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Implications of Individual QT/RR Profiles-Part 1: Inaccuracies and Problems of Population-Specific QT/Heart Rate Corrections.

A new interesting article has been published in Drug Saf. 2018 Sep 25. doi: 10.1007/s40264-018-0736-1. and titled:

Implications of Individual QT/RR Profiles-Part 1: Inaccuracies and Problems of Population-Specific QT/Heart Rate Corrections.

Authors of this article are:
Malik M Garnett C Hnatkova K Vicente J Johannesen L Stockbridge N.

A summary of the article is shown below:
INTRODUCTION: Universal QT correction formulas are potentially problematic in corrected QT (QTc) interval comparisons at different heart rates. Instead of individual-specific corrections, population-specific corrections are occasionally used based on QT/RR data pooled from all study subjects.OBJECTIVE: To investigate the performance of individual-specific and population-specific corrections, a statistical modeling study was performed using QT/RR data of 523 healthy subjects.METHODS: In each subject, full drug-free QT/RR profiles were available, characterized using non-linear regression models. In each subject, 50 baseline QT/RR readings represented baseline data of standard QT studies. Using these data, linear and log-linear heart rate corrections were optimized for each subject and for different groups of ten and 50 subjects. These corrections were applied in random combinations of heart rate changes between - 10 and + 25 beats per minute (bpm) and known QTc interval changes between - 25 and + 25 ms.RESULTS: Both the subject-specific and population-specific corrections based on the 50 baseline QT/RR readings tended to underestimate/overestimate the QTc interval changes when heart rate was increasing/decreasing, respectively. The result spread was much wider with population-specific corrections, making the estimates of QTc interval changes practically unpredictable.CONCLUSION: Subject-specific heart rate corrections based on limited baseline drug-free data may lead to inconsistent results and, in the presence of underlying heart rate changes, may potentially underestimate or overestimate QTc interval changes. The population-specific corrections lead to results that are much more influenced by the combination of individual QT/RR patterns than by the actual QTc interval changes. Subject-specific heart rate corrections based on full profiles derived from drug-free baseline recordings with wide QT/RR distribution should be used when studying drugs expected to cause heart rate changes.

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