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临床试验/NCT05220163
NCT05220163进行中(未招募)不适用

Evaluating the Impact of Computer-assisted X-ray Diagnosis and Other Triage Tools to Optimise Xpert Orientated Community-based Active Case Finding for TB and COVID-19

University of Cape Town3 个研究点 分布在 3 个国家目标入组 26,200 人开始时间: 2022年2月23日最近更新:
适应症
干预措施

试验速览

阶段
不适用
状态
进行中(未招募)
入组人数
26,200
试验地点
3
主要终点
Time to detection of microbiologically proven TB

研究概览

简要总结

Tuberculosis (TB) is now the commonest cause of death in many African countries. Globally, ~35% (almost 1 in 3) of TB cases are 'missed' (remain undiagnosed or undetected). In sub-Saharan Africa, 40-50% of the TB case burden remains undiagnosed within the community. These 'missed' TB cases (at primary care level) serve as a reservoir, which severely undermines TB control. With rapid advances in the development of TB screening tests, the investigators aim to determine the pragmatic utility of computer-assisted x-ray diagnosis (CAD). Recent data suggest that CAD performs on par with experienced radiologists to identify potential TB cases, hereby reducing the frequency at which Xpert tests are requested and helps to focus limited resources on the relevant cases. In addition, the investigators aim to test nascent screening technologies for TB diagnosis such as evaluating urine-based TB screening biosignatures. The COVID-19 pandemic has ravaged African peri-urban communities where TB is also common. With the pressing need to improve screening and diagnosis of COVID-19, the investigators plan to explore the potential for urine- and blood-based COVID-19 screening assays. Symptoms of COVID-19 and TB overlap, and limited affordability, as well as the stigma associated with both diseases, severely limits testing. Data are now urgently needed about the feasibility of co-screening and testing for TB and COVID-19. The utility of such an approach, if any, has not been studied in African communities.

详细描述

Tuberculosis (TB) is now the commonest cause of death in many African countries. Several factors drive this; however, transmission is the mechanism by which these risk factors translate into active TB. Globally, ~35% (almost 1 in 3) of TB cases are 'missed' (remain undiagnosed or undetected). In sub-Saharan Africa, 40-50% of the TB case burden remains undiagnosed within the community and ~30% of such cases are microscopically smear-positive. These 'missed' TB cases (at primary care level) serve as a reservoir, which severely undermines TB control. Thus, primary care and community-based case finding should be a critical component for TB control.

Detecting cases in the community, however, has been restricted by the lack of sensitive and user-friendly Point-of-Care (POC) diagnostic tools. To address this unmet need, in 2013 the investigators planned a programme of activities (sequential interlinked studies) with the overarching aim of optimising a model for Xpert-related community-based active case finding (ACF) for TB (XACT). By 2017, through the EDCTP-funded XACT-I study, the investigators solved the impasse of rapid POC diagnosis by showing that molecular Xpert-based community-based screening was effective in identifying missing TB cases in the peri-urban 'slums' of Cape Town and Harare using a mini-truck with a generator. However, such an approach was neither broadly affordable nor scalable. The investigators therefore derived a scalable model using portable battery-operated Xpert Edge installed within a low-cost (< US$) 15 000 Nissan panel van manned by two health care workers (thus making the ACF model affordable and scalable). This completed study, XACT-II, screened over 5 000 participants in the community. The model worked well and was more effective than smear microscopy. Based on these successes, and to translate the XACT concept into policy, the Wellcome Trust and UK MRC has funded the XACT-III study. Currently commenced, XACT-III was initiated as a multi-country demonstration project in four sub-Saharan African countries.

More recently, there have been rapid advances in the development of triage testing for TB, which refers to screening tests that are generally applied in a community-based setting (either at individual community or primary care clinic level). These tests have very high sensitivity (>95%) but modest specificity (>70%) as defined by TB-specific target product profiles. A forerunner TB-orientated triage test is computer-assisted x-ray diagnosis (CAD). This entails using artificial intelligence-enabled software to read a digital x-ray and produce a probability of TB within seconds. Recent data suggest that CAD performs on par with experienced radiologists to identify potential TB cases, hereby reducing the frequency at which Xpert tests are requested and helps to focus limited resources on the relevant cases. Although these data appear promising, the feasibility of this strategy in a pragmatic field setting has not been extensively tested. There are several other unanswered questions. Is the strategy of CAD combined with Xpert cost-effective and can it reduce Xpert usage without missing an unacceptable number of TB cases? The investigators will therefore determine the utility of CAD as a triage tool to further optimise the XACT model.

The COVID-19 pandemic, due to SARS-CoV-2, has ravaged African peri-urban communities where TB is also common. Symptoms of COVID-19 and TB overlap, and limited affordability, as well as the stigma associated with both diseases, severely limits testing. Data are now urgently needed about the feasibility of co-screening and testing for TB and COVID-19. The utility of such an approach, if any, has not been studied in African communities. As Xpert POC TB testing and x-rays for CAD will be performed in the proposed study, it affords a unique and easy opportunity to seamlessly screen for both diseases when appropriate.

