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Model-Based Relationship between the Molecular Bacterial Load Assay and Time to Positivity in Liquid Culture
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Pharmaceutical Biosciences.
Univ St Andrews, Sch Med, St Andrews, Fife, Scotland.
East African Hlth Res Commiss, Arusha, Tanzania.
NIMR Mbeya Med Res Ctr, Mbeya, Tanzania.
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2019 (English)In: Antimicrobial Agents and Chemotherapy, ISSN 0066-4804, E-ISSN 1098-6596, Vol. 63, no 10, article id e00652-19Article in journal (Refereed) Published
Abstract [en]

The molecular bacterial load (MBL) assay is a new tuberculosis biomarker which provides results in similar to 4 hours. The relationship between MBL and timeto-positivity (TTP) has not been thoroughly studied, and predictive models do not exist. We aimed to develop a model for MBL and identify the MBL-TTP relationship in patients. The model was developed on data from 105 tuberculosis patients from Malawi, Mozambique, and Tanzania with joint MBL and TTP observations quantified from patient sputum collected for 12 weeks. MBL was quantified using PCR of mycobacterial RNA and TTP using the mycobacterial growth indicator tube (MGIT) 960 system. Treatment consisted of isoniazid, pyrazinamide, and ethambutol in standard doses together with rifampin 10 or 35 mg/kg of body weight. The developed MBLTTP model included several linked submodels, a component describing decline of bacterial load in sputum, another component describing growth in liquid culture, and a hazard model translating bacterial growth into a TIP signal. Additional components for contaminated and negative TIP samples were included. Visual predictive checks performed using the developed model gave good description of the observed data. The model predicted greater total sample loss for TTP than MBL due to contamination and negative samples. The model detected an increase in bacterial killing for 35 versus 10 mg/kg rifampin (P = 0.002). In conclusion, a combined model for MBL and TIP was developed that described the MBL-TIP relationship. The full MBL-TTP model or each submodel was used separately. Second, the model can be used to predict biomarker response for MBL given TTP data or vice versa in historical or future trials.

Place, publisher, year, edition, pages
2019. Vol. 63, no 10, article id e00652-19
Keywords [en]
Mycobacterium tuberculosis, biomarker, mathematical modeling, pharmacodynamics, pharmacometrics, tuberculosis
National Category
Pharmaceutical Sciences
Identifiers
URN: urn:nbn:se:uu:diva-395782DOI: 10.1128/AAC.00652-19ISI: 000487320100053PubMedID: 31358585OAI: oai:DiVA.org:uu-395782DiVA, id: diva2:1366200
Available from: 2019-10-28 Created: 2019-10-28 Last updated: 2019-10-28Bibliographically approved

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Svensson, Robin J.Simonsson, Ulrika S H

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