A pharmacometric multistate model for predicting long-term treatment outcomes of patients with pulmonary TB.
Publication year
2024Source
Journal of Antimicrobial Chemotherapy, 79, 10, (2024), pp. 2561-2569ISSN
Publication type
Article / Letter to editor
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Organization
Pulmonary Diseases
Pharmacy
Journal title
Journal of Antimicrobial Chemotherapy
Volume
vol. 79
Issue
iss. 10
Page start
p. 2561
Page end
p. 2569
Subject
Pharmacy - Radboud University Medical Center; Pulmonary Diseases - Radboud University Medical CenterAbstract
BACKGROUND: Studying long-term treatment outcomes of TB is time-consuming and impractical. Early and reliable biomarkers reflecting treatment response and capable of predicting long-term outcomes are urgently needed. OBJECTIVES: To develop a pharmacometric multistate model to evaluate the link between potential predictors and long-term outcomes. METHODS: Data were obtained from two Phase II clinical trials (TMC207-C208 and TMC207-C209) with bedaquiline on top of a multidrug background regimen. Patients were typically followed throughout a 24 week investigational treatment period plus a 96 week follow-up period. A five-state multistate model (active TB, converted, recurrent TB, dropout, and death) was developed to describe observed transitions. Evaluated predictors included patient characteristics, baseline TB disease severity and on-treatment biomarkers. RESULTS: A fast bacterial clearance in the first 2 weeks and low TB bacterial burden at baseline increased probability to achieve conversion, whereas patients with XDR-TB were less likely to reach conversion. Higher estimated mycobacterial load at the end of 24 week treatment increased the probability of recurrence. At 120 weeks, the model predicted 55% (95% prediction interval, 50%-60%), 6.5% (4.2%-9.0%) and 7.5% (5.2%-10%) of patients in converted, recurrent TB and death states, respectively. Simulations predicted a substantial increase of recurrence after 24 weeks in patients with slow bacterial clearance regardless of baseline bacterial burden. CONCLUSIONS: The developed multistate model successfully described TB treatment outcomes. The multistate modelling framework enables prediction of several outcomes simultaneously, and allows mechanistically sound investigation of novel promising predictors. This may help support future biomarker evaluation, clinical trial design and analysis.
This item appears in the following Collection(s)
- Academic publications [246425]
- Electronic publications [134061]
- Faculty of Medical Sciences [93307]
- Open Access publications [107607]
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