Tuberculosis
Conditions
Keywords
Tuberculosis, Diagnostics, Global Health
Brief summary
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.
Detailed description
The Rapid Research in Diagnostics Development for TB Network (R2D2 TB Network) study seeks to identify and rigorously assess promising early stage tuberculosis (TB) triage, diagnostic and drug resistance tests (hereafter referred to as "novel tests") in clinical studies conducted in settings of intended use. Rapid diagnosis, identification of drug resistance and effective treatment are critical for improving patient outcomes and reducing TB transmission. However, analysis of care cascades and prevalence surveys indicate that 40-60% of patients with TB are not initiated on effective treatment.1,2 The different types of tests required to reduce this "diagnostic gap" have been described in the form of target product profiles (TPPs). The highest- priority TPPs are for: 1) a point-of-care, non-sputum biomarker-based test to facilitate rapid TB diagnosis using easily accessible samples (a biomarker-based diagnostic test) and 2) a simple, low-cost test that can be used by front-line health workers to rule-out TB (a triage test). The R2D2 TB Network study will evaluate the sensitivity and specificity of novel triage and diagnostic tests against a reference standard including sputum Xpert® MTB/RIF (Mycobacterium tuberculosis/Rifampin) Ultra and sputum mycobacterial culture. The sensitivity and specificity of rapid drug susceptibility tests (rDST) will be compared against a reference standard including culture-based phenotypic DST and whole genome sequencing (WGS) of mycobacterial DNA. In addition, the usability of novel tests will be assessed through direct observations and surveys of routine health workers.
Interventions
DIAGNOSTIC_TESTNovel mycobacterial culture techniques
We will evaluate tests intended to make culture more sensitive, faster, and have less contamination.
DIAGNOSTIC_TESTNovel sputum smear microscopy techniques
We will evaluate new staining techniques or visualization methods to increase the sensitivity of smear microscopy.
DIAGNOSTIC_TESTSputum-based molecular assays
We will evaluate semi-automated or automated molecular assays intended for use at near point of care or point of care.
DIAGNOSTIC_TESTTongue swab-based molecular assays
We will evaluate semi-automated or automated molecular assays intended for use at near point of care or point of care.
DIAGNOSTIC_TESTUrine LAM assays
We will evaluate urine LAM assays incorporating techniques such as analyte concentration, higher sensitivity or specificity antibodies, or enhanced visualization to improve LAM detection.
DIAGNOSTIC_TESTBlood-based host immune response assays
We will evaluate assays measuring host immune response parameters intended for use at near point of care or point of care.
DIAGNOSTIC_TESTBreath-based assays
We will evaluate assays assessing volatile organic compounds or exhaled breath condensate for near point of care of point of care detection of TB.
DIAGNOSTIC_TESTArtificial intelligence-based digital health tools
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).
DIAGNOSTIC_TESTPhage-based assays
We will evaluate assays using phages to lyse mycobacterial cells for detection of DNA or antigens.
DIAGNOSTIC_TESTCartridge-based molecular assays for detecting drug resistance
We will evaluate semi-automated or automated molecular assays intended for use at near point of care or point of care.
DIAGNOSTIC_TESTSequencing-based assays for detecting drug resistance
We will evaluate targeted and whole genome sequencing assays.
Sponsors
University of California, San Francisco
University Hospital Heidelberg
Christian Medical College, Vellore, India
Vietnam National Lung Hospital
De La Salle University Medical Center
University of Stellenbosch
Makerere University
Johns Hopkins Bloomberg School of Public Health
Harvard Medical School (HMS and HSDM)
Stanford University
Foundation for Innovative New Diagnostics, Switzerland
Socios En Salud Sucursal, Peru
Federal University of Mato Grosso
Medical Research Council
National Center for Tuberculosis and Lung Disease, Tbilisi, Georgia
Centre for Infectious Disease Research in Zambia
National Institute of Allergy and Infectious Diseases (NIAID)
Zankli Research Center
University of California, Irvine
Johns Hopkins University
Study design
Allocation
NON_RANDOMIZED
Intervention model
PARALLEL
Primary purpose
DIAGNOSTIC
Masking
NONE
Eligibility
Sex/Gender
ALL
Age
12 Years to No maximum
Healthy volunteers
No
Inclusion criteria
Novel TB triage and diagnostic tests: We will include non-hospitalized adults (age ≥ 12 years) with either 1) cough ≥2 weeks' duration, a commonly accepted criterion for identifying people with presumed pulmonary TB (to facilitate standardization across sites and comparison of test performance across sub-groups or 2) risk factors for which TB screening is recommended (HIV infection, self-reported close contact, history of mining work). People with risk factors will be included if they screen positive for TB based on WHO-recommended screening tools as specified below: Positive TB screening definitions by risk factor: 1. PLHIV (Risk Factor), CRP \>5 mg/dL OR abnormal CXR (Positive TB screening definition) 2. Self-reported Close Contact (Risk Factor), abnormal CXR (Positive TB screening definition) 3. History of mining work (Risk Factor), abnormal CXR (Positive TB screening definition) We will exclude people who: 1. completed latent or active TB treatment within the past 12 months (to increase TB prevalence and reduce false-positive results, respectively); 2. have taken any medication with anti-mycobacterial activity (including fluoroquinolones) for any reason, within 2 weeks of study entry (to reduce false-negatives); 3. reside \>20km from the study site or are unwilling to return for follow-up visits; or 4. are unwilling to provide informed consent Novel TB rDST assays: We will include adults (age ≥12 years) who are positive for TB and RIF resistance according to routine diagnostic testing (based typically on Xpert MTB/RIF, Xpert MTB/RIF Ultra, or Hain MTBDRplus). We will exclude people who: 1. have negative or contaminated results on all baseline (i.e., enrollment) sputum cultures 2. are unable to provide at least two sputum specimens of 3 mL each within one day of enrollment 3. are unable or unwilling to provide informed consent Assessment of the usability of novel TB tests: We will include health workers at each clinical site who are 1) aged ≥18 years and 2) involved in routine TB testing (collecting specimens for or performing TB tests). We will exclude staff who are unwilling to provide informed consent.
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Sensitivity | 7 months | 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 |
| Specificity | 7 months | 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 |
Countries
Georgia, India, Nigeria, Philippines, South Africa, Uganda, Vietnam, Zambia
Contacts
CONTACTAdithya Cattamanchi, MD
CONTACTCatherine Cook, MPH
PRINCIPAL_INVESTIGATORAdithya Cattamanchi, MD
University of California, San Francisco
Outcome results
None listed