Dataset Information

Plasma concentrations of second-line antituberculosis drugs in relation to minimum inhibitory concentrations in multidrug-resistant tuberculosis patients in China: a study protocol of a prospective observational cohort study.

ABSTRACT: INTRODUCTION:Individualised treatment through therapeutic drug monitoring (TDM) may improve tuberculosis (TB) treatment outcomes but is not routinely implemented. Prospective clinical studies of drug exposure and minimum inhibitory concentrations (MICs) in multidrug-resistant TB (MDR-TB) are scarce. This translational study aims to characterise the area under the concentration-time curve of individual MDR-TB drugs, divided by the MIC for Mycobacterium tuberculosis isolates, to explore associations with markers of treatment progress and to develop useful strategies for clinical implementation of TDM in MDR-TB. METHODS AND ANALYSIS:Adult patients with pulmonary MDR-TB treated in Xiamen, China, are included. Plasma samples for measure of drug exposure are obtained at 0, 1, 2, 4, 6, 8 and 10 hours after drug intake at week 2 and at 0, 4 and 6 hours during weeks 4 and 8. Sputum samples for evaluating time to culture positivity and MIC determination are collected at days 0, 2 and 7 and at weeks 2, 4, 8 and 12 after treatment initiation. Disease severity are assessed with a clinical scoring tool (TBscore II) and quality of life evaluated using EQ-5D-5L. Drug concentrations of pyrazinamide, ethambutol, levofloxacin, moxifloxacin, cycloserine, prothionamide and para-aminosalicylate are measured by liquid chromatography tandem-mass spectrometry and the levels of amikacin measured by immunoassay. Dried blood spot on filter paper, to facilitate blood sampling for analysis of drug concentrations, is also evaluated. The MICs of the drugs listed above are determined using custom-made broth microdilution plates and MYCOTB plates with Middlebrook 7H9 media. MIC determination of pyrazinamide is performed in BACTEC MGIT 960. ETHICS AND DISSEMINATION:This study has been approved by the ethical review boards of Karolinska Institutet, Sweden and Fudan University, China. Informed written consent is given by participants. The study results will be submitted to a peer-reviewed journal. TRIAL REGISTRATION NUMBER:NCT02816931; Pre-results.

SUBMITTER: Davies Forsman L

PROVIDER: S-EPMC6173237 | biostudies-literature | 2018 Oct

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Plasma concentrations of second-line antituberculosis drugs in relation to minimum inhibitory concentrations in multidrug-resistant tuberculosis patients in China: a study protocol of a prospective observational cohort study.

Davies Forsman Lina L Niward Katarina K Hu Yi Y Zheng Rongrong R Zheng Xubin X Ke Ran R Cai Weiping W Hong Chao C Li Yang Y Gao Yazhou Y Werngren Jim J Paues Jakob J Kuhlin Johanna J Simonsson Ulrika S H USH Eliasson Erik E Alffenaar Jan-Willem JW Mansjö Mikael M Hoffner Sven S Xu Biao B Schön Thomas T Bruchfeld Judith J

BMJ open 20181004 9

<h4>Introduction</h4>Individualised treatment through therapeutic drug monitoring (TDM) may improve tuberculosis (TB) treatment outcomes but is not routinely implemented. Prospective clinical studies of drug exposure and minimum inhibitory concentrations (MICs) in multidrug-resistant TB (MDR-TB) are scarce. This translational study aims to characterise the area under the concentration-time curve of individual MDR-TB drugs, divided by the MIC for <i>Mycobacterium tuberculosis</i> isolates, to exp ...[more]

PMID: 30287613

Similar Datasets

Project description:Lopinavir-ritonavir forms the backbone of current first-line antiretroviral regimens in young HIV-infected children. As multidrug-resistant (MDR) tuberculosis (TB) frequently occurs in young children in high-burden TB settings, it is important to identify potential interactions between MDR-TB treatment and lopinavir-ritonavir. We describe the pharmacokinetics of and potential drug-drug interactions between lopinavir-ritonavir and drugs routinely used for MDR-TB treatment in HIV-infected children. A combined population pharmacokinetic model was developed to jointly describe the pharmacokinetics of lopinavir and ritonavir in 32 HIV-infected children (16 with MDR-TB receiving treatment with combinations of high-dose isoniazid, pyrazinamide, ethambutol, ethionamide, terizidone, a fluoroquinolone, and amikacin and 16 without TB) who were established on a lopinavir-ritonavir-containing antiretroviral regimen. One-compartment models with first-order absorption and elimination for both lopinavir and ritonavir were combined into an integrated model. The dynamic inhibitory effect of the ritonavir concentration on lopinavir clearance was described using a maximum inhibition model. Even after adjustment for the effect of body weight with allometric scaling, a large variability in lopinavir and ritonavir exposure, together with strong correlations between the pharmacokinetic parameters of lopinavir and ritonavir, was detected. MDR-TB treatment did not have a significant effect on the bioavailability, clearance, or absorption rate constants of lopinavir or ritonavir. Most children (81% of children with MDR-TB, 88% of controls) achieved therapeutic lopinavir trough concentrations (>1 mg/liter). The coadministration of lopinavir-ritonavir with drugs routinely used for the treatment of MDR-TB was found to have no significant effect on the key pharmacokinetic parameters of lopinavir or ritonavir. These findings should be considered in the context of the large interpatient variability found in the present study and the study's modest sample size.

Project description:Resistance to second-line drugs develops during treatment of multidrug-resistant (MDR) tuberculosis, but the impact on treatment outcome has not been determined.Patients with MDR tuberculosis starting second-line drug treatment were enrolled in a prospective cohort study. Sputum cultures were analyzed at a central reference laboratory. We compared subjects with successful and poor treatment outcomes in terms of (1) initial and acquired resistance to fluoroquinolones and second-line injectable drugs (SLIs) and (2) treatment regimens.Of 1244 patients with MDR tuberculosis, 973 (78.2%) had known outcomes and 232 (18.6%) were lost to follow-up. Among those with known outcomes, treatment succeeded in 85.8% with plain MDR tuberculosis, 69.7% with initial resistance to either a fluoroquinolone or an SLI, 37.5% with acquired resistance to a fluoroquinolone or SLI, 29.3% with initial and 13.0% with acquired extensively drug-resistant tuberculosis (P < .001 for trend). In contrast, among those with known outcomes, treatment success increased stepwise from 41.6% to 92.3% as the number of drugs proven effective increased from ?1 to ?5 (P < .001 for trend), while acquired drug resistance decreased from 12% to 16% range, depending on the drug, down to 0%-2% (P < .001 for trend). In multivariable analysis, the adjusted odds of treatment success decreased 0.62-fold (95% confidence interval, .56-.69) for each increment in drug resistance and increased 2.1-fold (1.40-3.18) for each additional effective drug, controlling for differences between programs and patients. Specific treatment, patient, and program variables were also associated with treatment outcome.Increasing drug resistance was associated in a logical stepwise manner with poor treatment outcomes. Acquired resistance was worse than initial resistance to the same drugs. Increasing numbers of effective drugs, specific drugs, and specific program characteristics were associated with better outcomes and less acquired resistance.

Dataset Information

Plasma concentrations of second-line antituberculosis drugs in relation to minimum inhibitory concentrations in multidrug-resistant tuberculosis patients in China: a study protocol of a prospective observational cohort study.

Publications

Plasma concentrations of second-line antituberculosis drugs in relation to minimum inhibitory concentrations in multidrug-resistant tuberculosis patients in China: a study protocol of a prospective observational cohort study.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets