effect on average RR interval), or systematically biased (when a drug does affect average RR interval).
Schall
Robert
R
Department of Mathematical Statistics and Actuarial Science, University of the Free State, Bloemfontein, South Africa. schallr@ufs.ac.za
Ring
Arne
A
D001145:Arrhythmias, Cardiac / Q000139:chemically induced* / Q000175:diagnosis / Q000503:physiopathology; D002940:Circadian Rhythm; D018592:Cross-Over Studies; D003627:Data Interpretation, Statistical; D004562:Electrocardiography / Q000706:statistics & numerical data; D006339:Heart Rate / Q000187:drug effects*; D006801:Humans; D016014:Linear Models; D015233:Models, Statistical; D016032:Randomized Controlled Trials as Topic / Q000706:statistics & numerical data*; D013997:Time Factors