Start4All SCREEN-TB PROTOCOL (SCREEN-TB)

Start4All - Start Taking Action for TB Diagnosis SCREEN-TB

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

Study Overview

• Status: Not yet recruiting
• Conditions: TB - Tuberculosis
• Intervention / Treatment: Diagnostic test: Near point of care (NPOC) NAATs; Diagnostic test: Low-complexity nucleic acid amplification tests (LC-NAATs); Diagnostic test: LC-NAAT using pooled testing; Diagnostic test: Portable Chest X-ray Image Acquisition; Diagnostic test: Computer-Aided Detection (CAD) Chest X-ray (CXR-AI); Other: Screen TB&HIV sub-study diagnostic test; Other: Screen TB&HIV sub-study diagnostic test; Other: Screen TB&HIV sub-study diagnostic test

Detailed Description

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.

• Study Type: Interventional
• Enrollment (Estimated): 37000
• Phase: Not Applicable

Contacts and Locations

• Study Contact: Name: Lucy Read, BA; Phone Number: +44 (0)151 705 3715; Email: start4all@lstmed.ac.uk
• Study Contact Backup: Name: Vibol Lem, PhD; Email: vibol.lem@lstmed.ac.uk

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: Child; Adult; Older Adult
• Accepts Healthy Volunteers: Yes

Description

Inclusion Criteria:

1. Age

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

2. Facility setting

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

3. Screening eligibility

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

4. 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.

Exclusion Criteria:

1. Age

   o Below 10 years at enrolment

2. Screening eligibility

   o Do not screen positive on any tools.

3. 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.

4. Current TB treatment

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

5. Recent TB preventive therapy

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

6. 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

7. Duplicate enrolment o Previous enrolment in SCREEN-TB.

Study Plan

How is the study designed?

Design Details

• Primary Purpose: Diagnostic
• Allocation: N/A
• Interventional Model: Single Group Assignment
• Masking: None (Open Label)

Number of Arms

1

Arms and Interventions

Participant Group / Arm

Intervention / Treatment

Other: Diagnostic

Diagnostic test: 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.; Diagnostic test: 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; Diagnostic test: 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.; Diagnostic test: 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.; Diagnostic test: 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 highlighting findings in the lungs, pleura, mediastinum, bones, diaphragm, and heart. In addition to detecting disease, some systems can assist clinicians with tasks such as verifying device placement and measuring distances from anatomical landmarks.; Other: 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; Other: 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.; Other: 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 of less than 200 cells/mm3[23]. In outpatient settings, WHO suggests using LF-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 seriously ill; or else irrespective of signs and symptoms of TB and with a CD4 cell count of less than 100 cells/mm3[23]. LAM tests evaluated in SCREEN TB&HIV are:

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
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	Primary Endpoint 1.1: Diagnostic Yield of TB by algorithm, disaggregated by symptom status; WHO: All participants enrolled in the study (≥10 years); WHAT: Number and proportion (out of attempted TB testing) of participants diagnosed with TB (microbiologically confirmed and clinically diagnosed) per diagnostic algorithm pathway; WHEN: Primary = at completion of diagnostic work-up (Day 1-3); Secondary = confirmed via NTP registry data at treatment initiation; WHERE: Study healthcare facilities and referral laboratories in Bangladesh, Cameroon, Kenya, Nigeria, Viet Nam; WHY: To determine incremental case detection across different screening approaches; HOW MEASURED: oNumerator = number of TB cases identified; oDenominator = total participants screened by each algorithm (including those with invalid and inconclusive results); oStratification = symptomatic vs asymptomatic (per WHO 4-symptom screen); oCase definitions = WHO TB definitions (microbiologically confirmed, clinicaly diagnose	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	Primary Endpoint 1.2: Comparative diagnostic accuracy (sensitivity, specificity, PPV, NPV) of (i) CAD CXR-AI as an initial screening tool, (ii) NPOC tongue swab and sputum swab testing as initial screening tools.; WHO: All participants with interpretable test results; WHAT: Sensitivity, specificity, PPV, NPV of CAD CXR-AI and NPOC tongue swab and sputum swab as initial screening tools; WHEN: Calculated after completion of reference standard testing for all participants; WHERE: Central data analysis; WHY: To compare performance characteristics of screening tools; HOW MEASURED:Reference standard = LC-NAAT;Using standard diagnostic accuracy definitions and reporting all estimates together with 95% confidence intervals;Receiver operating characteristic (ROC) curves for CAD CXR-AI thresholdsPre-specified handling of indeterminate/uninterpretable results	Completed within 6 month of data collection

