Recruitment

Recruitment Status
Recruiting
Estimated Enrollment
Same as current

Summary

Conditions
Tuberculosis
Type
Interventional
Phase
Not Applicable
Design
Allocation: RandomizedIntervention Model: Parallel AssignmentMasking: None (Open Label)Primary Purpose: Screening

Participation Requirements

Age
Between 18 years and 70 years
Gender
Both males and females

Description

In the proposed study (XACT III) the investigators will use the same approach (as for XACT II), but it remains to be shown that such a strategy is scalable and feasible in different settings where the challenges and conditions vary. More importantly, the investigators need to methodologically optimi...

In the proposed study (XACT III) the investigators will use the same approach (as for XACT II), but it remains to be shown that such a strategy is scalable and feasible in different settings where the challenges and conditions vary. More importantly, the investigators need to methodologically optimize the ACF model. Thus, the investigators aim to determine where Xpert (the diagnostic test) should be optimally placed from a physical location point-of-view, i.e. does it really need to be installed in the mobile mini clinic, or, can it be located in centralized laboratories (as it is now) with samples being sent to these laboratories? This is a very important question: it is known that sending collected sputum samples to centralized laboratories will be much easier as it uses existing infrastructure, however, the downside is between 20 and 40% of patients fail to come back to collect their results (pre-treatment loss to follow-up; PTLF). Using the diagnostic in the mobile mini van (at point-of-care; POC) dramatically reduces this PTLF enabling quick diagnosis and interrupting transmission. To definitively settle the question, a study is needed using the two different strategies to find out which strategy is most cost-effective yet can rapidly pick up the most cases and minimize transmission. There are two other important sub-questions that the study will answer. Chest X-rays, which can identify people at high risk of having TB, can now be automatically read by a computer algorithm (called computer-assisted diagnosis of TB; CAD-TB). It will be very important to know whether mass screening using CAD-TB can triage individuals i.e. narrow the net so that the investigators target the ACF only to those at high risk of having TB. This could save even more money yet be just as effective. Secondly, a fundamental unanswered question is why individuals with minimal or no symptoms can be highly infectious (transmit disease)? The investigators need to study this phenomenon in greater detail using cough aerosol readouts, chest X-rays, and looking at the TB strains. In addition the investigators would like to screen contacts of individuals with confirmed tuberculosis This might provide medical science with the information it needs to design diagnostic or therapeutic interventions to address this important problem. However, the key priority now is to show that the XACT approach is feasible in different settings and to clarify how the molecular diagnostics should be optimally located. Answering these questions will allow the initiation of ACF programmes in many countries and will contribute critical data to policy makers so that guidelines on ACF can be disseminated and implemented.

Tracking Information

NCT #
NCT04303104
Collaborators
  • Zambart (University of Zambia), Zambia
  • Instituto Nacional de Saúde, Mozambique
  • Biomedical Research and Training Institute, Zimbabwe
  • Radboud University
  • London School of Hygiene and Tropical Medicine
  • University of Cape Town Lung Institute
Investigators
Principal Investigator: Keertan Dheda, MBChB, PhD Lung Infection and Immunity Unit and Division of Pulmonology