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Diagnostics and Pharmacotherapy for Severe Forms of TB (DMID 15-0100)

Diagnostics and Pharmacotherapy for Severe Forms of TB

Status
Completed
Phases
Unknown
Study type
Observational
Source
ClinicalTrials.gov
Registry ID
NCT03559582
Enrollment
478
Registered
2018-06-18
Start date
2016-04-28
Completion date
2021-01-31
Last updated
2022-03-09

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Tuberculosis

Brief summary

Major Research Aim: To study novel molecular diagnostics and the pharmacokinetic variability among a spectrum of TB disease states, including severe forms of TB like disseminated TB, TB meningitis and drug resistant TB, among adults and children from multiple international sites.

Detailed description

Aim 1. Measure pharmacokinetics to anti-tuberculosis (TB) medications in severe TB syndromes (including multidrug-resistant TB, pediatric TB, TB sepsis and TB meningitis) from diverse geographies (including Tanzania, Uganda, Bangladesh, and Siberia) and correlate these findings to TB treatment outcome (TB treatment failure: death/ default/ relapse/ further acquired drug resistance). Aim 2. Decipher mechanisms of pharmacokinetic variability to TB drugs, particularly malabsorption due to concurrent gastrointestinal disease. Aim 3. Deployment of quantitative susceptibility testing (minimum inhibitory concentration-MIC) and rapid MIC-informed molecular methods (e.g., TaqMan Array Card-TAC) for M. tuberculosis. In addition to the stated aims, the primary elements of capacity building requisite for this project include the training in and deployment of the fieldable molecular diagnostic platforms, onsite pharmacokinetic monitoring, and a broad strengthening of longitudinal cohort management for clinical research.

Interventions

None listed

Sponsors

National Institute of Allergy and Infectious Diseases (NIAID)
CollaboratorNIH
Scientific Center for Family Health and Human Reproduction Problems, Russia
CollaboratorOTHER_GOV
Kilimanjaro Christian Medical Centre, Tanzania
CollaboratorOTHER
Haydom Lutheran Hospital
CollaboratorOTHER
Mbarara University of Science and Technology
CollaboratorOTHER
International Centre for Diarrhoeal Disease Research, Bangladesh
CollaboratorOTHER
University of Florida
CollaboratorOTHER
University of Virginia
Lead SponsorOTHER

Study design

Observational model
COHORT
Time perspective
PROSPECTIVE

Eligibility

Sex/Gender
ALL
Healthy volunteers
No

Inclusion criteria

Patients admitted to one of the study site hospitals with at least ONE of the following: 1. Clinical suspicion for TB in a child, as defined by NIH Consensus Case Definitions for TB research in children, and started on TB treatment 2. Clinical suspicion for TB meningitis, as defined by the International TB Meningitis Workshop Consensus Case Definitions for TB Meningitis 3. Clinical suspicion for TB sepsis, as defined by the Uganda/PRISM-U definitions 4. Microbiologic evidence of MDR-TB from a respiratory specimen within the past 6 months

Exclusion criteria

1. Pregnant women-self reported 2. Patient unable per treating physician discretion to undergo sample collection 3. Patient or representative/guardian unable to sign written informed consent 4. Patient unable to return for follow-up or be contacted by phone for follow-up

Design outcomes

Primary

MeasureTime frameDescription
Measure area under the concentration curve (AUC) to anti-tuberculosis (TB) medications relative to TB treatment outcome in severe TB syndromesDecember 2019Severe TB syndromes include multidrug-resistant TB, pediatric TB, TB sepsis and TB meningitis from diverse geographies (including Tanzania, Uganda, Bangladesh, and Siberia). The parameter of most importance to cidal activity of anti-TB medications among the cohort is AUC. TB treatment outcome will be defined as death, microbiological failure, relapse or acquired drug resistance, and machine learning algorithms such as classification and regression tree analyses will be used to define AUC threshold for each anti-TB medication predictive of poor TB treatment outcome. Conventional logistic regression will then be used to determine the additive odds for a patient with one of more medications below an algorithm derived threshold being significantly more likely to have a poor TB treatment outcome.

Secondary

MeasureTime frameDescription
Collect stool in patients undergoing pharmacokinetic testing to measure the environmental enteropathy indexDecember 2019Stool will be collected in patients with severe TB syndromes undergoing pharmacokinetic testing and assayed for stool biomarkers of malabsorption (environmental enteropathy index) and modeled as a determinant of those with AUC values of one or more anti-TB medications below thresholds predictive of TB treatment outcome.
Collect stool in patients undergoing pharmacokinetic testing to measure the quantitative burden and species distribution of enteric pathogens by the enteric TAC assay- 35 bacterial, viral, parasitic species)December 2019Stool will be collected in patients with severe TB syndromes undergoing pharmacokinetic testing and assayed for detection of molecular targets of enteric pathogens by TaqMan Array Card (TAC) platform. Enteric pathogen burden (including the effect of multiple pathogens in a single sample) will be modeled as a determinant of those with AUC values of one or more anti-TB medications below thresholds predictive of TB treatment outcome.

Outcome results

None listed

Source: ClinicalTrials.gov · Data processed: Feb 23, 2026