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
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	Secondary Endpoint 1.1: Time from entering healthcare facility to being initiated on TB treatment according to National TB Programme (NTP) register record; WHO: Participants diagnosed with TB; WHAT: Time from entering healthcare facility to initiation of TB treatment, using NTP register records; WHEN: From date of facility attendance (and, where available, reported symptom onset) to date of treatment start; WHERE: Facility records and NTP registers; WHY: To evaluate timeliness of linkage to care under different algorithms; HOW MEASURED: Extract dates of facility attendance (or specimen collection), diagnosis confirmation, and treatment start from registers; calculate time to treatment initiation in days; analyse using descriptive and time-to-event methods; assessment limited to treatment initiation (no post-treatment follow-up).	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	Secondary Endpoint 1.2: Proportion of individuals screening positive on the diagnostic algorithm who then initiate TB treatment.; WHO: All participants screening positive on diagnostic algorithms; WHAT: Proportion who initiate TB treatment; WHEN: At time of registry-confirmed treatment initiation; WHERE: NTP registers; WHY: To determine effectiveness of linkage to care; HOW MEASURED: Numerator = number starting treatment; Denominator = number screening positive	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	Secondary Endpoint 2.1: Modelled incremental cost per person diagnosed with TB from a societal perspective (disaggregated by provider and beneficiary), comparing multiple screening and diagnostic algorithms where: CAD CXR-AI and NPOC are incorporated as initial screening tests Varying CAD thresholds for determining whether pooled or individual LC-NAAT testing is subsequently used are treated as independent and separate initial CAD CXR-AI screening tests; WHO: All participants enrolled; WHAT: Direct evaluation of costs and cost-effectiveness of CAD vs NPOC tongue swab and sputum swab as:stand-alone initial screening toolspart of diagnostic algorithms; WHEN: During study and at study end; WHERE: Facility costing and central analysis; WHY: To inform programmatic adoption; HOW MEASURED: Measured cost per TB case diagnosed, modelled incremental cost-effectiveness ratios	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	Secondary Endpoint 2.2: Modelled incremental cost per person diagnosed with TB who initiates treatment from a societal perspective (disaggregated by provider and beneficiary), comparing multiple screening and diagnostic algorithms where: CAD CXR-AI and NPOC are incorporated as initial screening tests Varying CAD thresholds for determining whether pooled or individual LC-NAAT testing is subsequently used are treated as independent and separate initial CAD CXR-AI screening tests; WHO: All participants enrolled; WHAT: Direct evaluation of costs and cost-effectiveness of CAD vs NPOC tongue swab and sputum swab as:stand-alone initial screening toolspart of diagnostic algorithms; WHEN: During study and at study end; WHERE: Facility costing and central analysis; WHY: To inform programmatic adoption; HOW MEASURED: Modelled cost per person who initiates treatment, modelled incremental cost-effectiveness ratios	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	Secondary Endpoint 3.1: Feasibility and acceptability of CAD CXR-AI and NPOC tongue swab and sputum swab from diverse perspectives including people seeking care, and health system, and policy makers; WHO: People seeking care, healthcare providers, policymakers; WHAT: Feasibility, acceptability, and scalability of CAD CXR-AI and NPOC tongue swab and sputum swab; WHEN: During and after implementation; WHERE: Study facilities and through qualitative sub-studies; WHY: To evaluate real-world integration and sustainability; HOW MEASURED: Participant and provider interviews, FGDs; structured observation; time-motion analysis; metrics such as proportion able to provide samples and proportion of valid results	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	Secondary Endpoint 4.1: Sensitivity and specificity of CAD-guided pooling relative to individual testing; WHO: All enrolled participants providing tongue or sputum swabs eligible for both individual and pooled testing.; WHAT: Diagnostic accuracy (sensitivity, specificity, PPV, NPV) of CAD-guided pooling compared with individual LC-NAAT results as reference.; WHEN: completion of diagnostic work-up; secondary confirmation against NTP registry data at treatment initiation.; WHERE: Study facilities and laboratories in Bangladesh, Cameroon, Kenya, Nigeria, Viet Nam.; WHY: To determine whether CAD-guided pooling maintains diagnostic accuracy while reducing testing volumes.; HOW MEASURED:Numerator (sensitivity) = number of TB-positive pools correctly identified.Denominator (specificity) = total number of TB-negative individuals per reference testing.Stratification = by CAD score band and specimen type (tongue swab, sputum swab).	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	Secondary Endpoint 4.2: Proportion of tests saved and associated change in turnaround time; WHO: All pooled samples from enrolled participants eligible for CAD-guided pooling.; WHAT: Number and proportion of tests saved by CAD-guided pooling compared with individual and turnaround time for reporting results.; WHEN: Measured in real-time during study implementation; time recorded from specimen collection to availability of test result.; WHERE: Study facilities and laboratories in Bangladesh, Cameroon, Kenya, Nigeria, Viet Nam.; WHY: To assess efficiency gains from pooling strategies and their impact on timeliness of results.; HOW MEASURED:Numerator (tests saved) = number of individual cartridges not required due to pooling.Denominator (tests saved) = total number of cartridges that would have been required for individual testing alone.Turnaround time = median hours from specimen collection to result availability; stratified by pooled vs individual pathways.	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	Secondary Endpoint 4.3: Feasibility and acceptability of CAD-guided pooling from perspectives of laboratory staff, providers, and policymakers; WHO: Laboratory staff, healthcare and policymakers engaged in or overseeing CAD-guided pooling activities.; WHAT: Perceptions of feasibility (integration into, training , workload, error rates) and acceptability (appropriateness, confidence, value); WHEN: During implementation and at study end via interviews, discussions, and surveys.; WHERE: Healthcare facilities, laboratories, and NTB programme offices in-country.; WHY: To identify barriers and facilitators to implementation of CAD-guided pooling informing potential scale-up.; HOW MEASURED:Qualitative data: thematically analysed from key informant interviews and focus groups.Quantitative data: survey scores on feasibility and acceptability domains (e.g. workload, clarity of purpose, perceived reliability).Stratification = by stakeholder group (lab staff, providers, policymakers).	Completed within 6 months of data collection

Other Outcome Measures

Outcome Measure	Measure Description	Time Frame
Exploratory objective (SCREEN-TB & HIV substudy) To assess added diagnostic value of newer ultra-sensitive LAM tests (Biopromic and Plasmonic Fluor LAM RDT) among people living with HIV	Exploratory Endpoint 1.1: Incremental TB cases detected using newer ultra-sensitive LAM vs. Alere LAM and vs no use of LAM testing among HIV positive patients; WHO: Presumptive TB patients (positive in one or more SCREEN-TB pathways) with HIV; WHAT: Number and proportion of participants additionally diagnosed with LAM testing in comparison to LC-NAAT-confirmed TB; WHEN: At completion of diagnostic work-up (Day 1-3); then confirmed via NTP registry data at treatment initiation; WHERE: Study facilities and laboratories in Cameroon, Kenya and Nigeria; WHY: To determine incremental case detection among people living with HIV (PLHIV) vs LC-NAAT; HOW MEASURED:Number of clinically diagnosed TB cases, microbiologically negative and positive by LAMTotal participants with an HIV positive test and clinically diagnosed with TB but had a negative LC-NAAT resultCD4 cell counts < 200/mm3, CD4 cell counts < 100/m3WHO TB definitions (microbiologically confirmed, clinically diagnosed)	Completed within 6 month of data collection
Exploratory objective (SCREEN-TB & HIV substudy) To assess added diagnostic value of newer ultra-sensitive LAM tests (Biopromic and Plasmonic Fluor LAM RDT) among people living with HIV	Exploratory Endpoint 1.2: Sensitivity and specificity of the ultra-sensitive LAM vs. Alere LAM (comparator) and of ultra-sensitive LAM compared to LC-NAAT-based reference standard; WHO: Presumptive TB patients with HIV; WHAT: Number and proportion of participants correctly diagnosed with ultrasensitive LAM test in comparison to ALERE test using LC-NAAT status and clinical TB diagnosis as the reference.; WHEN: Completion of diagnostic work-up (Day 1-3); then confirmed via NTP registry data at treatment initiation; WHERE: Study facilities and laboratories in Cameroon, Kenya and Nigeria; WHY: To determine sensitivity and specificity of ultrasensitive LAM tests vs ALERE and LC-NAAT among PLHIV; HOW MEASURED:Number of clinically diagnosed TB cases, microbiologically negative and positive by LAMTotal participants with an HIV positive test and clinically diagnosed with TB but had a negative LC-NAAT resultCD4 cell counts < 200/mm3, CD4 cell counts < 100/m3WHO TB definitions	Completed within 6 month of data collection
Exploratory objective (SCREEN-TB & HIV substudy) To assess added diagnostic value of newer ultra-sensitive LAM tests (Biopromic and Plasmonic Fluor LAM RDT) among people living with HIV	Exploratory Endpoint 1.3: Error/invalid rates; ease-of-use.; WHO: People seeking care, healthcare providers; WHAT: Feasibility, acceptability and scalability of ultrasensitive LAM tests in comparison to Alere; WHEN: During and after implementation; WHERE: Study facilities and through qualitative sub-studies; WHY: To evaluate real-world integration; HOW MEASURED: Operator questionnaires on technology easy-of-use, structured observation; time-motion analysis; metrics such as proportion able and willing to provide samples and proportion of valid results	Completed within 6 month of data collection
Exploratory objective (SCREEN-TB & HIV substudy) To assess added diagnostic value of newer ultra-sensitive LAM tests (Biopromic and Plasmonic Fluor LAM RDT) among people living with HIV	Exploratory Endpoint 1.4: Cost per additional case detected; WHO: All participants taking part in SCREEN-TB&HIV sub study; WHAT: Direct evaluation of costs and cost-effectiveness of LAM and CD4 count testingstand-alone as initial screening tools among PLHIV presumptive of TB infectionpart of diagnostic algorithms; WHEN: During study and at study end; WHERE: Facility costing and central analysis; WHY: To inform programmatic adoption; HOW MEASURED: Cost per TB case detected, incremental cost-effectiveness ratios	Completed within 6 month of data collection
Exploratory objective Pooling of Tongue Swabs and Sputum Swabs Sub-study Exploratory Objective 2: To evaluate the diagnostic yield, accuracy, and efficiency of pooled versus individual testing of tongue swabs and sputum swabs using NPOC	Exploratory Endpoint 2.1: Diagnostic yield of TB from pooled tongue swabs versus individual tongue swabs; WHO: All participants (≥10 years) providing tongue swab specimens.; WHAT: Number and proportion (out of attempted TB testing) of TB diagnoses from pooled tongue swabs compared with individual swabs (reference).; WHEN: At completion of diagnostic work-up (Day 1-3); confirmation via NTP register at treatment initiation.; WHERE: Study healthcare facilities and referral laboratories in Bangladesh, Cameroon, Kenya, Nigeria, Viet Nam.; WHY: To determine whether tongue swab pooling retains diagnostic yield compared with individual testing.; HOW MEASURED:Numerator = TB-positive results from pooled tongue swabs.Denominator = total number of individuals tested.Reference = individual tongue swab LC-NAAT results.Stratification = symptomatic vs asymptomatic.	Completed within 6 month of data collection
