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Model-Predicted Impact of ECG Monitoring Strategies During Bedaquiline Treatment

BACKGROUND: The M2 metabolite of bedaquiline causes QT-interval prolongation, making electrocardiogram (ECG) monitoring of patients receiving bedaquiline for drug-resistant tuberculosis necessary. The objective of this study was to determine the relationship between M2 exposure and Fridericia-correc...

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Autores principales: van Beek, Stijn W, Tanneau, Lénaïg, Meintjes, Graeme, Wasserman, Sean, Gandhi, Neel R, Campbell, Angie, Viljoen, Charle A, Wiesner, Lubbe, Aarnoutse, Rob E, Maartens, Gary, Brust, James C M, Svensson, Elin M
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9420883/
https://www.ncbi.nlm.nih.gov/pubmed/36043179
http://dx.doi.org/10.1093/ofid/ofac372
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author van Beek, Stijn W
Tanneau, Lénaïg
Meintjes, Graeme
Wasserman, Sean
Gandhi, Neel R
Campbell, Angie
Viljoen, Charle A
Wiesner, Lubbe
Aarnoutse, Rob E
Maartens, Gary
Brust, James C M
Svensson, Elin M
author_facet van Beek, Stijn W
Tanneau, Lénaïg
Meintjes, Graeme
Wasserman, Sean
Gandhi, Neel R
Campbell, Angie
Viljoen, Charle A
Wiesner, Lubbe
Aarnoutse, Rob E
Maartens, Gary
Brust, James C M
Svensson, Elin M
author_sort van Beek, Stijn W
collection PubMed
description BACKGROUND: The M2 metabolite of bedaquiline causes QT-interval prolongation, making electrocardiogram (ECG) monitoring of patients receiving bedaquiline for drug-resistant tuberculosis necessary. The objective of this study was to determine the relationship between M2 exposure and Fridericia-corrected QT (QTcF)-interval prolongation and to explore suitable ECG monitoring strategies for 6-month bedaquiline treatment. METHODS: Data from the PROBeX study, a prospective observational cohort study, were used to characterize the relationship between M2 exposure and QTcF. Established nonlinear mixed-effects models were fitted to pharmacokinetic and ECG data. In a virtual patient population, QTcF values were simulated for scenarios with and without concomitant clofazimine. ECG monitoring strategies to identify patients who need to interrupt treatment (QTcF > 500 ms) were explored. RESULTS: One hundred seventy patients were included, providing 1131 bedaquiline/M2 plasma concentrations and 1702 QTcF measurements; 2.1% of virtual patients receiving concomitant clofazimine had QTcF > 500 ms at any point during treatment (0.7% without concomitant clofazimine). With monthly monitoring, almost all patients with QTcF > 500 ms were identified by week 12; after week 12, patients were predominantly falsely identified as QTcF > 500 ms due to stochastic measurement error. Following a strategy with monitoring before treatment and at weeks 2, 4, 8, and 12 in simulations with concomitant clofazimine, 93.8% of all patients who should interrupt treatment were identified, and 26.4% of all interruptions were unnecessary (92.1% and 32.2%, respectively, without concomitant clofazimine). CONCLUSIONS: Our simulations enable an informed decision for a suitable ECG monitoring strategy by weighing the risk of missing patients with QTcF > 500 ms and that of interrupting bedaquiline treatment unnecessarily. We propose ECG monitoring before treatment and at weeks 2, 4, 8, and 12 after starting bedaquiline treatment.
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spelling pubmed-94208832022-08-29 Model-Predicted Impact of ECG Monitoring Strategies During Bedaquiline Treatment van Beek, Stijn W Tanneau, Lénaïg Meintjes, Graeme Wasserman, Sean Gandhi, Neel R Campbell, Angie Viljoen, Charle A Wiesner, Lubbe Aarnoutse, Rob E Maartens, Gary Brust, James C M Svensson, Elin M Open Forum Infect Dis Major Article BACKGROUND: The M2 metabolite of bedaquiline causes QT-interval prolongation, making electrocardiogram (ECG) monitoring of patients receiving bedaquiline for drug-resistant tuberculosis necessary. The objective of this study was to determine the relationship between M2 exposure and Fridericia-corrected QT (QTcF)-interval prolongation and to explore suitable ECG monitoring strategies for 6-month bedaquiline treatment. METHODS: Data from the PROBeX study, a prospective observational cohort study, were used to characterize the relationship between M2 exposure and QTcF. Established nonlinear mixed-effects models were fitted to pharmacokinetic and ECG data. In a virtual patient population, QTcF values were simulated for scenarios with and without concomitant clofazimine. ECG monitoring strategies to identify patients who need to interrupt treatment (QTcF > 500 ms) were explored. RESULTS: One hundred seventy patients were included, providing 1131 bedaquiline/M2 plasma concentrations and 1702 QTcF measurements; 2.1% of virtual patients receiving concomitant clofazimine had QTcF > 500 ms at any point during treatment (0.7% without concomitant clofazimine). With monthly monitoring, almost all patients with QTcF > 500 ms were identified by week 12; after week 12, patients were predominantly falsely identified as QTcF > 500 ms due to stochastic measurement error. Following a strategy with monitoring before treatment and at weeks 2, 4, 8, and 12 in simulations with concomitant clofazimine, 93.8% of all patients who should interrupt treatment were identified, and 26.4% of all interruptions were unnecessary (92.1% and 32.2%, respectively, without concomitant clofazimine). CONCLUSIONS: Our simulations enable an informed decision for a suitable ECG monitoring strategy by weighing the risk of missing patients with QTcF > 500 ms and that of interrupting bedaquiline treatment unnecessarily. We propose ECG monitoring before treatment and at weeks 2, 4, 8, and 12 after starting bedaquiline treatment. Oxford University Press 2022-07-27 /pmc/articles/PMC9420883/ /pubmed/36043179 http://dx.doi.org/10.1093/ofid/ofac372 Text en © The Author(s) 2022. Published by Oxford University Press on behalf of Infectious Diseases Society of America. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Major Article
van Beek, Stijn W
Tanneau, Lénaïg
Meintjes, Graeme
Wasserman, Sean
Gandhi, Neel R
Campbell, Angie
Viljoen, Charle A
Wiesner, Lubbe
Aarnoutse, Rob E
Maartens, Gary
Brust, James C M
Svensson, Elin M
Model-Predicted Impact of ECG Monitoring Strategies During Bedaquiline Treatment
title Model-Predicted Impact of ECG Monitoring Strategies During Bedaquiline Treatment
title_full Model-Predicted Impact of ECG Monitoring Strategies During Bedaquiline Treatment
title_fullStr Model-Predicted Impact of ECG Monitoring Strategies During Bedaquiline Treatment
title_full_unstemmed Model-Predicted Impact of ECG Monitoring Strategies During Bedaquiline Treatment
title_short Model-Predicted Impact of ECG Monitoring Strategies During Bedaquiline Treatment
title_sort model-predicted impact of ecg monitoring strategies during bedaquiline treatment
topic Major Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9420883/
https://www.ncbi.nlm.nih.gov/pubmed/36043179
http://dx.doi.org/10.1093/ofid/ofac372
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