Start4All SCREEN-TB PROTOCOL

Официальное название

Start4All - Start Taking Action for TB Diagnosis SCREEN-TB

Обзор

Tuberculosis (TB) remains the leading cause of death from a single infectious agent globally, with millions of people still undiagnosed or diagnosed late. Conventional case-finding strategies rely heavily on symptom screening using the WHO Four-Symptom Screen ((W4SS; comprising any one of current cough, fever, night sweats, or weight loss) and sputum testing, but these approaches miss a substantial proportion of individuals with active TB disease, particularly those who are asymptomatic or unable to produce sputum. Missed and delayed diagnoses drive ongoing transmission and undermine global TB elimination goals. Recent evidence has shown that diagnostic tools which are more accessible, even if somewhat less sensitive, can still substantially improve TB case detection by reducing diagnostic loss associated with access barriers. This suggests that near point-of-care (NPOC) tests might be highly cost-effective in many settings, because the gains from earlier diagnosis, reduced delays, and broader reach could outweigh losses from slightly lower accuracy. The purpose of this study is to evaluate new, symptom-agnostic screening and diagnostic approaches that can be implemented at lower-level health facilities in high TB-burden, low and middle-income (LMIC) countries for adults ≥15 years and 10-14 years old young adolescents

Подробное описание

The study will generate evidence on the performance, cost-effectiveness, feasibility, acceptability, and scalability of symptom-agnostic algorithms initiated by of computer-aided detection chest radiography (CAD CXR-AI) and near point-of-care (NPOC) molecular assays applied to tongue and sputum swabs. These tools have the potential to identify TB earlier, including among asymptomatic individuals, and to reduce dependence on sputum-based diagnostics alone.

The research questions being addressed are of direct global relevance. There is currently limited real-world evidence on: how CAD CXR-AI and NPOC tongue swab and sputum swab assays compare as initial screening tools; how they can be integrated with WHO-recommended low-complexity nucleic acid amplification tests (LC-NAATs), in efficient algorithms; and whether these approaches can be delivered effectively in primary care and outpatient settings in high TB burden LMIC. Data generated through this study will directly inform WHO guideline development and national TB programme decisions, especially concerning the detection of asymptomatic TB and the role of non-sputum samples.

Вмешательства

• Диагностический тест Near point of care (NPOC) NAATs
  * Near point of care instrument that can test tongue swabs and sputum swabs. * Rapid molecular detection system for detecting infectious diseases included TB, able to provide accurate test results that are comparable to top laboratory PCR tests, while it is easier to use and move around and only takes 15 to 35 minutes to conclude the result.
• Диагностический тест Low-complexity nucleic acid amplification tests (LC-NAATs)
  Semi-quantitative, nested real-time polymerase chain reaction (PCR) diagnostic test for the detection of Mycobacterium tuberculosis (MTB) complex DNA in unprocessed sputum samples\[18\]. It can also detect rifampicin-resistance associated mutations in MTB. Results are automatically displayed on the screen of the system in less than 80 minutes
• Диагностический тест LC-NAAT using pooled testing
  Pooled testing involves combining equal volumes from multiple individuals' samples and testing them together using a single test\[. Pools will be created using remaining samples from 2-4 participants who have screened positive and were able to produce a sputum, guided by CAD CXR-AI thresholds\[20\]. To the possible extend, pools will be suggested by CAD band score: CAD \<0.3 pooled together and 0.3 ≤ CAD \< 0.8 pooled together.
• Диагностический тест Portable Chest X-ray Image Acquisition
  Portable X-ray systems are designed to bring diagnostic imaging to environments where conventional radiography is impractical. They are lightweight, compact, and battery-powered, making them suitable for use in remote or resource-limited settings, or for reaching people with limited mobility. Depending on the model, they can produce between 100 and 400 images on a full charge, allowing extended use without access to electricity.
• Диагностический тест Computer-Aided Detection (CAD) Chest X-ray (CXR-AI)
  Computer-aided detection (CAD) software for chest X-rays is designed to support rapid, automated screening for tuberculosis and other thoracic abnormalities. Software for the study has not been selected yet. It will be a WHO-approved CAD software with final selection through tender processes and in compliance with national regulatory approvals. Operating on mobile or computer platforms, these tools can analyse chest X-rays in less than a minute, distinguishing normal from abnormal scans and high
• Другое Screen TB&HIV sub-study diagnostic test
  The SCREEN TB\&HIV substudy is implemented only in Cameroon, Nigeria and Kenya. HIV testing will therefore not be conducted in Bangladesh or Viet Nam, as HIV testing is not part of routine care pathways at the participating facilities and the study does not introduce additional HIV testing. In addition, Bangladesh and Viet Nam have substantially lower HIV prevalence, making implementation of the HIV substudy operationally unnecessary and not aligned with clinical need
• Другое Screen TB&HIV sub-study diagnostic test
  The CD4 cell count is performed in venous blood in HIV positive patients to assess progression of HIV disease, including risk for developing opportunistic infections. The normal range of CD4 count is from 500 to 1500 cells/mm3 of blood, and it progressively decreases over time in persons who are not receiving or not responding well to ART. Someone with a CD4 count below 200 is described as having advanced HIV disease.
• Другое Screen TB&HIV sub-study diagnostic test
  LAM is a glycolipid of the cell wall of Mycobacterium tuberculosis. LAM is excreted in urine, where it can be detected using rapid lateral flow tests. In inpatient settings, WHO strongly recommends using LAM to assist in the diagnosis of active TB in HIV-positive adults, adolescents and children with signs and symptoms of TB (pulmonary and/or extrapulmonary), or with advanced HIV disease (1) or who are seriously ill (2) or else irrespective of signs and symptoms of TB and with a CD4 cell count o

