Young children and children living with HIV are at high risk of progressing to tuberculosis (TB) disease following Mycobacterium tuberculosis (Mtb) exposure and infection, and also of developing severe forms of disease and TB-related mortality. Identifying children who have very early (sub-clinical) TB disease, prior to progression to clinically apparent TB, would mean that TB preventive treatment (TPT) could be more efficiently targeted to this group. Identifying biomarker changes on drug therapy in children with Mtb infection or very early disease could pave the way for the development of tests that can identify which children have viable bacilli and are therefore at increased risk of disease progression.

The INTREPID study will use already collected samples taken from well-phenotyped paediatric cohorts in three clinical studies conducted in South Africa in children Mtb exposure to disease and from children treated for Mtb infection and early TB disease, as well as targeted Mtb antibody analysis. Data on viral co-infections and relevant clinical and epidemiological parameters will be integrated and evaluated to identify the optimal biosignatures that can predict future progression to clinically overt disease in children below 5 years of age, including those living with HIV.

The study protocol received ethical approval from the Stellenbosch University Health Research Ethics Committee (N23/03/025). The study findings will be disseminated through peer-reviewed publications, scientific conferences and formal presentations to healthcare professionals and to local communities, in collaboration with the Desmond Tutu TB Centre Community Advisory Board.

In 2022, the WHO conditionally recommended the use of treatment decision algorithms (TDAs) for treatment decision-making in children

Within the Decide-TB project (PACT ID: PACTR202407866544155, 23 July 2024), we aim to generate an individual-participant dataset (IPD) from prospective TB diagnostic accuracy cohorts (RaPaed-TB, UMOYA and two cohorts from TB-Speed). Using the IPD, we aim to: (1) assess the diagnostic accuracy of published TDAs using a set of consensus case definitions produced by the National Institute of Health as reference standard (confirmed and unconfirmed vs unlikely TB); (2) evaluate the added value of novel tools (including biomarkers and artificial intelligence-interpreted radiology) in the existing TDAs; (3) generate an artificial population, modelling the target population of children eligible for WHO-endorsed TDAs presenting at primary and secondary healthcare levels and assess the diagnostic accuracy of published TDAs and (4) identify clinical predictors of radiological disease severity in children from the study population of children with presumptive TB.

This study will externally validate the first data-driven WHO TDAs in a large, well-characterised and diverse paediatric IPD derived from four large paediatric cohorts of children investigated for TB. The study has received ethical clearance for sharing secondary deidentified data from the ethics committees of the parent studies (RaPaed-TB, UMOYA and TB Speed) and as the aims of this study were part of the parent studies’ protocols, a separate approval was not necessary. Study findings will be published in peer-reviewed journals and disseminated at local, regional and international scientific meetings and conferences. This database will serve as a catalyst for the assessment of the inclusion of novel tools and the generation of an artificial population to simulate the impact of novel diagnostic pathways for TB in children at lower levels of healthcare. TDAs have the potential to close the diagnostic gap in childhood TB. Further finetuning of the currently available algorithms will facilitate this and improve access to care.