Abstract
The safety and regulatory needs to detect small drug-induced changes in the QT interval have created many challenges for the design and analysis of “thorough” QT studies. The measurement techniques available, the correlation between the RR interval and the QT interval, and the high variability in the QT interval have made the detection of changes in the QT interval difficult, and the verification of a lack of an effect on the QT interval even more difficult. The purpose of this chapter is to provide statistical and empirical rationales for key elements of study design, and statistical analysis that will control for sources of QT variability and will enhance study sensitivity. We will identify study design and statistical techniques to reduce QT variability, discuss the assumptions inherent in many of the choices available in study design, and recommend study designs based on these principles.
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Hollister, A.S., Montague, T.H. (2005). Statistical Analysis Plans for ECG Data. In: Morganroth, J., Gussak, I. (eds) Cardiac Safety of Noncardiac Drugs. Humana Press. https://doi.org/10.1007/978-1-59259-884-7_14
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DOI: https://doi.org/10.1007/978-1-59259-884-7_14
Publisher Name: Humana Press
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