Lars Johannesen1, Christine Garnett, Marek Malik. 1. Division of Pharmacometrics, Office of Clinical Pharmacology, Office of Translational Sciences, Center for Drug Evaluation and Research, US FDA, Silver Spring, MD, USA, lars.johannesen@fda.hhs.gov.
Abstract
BACKGROUND: Most drugs with systemic bioavailability have to undergo a thorough QT (TQT) study, which includes a pharmacologic positive control. A set of QTc-quality tests was recently proposed with the possible aim of removing the need for a positive control. OBJECTIVE: We evaluated the influence of QT measurement and QTc computation methodology on the proposed QTc-quality tests. METHODS: The baseline ECG waveforms and fiducial points were retrieved from 34 crossover TQT studies that had full-day baseline ECGs prior to each study period. The QT measurement methodology and recorder type were retrieved from study reports. The influence of QTc computation methodology was investigated by applying the pattern-matching technique and/or using the 10-s average heart rate. RESULTS: There were no statistical differences in any QTc-quality test values between studies using continuous or 10-s bedside recordings and, in a subset of the quality test, an increase of data quality for semi-automatically read studies compared with those manually read (p < 0.01). There was a significant improvement (p < 0.01) in all the QTc-quality test values for QTc measurements obtained by using pattern matching with or without 10-s average heart rate in comparison to the original QTc measurements. CONCLUSION: The findings suggest that QTc quality is mostly driven by the QTc measurement methodology rather than other study-related factors.
BACKGROUND: Most drugs with systemic bioavailability have to undergo a thorough QT (TQT) study, which includes a pharmacologic positive control. A set of QTc-quality tests was recently proposed with the possible aim of removing the need for a positive control. OBJECTIVE: We evaluated the influence of QT measurement and QTc computation methodology on the proposed QTc-quality tests. METHODS: The baseline ECG waveforms and fiducial points were retrieved from 34 crossover TQT studies that had full-day baseline ECGs prior to each study period. The QT measurement methodology and recorder type were retrieved from study reports. The influence of QTc computation methodology was investigated by applying the pattern-matching technique and/or using the 10-s average heart rate. RESULTS: There were no statistical differences in any QTc-quality test values between studies using continuous or 10-s bedside recordings and, in a subset of the quality test, an increase of data quality for semi-automatically read studies compared with those manually read (p < 0.01). There was a significant improvement (p < 0.01) in all the QTc-quality test values for QTc measurements obtained by using pattern matching with or without 10-s average heart rate in comparison to the original QTc measurements. CONCLUSION: The findings suggest that QTc quality is mostly driven by the QTc measurement methodology rather than other study-related factors.
Authors: Katerina Hnatkova; Peter Smetana; Ondrej Toman; Axel Bauer; Georg Schmidt; Marek Malik Journal: Pacing Clin Electrophysiol Date: 2009-01 Impact factor: 1.976
Authors: Katerina Hnatkova; Ondřej Toman; Martina Šišáková; Peter Smetana; Katharina M Huster; Petra Barthel; Tomáš Novotný; Georg Schmidt; Marek Malik Journal: Sci Rep Date: 2019-12-27 Impact factor: 4.379