Rapid Research in Diagnostics Development for TB Network

Tuberculosis Clinical Trial

— R2D2TB Network  

Official title:

Rapid Research in Diagnostics Development for TB Network (R2D2 TB Network) Study

Clinical Trial Details — Status: Recruiting

Administrative data

• NCT number: NCT04923958
• Other study ID #: U01AI152087
• Secondary ID: U01AI152087
• Status: Recruiting
• Phase: N/A
• Start date: April 14, 2021
• Est. completion date: May 31, 2025

Study information

• Verified date: June 2023
• Source: University of California, San Francisco
• Contact: Adithya Cattamanchi, MD
• Phone: +1-415-206-5489
• Email: adithya.cattamanchi[@]ucsf.edu
• Is FDA regulated: No
• Study type: Interventional

Clinical Trial 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

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.

Recruitment information / eligibility

• Status: Recruiting
• Enrollment: 6050
• Est. completion date: May 31, 2025
• Est. primary completion date: May 31, 2025
• Accepts healthy volunteers: No
• Gender: All
• Age group: 12 Years and older

Eligibility

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.

Related Conditions & MeSH terms

• Tuberculosis

Intervention

Diagnostic Test:
• Novel mycobacterial culture techniques
We will evaluate tests intended to make culture more sensitive, faster, and have less contamination.
• Novel sputum smear microscopy techniques
We will evaluate new staining techniques or visualization methods to increase the sensitivity of smear microscopy.
• Sputum-based molecular assays
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
We will evaluate semi-automated or automated molecular assays intended for use at near point of care or point of care.
• Urine 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.
• Blood-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.
• Breath-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.
• Artificial 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).
• Phage-based assays
We will evaluate assays using phages to lyse mycobacterial cells for detection of DNA or antigens.
• Cartridge-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.
• Sequencing-based assays for detecting drug resistance
We will evaluate targeted and whole genome sequencing assays.

Locations

Country	Name	City	State
Georgia	National Center for Tuberculosis and Lung Diseases	Tbilisi
India	Chitoor (Christian Medical College satellite campus)	Vellore
India	Christian Medical College CMC Pulmonary Outpatient Department	Vellore
India	Primary care clinics (Shalom/LCC, CHAD)	Vellore
Philippines	De La Salle Medical and Health Sciences Institute	Dasmariñas
South Africa	Brooklyn Chest Hospital	Cape Town
South Africa	Khayelitsha District Health Center	Cape Town
South Africa	Kraaifontein Community Health Clinic	Cape Town
South Africa	Scottsdene primary care clinic	Cape Town
South Africa	Wallacedene primary care clinic	Cape Town
Uganda	Kisenyi Health Center	Kampala
Uganda	Mulago Outpatient Department	Kampala
Vietnam	Hanoi Lung Hospital, Outpatient departments	Hanoi
Vietnam	National Lung Hospital, Outpatient departments	Hanoi

Sponsors (17)

Lead Sponsor

Collaborator

University of California, San Francisco

Centre for Infectious Disease Research in Zambia, Christian Medical College, Vellore, India, De La Salle University Medical Center, Federal University of Mato Grosso, Foundation for Innovative New Diagnostics, Switzerland, Harvard Medical School (HMS and HSDM), Johns Hopkins Bloomberg School of Public Health, Makerere University, Medical Research Council, National Center for Tuberculosis and Lung Disease, Tbilisi, Georgia, National Institute of Allergy and Infectious Diseases (NIAID), Socios En Salud Sucursal, Peru, Stanford University, University Hospital Heidelberg, University of Stellenbosch, Vietnam National Lung Hospital

Countries where clinical trial is conducted

Georgia,  India,  Philippines,  South Africa,  Uganda,  Vietnam, 

References & Publications (38)

Ahmad Khan F, Pande T, Tessema B, Song R, Benedetti A, Pai M, Lonnroth K, Denkinger CM. Computer-aided reading of tuberculosis chest radiography: moving the research agenda forward to inform policy. Eur Respir J. 2017 Jul 13;50(1):1700953. doi: 10.1183/13993003.00953-2017. Print 2017 Jul. No abstract available. — View Citation

Boehme CC, Nabeta P, Hillemann D, Nicol MP, Shenai S, Krapp F, Allen J, Tahirli R, Blakemore R, Rustomjee R, Milovic A, Jones M, O'Brien SM, Persing DH, Ruesch-Gerdes S, Gotuzzo E, Rodrigues C, Alland D, Perkins MD. Rapid molecular detection of tuberculosis and rifampin resistance. N Engl J Med. 2010 Sep 9;363(11):1005-15. doi: 10.1056/NEJMoa0907847. Epub 2010 Sep 1. — View Citation

Cho SN, Brennan PJ. Tuberculosis: diagnostics. Tuberculosis (Edinb). 2007 Aug;87 Suppl 1:S14-7. doi: 10.1016/j.tube.2007.05.001. Epub 2007 Jun 20. — View Citation

Colman RE, Mace A, Seifert M, Hetzel J, Mshaiel H, Suresh A, Lemmer D, Engelthaler DM, Catanzaro DG, Young AG, Denkinger CM, Rodwell TC. Whole-genome and targeted sequencing of drug-resistant Mycobacterium tuberculosis on the iSeq100 and MiSeq: A performance, ease-of-use, and cost evaluation. PLoS Med. 2019 Apr 30;16(4):e1002794. doi: 10.1371/journal.pmed.1002794. eCollection 2019 Apr. Erratum In: PLoS Med. 2019 Jun 3;16(6):e1002823. — View Citation

Colman RE, Schupp JM, Hicks ND, Smith DE, Buchhagen JL, Valafar F, Crudu V, Romancenco E, Noroc E, Jackson L, Catanzaro DG, Rodwell TC, Catanzaro A, Keim P, Engelthaler DM. Detection of Low-Level Mixed-Population Drug Resistance in Mycobacterium tuberculosis Using High Fidelity Amplicon Sequencing. PLoS One. 2015 May 13;10(5):e0126626. doi: 10.1371/journal.pone.0126626. eCollection 2015. — View Citation

Dalton T, Cegielski P, Akksilp S, Asencios L, Campos Caoili J, Cho SN, Erokhin VV, Ershova J, Gler MT, Kazennyy BY, Kim HJ, Kliiman K, Kurbatova E, Kvasnovsky C, Leimane V, van der Walt M, Via LE, Volchenkov GV, Yagui MA, Kang H; Global PETTS Investigators; Akksilp R, Sitti W, Wattanaamornkiet W, Andreevskaya SN, Chernousova LN, Demikhova OV, Larionova EE, Smirnova TG, Vasilieva IA, Vorobyeva AV, Barry CE 3rd, Cai Y, Shamputa IC, Bayona J, Contreras C, Bonilla C, Jave O, Brand J, Lancaster J, Odendaal R, Chen MP, Diem L, Metchock B, Tan K, Taylor A, Wolfgang M, Cho E, Eum SY, Kwak HK, Lee J, Lee J, Min S, Degtyareva I, Nemtsova ES, Khorosheva T, Kyryanova EV, Egos G, Perez MT, Tupasi T, Hwang SH, Kim CK, Kim SY, Lee HJ, Kuksa L, Norvaisha I, Skenders G, Sture I, Kummik T, Kuznetsova T, Somova T, Levina K, Pariona G, Yale G, Suarez C, Valencia E, Viiklepp P. Prevalence of and risk factors for resistance to second-line drugs in people with multidrug-resistant tuberculosis in eight countries: a prospective cohort study. Lancet. 2012 Oct 20;380(9851):1406-17. doi: 10.1016/S0140-6736(12)60734-X. Epub 2012 Aug 30. Erratum In: Lancet. 2012 Oct 20;380(9851):1386. — View Citation

de Vos M, Ley SD, Wiggins KB, Derendinger B, Dippenaar A, Grobbelaar M, Reuter A, Dolby T, Burns S, Schito M, Engelthaler DM, Metcalfe J, Theron G, van Rie A, Posey J, Warren R, Cox H. Bedaquiline Microheteroresistance after Cessation of Tuberculosis Treatment. N Engl J Med. 2019 May 30;380(22):2178-2180. doi: 10.1056/NEJMc1815121. No abstract available. — View Citation

