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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...
Autores principales: | , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2022
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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. |
format | Online Article Text |
id | pubmed-9420883 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
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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