Exploratory objective Pooling of Tongue Swabs and Sputum Swabs Sub-study Exploratory Objective 2: To evaluate the diagnostic yield, accuracy, and efficiency of pooled versus individual testing of tongue swabs and sputum swabs using NPOC	Exploratory Endpoint 2.2: Diagnostic yield of TB from pooled tongue swabs versus individual sputum swabs; WHO: All participants (≥10 years) providing tongue swab specimens.; WHAT: Number and proportion (out of attempted TB testing) of TB diagnoses from pooled sputum swabs compared with individual swabs (reference).; WHEN: At completion of diagnostic work-up (Day 1-3); confirmation via NTP register at treatment initiation.; WHERE: Study healthcare facilities and referral laboratories in Bangladesh, Cameroon, Kenya, Nigeria, Viet Nam.; WHY: To determine whether sputum swab pooling retains diagnostic yield compared with individual testing.; HOW MEASURED:Numerator = TB-positive results from pooled sputum swabs.Denominator = total number of individuals tested.Reference = individual sputum swab LC-NAAT results.Stratification = symptomatic vs asymptomatic.	Completed within 6 month of data collection
Exploratory objective Pooling of Tongue Swabs and Sputum Swabs Sub-study Exploratory Objective 2: To evaluate the diagnostic yield, accuracy, and efficiency of pooled versus individual testing of tongue swabs and sputum swabs using NPOC	Exploratory Endpoint 2.3: Comparative diagnostic accuracy (sensitivity, specificity, PPV, NPV) of tongue vs sputum pooling; WHO: All participants providing both tongue and sputum swabs.; WHAT: Accuracy of pooled tongue vs sputum swab testing relative to individual results.; WHEN: At completion of diagnostic work-up (Day 1-3).; WHERE: Study sites as above.; WHY: To identify whether tongue or sputum pooling offers better performance.; HOW MEASURED:Sensitivity, specificity, PPV, NPV calculated against individual swab results.Stratification = by symptom status and CAD score band.	Within 6 months of data collection
Exploratory objective Pooling of Tongue Swabs and Sputum Swabs Sub-study Exploratory Objective 2: To evaluate the diagnostic yield, accuracy, and efficiency of pooled versus individual testing of tongue swabs and sputum swabs using NPOC	Exploratory Endpoint 2.4: Invalid or error rate of pooled vs individual testing; WHO: All pooled and individual swab samples tested.; WHAT: Proportion of invalid/error results in pooled vs individual testing.; WHEN: During study implementation, measured in real-time.; WHERE: Study labs across all participating countries.; WHY: To assess whether pooling increases technical error rates.; HOW MEASURED:Numerator = number of invalid/error results.Denominator = total tests conducted (pooled or individual).	Within 6 months of data collection
Exploratory objective Pooling of Tongue Swabs and Sputum Swabs Sub-study Exploratory Objective 2: To evaluate the diagnostic yield, accuracy, and efficiency of pooled versus individual testing of tongue swabs and sputum swabs using NPOC	Exploratory Endpoint 2.5: Efficiency outcomes (tests saved, cartridge use, estimated cost savings); WHO: All swab tests (tongue and sputum) eligible for pooling.; WHAT: Number of cartridges/tests saved and estimated cost savings compared with individual-only testing.; WHEN: Throughout study implementation.; WHERE: All study sites and labs.; WHY: To measure efficiency benefits of pooling strategies.; HOW MEASURED:Numerator = cartridges saved by pooling.Denominator = total that would have been used for individual-only testing.Costs = estimated from provider and beneficiary perspectives.	Within 6 months of data collection
Exploratory objective Self-Swab Sub-study Exploratory Objective 3: Comparison between Provider-collected swab and Self-swab collection	Secondary Endpoint 3.1: Feasibility and acceptability of CAD CXR-AI and NPOC tongue swab and sputum swab from diverse perspectives including people seeking care, and health system, and policy makers; WHO: People seeking care, healthcare providers, policymakers; WHAT: Feasibility, acceptability, and scalability of CAD CXR-AI and NPOC tongue swab and sputum swab; WHEN: During and after implementation; WHERE: Study facilities and through qualitative sub-studies; WHY: To evaluate real-world integration and sustainability; HOW MEASURED: Participant and provider interviews, FGDs; structured observation; time-motion analysis; metrics such as proportion able to provide samples and proportion of valid results	Within 6 Months of data collection
Exploratory objective Self-Swab Sub-study Exploratory Objective 3: Comparison between Provider-collected swab and Self-swab collection	Exploratory Endpoint 3.2: Diagnostic accuracy of self-collected tongue swabs; WHO: Participants who completed self-swab and had individual results available.; WHAT: Sensitivity, specificity, PPV, NPV of self-swabs relative to HCW-swabs as reference.; WHEN: At completion of diagnostic work-up (Day 1-3); confirmation via NTP register at treatment initiation.; WHERE: Study healthcare facilities in all countries.; WHY: To assess whether self-collection achieves comparable diagnostic yield to HCW collection.; HOW MEASURED: Standard accuracy metrics using HCW swabs and final diagnostic algorithm as reference.	Within 6 months of data collection
Exploratory objective Self-Swab Sub-study Exploratory Objective 3: Comparison between Provider-collected swab and Self-swab collection	Exploratory Endpoint 3.3: Diagnostic accuracy of HCW-collected tongue swabs; WHO: All participants (≥10 years) eligible for both self- and HCW-collected swabs.; WHAT: Number and proportion of TB diagnoses from self-collected vs HCW-collected swabs with HCW swabs evaluated against an LC-NAAT-based reference standard.; WHEN: At completion of diagnostic work-up (Day 1-3); confirmation via NTP register at treatment initiation.; WHERE: Study healthcare facilities in all countries.; WHY: To assess whether self-collection achieves comparable diagnostic yield to HCW collection.; HOW MEASURED: Standard accuracy metrics using HCW swabs and final diagnostic algorithm as reference.	Within 6 months of data collection
