Rapid Research in Diagnostics Development for TB Network (R2D2 Kids) and Assessing Diagnostics At POC for TB in Children (ADAPT for Kids)

NCT05989802 | Recruiting FDA Device

• 3 other identifiers: R01HL169449U01AI1520877200AA22RFA00004
• Study Type: interventional
• Target: 2,100
• Locations: 3 countries
• Sites: 3

Brief Summary

Every year there are an estimated 230,000 childhood deaths from TB. There is an urgent need for novel tests for TB diagnosis in children under 15 years. The Rapid Research in Diagnostics Development for TB Network (R2D2 Kids) and the Assessing Diagnostics at Point-of-care for Tuberculosis in children (ADAPT for Kids) studies seek to reduce the burden of TB worldwide by evaluating faster, simpler, and less expensive TB triage and diagnostic tests for use in children.

Conditions

Diagnostics; Global Health; Tuberculosis

Outcome Measures

Primary Outcomes (2)

• Proportion with positive index test result among participants with tuberculosis (TB)

  Sensitivity - Number with positive index test result/(Number with positive or negative index t test result) among participants with TB. TB will be defined based on a microbiological reference standard (sputum mycobacterial culture results)

  2 years

• Proportion with negative index test result among participants without tuberculosis (TB)

  Specificity - Number with negative index test results/(Number with positive or negative index t test result) among participants without TB. TB will be defined based on a microbiological reference standard (sputum mycobacterial culture results)

  2 years

Study Arms (1)

Evaluation of various novel TB triage and diagnostic tests

EXPERIMENTAL

The investigators will conduct evaluation of novel TB triage and diagnostic tests in a cohort of children with presumed TB. The investigators aim to enroll 250 participants per year at each of three enrollment sites for evaluation of various novel TB triage and diagnostic tests and 30 health workers to assess test usability. Novel test evaluations will be conducted on a rolling basis as new tests ready for field evaluation are identified.

Diagnostic Test: Oral swab molecular testing; Diagnostic Test: Automated Cough Sound Analysis; Diagnostic Test: Automated Lung Sound Analysis; Other: Chest X Ray Computer Aided Detection

Interventions

Automated Cough Sound Analysis DIAGNOSTIC_TEST

Cough sounds can be collected through a mobile phone and tablet, and then analyzed with machine learning algorithms to predict TB.

Evaluation of various novel TB triage and diagnostic tests

Automated Lung Sound Analysis DIAGNOSTIC_TEST

Lung sounds can be collected with a non-invasive digital stethoscope, and then saved on a tablet or phone and analyzed by machine learning algorithms to predict TB.

Evaluation of various novel TB triage and diagnostic tests

Chest X Ray Computer Aided Detection OTHER

Several artificial intelligence algorithms have been developed to predict TB, though this has not yet been validated in children.

Also known as: Artificial Intelligence algorithm

Evaluation of various novel TB triage and diagnostic tests

Oral swab molecular testing DIAGNOSTIC_TEST

Swab-based testing provides a non-invasive approach to collect respiratory specimens for TB testing. Data in adults suggests that swab-based testing could be valuable when sputum collection is not feasible or available.

Evaluation of various novel TB triage and diagnostic tests

Eligibility Criteria

• Age: Up to 65 Years
• Sex: all
• Healthy Volunteers: Yes
• Age Groups: Child (0-17), Adult (18-64), Older Adult (65+)

Participant eligibility criteria: Participants will include children (age \<15 years) who present to care with: A. 2 or more of the following: * Unexplained cough for any duration * TB contact or tuberculin skin test or interferon gamma release assay positive * Abnormal chest X-ray (any abnormality) OR B. Any one of criteria A AND any one of the following: * Unexplained weight loss OR unexplained failure to thrive OR Severe Acute Malnutrition * Unexplained fever ≥2 weeks * Unexplained lethargy or reduced playfulness ≥2 weeks The study will exclude participants who: 1. Completed preventive 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 for any reason for greater than 3 days at the time of enrollment (to reduce false-negatives); 3. Are unable to return for follow-up visits; or 4. Whose parents/guardians are unwilling to provide informed consent or who are unwilling to provide assent if applicable (age determined by local IRB) Assessment of the usability of novel TB tests: The study will also 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). Personnel who are unwilling to provide informed consent will be excluded.

Contact the study team to discuss eligibility requirements. They can help determine if this study is right for you.

Sponsors & Collaborators

• University of California, San Francisco: lead
• Instituto Nacional de Saúde, Mozambique: collaborator
• National Referral Hospital: collaborator
• University of Cape Town: collaborator
• Johns Hopkins University: collaborator
• Elizabeth Glaser Pediatric AIDS Foundation: collaborator
• National Institute of Allergy and Infectious Diseases (NIAID): collaborator
• University of California, Irvine: collaborator

Study Sites (3)

Instituto Nacional de Saúde

Maputo, Mozambique

RECRUITING

Dora Nginza Hospital

Cape Town, South Africa

NOT YET RECRUITING

Mulago National Referral Hospital

Kampala, Uganda

NOT YET RECRUITING

Related Publications (19)

• Perez-Velez CM, Marais BJ. Tuberculosis in children. N Engl J Med. 2012 Jul 26;367(4):348-61. doi: 10.1056/NEJMra1008049. No abstract available.

  PMID: 22830465 BACKGROUND

• World Health Organization. Roadmap towards ending TB in children and adolescents. Geneva: World Health Organization, 2018. Available at: https://www.who.int/tb/publications/2018/tb-childhoodroadmap/en/. Last accessed 1 June 2022.

  BACKGROUND

• WHO. High-priority target product profiles for new tuberculosis diagnostics: Report of a consensus meeting. Geneva, Switzerland. Available at: http://www.who.int/tb/publications/tpp_report/en/, 2014.

  BACKGROUND

• Graham SM, Cuevas LE, Jean-Philippe P, Browning R, Casenghi M, Detjen AK, Gnanashanmugam D, Hesseling AC, Kampmann B, Mandalakas A, Marais BJ, Schito M, Spiegel HM, Starke JR, Worrell C, Zar HJ. Clinical Case Definitions for Classification of Intrathoracic Tuberculosis in Children: An Update. Clin Infect Dis. 2015 Oct 15;61Suppl 3(Suppl 3):S179-87. doi: 10.1093/cid/civ581.

  PMID: 26409281 BACKGROUND

• World Health Organization. Global Tuberculosis Report 2021. Geneva: World Health Organization, 2021.

  BACKGROUND

• World Health Organization. Roadmap towards ending TB in children and adolescents. Geneva: World Health Organization, 2018.

  BACKGROUND

• Lewinsohn DM, Leonard MK, LoBue PA, Cohn DL, Daley CL, Desmond E, Keane J, Lewinsohn DA, Loeffler AM, Mazurek GH, O'Brien RJ, Pai M, Richeldi L, Salfinger M, Shinnick TM, Sterling TR, Warshauer DM, Woods GL. Official American Thoracic Society/Infectious Diseases Society of America/Centers for Disease Control and Prevention Clinical Practice Guidelines: Diagnosis of Tuberculosis in Adults and Children. Clin Infect Dis. 2017 Jan 15;64(2):111-115. doi: 10.1093/cid/ciw778.

  PMID: 28052967 BACKGROUND

• WHO consolidated guidelines on tuberculosis: Module 5: Management of tuberculosis in children and adolescents [Internet]. Geneva: World Health Organization; 2022. Available from http://www.ncbi.nlm.nih.gov/books/NBK579387/

  PMID: 35404556 BACKGROUND

• Jaganath D, Beaudry J, Salazar-Austin N. Tuberculosis in Children. Infect Dis Clin North Am. 2022 Mar;36(1):49-71. doi: 10.1016/j.idc.2021.11.008.

  PMID: 35168714 BACKGROUND

• Zawedde-Muyanja S, Reuter A, Tovar MA, Hussain H, Loando Mboyo A, Detjen AK, Yuen CM. Provision of Decentralized TB Care Services: A Detect-Treat-Prevent Strategy for Children and Adolescents Affected by TB. Pathogens. 2021 Dec 1;10(12):1568. doi: 10.3390/pathogens10121568.

  PMID: 34959523 BACKGROUND

• Dodd PJ, Yuen CM, Sismanidis C, Seddon JA, Jenkins HE. The global burden of tuberculosis mortality in children: a mathematical modelling study. Lancet Glob Health. 2017 Sep;5(9):e898-e906. doi: 10.1016/S2214-109X(17)30289-9.

  PMID: 28807188 BACKGROUND

• World Health Organization. High-priority target product profiles for new tuberculosis diagnostics: report of a consensus meeting. Available at: http://apps.who.int/iris/bitstream/handle/10665/135617/WHO_HTM_TB_2014.18_eng.pdf?sequence=12014.