Farhat MR, Sultana R, Iartchouk O, Bozeman S, Galagan J, Sisk P, Stolte C, Nebenzahl-Guimaraes H, Jacobson K, Sloutsky A, Kaur D, Posey J, Kreiswirth BN, Kurepina N, Rigouts L, Streicher EM, Victor TC, Warren RM, van Soolingen D, Murray M. Genetic Determinants of Drug Resistance in Mycobacterium tuberculosis and Their Diagnostic Value. Am J Respir Crit Care Med. 2016 Sep 1;194(5):621-30. doi: 10.1164/rccm.201510-2091OC. — View Citation

Fernandez-Carballo BL, Broger T, Wyss R, Banaei N, Denkinger CM. Toward the Development of a Circulating Free DNA-Based In Vitro Diagnostic Test for Infectious Diseases: a Review of Evidence for Tuberculosis. J Clin Microbiol. 2019 Mar 28;57(4):e01234-18. doi: 10.1128/JCM.01234-18. Print 2019 Apr. — View Citation

Fleming TR. One-sample multiple testing procedure for phase II clinical trials. Biometrics. 1982 Mar;38(1):143-51. — View Citation

Gandhi NR, Moll A, Sturm AW, Pawinski R, Govender T, Lalloo U, Zeller K, Andrews J, Friedland G. Extensively drug-resistant tuberculosis as a cause of death in patients co-infected with tuberculosis and HIV in a rural area of South Africa. Lancet. 2006 Nov 4;368(9547):1575-80. doi: 10.1016/S0140-6736(06)69573-1. — View Citation

Lange C, Chesov D, Furin J, Udwadia Z, Dheda K. Revising the definition of extensively drug-resistant tuberculosis. Lancet Respir Med. 2018 Dec;6(12):893-895. doi: 10.1016/S2213-2600(18)30428-4. Epub 2018 Nov 9. No abstract available. — View Citation

Lee JJ, Feng L. Randomized phase II designs in cancer clinical trials: current status and future directions. J Clin Oncol. 2005 Jul 1;23(19):4450-7. doi: 10.1200/JCO.2005.03.197. — View Citation

Liu C, Lyon CJ, Bu Y, Deng Z, Walters E, Li Y, Zhang L, Hesseling AC, Graviss EA, Hu Y. Clinical Evaluation of a Blood Assay to Diagnose Paucibacillary Tuberculosis via Bacterial Antigens. Clin Chem. 2018 May;64(5):791-800. doi: 10.1373/clinchem.2017.273698. Epub 2018 Jan 18. — View Citation

Luabeya AK, Wood RC, Shenje J, Filander E, Ontong C, Mabwe S, Africa H, Nguyen FK, Olson A, Weigel KM, Jones-Engel L, Hatherill M, Cangelosi GA. Noninvasive Detection of Tuberculosis by Oral Swab Analysis. J Clin Microbiol. 2019 Feb 27;57(3):e01847-18. doi: 10.1128/JCM.01847-18. Print 2019 Mar. — View Citation

Makhado NA, Matabane E, Faccin M, Pincon C, Jouet A, Boutachkourt F, Goeminne L, Gaudin C, Maphalala G, Beckert P, Niemann S, Delvenne JC, Delmee M, Razwiedani L, Nchabeleng M, Supply P, de Jong BC, Andre E. Outbreak of multidrug-resistant tuberculosis in South Africa undetected by WHO-endorsed commercial tests: an observational study. Lancet Infect Dis. 2018 Dec;18(12):1350-1359. doi: 10.1016/S1473-3099(18)30496-1. Epub 2018 Oct 18. — View Citation

