A randomised controlled trial (RCT) to evaluate a scalable active case finding primary care-based intervention for tuberculosis using a point-of-care
Lead Research Organisation:
University of Cape Town
Department Name: Clinical Research Unit
Abstract
TB remains the foremost infectious disease killer globally. A starling statistic is that 2 out of every 5 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). TB will never be brought under control unless this large reservoir of transmission is wiped out. 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. Small portable battery-operated versions of these tests are now available (OMNI). We 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. In a subsequent study funded by the American government (XACT II) we 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; see preliminary data).
In the proposed study (XACT III) we will use the same approach, but we need to be sure that such a strategy is scalable and feasible in different settings where the challenges and conditions vary. More importantly, we need to methodologically optimise the ACF model. Thus, we need to determine where Xpert (the diagnostic test) should be optimally placed from a physical location point-of-view, i.e. do we really need to install it on the mobile mini clinic, or, can it be located in centralised laboratories (as it is now) with samples being sent to these laboratories? This is a very important question: we know that sending collected sputum samples to centralised 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 we need a study using the 2 different strategies to find out which strategy is most cost-effective yet can rapidly pick up the most cases and minimise transmission.
There are 2 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 we 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)? We need to study this phenomenon in greater detail using cough aerosol readouts, chest x rays, and looking at the TB strains. 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.
In the proposed study (XACT III) we will use the same approach, but we need to be sure that such a strategy is scalable and feasible in different settings where the challenges and conditions vary. More importantly, we need to methodologically optimise the ACF model. Thus, we need to determine where Xpert (the diagnostic test) should be optimally placed from a physical location point-of-view, i.e. do we really need to install it on the mobile mini clinic, or, can it be located in centralised laboratories (as it is now) with samples being sent to these laboratories? This is a very important question: we know that sending collected sputum samples to centralised 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 we need a study using the 2 different strategies to find out which strategy is most cost-effective yet can rapidly pick up the most cases and minimise transmission.
There are 2 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 we 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)? We need to study this phenomenon in greater detail using cough aerosol readouts, chest x rays, and looking at the TB strains. 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.
Technical Summary
A startling statistic is that more than 40% of TB cases in endemic countries are "missing" (~4.2 million cases globally remain undiagnosed or unreported)! Most of these undiagnosed cases, which continue to transmit disease, are concentrated in the peri-urban 'slums' and 'shanty towns' of large African cities. Without addressing the 'missing cases' the TB epidemic will never be controlled. However, the lack of suitable diagnostic tools has been a major hurdle in finding the 'missing cases'. However, we have recently shown that community-based screening with molecular diagnostic tools (Gene Xpert) is highly effective in detecting these missing cases (Calligaro & Dheda, Lancet Infect Dis, 2017; XACT I study). This has now been superseded by a new simple to use portable, battery operated, point-of care (POC) version of Xpert (OMNI). For the first time we have a highly sensitive tool that is ideally suited for community-based active case finding (ACF). We have now validated this tool in a NIH-funded RCT in Cape Town (XACT II study; n= 5500 participants). The results show that Xpert is feasible at community-based POC and works much better than POC smear microscopy. However, we now need to validate the methodology and results in different settings to enable uptake and policy recommendations for primary care. Moreover, we now need to optimise the ACF model and determine where Xpert should optimally be located. Thus, we propose conducting a RCT to evaluate the feasibility and impact of primary care-based Xpert performed at POC compared Xpert performed in a centralized laboratory (XACT III). This study will set a new standard of care for ACF and likely revolutionize TB detection, moving it out of clinics and into the community. Furthermore, this project will enable, for the first time, the bio-phenotyping of TB patients in the community who have minimal or no TB symptoms using novel technologies including cough aerosol sampling and whole genome sequencing.
Planned Impact
(i) Impact on practice and policy (including guidelines):
If the key trial questions (multi-country feasibility and optimal placement of Xpert to facilitate ACF) can be successfully answered the trial results will have impact on policy and practice at several levels. At local, national, and regional level the study findings will feed into municipal, government, and policy decision-making bodies (and their guidelines), and will be used by multi-lateral agencies like UNITAID and UKAID to roll out multi-country projects (see pathways to impact for details). At a global level the data, with facilitation from FIND and the STOP TB Partnership, will contribute to WHO recommendations on Xpert and ACF. We will collect data that will inform cost-effective and affordability analyses (within the context of national GDP), which are essential to policy makers to base decisions on.
Thus, XACT III is a potentially disruptive study that promises to define a new standard of care for TB-specific ACF globally. This a realistic vision now that we, for the first time ever, have user-friendly tools for ACF.
ii) Impact on disease burden, morbidity, QoL, and mortality:
Modelling studies have shown that, for a molecular diagnostic study to have impact on transmission of TB, it has to incorporate an active case finding strategy. Thus, XACT III has the potential to significantly reduce TB transmission in the community, thus reducing the overall burden of disease in underprivileged communities. For the first time we will be able to use hard data about infectiousness (including cough aerosol sampling and imaging studies) to accurately model transmission so that we can calculate the net impact of the ACF intervention. Thus, besides direct benefit to individuals, the community, and the economy (see below), public health services will benefit from the reduced disease burden, accelerated case detection, and new tools to prevent disease amplification.
