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NCT06017843: SPOT-TB
Impact Evaluation of Use of MATCH AI Predictive Modelling for Identification of Hotspots for TB Active Case Finding
NA trial testing Camps site selection for active case finding for TB using MATCH-AI in Tuberculosis in 180,000 participants. Currently enrolling.
31 October 2024
Quick facts
| Lead sponsor | Centre for Global Public Health Pakistan |
|---|---|
| Phase | NA |
| Status | Recruiting now |
| Study type | INTERVENTIONAL |
| Allocation | randomized |
| Design | crossover |
| Masking | single |
| Primary purpose | health services research |
| Enrollment | 180,000 |
| Start date | 1 September 2023 |
| Primary completion | 31 October 2024 |
| Estimated completion | 30 June 2025 |
| Sites | 1 location across Pakistan |
Drugs / interventions tested
- Camps site selection for active case finding for TB using MATCH-AI
Conditions studied
- Tuberculosis — all drugs for Tuberculosis →
Sponsor
Centre for Global Public Health Pakistan
Who can join
15 and older, any sex, with Tuberculosis. Patients with the condition only — healthy volunteers not accepted.
Sponsor's own description
The aim of this pragmatic, stepped wedge cluster-randomized trial is to measure the comparative yield (number of incident TB cases diagnosed during active case-finding camps) using a site selection approach based on predictions generated via an artificial intelligence software called MATCH-AI (intervention group) versus the conventional approach of camp site selection using field-staff knowledge and experience (control group). The trial will help inform whether a targeted approach towards screening for TB using artificial-intelligence can improve yields of TB cases detected through community-based active case-finding.
Publications & conference data
2 peer-reviewed publications reference this trial (live from Europe PMC):
-
Geographical targeting of active case finding for tuberculosis in Pakistan using hotspots identified by artificial intelligence software (SPOT-TB): study protocol for a pragmatic stepped wedge cluster randomised control trial.
Zaidi SMA, Mahfooz A, Latif A, Nawaz N, et al · · 2024 · cited 4× · PMID 38991950 · DOI 10.1136/bmjresp-2023-002079 -
Geographical targeting of active case finding for tuberculosis in Pakistan using artificial intelligence software (SPOT-TB): a pragmatic stepped wedge cluster randomized control trial
Mahfooz A, Latif A, Asad Zaidi SM, Ahmed W, et al · · 2026 · DOI 10.64898/2026.05.20.26348577
Verify or expand the search:
- PubMed search for NCT06017843
- Europe PMC full search
- ASCO Meeting Library
- ESMO Meeting Library
- bioRxiv preprints
- medRxiv preprints
- Google Scholar
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Verify against primary sources
- ClinicalTrials.gov — authoritative US registry record
- WHO ICTRP — international registry index
- EU Clinical Trials Register
- Sponsor press releases (Google)
- Trial protocol + status: ClinicalTrials.gov NCT06017843 (US National Library of Medicine, public domain)
- Publications: Europe PMC API search by NCT ID, retrieved 10 June 2026
- Drug + disease cross-links: matched in real time against Drug Landscape's normalised drug + company + condition tables
- Sponsor: as reported to ClinicalTrials.gov by Centre for Global Public Health Pakistan
- Last refreshed: 25 July 2024
Drug Landscape aggregates and links these public records for informational use only. Always verify against the primary source before clinical or regulatory decisions. Canonical URL: https://druglandscape.com/trial/NCT06017843.
Primary sources · FDA · ClinicalTrials.gov · EMA · SEC EDGAR · ChEMBL · Wikidata · full sourcing