Masjedi MR, Farnia P, Sorooch S, Pooramiri MV, Mansoori SD, Zarifi AZ, Akbarvelayati A, Hoffner S. Extensively drug-resistant tuberculosis: 2 years of surveillance in Iran. Clin Infect Dis. 2006 Oct 1;43(7):841-7. doi: 10.1086/507542. Epub 2006 Aug 21. — View Citation

Mesman AW, Calderon R, Soto M, Coit J, Aliaga J, Mendoza M, Franke MF. Mycobacterium tuberculosis detection from oral swabs with Xpert MTB/RIF ULTRA: a pilot study. BMC Res Notes. 2019 Jun 20;12(1):349. doi: 10.1186/s13104-019-4385-y. — View Citation

Metcalfe JZ, Streicher E, Theron G, Colman RE, Penaloza R, Allender C, Lemmer D, Warren RM, Engelthaler DM. Mycobacterium tuberculosis Subculture Results in Loss of Potentially Clinically Relevant Heteroresistance. Antimicrob Agents Chemother. 2017 Oct 24;61(11):e00888-17. doi: 10.1128/AAC.00888-17. Print 2017 Nov. — View Citation

Nakhleh MK, Jeries R, Gharra A, Binder A, Broza YY, Pascoe M, Dheda K, Haick H. Detecting active pulmonary tuberculosis with a breath test using nanomaterial-based sensors. Eur Respir J. 2014 May;43(5):1522-5. doi: 10.1183/09031936.00019114. No abstract available. — View Citation

Organization WH. High-priority target product profiles for new tuberculosis diagnostics: report of a consensus meeting. Geneva, Switzerland: WHO Press; 2014. p. 98.

Paris L, Magni R, Zaidi F, Araujo R, Saini N, Harpole M, Coronel J, Kirwan DE, Steinberg H, Gilman RH, Petricoin EF 3rd, Nisini R, Luchini A, Liotta L. Urine lipoarabinomannan glycan in HIV-negative patients with pulmonary tuberculosis correlates with disease severity. Sci Transl Med. 2017 Dec 13;9(420):eaal2807. doi: 10.1126/scitranslmed.aal2807. — View Citation

Portevin D, Moukambi F, Clowes P, Bauer A, Chachage M, Ntinginya NE, Mfinanga E, Said K, Haraka F, Rachow A, Saathoff E, Mpina M, Jugheli L, Lwilla F, Marais BJ, Hoelscher M, Daubenberger C, Reither K, Geldmacher C. Assessment of the novel T-cell activation marker-tuberculosis assay for diagnosis of active tuberculosis in children: a prospective proof-of-concept study. Lancet Infect Dis. 2014 Oct;14(10):931-8. doi: 10.1016/S1473-3099(14)70884-9. Epub 2014 Aug 31. — View Citation

Prasad R, Singh A, Balasubramanian V, Gupta N. Extensively drug-resistant tuberculosis in India: Current evidence on diagnosis & management. Indian J Med Res. 2017 Mar;145(3):271-293. doi: 10.4103/ijmr.IJMR_177_16. — View Citation

Schmidt S. Bringing cheap and accurate tuberculosis tests to Africa. University of Wisconsin - News. 2018.

Shin SS, Modongo C, Baik Y, Allender C, Lemmer D, Colman RE, Engelthaler DM, Warren RM, Zetola NM. Mixed Mycobacterium tuberculosis-Strain Infections Are Associated With Poor Treatment Outcomes Among Patients With Newly Diagnosed Tuberculosis, Independent of Pretreatment Heteroresistance. J Infect Dis. 2018 Nov 5;218(12):1974-1982. doi: 10.1093/infdis/jiy480. — View Citation