Other nascent screening technologies are rapidly emerging for TB and COVID-19, including urine- and blood-based triage tests. XACT-19 provides a unique opportunity to collect the relevant samples and test new technologies in a pragmatic community-based setting.

研究设计

研究类型
Interventional
分配方式
Randomized
干预模型
Parallel
主要目的
Screening
盲法
None

入排标准

年龄范围
18 Years 至 —(Adult, Older Adult)
性别
All
接受健康志愿者

入选标准

  • Participants willing to complete community-based symptom screening, finger-prick and venepuncture blood sampling, urine testing, and/or undergo TB and/or COVID-19 diagnostic testing.
  • Provision of informed consent.
  • Participant 18 years or above.
  • HIV-positive or negative participants will be included.

排除标准

  • Inability to provide informed consent (e.g., mentally impaired).
  • Participants who have completed TB treatment in the last two months, or who have self-presented to their local TB clinic and are currently being worked up for suspected TB.
  • Participants already diagnosed with active TB on treatment.
  • Participants unable to commit to at least a two-month follow-up.
  • Female participants who are pregnant or who refuse a urine pregnancy test.
  • Participants in the community who cannot access healthcare due to severe ill health or lack of access to the local clinic.

研究组 & 干预措施

CAD + POC Xpert

Experimental

CAD followed by Xpert in CAD-positive participants (performed at POC) employing a low-cost panel van that is staffed by three health care workers. CAD-negative participants will be followed up, while CAD-positive participants will be offered POC Xpert. Xpert-positive participants will be referred for TB treatment initiation, while Xpert-negative (but CAD-positive) participants will undergo a clinical review. Thus, the active case finding (ACF) interventional package is one of CAD + POC Xpert (only in CAD positive participants).

干预措施: CAD (Diagnostic Test)

CAD + POC Xpert

Experimental

CAD followed by Xpert in CAD-positive participants (performed at POC) employing a low-cost panel van that is staffed by three health care workers. CAD-negative participants will be followed up, while CAD-positive participants will be offered POC Xpert. Xpert-positive participants will be referred for TB treatment initiation, while Xpert-negative (but CAD-positive) participants will undergo a clinical review. Thus, the active case finding (ACF) interventional package is one of CAD + POC Xpert (only in CAD positive participants).

干预措施: Xpert (Diagnostic Test)

POC Xpert only

Active Comparator

Participants who are Xpert-positive will be referred for TB treatment initiation while Xpert-negative participants will be followed up. Thus, the active case finding (ACF) standard of care package is POC Xpert.

干预措施: Xpert (Diagnostic Test)

结局指标

主要结局

Time to detection of microbiologically proven TB

时间窗: Through study completion, up to 48 months

The microbiological reference standard for TB will be culture and/or Xpert positivity. Thus, the overall time to detection (using a proportional hazards model) and the proportion of TB cases detected at a specific time-point (e.g., 14-, 30- and 60-days) with and without culture (Xpert alone) will be reported.

次要结局

  • Time to TB treatment initiation (both the median time to treatment in each group and time to event [treatment] analyses will be conducted)(Through study completion, up to 48 months)
  • Yield of culture positive TB in household contacts of index participants(Through study completion, up to 48 months)
  • Global and country-specific cost-effectiveness analysis for each strategy(Through study completion, up to 48 months)
  • Middleware/dashboard design requirements and deployment models for each strategy(Through study completion, up to 48 months)
  • Feasibility and yield of POC Xpert (Xpress cartridge) for COVID-19 detection(Through study completion, up to 48 months)
  • Feasibility of a novel mass screening strategy for COVID-19 that uses pooling of specimen from a group of COVID-19 suspects(Through study completion, up to 48 months)
  • Proportion of culture-positive TB cases completing three- and six-months of TB treatment in each study arm(Through study completion, up to 48 months)
  • Feasibility and performance of CAD4COVID for PCR-positive COVID-19 detection(Through study completion, up to 48 months)
  • Feasibility of CAD + POC Xpert performed by minimally trained healthcare workers(Through study completion, up to 48 months)
  • Time-specific proportion of participants initiated on TB treatment up to 60 days post-sample donation in each arm (7-, 14-, 30- and 60-days)(Through study completion, up to 48 months)
  • Transmission and disease burden impact using modelling based on exposure scores, imaging, and CASS(Through study completion, up to 48 months)
  • Number of infectious TB cases detected (defined by cough aerosol sampling system [CASS] and/or smear and/or cavitatory disease positive)(Through study completion, up to 48 months)
  • NPV and false negative rate (TB cases missed per 1 000 persons screened) of CAD and other screening tests for TB(Through study completion, up to 48 months)
  • Reduction in number of sputum induction procedures and/or Xpert tests performed(Through study completion, up to 48 months)
  • Rates or prevalence of microbiological versus probable (clinical TB)(Through study completion, up to 48 months)

研究者

申办方类型
Other
责任方
Principal Investigator
主要研究者

Keertan Dheda

Professor

University of Cape Town

研究点 (3)

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