JSM 2004 - Toronto

Abstract #300090

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Activity Number: 318
Type: Invited
Date/Time: Wednesday, August 11, 2004 : 10:30 AM to 12:20 PM
Sponsor: Biopharmaceutical Section
Abstract - #300090
Title: Reliable QT Correction for Clinical Studies: The Best Linear Unbiased Predictor (BLUP) Method
Author(s): Daniel C. Park*+ and Kwan R. Lee and Xiwu Lin
Companies: GlaxoSmithKline and GlaxoSmithKline and GlaxoSmithKline
Address: 1250 S. Collegeville Rd, Collegeville, PA, 19426,
Keywords: drug-induced QTc prolongation ; QTc interval ; best linear unbiased predictor (BLUP)
Abstract:

The estimation of QT interval prolongation induced by compounds of pharmacological interest has become very important in the development and safety assessment of every drug. However, reliably identifying QT prolongation has been very difficult because of the strong dependence of the QT interval on heart rate. Many heart rate correction formulas have been proposed since Bazett first introduced his correction formula for the QT interval in 1920. These published formulas, however, are problematic: they fail to remove correlation between the QT interval and heart rate, and they often under- or over-correct the QT interval. To improve on these formulas, both pooled and individually optimized regression methods have been proposed. The pooled methods are not always reliable because they do not account for variations among individuals, and the individual methods are not always practical for use in clinical studies. We propose a powerful and practical approach to correcting the QT interval using the random coefficient regression model. Through simulations, we provide comparisons of this method with other correction methods that are currently being used.

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