Subbaraman R, Nathavitharana RR, Satyanarayana S, Pai M, Thomas BE, Chadha VK, Rade K, Swaminathan S, Mayer KH. The Tuberculosis Cascade of Care in India's Public Sector: A Systematic Review and Meta-analysis. PLoS Med. 2016 Oct 25;13(10):e1002149. doi: 10.1371/journal.pmed.1002149. eCollection 2016 Oct. — View Citation

Systematic Screening for Active Tuberculosis: Principles and Recommendations. Geneva: World Health Organization; 2013. Available from http://www.ncbi.nlm.nih.gov/books/NBK294083/ — View Citation

UNITAID. TB Diagnostics Market in Select High-Burden Countries: Current Market and Future Opportunities for Novel Diagnostics. Geneva, Switzerland, 2015.

Walker TM, Kohl TA, Omar SV, Hedge J, Del Ojo Elias C, Bradley P, Iqbal Z, Feuerriegel S, Niehaus KE, Wilson DJ, Clifton DA, Kapatai G, Ip CLC, Bowden R, Drobniewski FA, Allix-Beguec C, Gaudin C, Parkhill J, Diel R, Supply P, Crook DW, Smith EG, Walker AS, Ismail N, Niemann S, Peto TEA; Modernizing Medical Microbiology (MMM) Informatics Group. Whole-genome sequencing for prediction of Mycobacterium tuberculosis drug susceptibility and resistance: a retrospective cohort study. Lancet Infect Dis. 2015 Oct;15(10):1193-1202. doi: 10.1016/S1473-3099(15)00062-6. Epub 2015 Jun 23. Erratum In: Lancet Infect Dis. 2017 Nov 21;: — View Citation

Walusimbi S, Bwanga F, De Costa A, Haile M, Joloba M, Hoffner S. Meta-analysis to compare the accuracy of GeneXpert, MODS and the WHO 2007 algorithm for diagnosis of smear-negative pulmonary tuberculosis. BMC Infect Dis. 2013 Oct 30;13:507. doi: 10.1186/1471-2334-13-507. — View Citation

Wood A, Barizuddin S, Darr CM, Mathai CJ, Ball A, Minch K, Somoskovi A, Hamasur B, Connelly JT, Weigl B, Andama A, Cattamanchi A, Gangopadhyay K, Bok S, Gangopadhyay S. Ultrasensitive detection of lipoarabinomannan with plasmonic grating biosensors in clinical samples of HIV negative patients with tuberculosis. PLoS One. 2019 Mar 26;14(3):e0214161. doi: 10.1371/journal.pone.0214161. eCollection 2019. — View Citation

World Health Organization. Drug-resistant TB. https://www.who.int/tb/areas-of-work/drug-resistant-tb/en/.

World Health Organization. Global tuberculosis report Geneva, Switzerland: World Health Organization, 2015.

World Health Organization. High-priority target product profiles for new tuberculosis diagnostics: report of a consensus meeting. Geneva, Switzerland, 2014.

World Health Organization. Rapid Implementation of the Xpert MTB / RIF diagnostic test. Technical and operational 'how-to' practical considerations. Geneva, Switzerland, 2011.

Yoon C, Dowdy DW, Esmail H, MacPherson P, Schumacher SG. Screening for tuberculosis: time to move beyond symptoms. Lancet Respir Med. 2019 Mar;7(3):202-204. doi: 10.1016/S2213-2600(19)30039-6. No abstract available. — View Citation

Yoon C, Semitala FC, Atuhumuza E, Katende J, Mwebe S, Asege L, Armstrong DT, Andama AO, Dowdy DW, Davis JL, Huang L, Kamya M, Cattamanchi A. Point-of-care C-reactive protein-based tuberculosis screening for people living with HIV: a diagnostic accuracy study. Lancet Infect Dis. 2017 Dec;17(12):1285-1292. doi: 10.1016/S1473-3099(17)30488-7. Epub 2017 Aug 25. — View Citation

* Note: There are 38 references in all — Click here to view all references

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	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	2 years
Primary	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	2 years