Exploratory objective Sequential Tongue Swab Collection Sub-study Exploratory Objective 4: To evaluate the diagnostic yield and incremental value of sequentially collected tongue swabs for TB diagnosis using an NPOC test device	Exploratory Endpoint 4.1: Diagnostic yield of TB by swab order (1 through 4); WHO: All participants providing four sequential tongue swabs.; WHAT: Number and proportion of TB-positive results for each swab order (1-4).; WHEN: At completion of diagnostic work-up (Day 1-3).; WHERE: Study healthcare facilities and labs in all countries.; WHY: To evaluate whether diagnostic yield varies by swab sequence.; HOW MEASURED:Numerator = TB-positive results per swab order.Denominator = total tests attempted.	Within 6 months of data collection
Exploratory objective Sequential Tongue Swab Collection Sub-study Exploratory Objective 4: To evaluate the diagnostic yield and incremental value of sequentially collected tongue swabs for TB diagnosis using an NPOC test	Exploratory Endpoint 4.2: Diagnostic accuracy using first swab only, 1-2 combined, 1-3 combined, 1-4 combined; WHO: Participants with complete sequential swab sets.; WHAT: Sensitivity, specificity, PPV, NPV across cumulative swab combinations.; WHEN: At completion of diagnostic work-up.; WHERE: Study sites.; WHY: To determine optimal number of swabs required for reliable detection.; HOW MEASURED: Accuracy statistics estimated using LC-NAAT as the reference standard.	Within 6 months of data collection
Exploratory objective Sequential Tongue Swab Collection Sub-study Exploratory Objective 4: To evaluate the diagnostic yield and incremental value of sequentially collected tongue swabs for TB diagnosis using an NPOC test device	Exploratory Endpoint 4.3: Incremental diagnostic yield by swab order (additional positives with each subsequent swab); WHO: Participants with sequential swab sets.; WHAT: Number of additional TB-positive results detected as each swab is added (e.g. swab 2 beyond swab 1, etc).; WHEN: Day 1-3 diagnostic period.; WHERE: All study sites.; WHY: To quantify added value of each extra swab for diagnostic sensitivity.; HOW MEASURED:Incremental positives = TB-positive cases detected by swab n but missed by swabs 1 to n-1.Denominator = total participants tested.	Within 6 months of data collection
Objective 5 Exploratory objective Lung Flute ECO sub study To evaluate the diagnostic yield of tuberculosis and sputum production using the Lung Flute ECO device compared with standard sputum collection without the device	Exploratory Endpoint 5.1: Incremental diagnostic yield of TB compared with sputum collection without the Lung Flute ECO device; WHO: Participants enrolled in SCREEN-TB who are unable or have difficulty producing sputum at baseline.; WHAT: Difference in the proportion of participants with TB detected on diagnostic testing using sputum collected with the Lung Flute ECO device compared with sputum collection without the device.; WHEN: Assessed after completion of diagnostic testing.; WHERE: Central data analysis and across participating SCREEN-TB countries.; WHY: To determine whether the Lung Flute ECO increases TB detection among people with difficulty producing sputum in community-based screening settings.; HOW MEASURED: Comparison of TB yield on diagnostic tests performed on sputum collected with versus without the Lung Flute ECO device, with confidence intervals and pre-specified handling of invalid results.	within 6 months of data collection
Objective 5 Exploratory objective Lung Flute ECO sub study To evaluate the diagnostic yield of tuberculosis and sputum production using the Lung Flute ECO device compared with standard sputum collection without the devic	Exploratory Endpoint 5.2 : Incremental yield of participants able to produce sputum greater than 1 mL compared with sputum collection without the Lung Flute ECO device; WHO: Adults and adolescents enrolled in SCREEN-TB who are unable or have difficulty producing sputum at baseline.; WHAT: Difference in the proportion of participants able to produce sputum volume greater than 1 mL with the Lung Flute ECO device compared with without the device.; WHEN: Assessed at the sputum collection visit.; WHERE: Central data analysis and across participating SCREEN-TB countries.; WHY: To determine whether the Lung Flute ECO improves sputum provision among people with difficulty producing sputum.; HOW MEASURED: Comparison of proportions producing sputum volume greater than 1 mL with versus without the Lung Flute ECO device	Within 6 months of data collection
Exploratory Objective 6: To estimate downstream health economic outcomes such as disability-adjusted life years (DALYs)	Secondary Endpoint 6.1: Incremental cost per DALY averted (by diagnostic algorithm); WHO: All participants enrolled; WHAT: Direct evaluation of costs and cost-effectiveness of CAD vs NPOC tongue swab and sputum swab as:stand-alone initial screening toolspart of diagnostic algorithms; WHEN: During study and at study end; WHERE: Facility costing and central analysis; WHY: To inform global policy; HOW MEASURED: Modelled incremental cost per DALY averted	within 6 months of data collection

