Dataset Information

Application of the Multistate Tuberculosis Pharmacometric Model in Patients With Rifampicin-Treated Pulmonary Tuberculosis.

ABSTRACT: This is the first clinical implementation of the Multistate Tuberculosis Pharmacometric (MTP) model describing fast-, slow-, and nonmultiplying bacterial states of Mycobacterium tuberculosis. Colony forming unit data from 19 patients treated with rifampicin were analyzed. A previously developed rifampicin population pharmacokinetic (PK) model was linked to the MTP model previously developed using in vitro data. Drug effect was implemented as exposure-response relationships tested at several effect sites, both alone and in combination. All MTP model parameters were fixed to in vitro estimates except Bmax . Drug effect was described by an on/off effect inhibiting growth of fast-multiplying bacteria in addition to linear increase of the stimulation of the death rate of slow- and nonmultiplying bacteria with increasing drug exposure. Clinical trial simulations predicted well three retrospective clinical trials using the final model that confirmed the potential utility of the MTP model in antitubercular drug development.

SUBMITTER: Svensson RJ

PROVIDER: S-EPMC4873565 | biostudies-literature | 2016 May

REPOSITORIES: biostudies-literature

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Application of the Multistate Tuberculosis Pharmacometric Model in Patients With Rifampicin-Treated Pulmonary Tuberculosis.

Svensson R J RJ Simonsson Ush U

CPT: pharmacometrics & systems pharmacology 20160517 5

This is the first clinical implementation of the Multistate Tuberculosis Pharmacometric (MTP) model describing fast-, slow-, and nonmultiplying bacterial states of Mycobacterium tuberculosis. Colony forming unit data from 19 patients treated with rifampicin were analyzed. A previously developed rifampicin population pharmacokinetic (PK) model was linked to the MTP model previously developed using in vitro data. Drug effect was implemented as exposure-response relationships tested at several effe ...[more]

PMID: 27299939

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Project description:Background and objectivesDiagnosis of Pulmonary Rifampicin Resistant Tuberculosis (RR-TB) with the Drug-Susceptibility Test (DST) is costly and time-consuming. Furthermore, GeneXpert for rapid diagnosis is not widely available in Indonesia. This study aims to develop and evaluate the CUHAS-ROBUST model performance, an artificial-intelligence-based RR-TB screening tool.MethodsA cross-sectional study involved suspected all type of RR-TB patients with complete sputum Lowenstein Jensen DST (reference) and 19 clinical, laboratory, and radiology parameter results, retrieved from medical records in hospitals under the Faculty of Medicine, Hasanuddin University Indonesia, from January 2015-December 2019. The Artificial Neural Network (ANN) models were built along with other classifiers. The model was tested on participants recruited from January 2020-October 2020 and deployed into CUHAS-ROBUST (index test) application. Sensitivity, specificity, and accuracy were obtained for assessment.ResultsA total of 487 participants (32 Multidrug-Resistant/MDR 57 RR-TB, 398 drug-sensitive) were recruited for model building and 157 participants (23 MDR and 21 RR) in prospective testing. The ANN full model yields the highest values of accuracy (88% (95% CI 85-91)), and sensitivity (84% (95% CI 76-89)) compare to other models that show sensitivity below 80% (Logistic Regression 32%, Decision Tree 44%, Random Forest 25%, Extreme Gradient Boost 25%). However, this ANN has lower specificity among other models (90% (95% CI 86-93)) where Logistic Regression demonstrates the highest (99% (95% CI 97-99)). This ANN model was selected for the CUHAS-ROBUST application, although still lower than the sensitivity of global GeneXpert results (87.5%).ConclusionThe ANN-CUHAS ROBUST outperforms other AI classifiers model in detecting all type of RR-TB, and by deploying into the application, the health staff can utilize the tool for screening purposes particularly at the primary care level where the GeneXpert examination is not available.Trial registrationNCT04208789.

