Kloprogge, Frank, Mwandumba, Henry ORCID: https://orcid.org/0000-0003-4470-3608, Banda, Gertrude, Kamdolozi, Mercy, Shani, Doris, Corbett, Elizabeth L, Kontogianni, Nadia, Ward, Steve ORCID: https://orcid.org/0000-0003-2331-3192, Khoo, Saye H, Davies, Geraint R and Sloan, Derek (2020) 'Longitudinal PKPD biomarkers correlate with treatment outcome in drug sensitive pulmonary tuberculosis; a population pharmacokinetic-pharmacodynamic analysis'. Open Forum Infectious Diseases, Vol 7, Issue 7, ofaa218.
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Abstract
Background
This study aims to explore relationships between baseline demographic covariates, plasma antibiotic exposure, sputum bacillary load and clinical outcome data to help improve future TB treatment response predictions.
Methods
Data were available from a longitudinal cohort study in Malawian drug sensitive TB patients on standard therapy, including steady-state plasma antibiotic exposure (154 patients), sputum bacillary load (102 patients), final outcome (87 patients) and clinical details. Population pharmacokinetic and pharmacokinetic-pharmacodynamic models were developed in the software package NONMEM. Outcome data were analysed using univariate logistic regression and Cox proportional hazard models in R, a free software for statistical computing.
Results
Higher isoniazid exposure correlated with increased bacillary killing in sputum (p<0.01). Bacillary killing in sputum remained fast, with later progression to biphasic decline, in patients with higher rifampicin AUC0-24 (p<0.01). Serial Sputum Colony Counting negativity at month 2 (P<0.05), isoniazid CMAX (p<0.05), isoniazid CMAX/MIC (p<0.01) and isoniazid AUC0-24/MIC (p<0.01) correlated with treatment success but not with remaining free of TB. Slower bacillary killing (P<0.05) and earlier progression to biphasic bacillary decline (p<0.01) both correlate with treatment failure. Post-treatment recurrence only correlated with slower bacillary killing (P<0.05).
Conclusions
Patterns of early bacillary clearance matter. Static measurements such as month 2 sputum conversion and pharmacokinetic parameters such as CMAX/MIC and AUC0-24/MIC were predictive of treatment failure, but modelling of quantitative longitudinal data was required to assess the risk of recurrence. Pooled individual patient data analyses from larger datasets are needed to confirm these findings.
Item Type: | Article |
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Subjects: | QV Pharmacology > Anti-Inflammatory Agents. Anti-Infective Agents. Antineoplastic Agents > QV 268 Antitubercular agents. Antitubercular antibiotics QV Pharmacology > QV 38 Drug action. QW Microbiology and Immunology > Immunity by Type > QW 541 Natural immunity. Immunogenetics QY Clinical Pathology > Diagnostic Tests > QY 120 Sputum WF Respiratory System > Tuberculosis > WF 200 Tuberculosis (General) |
Faculty: Department: | Clinical Sciences & International Health > Clinical Sciences Department Clinical Sciences & International Health > Malawi-Liverpool-Wellcome Programme (MLW) |
Digital Object Identifer (DOI): | https://doi.org/10.1093/ofid/ofaa218 |
Depositing User: | Stacy Murtagh |
Date Deposited: | 22 Jun 2020 09:39 |
Last Modified: | 12 Aug 2020 10:26 |
URI: | https://archive.lstmed.ac.uk/id/eprint/14802 |
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