Collaborators and Investigators

• Sponsor: Liverpool School of Tropical Medicine
• Investigators: Study Director: Tom Wingfield, PhD FRCP DTMH DipHIV, Liverpool School of Tropical Medicine; Study Director: Vibol Lem, PhD, Liverpool School of Tropical Medicine

Publications and helpful links

General Publications

• Harris PA, Taylor R, Thielke R, Payne J, Gonzalez N, Conde JG. Research electronic data capture (REDCap)--a metadata-driven methodology and workflow process for providing translational research informatics support. J Biomed Inform. 2009 Apr;42(2):377-81. doi: 10.1016/j.jbi.2008.08.010. Epub 2008 Sep 30.
• 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.
• 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.
• Theron G, Zijenah L, Chanda D, Clowes P, Rachow A, Lesosky M, Bara W, Mungofa S, Pai M, Hoelscher M, Dowdy D, Pym A, Mwaba P, Mason P, Peter J, Dheda K; TB-NEAT team. Feasibility, accuracy, and clinical effect of point-of-care Xpert MTB/RIF testing for tuberculosis in primary-care settings in Africa: a multicentre, randomised, controlled trial. Lancet. 2014 Feb 1;383(9915):424-35. doi: 10.1016/S0140-6736(13)62073-5. Epub 2013 Oct 28.
• WHO consolidated guidelines on tuberculosis: Module 2: screening - systematic screening for tuberculosis disease [Internet]. Geneva: World Health Organization; 2021. No abstract available. Available from http://www.ncbi.nlm.nih.gov/books/NBK569338/
• 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.
• 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.
• 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.
• Codlin AJ, Vo LNQ, Garg T, Banu S, Ahmed S, John S, Abdulkarim S, Muyoyeta M, Sanjase N, Wingfield T, Iem V, Squire B, Creswell J. Expanding molecular diagnostic coverage for tuberculosis by combining computer-aided chest radiography and sputum specimen pooling: a modeling study from four high-burden countries. BMC Glob Public Health. 2024;2(1):52. doi: 10.1186/s44263-024-00081-2. Epub 2024 Aug 1.
• Iem V, Byrne RL, Garg T, Santos V, Yassin MA, Kathure I, Donkeng Donfack VF, Vuchas C, Bilder CR, Creswell J, Squire SB, Wingfield T. Pooled testing for TB: revisiting a cost-saving innovation. Lancet Respir Med. 2025 Nov;13(11):958-961. doi: 10.1016/S2213-2600(25)00328-5. Epub 2025 Sep 25. No abstract available.
• Kohli M, Inbaraj LR, Salomon A, Scandrett K, Korobitsyn A, Ismail N, Srinivasalu VA, Daniel J, Steingart KR, Takwoingi Y. Low-complexity automated nucleic acid amplification tests for extrapulmonary tuberculosis and rifampicin resistance in adults and adolescents. Cochrane Database Syst Rev. 2025 Aug 4;8(8):CD012768. doi: 10.1002/14651858.CD012768.pub4.
• Qin ZZ, Naheyan T, Ruhwald M, Denkinger CM, Gelaw S, Nash M, Creswell J, Kik SV. A new resource on artificial intelligence powered computer automated detection software products for tuberculosis programmes and implementers. Tuberculosis (Edinb). 2021 Mar;127:102049. doi: 10.1016/j.tube.2020.102049. Epub 2021 Jan 4.
• Steadman A, Kumar KM, Asege L, Kato-Maeda M, Mukwatamundu J, Shah K, Trang T, Ball A, Khimani K, Kim Dung DT, Michael JS, Christopher DJ, Phan H, Yerlikaya S, Nahid P, Denkinger CM, Cattamanchi A, Andama A. Diagnostic accuracy of swab-based molecular tests for tuberculosis using near-point-of-care platforms: a multi-country evaluation. EBioMedicine. 2025 Nov;121:105991. doi: 10.1016/j.ebiom.2025.105991. Epub 2025 Oct 31.
• 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 2025 Jan 28.
• 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.
• 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.
• Husereau D, Drummond M, Augustovski F, de Bekker-Grob E, Briggs AH, Carswell C, Caulley L, Chaiyakunapruk N, Greenberg D, Loder E, Mauskopf J, Mullins CD, Petrou S, Pwu RF, Staniszewska S; CHEERS 2022 ISPOR Good Research Practices Task Force. Consolidated Health Economic Evaluation Reporting Standards 2022 (CHEERS 2022) statement: updated reporting guidance for health economic evaluations. BMC Med. 2022 Jan 12;20(1):23. doi: 10.1186/s12916-021-02204-0.
