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

Summary

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.

Conditions

• Tuberculosis
• COVID-19
• HIV Infections

Interventions

DIAGNOSTIC_TEST

CAD

It is an artificial intelligence (AI) system for detection of TB on CXR images. The system input is a frontal CXR, and the outputs are 1) a heatmap indicating suspicious regions on the image; and 2) a score (0-100) which implies the likelihood that the x-ray image shows TB.

DIAGNOSTIC_TEST

Xpert

A novel diagnostic for active case finding (GeneXpert MTB/RIF) for TB on sputum collected and performed at POC in a mobile van.

Sponsors & Collaborators

• European and Developing Countries Clinical Trials Partnership (EDCTP)

  collaborator OTHER_GOV

• Zambart

  collaborator OTHER

• Biomedical Research and Training Institute

  collaborator OTHER

• Ospedale San Raffaele

  collaborator OTHER

• Radboud University Medical Center

  collaborator OTHER

• Foundation for Innovative New Diagnostics, Switzerland

  collaborator OTHER

• University of Stellenbosch

  collaborator OTHER

• University of Cape Town

  lead OTHER

Principal Investigators

• Keertan Dheda, PhD · University of Cape Town

Study Design

Allocation

RANDOMIZED

Purpose

SCREENING

Masking

NONE

Model

PARALLEL

Eligibility

Min Age

18 Years

Sex

ALL

Healthy Volunteers

Yes

Timeline & Regulatory

Start

2022-02-23

Primary Completion

2026-06-30

Completion

2026-12-30

Countries

• South Africa
• Zambia
• Zimbabwe

Study Locations