Earlier initiation of effective treatment will reduce morbidity (due to lung destruction and post-tuberculous bronchiectasis), improve quality of life, and reduce mortality (5 to 15% depending on HIV status and other factors).
(iii) Economic impact:
TB is one of the greatest killers in Africa, often targeting individuals in the prime of their lives with deleterious consequences on the economies of these countries (for example, TB will cost South Africa ~130 billion USD by 2030 equating to 2.5% of GDP per year!). These effects are through premature death, inability to work and long-term lung disability. ACF thus has the potential for substantial economic impact and we will present our cost analysis in terms of cases averted/ detected and potential gain to the GDP (so that policy-makers can better understand the impact).
(iv) Impact on antimicrobial resistance and HIV co-infection: As the Xpert OMNI platform will also detect DR-TB in the community, thus circumventing transmission, it will also contribute to reduction in the burden of DR-TB, which threatens to derail TB control in many countries and has a mortality of 25%. This represents a major advantage of the XACT strategy. We have also demonstrated that we have a high pick up rate of undiagnosed HIV with obvious implications for disease amplification, mortality and the economy.
(v) Research and scientific development: This study will inform the fundamental biology of TB transmission within the community, which will enable researchers to develop and target transmission-specific tools and interventions to potentially eradicate TB (see academic beneficiaries section for details).
(vi) Capacity development and networking: Infrastructure and laboratory capacity will be improved at the various clinical trial sites and they will also develop the capability to perform cough aerosol sampling studies. Training of staff and students will facilitate sustainable research capacity.
If the key trial questions (multi-country feasibility and optimal placement of Xpert to facilitate ACF) can be successfully answered the trial results will have impact on policy and practice at several levels. At local, national, and regional level the study findings will feed into municipal, government, and policy decision-making bodies (and their guidelines), and will be used by multi-lateral agencies like UNITAID and UKAID to roll out multi-country projects (see pathways to impact for details). At a global level the data, with facilitation from FIND and the STOP TB Partnership, will contribute to WHO recommendations on Xpert and ACF. We will collect data that will inform cost-effective and affordability analyses (within the context of national GDP), which are essential to policy makers to base decisions on.
Thus, XACT III is a potentially disruptive study that promises to define a new standard of care for TB-specific ACF globally. This a realistic vision now that we, for the first time ever, have user-friendly tools for ACF.
ii) Impact on disease burden, morbidity, QoL, and mortality:
Modelling studies have shown that, for a molecular diagnostic study to have impact on transmission of TB, it has to incorporate an active case finding strategy. Thus, XACT III has the potential to significantly reduce TB transmission in the community, thus reducing the overall burden of disease in underprivileged communities. For the first time we will be able to use hard data about infectiousness (including cough aerosol sampling and imaging studies) to accurately model transmission so that we can calculate the net impact of the ACF intervention. Thus, besides direct benefit to individuals, the community, and the economy (see below), public health services will benefit from the reduced disease burden, accelerated case detection, and new tools to prevent disease amplification.
Earlier initiation of effective treatment will reduce morbidity (due to lung destruction and post-tuberculous bronchiectasis), improve quality of life, and reduce mortality (5 to 15% depending on HIV status and other factors).
(iii) Economic impact:
TB is one of the greatest killers in Africa, often targeting individuals in the prime of their lives with deleterious consequences on the economies of these countries (for example, TB will cost South Africa ~130 billion USD by 2030 equating to 2.5% of GDP per year!). These effects are through premature death, inability to work and long-term lung disability. ACF thus has the potential for substantial economic impact and we will present our cost analysis in terms of cases averted/ detected and potential gain to the GDP (so that policy-makers can better understand the impact).
(iv) Impact on antimicrobial resistance and HIV co-infection: As the Xpert OMNI platform will also detect DR-TB in the community, thus circumventing transmission, it will also contribute to reduction in the burden of DR-TB, which threatens to derail TB control in many countries and has a mortality of 25%. This represents a major advantage of the XACT strategy. We have also demonstrated that we have a high pick up rate of undiagnosed HIV with obvious implications for disease amplification, mortality and the economy.
(v) Research and scientific development: This study will inform the fundamental biology of TB transmission within the community, which will enable researchers to develop and target transmission-specific tools and interventions to potentially eradicate TB (see academic beneficiaries section for details).
(vi) Capacity development and networking: Infrastructure and laboratory capacity will be improved at the various clinical trial sites and they will also develop the capability to perform cough aerosol sampling studies. Training of staff and students will facilitate sustainable research capacity.