• Hamasur B, Okunola AO, Sserubiri J, Nwamba WV, Abdulgader SM, Ignatowich L, Rasool O, Nabatanzi R, Lorente SP, Giraldos D, Joloba M, Warren RM, Ssengooba W, Theron G. A new rapid lipoarabinomannan urine assay for tuberculosis: a two-centre diagnostic accuracy evaluation in outpatients with and without HIV. Res Sq [Preprint]. 2025 Feb 18:rs.3.rs-5386988. doi: 10.21203/rs.3.rs-5386988/v2.
• Gils T, Hella J, Jacobs BKM, Sossen B, Mukoka M, Muyoyeta M, Nakabugo E, Van Nguyen H, Ubolyam S, Mace A, Vermeulen M, Nyangu S, Sanjase N, Sasamalo M, Dinh HT, Ngo TA, Manosuthi W, Jirajariyavej S, Denkinger CM, Nguyen NV, Avihingsanon A, Nakiyingi L, Szekely R, Kerkhoff AD, MacPherson P, Meintjes G, Reither K, Ruhwald M. A Prospective Evaluation of the Diagnostic Accuracy of the Point-of-Care VISITECT CD4 Advanced Disease Test in 7 Countries. J Infect Dis. 2025 Feb 4;231(1):e82-e90. doi: 10.1093/infdis/jiae374.
• Febi AR, Manu MK, Mohapatra AK, Praharaj SK, Guddattu V. Psychological stress and health-related quality of life among tuberculosis patients: a prospective cohort study. ERJ Open Res. 2021 Aug 31;7(3):00251-2021. doi: 10.1183/23120541.00251-2021. eCollection 2021 Jul.
• Kojima N, Turner F, Slepnev V, Bacelar A, Deming L, Kodeboyina S, Klausner JD. Self-Collected Oral Fluid and Nasal Swabs Demonstrate Comparable Sensitivity to Clinician Collected Nasopharyngeal Swabs for Coronavirus Disease 2019 Detection. Clin Infect Dis. 2021 Nov 2;73(9):e3106-e3109. doi: 10.1093/cid/ciaa1589.
• WHO consolidated guidelines on tuberculosis: Module 3: Diagnosis [Internet]. Geneva: World Health Organization; 2025. No abstract available. Available from http://www.ncbi.nlm.nih.gov/books/NBK614646/
• Storla DG, Yimer S, Bjune GA. A systematic review of delay in the diagnosis and treatment of tuberculosis. BMC Public Health. 2008 Jan 14;8:15. doi: 10.1186/1471-2458-8-15.
• Sossen B, Meintjes G. Development of accurate non-sputum-based diagnostic tests for tuberculosis: an ongoing challenge. Lancet Glob Health. 2023 Jan;11(1):e16-e17. doi: 10.1016/S2214-109X(22)00513-7. No abstract available.
• Han ZL, Zhang YY, Li J, Gao S, Liu W, Yang WJ, Xing ZH. A systematic review and meta-analysis of artificial intelligence software for tuberculosis diagnosis using chest X-ray imaging. J Thorac Dis. 2025 May 30;17(5):3223-3237. doi: 10.21037/jtd-2025-604. Epub 2025 May 27.
• Wood RC, Andama A, Hermansky G, Burkot S, Asege L, Job M, Katumba D, Nakaye M, Mwebe SZ, Mulondo J, Bachman CM, Nichols KP, Le Ny AM, Ortega C, Olson RN, Weigel KM, Olson AM, Madan D, Bell D, Cattamanchi A, Worodria W, Semitala FC, Somoskovi A, Cangelosi GA, Minch KJ. Characterization of oral swab samples for diagnosis of pulmonary tuberculosis. PLoS One. 2021 May 17;16(5):e0251422. doi: 10.1371/journal.pone.0251422. eCollection 2021.
• Lessells RJ, Cooke GS, McGrath N, Nicol MP, Newell ML, Godfrey-Faussett P. Impact of Point-of-Care Xpert MTB/RIF on Tuberculosis Treatment Initiation. A Cluster-randomized Trial. Am J Respir Crit Care Med. 2017 Oct 1;196(7):901-910. doi: 10.1164/rccm.201702-0278OC.
• Frascella B, Richards AS, Sossen B, Emery JC, Odone A, Law I, Onozaki I, Esmail H, Houben RMGJ. Subclinical Tuberculosis Disease-A Review and Analysis of Prevalence Surveys to Inform Definitions, Burden, Associations, and Screening Methodology. Clin Infect Dis. 2021 Aug 2;73(3):e830-e841. doi: 10.1093/cid/ciaa1402.
• Stuck L, Klinkenberg E, Abdelgadir Ali N, Basheir Abukaraig EA, Adusi-Poku Y, Alebachew Wagaw Z, Fatima R, Kapata N, Kapata-Chanda P, Kirenga B, Maama-Maime LB, Mfinanga SG, Moyo S, Mvusi L, Nandjebo N, Nguyen HV, Nguyen HB, Obasanya J, Adedapo Olufemi B, Patrobas Dashi P, Raleting Letsie TJ, Ruswa N, Rutebemberwa E, Senkoro M, Sivanna T, Yuda HC, Law I, Onozaki I, Tiemersma E, Cobelens F; scTB Meta Investigator Group. Prevalence of subclinical pulmonary tuberculosis in adults in community settings: an individual participant data meta-analysis. Lancet Infect Dis. 2024 Jul;24(7):726-736. doi: 10.1016/S1473-3099(24)00011-2. Epub 2024 Mar 12.
• Dheda K, Perumal T, Fox GJ. Asymptomatic tuberculosis: undetected and underestimated, but not unimportant. Lancet. 2025 May 24;405(10492):1797-1800. doi: 10.1016/S0140-6736(25)00555-0. Epub 2025 Mar 22. No abstract available.

