Rapid Research in Diagnostics Development for TB Network

ConditionTuberculosis
Trial statusRecruiting
Trial phaseNot applicable
Trial typeInterventional
Biological sexAll
Age12+
SponsorUniversity of California, San Francisco

About this trial

To reduce the burden of TB worldwide through more accurate, faster, simpler, and less expensive diagnosis of TB Every year, more than 3 million people with TB remain undiagnosed and 1 million die. Better diagnostics are essential to reducing the enormous burden of TB worldwide. The Rapid Research in Diagnostics Development for TB Network (R2D2 TB Network) brings together experts in TB care, technology assessment, diagnostics development, laboratory medicine, epidemiology, health economics and mathematical modeling with highly experienced clinical study sites in 10 countries.

Eligibility criteria

This trial does not accept healthy volunteers

Qualifiers

PLHIV (Risk Factor), CRP >5 mg/dL OR abnormal CXR (Positive TB screening definition)

Self-reported Close Contact (Risk Factor), abnormal CXR (Positive TB screening definition)

History of mining work (Risk Factor), abnormal CXR (Positive TB screening definition)

completed latent or active TB treatment within the past 12 months (to increase TB prevalence and reduce false-positive results, respectively);

Disqualifiers

None

Trial design

Design model

Parallel

Treatments tested in this trial

  • Novel mycobacterial culture techniques

    Diagnostic test

    We will evaluate tests intended to make culture more sensitive, faster, and have less contamination.

  • Novel sputum smear microscopy techniques

    Diagnostic test

    We will evaluate new staining techniques or visualization methods to increase the sensitivity of smear microscopy.

  • Sputum-based molecular assays

    Diagnostic test

    We will evaluate semi-automated or automated molecular assays intended for use at near point of care or point of care.

  • Tongue swab-based molecular assays

    Diagnostic test

    We will evaluate semi-automated or automated molecular assays intended for use at near point of care or point of care.

  • Urine LAM assays

    Diagnostic test

    We will evaluate urine LAM assays incorporating techniques such as analyte concentration, higher sensitivity or specificity antibodies, or enhanced visualization to improve LAM detection.

  • Blood-based host immune response assays

    Diagnostic test

    We will evaluate assays measuring host immune response parameters intended for use at near point of care or point of care.

  • Breath-based assays

    Diagnostic test

    We will evaluate assays assessing volatile organic compounds or exhaled breath condensate for near point of care of point of care detection of TB.

  • Artificial intelligence-based digital health tools

    Diagnostic test

    We will evaluate AI-based algorithms evaluating images (chest x-ray, ultrasound) or sounds (cough sounds, lung sounds) including an Infrasound-to-ultrasound e-stethoscope (Level 42 AI, USA).

  • Phage-based assays

    Diagnostic test

    We will evaluate assays using phages to lyse mycobacterial cells for detection of DNA or antigens.

  • Cartridge-based molecular assays for detecting drug resistance

    Diagnostic test

    We will evaluate semi-automated or automated molecular assays intended for use at near point of care or point of care.

  • Sequencing-based assays for detecting drug resistance

    Diagnostic test

    We will evaluate targeted and whole genome sequencing assays.

Treatment groups

26,436 Participants
are divided into 2 treatment groups
Group A: Evaluation of various novel TB triage and diagnostic tests.Experimental treatment 9 interventions
Group B: Evaluation of novel rDST assaysExperimental treatment 2 interventions

Trial outcomes

Primary outcomes

1

Sensitivity

Number of positive results for a given index test/(Total positive + negative results for a given index test) among patients with TB using the microbiological reference standard

Time frame
7 months
2

Specificity

Number of negative results for a given index test/(Total positive + negative results for a given index test) among patients without TB using the microbiological reference standard

Time frame
7 months

Secondary outcomes

Other outcomes

Sponsors and contacts

Click on the lead sponsor to view all of their trials.

University of California, San Francisco

Lead sponsor

University Hospital Heidelberg

Collaborator

Christian Medical College, Vellore, India

Collaborator

Vietnam National Lung Hospital

Collaborator

De La Salle University Medical Center

Collaborator

University of Stellenbosch

Collaborator

Makerere University

Collaborator

Johns Hopkins Bloomberg School of Public Health

Collaborator

Harvard Medical School (HMS and HSDM)

Collaborator

Stanford University

Collaborator

Foundation for Innovative New Diagnostics, Switzerland

Collaborator

Socios En Salud Sucursal, Peru

Collaborator

Federal University of Mato Grosso

Collaborator

Medical Research Council

Collaborator

National Center for Tuberculosis and Lung Disease, Tbilisi, Georgia

Collaborator

Centre for Infectious Disease Research in Zambia

Collaborator

National Institute of Allergy and Infectious Diseases (NIAID)

Collaborator

Zankli Research Center

Collaborator

University of California, Irvine

Collaborator

Johns Hopkins University

Collaborator