Reimagining the status quo: How close are we to rapid sputum-free tuberculosis diagnostics for all?

Abstract

Rapid, accurate, sputum-free tests for tuberculosis (TB) triage and confirmation are urgently needed to close the widening diagnostic gap. We summarise key technologies and review programmatic, systems, and resource issues that could affect the impact of diagnostics. Mid-to-early-stage technologies like artificial intelligence-based automated digital chest X-radiography and capillary blood point-of-care assays are particularly promising. Pitfalls in the diagnostic pipeline, included a lack of community-based tools. We outline how these technologies may complement one another within the context of the TB care cascade, help overturn current paradigms (eg, reducing syndromic triage reliance, permitting subclinical TB to be diagnosed), and expand options for extra-pulmonary TB. We review challenges such as the difficulty of detecting paucibacillary TB and the limitations of current reference standards, and discuss how researchers and developers can better design and evaluate assays to optimise programmatic uptake. Finally, we outline how leveraging the urgency and innovation applied to COVID-19 is critical to improving TB patients' diagnostic quality-of-care.

Keywords: Active disease; Diagnosis; Non-sputum; Point-of-care; Tuberculosis.

Figure 1

Approaches to diagnosing TB. (a) An overview of a typical facility-based TB diagnostic algorithm. People in a community (without risk factors for TB, white; with symptoms or risk factors for TB, grey; with TB, red) attend a health facility. After screening, all at-risk individuals are ideally identified and receive a triage test (note in some very high burden settings, all clinical attendees may be considered at risk; the definition of at-risk is setting-specific), which is done to exclude unnecessary confirmatory testing. Patients who triage positive then receive typically expensive (yet critical) confirmatory testing, which is used to inform treatment. Importantly, screening (and potentially testing) could occur in the community, however, this is not shown as most new technologies need to first demonstrate potential in facilities. (b) Some of the novel materials under investigation for triage or confirmation are shown (some applicable to both use cases), and (c) a selection of products and technologies that use these materials, their developmental stage (if known to be under commercialisation), and potential health system-level of deployment. Notably, there are insufficient late-stage and design-locked triage tests, as well as early and design-locked confirmatory tests useful for facility-based point-of-care testing (this deficit is even more serious for community-based testing, which is diagnostically and operationally more challenging). Abbreviations: AI: artificial intelligence, dCXR: digital chest X-ray.