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Activity Number:
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318
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Type:
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Invited
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Date/Time:
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Wednesday, August 11, 2004 : 10:30 AM to 12:20 PM
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Sponsor:
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Biopharmaceutical Section
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| Abstract - #300019 |
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Title:
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Repeated-measures Models in the Analysis of QT Interval
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Author(s):
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Brian P. Smith*+
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Companies:
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Eli Lilly and Company
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Address:
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Lilly Research Laboratories, Indianapolis, IN, 46285,
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Keywords:
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QT interval ; QT correction ; repeated-measures models
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Abstract:
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Because of the recent regulatory emphasis on issues related to drug-induced cardiac repolarization that can potentially lead to sudden death, the analysis of QT interval has received much attention in the clinical trial literature. The analysis of QT data is complicated by the fact that QT interval is correlated with heart rate and other prognostic factors. Several attempts have been made in the literature to derive an optimal method for correcting QT interval for heart rate. However, obtained QT correction formulas are not universal because of substantial variability observed across different patient populations. It is shown that the widely used fixed QT correction formulas do not provide an adequate fit to QT and RR data and provide bias estimates of treatment effect. The QT correction formulas derived from baseline data in clinical trials are also likely to lead to Type I error rate inflation. We developed a QT interval analysis framework based on repeated-measures models accommodating the correlation between QT interval and heart rate and the correlation among QT measurements collected over time.
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- The address information is for the authors that have a + after their name.
- Authors who are presenting talks have a * after their name.
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