Tuberculosis Clinical Trial
Official title:
A Randomized Controlled Trial to Evaluate a Scalable Active Case Finding Intervention for TB Using a Point-of-care Molecular Tool (Gene Xpert)
TB remains the foremost infectious disease killer globally. A startling statistic is that two out of every five TB cases globally (40%) remain undiagnosed and untreated. These 'missed' or undiagnosed cases are disproportionately concentrated in large peri-urban 'slums' and informal settlements of large cities in Africa and Asia (they are frequently minimally symptomatic but remain infectious). The lack of a sensitive low cost same-day test represented a major challenge to active community-based case finding (ACF) compared to the current model where patients 'self-seek' care (passive case finding). More recently, sensitive TB DNA-detection tests called Gene Xpert (Xpert) have become available. This is a nucleic acid amplification test-based technology which can rule-in a diagnosis of TB in two thirds of smear negative pulmonary TB cases. GeneXpert® has now been rolled out in many African countries and is the frontline TB test in primary care clinics in South Africa. The investigators recently showed that GeneXpert® significantly reduced the time to treatment initiation in the setting of passive case finding (elaborated in next section). The investigators further showed that GeneXpert® can be performed by a minimally trained healthcare worker. However, historically technical and logistical demands meant that the GeneXpert® MTB-RIF assay was not ideally suited to use at point of care and in South Africa it is still centrally located. Small portable battery-operated versions of these tests are now available (EDGE, GeneXpert two-module mobile platform). The investigators conducted a large study in South Africa and Zimbabwe (published in 2016) that showed that using the old non-portable version of Xpert on a mini-truck equipped with a generator was feasible and highly effective for ACF. A subsequent study funded by the American government (XACT II), showed that using the portable version of Xpert on the back of a small low-cost scalable panel van (in effect a mobile mini-clinic) was feasible and had a very high pick-up rate of TB in peri-urban communities (~10% of those undergoing targeted screening). In this study, the investigators will test the hypothesis that community-based active case finding (ACF) using Gene Xpert Edge (in a low cost scalable mini-mobile clinic) performed at point-of-care (POC) is feasible and more effective (lower proportion of TB cases failing to initiate treatment especially if they are 'super-spreaders' i.e. highly infectious) than Xpert performed in a centralised laboratory.
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. ;
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