Study record dates

Study Major Dates

• Study Start (Estimated): April 1, 2026
• Primary Completion (Estimated): January 1, 2027
• Study Completion (Estimated): May 1, 2027

Study Registration Dates

• First Submitted: February 4, 2026
• First Submitted That Met QC Criteria: April 1, 2026
• First Posted (Actual): April 8, 2026

Study Record Updates

• Last Update Posted (Actual): April 8, 2026
• Last Update Submitted That Met QC Criteria: April 1, 2026
• Last Verified: November 1, 2025

More Information

Terms related to this study

• Keywords: TB; Diagnostics
• Additional Relevant MeSH Terms: Latent Infection; Infections; Gram-Positive Bacterial Infections; Bacterial Infections; Bacterial Infections and Mycoses; Actinomycetales Infections; Mycobacterium Infections; Tuberculosis; Latent Tuberculosis; Diagnostic Techniques and Procedures; Diagnosis; Diagnostic Imaging; Diagnosis, Computer-Assisted
• Other Study ID Numbers: 125 (Norgine)

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: YES
• IPD Plan Description: At the end of the study, after the primary results have been published, the individual participant data (IPD) and associated documentation (e.g. protocol, statistical analysis plan, annotated blank CRF) will be prepared in order to be shared with external researchers. IPD will only be shared with external researchers if the participants have consented to this onward disclosure, IPD has been fully anonymised prior to sharing.
• IPD Sharing Time Frame: IPD will be available for a maximum of 5 years after study close
• IPD Sharing Access Criteria: All requests for access to the IPD will be assessed by the Sponsor and must be agreed by all Data Controller organisations.
• IPD Sharing Supporting Information Type: STUDY_PROTOCOL; SAP; CSR

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No