Model-predicted impact of ECG monitoring strategies during bedaquiline treatment. van Beek, S. W, Tanneau, L., Meintjes, G., Wasserman, S., Gandhi, N. R, Campbell, A., Viljoen, C. A, Wiesner, L., Aarnoutse, R. E, Maartens, G., Brust, J. C M, & Svensson, E. M Open Forum Infectious Diseases, 9(8):ofac372, jul, 2022. ![Model-predicted impact of ECG monitoring strategies during bedaquiline treatment [link]](https://bibbase.org/img/filetypes/link.svg "link")
Paper doi abstract bibtex Background The M2 metabolite of bedaquiline causes QT-interval prolongation, making 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 six-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 non-linear 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 \textgreater 500 ms) were explored. Results 170 patients were included, providing 1131 bedaquiline/M2 plasma concentrations and 1702 QTcF measurements. 2.1% of virtual patients receiving concomitant clofazimine had QTcF \textgreater 500 ms at any point during treatment (0.7% without concomitant clofazimine). With monthly monitoring, almost all patients with QTcF \textgreater 500 ms were identified by week 12; after week 12, patients were predominantly falsely identified as QTcF \textgreater 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). Conclusion Our simulations enable an informed decision for a suitable ECG monitoring strategy by weighing the risk of missing patients with QTcF \textgreater 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.
@article{VanBeek2022,
abstract = {Background The M2 metabolite of bedaquiline causes QT-interval prolongation, making 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 six-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 non-linear 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 {\textgreater} 500 ms) were explored. Results 170 patients were included, providing 1131 bedaquiline/M2 plasma concentrations and 1702 QTcF measurements. 2.1{\%} of virtual patients receiving concomitant clofazimine had QTcF {\textgreater} 500 ms at any point during treatment (0.7{\%} without concomitant clofazimine). With monthly monitoring, almost all patients with QTcF {\textgreater} 500 ms were identified by week 12; after week 12, patients were predominantly falsely identified as QTcF {\textgreater} 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). Conclusion Our simulations enable an informed decision for a suitable ECG monitoring strategy by weighing the risk of missing patients with QTcF {\textgreater} 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.},
author = {van Beek, Stijn W and Tanneau, L{\'{e}}na{\"{i}}g and Meintjes, Graeme and Wasserman, Sean and Gandhi, Neel R and Campbell, Angie and Viljoen, Charle A and Wiesner, Lubbe and Aarnoutse, Rob E and Maartens, Gary and Brust, James C M and Svensson, Elin M},
doi = {10.1093/OFID/OFAC372},
file = {:C$\backslash$:/Users/01462563/AppData/Local/Mendeley Ltd./Mendeley Desktop/Downloaded/van Beek et al. - 2022 - Model-predicted impact of ECG monitoring strategies during bedaquiline treatment.pdf:pdf},
issn = {2328-8957},
journal = {Open Forum Infectious Diseases},
keywords = {OA,OA{\_}PMC,fund{\_}ack,original},
mendeley-tags = {OA,OA{\_}PMC,fund{\_}ack,original},
month = {jul},
number = {8},
pages = {ofac372},
pmid = {36043179},
title = {{Model-predicted impact of ECG monitoring strategies during bedaquiline treatment}},
url = {https://academic.oup.com/ofid/advance-article/doi/10.1093/ofid/ofac372/6650803},
volume = {9},
year = {2022}
}
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Methods Data from the PROBeX study, a prospective observational cohort study, were used to characterize the relationship between M2 exposure and QTcF. Established non-linear 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 \\textgreater 500 ms) were explored. Results 170 patients were included, providing 1131 bedaquiline/M2 plasma concentrations and 1702 QTcF measurements. 2.1% of virtual patients receiving concomitant clofazimine had QTcF \\textgreater 500 ms at any point during treatment (0.7% without concomitant clofazimine). With monthly monitoring, almost all patients with QTcF \\textgreater 500 ms were identified by week 12; after week 12, patients were predominantly falsely identified as QTcF \\textgreater 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). Conclusion Our simulations enable an informed decision for a suitable ECG monitoring strategy by weighing the risk of missing patients with QTcF \\textgreater 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.","author":[{"propositions":["van"],"lastnames":["Beek"],"firstnames":["Stijn","W"],"suffixes":[]},{"propositions":[],"lastnames":["Tanneau"],"firstnames":["Lénaïg"],"suffixes":[]},{"propositions":[],"lastnames":["Meintjes"],"firstnames":["Graeme"],"suffixes":[]},{"propositions":[],"lastnames":["Wasserman"],"firstnames":["Sean"],"suffixes":[]},{"propositions":[],"lastnames":["Gandhi"],"firstnames":["Neel","R"],"suffixes":[]},{"propositions":[],"lastnames":["Campbell"],"firstnames":["Angie"],"suffixes":[]},{"propositions":[],"lastnames":["Viljoen"],"firstnames":["Charle","A"],"suffixes":[]},{"propositions":[],"lastnames":["Wiesner"],"firstnames":["Lubbe"],"suffixes":[]},{"propositions":[],"lastnames":["Aarnoutse"],"firstnames":["Rob","E"],"suffixes":[]},{"propositions":[],"lastnames":["Maartens"],"firstnames":["Gary"],"suffixes":[]},{"propositions":[],"lastnames":["Brust"],"firstnames":["James","C","M"],"suffixes":[]},{"propositions":[],"lastnames":["Svensson"],"firstnames":["Elin","M"],"suffixes":[]}],"doi":"10.1093/OFID/OFAC372","file":":C$\\$:/Users/01462563/AppData/Local/Mendeley Ltd./Mendeley Desktop/Downloaded/van Beek et al. - 2022 - Model-predicted impact of ECG monitoring strategies during bedaquiline treatment.pdf:pdf","issn":"2328-8957","journal":"Open Forum Infectious Diseases","keywords":"OA,OA_PMC,fund_ack,original","mendeley-tags":"OA,OA_PMC,fund_ack,original","month":"jul","number":"8","pages":"ofac372","pmid":"36043179","title":"Model-predicted impact of ECG monitoring strategies during bedaquiline treatment","url":"https://academic.oup.com/ofid/advance-article/doi/10.1093/ofid/ofac372/6650803","volume":"9","year":"2022","bibtex":"@article{VanBeek2022,\r\nabstract = {Background The M2 metabolite of bedaquiline causes QT-interval prolongation, making 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 six-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 non-linear 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 {\\textgreater} 500 ms) were explored. Results 170 patients were included, providing 1131 bedaquiline/M2 plasma concentrations and 1702 QTcF measurements. 2.1{\\%} of virtual patients receiving concomitant clofazimine had QTcF {\\textgreater} 500 ms at any point during treatment (0.7{\\%} without concomitant clofazimine). With monthly monitoring, almost all patients with QTcF {\\textgreater} 500 ms were identified by week 12; after week 12, patients were predominantly falsely identified as QTcF {\\textgreater} 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). Conclusion Our simulations enable an informed decision for a suitable ECG monitoring strategy by weighing the risk of missing patients with QTcF {\\textgreater} 500 ms and that of interrupting bedaquiline treatment unnecessarily. 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