Trial reportAntimicrobial agents and chemotherapy2013
A time-to-event pharmacodynamic model describing treatment response in patients with pulmonary tuberculosis using days to positivity in automated liquid mycobacterial culture.
Trial report in Antimicrobial agents and chemotherapy, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT03827811 (Pharmacometrics to Advance Novel Regimens for Drug-resistant Tuberculosis), which is not on this map. Cited by 32 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Pharmacometrics to Advance Novel Regimens for Drug-resistant Tuberculosis
Who cites it
32 citing papers in PubMed, 43 citations in OpenAlex.
- Assessing whether isoniazid is essential during the first 14 days of tuberculosis therapy: a phase 2a, open-label, randomised controlled trial.The Lancet. Microbe · 2020Trial
- Impact of nonlinear interactions of pharmacokinetics and MICs on sputum bacillary kill rates as a marker of sterilizing effect in tuberculosis.Antimicrobial agents and chemotherapy · 2015Trial
- The pyrazinamide susceptibility breakpoint above which combination therapy fails.The Journal of antimicrobial chemotherapy · 2014Trial
- Insights into the Role of Rifampicin Exposure and Clinical Baseline Covariates on the Response to Pulmonary Tuberculosis Treatment.Clinical infectious diseases : an official publication of the Infectious Diseases Society of America · 2026Article
- Pyrazinamide susceptibility testing inFrontiers in cellular and infection microbiology · 2026Article
- Improving the efficiency of drug resistant tuberculosis treatment trials: a time-to-event alternative marker for bacteriological response and adaptive minimization for randomization.BMC medical research methodology · 2025Article
- The identification Mycobacterium tuberculosis genes that modulate long term survival in the presence of rifampicin and streptomycin.Scientific reports · 2025Article
- Analysis of time-to-positivity data in tuberculosis treatment studies: Identifying a new limit of quantification.International journal of antimicrobial agents · 2025Article
- Analysis of time-to-positivity data in tuberculosis treatment studies: Identifying a new limit of quantification.medRxiv : the preprint server for health sciences · 2024Article
- Analysis of Dynamic Efficacy Endpoints of the Nix-TB Trial.Clinical infectious diseases : an official publication of the Infectious Diseases Society of America · 2023Article
- Hollow-fibre system model of tuberculosis reproducibility and performance specifications for best practice in drug and combination therapy development.The Journal of antimicrobial chemotherapy · 2023Article
- Combined quantitative tuberculosis biomarker model for time-to-positivity and colony forming unit to support tuberculosis drug development.Frontiers in pharmacology · 2023Article
- Finding the right hazard function for time-to-event modeling: A tutorial and Shiny application.CPT: pharmacometrics & systems pharmacology · 2022Article
- Effects of Increasing Concentrations of Rifampicin on Different Mycobacterium tuberculosis Lineages in a Whole-Blood Bactericidal Activity Assay.Antimicrobial agents and chemotherapy · 2022Article
- Longitudinal Model-Based Biomarker Analysis of Exposure-Response Relationships in Adults with Pulmonary Tuberculosis.Antimicrobial agents and chemotherapy · 2021Article
- Explorative Analysis of Treatment Outcomes of Levofloxacin- and Moxifloxacin-Based Regimens and Outcome Predictors in Ethiopian MDR-TB Patients: A Prospective Observational Cohort Study.Infection and drug resistance · 2021Article
- Mechanisms of Drug-Induced Tolerance in Mycobacterium tuberculosis.Clinical microbiology reviews · 2020Review
- Model-Based Relationship between the Molecular Bacterial Load Assay and Time to Positivity in Liquid Culture.Antimicrobial agents and chemotherapy · 2019Article
- Modeling and Simulation of Pretomanid Pharmacodynamics in Pulmonary Tuberculosis Patients.Antimicrobial agents and chemotherapy · 2019Article
- Accelerating the transition of new tuberculosis drug combinations from Phase II to Phase III trials: New technologies and innovative designs.PLoS medicine · 2019Article
Corrections and comments
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Authors and funding
8 authors at 4 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Days to positivity in automated liquid mycobacterial culture have been shown to correlate with mycobacterial load and have been proposed as a useful biomarker for treatment responses in tuberculosis. However, there is currently no quantitative method or model to analyze the change in days to positivity with time on treatment. The objectives of this study were to describe the decline in numbers of mycobacteria in sputum collected once weekly for 8 weeks from patients on treatment for tuberculosis using days to positivity in liquid culture. One hundred forty-four patients with smear-positive pulmonary tuberculosis were recruited from a tuberculosis clinic in Cape Town, South Africa. A nonlinear mixed-effects repeated-time-to-event modeling approach was used to analyze the time-to-positivity data. A biexponential model described the decline in the estimated number of bacteria in patients' sputum samples, while a logistic model with a lag time described the growth of the bacteria in liquid culture. At baseline, the estimated number of rapidly killed bacteria is typically 41 times higher than that of those that are killed slowly. The time to kill half of the rapidly killed bacteria was about 1.8 days, while it was 39 days for slowly killed bacteria. Patients with lung cavitation had higher bacterial loads than patients without lung cavitation. The model successfully described the increase in days to positivity as treatment progressed, differentiating between bacteria that are killed rapidly and those that are killed slowly. Our model can be used to analyze similar data from studies testing new drug regimens.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.