Sample Size, Power Calculations, and Their Implications for the Cost of Thorough Studies of Drug Induced QT Interval Prolongation

Abstract

Regulatory authorities require new drugs to be investigated using a so-called "thorough QT/QTc study" to identify compounds with a potential of influencing cardiac repolarization in man. Presently drafted regulatory consensus requires these studies to be powered for the statistical detection of QTc interval changes as small as 5 ms. Since this translates into a noticeable drug development burden, strategies need to be identified allowing the size and thus the cost of thorough QT/QTc studies to be minimized. This study investigated the influence of QT and RR interval data quality and the precision of heart rate correction on the sample sizes of thorough QT/QTc studies. In 57 healthy subjects (26 women, age range 19-42 years), a total of 4,195 drug-free digital electrocardiograms (ECG) were obtained (65-84 ECGs per subject). All ECG parameters were measured manually using the most accurate approach with reconciliation of measurement differences between different cardiologists and aligning the measurements of corresponding ECG patterns. From the data derived in this measurement process, seven different levels of QT/RR data quality were obtained, ranging from the simplest approach of measuring 3 beats in one ECG lead to the most exact approach. Each of these QT/RR data-sets was processed with eight different heart rate corrections ranging from Bazett and Fridericia corrections to the individual QT/RR regression modelling with optimization of QT/RR curvature. For each combination of data quality and heart rate correction, standard deviation of individual mean QTc values and mean of individual standard deviations of QTc values were calculated and used to derive the size of thorough QT/QTc studies with an 80% power to detect 5 ms QTc changes at the significance level of 0.05. Irrespective of data quality and heart rate corrections, the necessary sample sizes of studies based on between-subject comparisons (e.g., parallel studies) are very substantial requiring >140 subjects per group. However, the required study size may be substantially reduced in investigations based on within-subject comparisons (e.g., crossover studies or studies of several parallel groups each crossing over an active treatment with placebo). While simple measurement approaches with ad-hoc heart rate correction still lead to requirements of >150 subjects, the combination of best data quality with most accurate individualized heart rate correction decreases the variability of QTc measurements in each individual very substantially. In the data of this study, the average of standard deviations of QTc values calculated separately in each individual was only 5.2 ms. Such a variability in QTc data translates to only 18 subjects per study group (e.g., the size of a complete one-group crossover study) to detect 5 ms QTc change with an 80% power. Cost calculations show that by involving the most stringent ECG handling and measurement, the cost of a thorough QT/QTc study may be reduced to approximately 25%-30% of the cost imposed by the simple ECG reading (e.g., three complexes in one lead only).