Первичные конечные точки

• Primary Objective 1: To evaluate the diagnostic yield and comparative accuracy of diagnostic algorithms initiated by CAD CXR-AI and/or NPOC tongue swab and sputum swab screening as initial screening tools in a facility-based case finding strategy [Срок оценки: Completed within 6 month of data collection]
• Primary Objective 1: To evaluate the diagnostic yield and comparative accuracy of diagnostic algorithms initiated by CAD CXR-AI and/or NPOC tongue swab and sputum swab screening as initial screening tools in a facility-based case finding strategy [Срок оценки: Completed within 6 month of data collection]

Вторичные конечные точки (8)

• Secondary Objective 1: To assess timeliness (time to treatment initiation) and proportion initiated on treatment, of CAD CXR-AI and/or NPOC tongue swab and sputum swab -based initiated algorithms [Срок оценки: Completed within 6 month of data collection]
• Secondary Objective 1: To assess timeliness (time to treatment initiation) and proportion initiated on treatment, of CAD CXR-AI and/or NPOC tongue swab and sputum swab -based initiated algorithms [Срок оценки: Completed within 6 month of data collection]
• Secondary Objective 2: To evaluate the cost-effectiveness of CAD CXR-AI and NPOC tongue swab and sputum swab as initial screening tools in facility-based case finding [Срок оценки: Completed within 6 month of data collection]
• Secondary Objective 2: To evaluate the cost-effectiveness of CAD CXR-AI and NPOC tongue swab and sputum swab as initial screening tools in facility-based case finding [Срок оценки: Completed within 6 month of data collection]
• Secondary Objective 3: To evaluate feasibility, acceptability, and scalability of CAD CXR-AI and NPOC tongue swab and sputum swab in routine facility workflows [Срок оценки: Completed within 6 month of data collection]
• Secondary Objective 4: To evaluate the diagnostic performance, efficiency, and feasibility of CAD-guided pooling compared with individual testing [Срок оценки: Completed within 6 month of data collection]
• Secondary Objective 4: To evaluate the diagnostic performance, efficiency, and feasibility of CAD-guided pooling compared with individual testing [Срок оценки: Completed within 6 month of data collection]
• Secondary Objective 4: To evaluate the diagnostic performance, efficiency, and feasibility of CAD-guided pooling compared with individual testing [Срок оценки: Completed within 6 months of data collection]

Критерии участия

Критерии включения

• Age

• Adults aged 15 years and above or
• Adolescents aged 10-14 years
• Facility setting

o Participating healthcare facilities (e.g., primary health centres, district hospitals), including both rural and urban facilities.

• Screening eligibility

o All individuals presenting to the facility, regardless of symptoms or ability to produce sputum, will be eligible for inclusion.

• Consent

• Written informed consent (and assent for adolescents (10-14 years) and adults (≥15 - 17 years) if included) must be obtained according to local ethics and regulatory requirements.