  BACKGROUND

• Andama A, Whitman GR, Crowder R, Reza TF, Jaganath D, Mulondo J, Nalugwa TK, Semitala FC, Worodria W, Cook C, Wood RC, Weigel KM, Olson AM, Lohmiller Shaw J, Kato-Maeda M, Denkinger CM, Nahid P, Cangelosi GA, Cattamanchi A. Accuracy of Tongue Swab Testing Using Xpert MTB-RIF Ultra for Tuberculosis Diagnosis. J Clin Microbiol. 2022 Jul 20;60(7):e0042122. doi: 10.1128/jcm.00421-22. Epub 2022 Jun 27.

  PMID: 35758702 BACKGROUND

• Nkereuwem E, Togun T, Gomez MP, Szekely R, Mace A, Jobe D, Schumacher SG, Kampmann B, Denkinger CM; Reach4KidsAfrica (R4KA) Consortium. Comparing accuracy of lipoarabinomannan urine tests for diagnosis of pulmonary tuberculosis in children from four African countries: a cross-sectional study. Lancet Infect Dis. 2021 Mar;21(3):376-384. doi: 10.1016/S1473-3099(20)30598-3. Epub 2020 Dec 11.

  PMID: 33316214 BACKGROUND

• Yellapu GD, Rudraraju G, Sripada NR, Mamidgi B, Jalukuru C, Firmal P, Yechuri V, Varanasi S, Peddireddi VS, Bhimarasetty DM, Kanisetti S, Joshi N, Mohapatra P, Pamarthi K. Development and clinical validation of Swaasa AI platform for screening and prioritization of pulmonary TB. Sci Rep. 2023 Mar 23;13(1):4740. doi: 10.1038/s41598-023-31772-9.

  PMID: 36959347 BACKGROUND

• Kevat A, Kalirajah A, Roseby R. Artificial intelligence accuracy in detecting pathological breath sounds in children using digital stethoscopes. Respir Res. 2020 Sep 29;21(1):253. doi: 10.1186/s12931-020-01523-9.

  PMID: 32993620 BACKGROUND

• Harris M, Qi A, Jeagal L, Torabi N, Menzies D, Korobitsyn A, Pai M, Nathavitharana RR, Ahmad Khan F. A systematic review of the diagnostic accuracy of artificial intelligence-based computer programs to analyze chest x-rays for pulmonary tuberculosis. PLoS One. 2019 Sep 3;14(9):e0221339. doi: 10.1371/journal.pone.0221339. eCollection 2019.

  PMID: 31479448 BACKGROUND

• UCSF Human Research Protection Program. The Level of Review and Minimal Risk. Available at: https://irb.ucsf.edu/levels-review#Category-2-Blood-sampling-limited-amounts. Last accessed 4 Jan 2023.

  BACKGROUND

• Howie SR. Blood sample volumes in child health research: review of safe limits. Bull World Health Organ. 2011 Jan 1;89(1):46-53. doi: 10.2471/BLT.10.080010. Epub 2010 Sep 10.

  PMID: 21346890 BACKGROUND

MeSH Terms

Conditions

Tuberculosis

Condition Hierarchy (Ancestors)

Mycobacterium Infections; Actinomycetales Infections; Gram-Positive Bacterial Infections; Bacterial Infections; Bacterial Infections and Mycoses; Infections

Study Officials

• Adithya Cattamanchi, MD, MAS

  University of California, Irvine

  PRINCIPAL INVESTIGATOR

• Nilesh Bhatt

  Elizabeth Glazer Pediatric AIDS Foundation

  PRINCIPAL INVESTIGATOR

Central Study Contacts

Devan Jaganath, MD

CONTACT

415-514-4692; devan.jaganath@ucsf.edu

Brittney Sweetser, MPH

CONTACT

bsweetse@hs.uci.edu

Study Design

• Study Type: interventional
• Phase: not applicable
• Allocation: NA
• Masking: NONE
• Purpose: DIAGNOSTIC
• Intervention Model: SINGLE GROUP
• Sponsor Type: OTHER
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: July 28, 2023
• First Posted: August 14, 2023
• Study Start: January 26, 2024
• Primary Completion (Estimated): September 1, 2026
• Study Completion (Estimated): September 1, 2026
• Last Updated: March 11, 2026

Record last verified: 2026-03

Data Sharing

• IPD Sharing: Will not share

Locations

UG (1); MO (1); ZA (1)