Project description:Background: Meropenem is being investigated for repurposing as an anti-tuberculosis drug. This study aimed to develop a meropenem population pharmacokinetics model in patients with pulmonary tuberculosis and identify covariates explaining inter-individual variability. Methods: Patients were randomized to one of four treatment groups: meropenem 2 g three times daily plus oral rifampicin 20 mg/kg once daily, meropenem 2 g three times daily, meropenem 1 g three times daily, and meropenem 3 g once daily. Meropenem was administered by intravenous infusion over 0.5-1 h. All patients also received oral amoxicillin/clavulanate together with each meropenem dose, and treatments continued daily for 14 days. Intensive plasma pharmacokinetics sampling over 8 h was conducted on the 14th day of the study. Nonlinear mixed-effects modeling was used for data analysis. The best model was chosen based on likelihood metrics, goodness-of-fit plots, and parsimony. Covariates were tested stepwise. Results: A total of 404 concentration measurements from 49 patients were included in the analysis. A two-compartment model parameterized with clearance (CL), inter-compartmental clearance (Q), and central (V1) and peripheral (V2) volumes of distribution fitted the data well. Typical values of CL, Q, V1, and V2 were 11.8 L/h, 3.26 L/h, 14.2 L, and 3.12 L, respectively. The relative standard errors of the parameter estimates ranged from 3.8 to 35.4%. The covariate relations included in the final model were creatinine clearance on CL and allometric scaling with body weight on all disposition parameters. An effect of age on CL as previously reported could not be identified. Conclusion: A two-compartment model described meropenem population pharmacokinetics in patients with pulmonary tuberculosis well. Covariates found to improve model fit were creatinine clearance and body weight but not rifampicin treatment. The final model will be used for an integrated pharmacokinetics/pharmacodynamics analysis linking meropenem exposure to early bactericidal activity.

Project description:BackgroundMulti-drug resistant Mycobacterium tuberculosis is a growing public health problem in developing countries including Somalia. Although, the prevalence of multi-drug resistant tuberculosis among new and retreated cases is high, data on GeneXpert- Mycobacterium tuberculosis/rifampicin-resistant assay, which is a surrogate marker for multidrug resistance, is not well explored in Mogadishu.ObjectivesTo determine the prevalence of rifampicin-resistant Mycobacterium tuberculosis and its associated factors among presumptive pulmonary tuberculosis patients visiting tuberculosis centers in Mogadishu, Somalia.MethodsA multicenter cross-sectional study was conducted in three tuberculosis treatment centers from March 12 to April 30, 2021. Laboratory professionals collected sputum sample consecutively from presumptive pulmonary tuberculosis participants and performed a GeneXpert assay to determine the rifampicin resistance. Socio-demographic and clinical data were collected using structured questionnaire. Logistic regression analyses were performed to assess factors associated with rifampicin resistance using an adjusted odds ratio at a 95% confidence interval. Statistical significance was considered at a p-value of less than 0.05.ResultsA total of 370 presumptive tuberculosis suspects were included; of whom 58.4% were females and the mean age of the participants was 44.3 ± 14 years. Mycobacterium tuberculosis was detected in 63 (17%) (95% confidence interval = 13.2-20.8) suspects. Of these the prevalence of rifampicin-resistant Mycobacterium tuberculosis was 35% (95% confidence interval = 30.2-39.8). Anti-tuberculosis treatment history (adjusted odds ratio = 4.1; 95% confidence interval = 1.91-6.75), monthly income less than $100 USD (adjusted odds ratio = 2.2; 95% confidence interval = 1.77-5.98) and being diagnosed with Asthma (adjusted odds ratio = 2.63; 95% confidence interval = 1.3-7.3) were significantly associated with rifampicin-resistant tuberculosis.ConclusionA considerable proportion of rifampicin-resistant tuberculosis is reported in these study settings. The strong association between multidrug resistance tuberculosis and patients' retreatment history of tuberculosis, low income, and co-morbidity with asthma highlights the need for more efforts in tuberculosis treatment and monitoring programs to limit the emergence of multi-drug resistant strain in the study areas.

Dataset Information

Application of the Multistate Tuberculosis Pharmacometric Model in Patients With Rifampicin-Treated Pulmonary Tuberculosis.

Publications

Application of the Multistate Tuberculosis Pharmacometric Model in Patients With Rifampicin-Treated Pulmonary Tuberculosis.

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