Критерии исключения

• Age

o Below 10 years at enrolment

• Screening eligibility

o Do not screen positive on any tools.

• Consent and follow-up

o Unable or unwilling to provide written informed consent (and assent where applicable) or unwilling to agree to follow-up visits.

• Current TB treatment

o Receiving anti-TB treatment at the time of enrolment, defined as having taken ≥3 doses of TB treatment.

• Recent TB preventive therapy

o Receipt of TB preventive therapy within the last 6 months prior to enrolment.

• Clinical danger signs

o Presence of severe illness at screening, including but not limited to: Respiratory rate >30/min Fever >39°C Pulse rate >120/min Inability to walk unaided

• Duplicate enrolment o Previous enrolment in SCREEN-TB.

Критерии приведены из реестра в оригинале (на английском). Окончательную оценку соответствия проводит исследовательский центр.

Здоровые добровольцы: Да

Дизайн исследования

Распределение

Не применимо

Модель

Одна группа

Маскирование

Открытое

Основная цель

Диагностика

Центры проведения

Список центров уточняется — проверьте первичный протокол.

Публикации

• David A, Singh L, Peloakgosi-Shikwambani K, Nsingwane Z, Molepo V, Cangelosi G, da Silva P, Stevens W, Scott L. Diagnostic accuracy of self-collected tongue swabs for Mycobacterium tuberculosis complex detection in individuals being assessed for tuberculosis in South Africa using the Xpert MTB/RIF Ultra assay. Clin Microbiol Infect. 2025 Jun;31(6):1040-1045. doi: 10.1016/j.cmi.2025.01.029. Epub 20 PMID 39884504
• Ricks S, Denkinger CM, Schumacher SG, Hallett TB, Arinaminpathy N. The potential impact of urine-LAM diagnostics on tuberculosis incidence and mortality: A modelling analysis. PLoS Med. 2020 Dec 11;17(12):e1003466. doi: 10.1371/journal.pmed.1003466. eCollection 2020 Dec. PMID 33306694
• Bjerrum S, Schiller I, Dendukuri N, Kohli M, Nathavitharana RR, Zwerling AA, Denkinger CM, Steingart KR, Shah M. Lateral flow urine lipoarabinomannan assay for detecting active tuberculosis in people living with HIV. Cochrane Database Syst Rev. 2019 Oct 21;10(10):CD011420. doi: 10.1002/14651858.CD011420.pub3. PMID 31633805
• Cohen JF, Korevaar DA, Altman DG, Bruns DE, Gatsonis CA, Hooft L, Irwig L, Levine D, Reitsma JB, de Vet HC, Bossuyt PM. STARD 2015 guidelines for reporting diagnostic accuracy studies: explanation and elaboration. BMJ Open. 2016 Nov 14;6(11):e012799. doi: 10.1136/bmjopen-2016-012799. PMID 28137831
• Sekhon M, Cartwright M, Francis JJ. Acceptability of healthcare interventions: an overview of reviews and development of a theoretical framework. BMC Health Serv Res. 2017 Jan 26;17(1):88. doi: 10.1186/s12913-017-2031-8. PMID 28126032
• French SD, Green SE, O'Connor DA, McKenzie JE, Francis JJ, Michie S, Buchbinder R, Schattner P, Spike N, Grimshaw JM. Developing theory-informed behaviour change interventions to implement evidence into practice: a systematic approach using the Theoretical Domains Framework. Implement Sci. 2012 Apr 24;7:38. doi: 10.1186/1748-5908-7-38. PMID 22531013
• Barker PM, Reid A, Schall MW. A framework for scaling up health interventions: lessons from large-scale improvement initiatives in Africa. Implement Sci. 2016 Jan 29;11:12. doi: 10.1186/s13012-016-0374-x. PMID 26821910
• Klaic M, Kapp S, Hudson P, Chapman W, Denehy L, Story D, Francis JJ. Implementability of healthcare interventions: an overview of reviews and development of a conceptual framework. Implement Sci. 2022 Jan 27;17(1):10. doi: 10.1186/s13012-021-01171-7. PMID 35086538

Идентификаторы

NCT: NCT07517471 · 125

Первоисточники (государственные реестры)

• ClinicalTrials.gov (NIH, США)

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