Which QT Correction Method is Most Consistent?

Abstract

An important aspect of the drug development is the preclinical determination of the effect a drug candidate has on the ECG QT-interval. The QT-interval is the period between the start of the Q-wave and end of the T-wave. This represents the time from the start of ventricular depolarization to the end of ventricular repolarization. A prolonged QT-interval is linked to the arrhythmia risk Torsade de Pointes and is used as a biomarker in preclinical safety pharmacology studies. Determining a compound's arrhythmia risk based on QT-interval prolongation is insufficient as the drug effect can be obscured by the physiological inverse relationship between heart rate and QT-interval. To better elucidate the drug-induced effect on QT-interval, it is standard practice to correct the QT-interval for changes in heart rate. The majority of safety pharmacology studies use telemetry techniques in conscious ambulatory animals. In these studies, a wide range of heart rates occur and correction methods are required regardless of test drug effects on heart rate. Many correction methods have been designed to account for the heart rate effect on QT. Adequacy of QT correction is dependent on the correction method, the species, sex, age, and even on environmental conditions. Historically fixed population QT correction methods are used, such as Bazett's and Fridericia's which rely on set formulas with effectiveness that varies by species. Individual animal correction methods are gaining popularity and are theoretically better to deal with variations in the individual relationship between heart rate and QT-interval. We aim to identify which correction methods are most broadly applicable and introduce the least variability in the corrected QT values. We hypothesize that an individual correction method, that accounts for multiple variables that affect the RR/QT relationship will be the most consistent across individuals, days, and species. To test this hypothesis, we utilized baseline data collected during numerous safety pharmacology assessments and calculated corrected QT values using various methods. The relationship between the corrected QT and heart rate were then compared. For each ECG recording, the correction method resulting in the lowest correlation between the corrected QT and heart rate was identified. A chi-squared test was used to determine which method was the best at reducing the correlation between heart rate and QT interval. We also determined which method produced the lowest variability in the corrected QT values. To do this, the corrected QT values were averaged for the entire recording for each method, and the resulting variabilities were compared. For each ECG recording, the correction method resulting in the lowest variability was determined and a chi-squared test was applied to determine which is most consistent. In conclusion our results demonstrate that individual correction methods are the most consistent, allowing for more accurate comparisons between subjects, species, and dose groups.