Biomarker tests of progression from tuberculosis infection to disease: a systematic review

Tuberculosis (TB) remains a global health threat, with millions of new infections annually. While most infected individuals remain asymptomatic, a subset progresses to active disease. Effective tests predicting TB progression are urgently needed to enhance prevention strategies and reduce the global TB burden.

To evaluate biomarker-based tests designed to predict progression from TB infection to active disease.

We conducted a systematic literature search of four electronic databases for studies published between 2016, when the first trial evaluating biomarker-based tests for TB progression was published, and 2024. Quality assessment was performed using QUADAS-2 (Quality Assessment of Diagnostic Accuracy Studies 2). Data on study design, population, biomarkers, and diagnostic accuracy were extracted and synthesised narratively.

19 studies were included, reporting 70 biomarker-based tests for predicting TB progression. These included 23 gene signatures, 14 protein signatures and 33 cytokines/chemokines. Heterogeneity in study populations, methodologies and outcome definitions precluded direct comparisons. Many studies lacked transparency in reporting key population characteristics, reference standards and diagnostic accuracy outcomes, limiting clinical applicability. Most tests demonstrated only moderate predictive accuracy, with no single biomarker approach emerging as a definitive tool for clinical use.

No biomarker-based test to predict TB progression is currently ready for clinical implementation. Standardised methodologies, larger validation studies and improved reporting transparency are necessary to advance TB diagnostics and improve early detection efforts. Future research should prioritise refining tests for TB progression by improving their predictive accuracy, identifying appropriate target populations and evaluating their cost-effectiveness and feasibility for integration into TB prevention programmes, particularly in high-burden settings.