Research on Key Interventional Technologies for Controlling the Epidemic in High-prevalence Areas of Tuberculosis in Guangxi, China

NCT06702774 | Recruiting DMC

• 1 other identifier: GXTB202108
• Study Type: interventional
• Target: 72,000
• Locations: 1 country
• Sites: 1

Brief Summary

The goal of this study is to find out if using mobile vans with advanced technology can help reduce tuberculosis (TB) in rural Guangxi, China. The study will also examine how practical and cost-effective this approach is. The main questions it aims to answer are: 1) Does this new screening method lower the number of TB cases among high-risk groups? and 2) Is this method practical and acceptable for communities and healthcare workers? Participants in the study will: 1) undergo TB screening with mobile vans that use artificial intelligence (AI) to read chest X-rays, 2) answer a short questionnaire about their symptoms and health history, and 3) provide sputum samples for GeneXpert testing if needed. Some communities will receive the new screening method, while others will continue with usual care. Researchers will compare TB rates in the two groups over three years to see if the new approach works better for TB control. If successful, this method could be used to improve TB control in other areas.

Conditions

Tuberculosis (TB)

Keywords

Tuberculosis; active case finding; mobile van; artificial intelligence; cluster randomized controlled trial; China

Outcome Measures

Primary Outcomes (1)

• Prevalence rate of bacteriologically positive TB

  Prevalence rate of bacteriologically positive TB in Year 3 among the high-risk populations , including those of 65 and older, those who are under 65 but have a history of tuberculosis treatment or have been in close contact with a person diagnosed of TB within the past three years, have been clinically diagnosed with diabetes, HIV, or have a background of working as a miner.

  In year 3 after recruitment

Secondary Outcomes (3)

• Prevalence rate of active TB

  In Year 3 after recruitment

• Notification rates of bacteriologically positive TB

  In Year 3 after recruitment

• Notification rates of active TB cases

  In Year 3 after recruitment

Study Arms (2)

Intervention

EXPERIMENTAL

A single active case finding campaign for Tuberculosis will occur in Year 1 alongside the usual care.

Diagnostic Test: Active case finding

Control

NO INTERVENTION

Usual care will be provided and no active case finding activities will be implemented.

Interventions

Active case finding DIAGNOSTIC_TEST

Villagers will be informed through public announcements and social workers. Before the campaign, social workers and village doctors will recruit participants and obtain consent through door-to-door visits. A mobile van equipped with an AI-assisted digital radiography (DR) machine and a refrigerator will visit villages on agreed dates. Participants will complete a TB symptom questionnaire and undergo DR screening. Those with TB symptoms or abnormal DR results will provide on-site sputum samples and collect additional morning and night samples. Trained staff will ensure proper collection and offer nebulizer support if needed. Samples will be transported daily to hospitals for testing using smear, culture, and GeneXpert. Participants with negative bacteriological results but abnormal findings will be referred for further clinical assessment.

Intervention

Eligibility Criteria

• Age: 15 Years+
• Sex: all
• Healthy Volunteers: Yes
• Age Groups: Child (0-17), Adult (18-64), Older Adult (65+)

You may qualify if:

• all residents who are elderly (i.e., aged 65 and above)
• all residents who are aged 15 to 64 with one of the following conditions: being patients previously treated for TB or close contacts of a patient with a TB patient diagnosed within the last three years; having been clinically diagnosed with diabetes, HIV positive, or worked as a miner
• Have signed consent form

You may not qualify if:

• Residents who refuse participation.

Sponsors & Collaborators

• University of Toronto: lead
• Guangxi Zhuang Autonomous Region Center for Disease Control and Prevention: collaborator

Study Sites (1)

Guangxi Zhuang Autonomous Region Center for Disease Control and Prevention

Nanning, Guangxi, 530000, China

RECRUITING

Related Publications (1)

• Wei X, Liang D, Zhang Z, Thorpe KE, Zhou L, Zhao J, Qin H, Liang X, Cui Z, Huang Y, Huang L, Lin M. Active case finding using mobile vans with artificial intelligence aided radiology tests and sputum collection for rapid diagnostic tests to reduce tuberculosis prevalence among high-risk population in rural China: Protocol for a pragmatic trial. PLoS One. 2025 Apr 11;20(4):e0316073. doi: 10.1371/journal.pone.0316073. eCollection 2025.

  PMID: 40215230 DERIVED

MeSH Terms

Conditions

Tuberculosis

Condition Hierarchy (Ancestors)

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

Study Officials

• Dabin Liang, PhD

  Guangxi Zhuang Autonomous Region Center for Disease Control and Prevention

  PRINCIPAL INVESTIGATOR

• Xiaolin Wei, PhD

  University of Toronto

  PRINCIPAL INVESTIGATOR

Central Study Contacts

Dabin Liang, PhD

CONTACT

+86 771 251 8743; gxmu958@163.com

Xiaoyan Liang

CONTACT

+86 183 7717 1573; lxy530028@163.com

Study Design

• Study Type: interventional
• Phase: not applicable
• Allocation: RANDOMIZED
• Masking: SINGLE
• Who Masked: OUTCOMES ASSESSOR
• Purpose: SCREENING
• Intervention Model: PARALLEL
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Professor

Study Record Dates

• First Submitted: November 20, 2024
• First Posted: November 25, 2024
• Study Start: November 20, 2021
• Primary Completion: January 31, 2025
• Study Completion: April 30, 2025
• Last Updated: December 6, 2024

Record last verified: 2024-12

Data Sharing

• IPD Sharing: Will not share

Locations

CN (1)