High costs of screening and diagnostic tests remain a major barrier to timely tuberculosis (TB) identification in resource-limited settings. Evidence on the cost-effectiveness of scalable screening algorithms is limited. Start4All is a research project aimed at developing and evaluating algorithmic approaches to TB screening and diagnosis, with the goal of optimising technical and allocative efficiency when expanding diagnostic coverage to primary healthcare and community settings.

Five screening and diagnostic tests will be evaluated: a capillary blood-based assay (C-reactive protein (CRP)), sputum-based rapid molecular tests (PCR; individual and pooled Xpert MTB/RIF Ultra assay (Xpert Ultra, Cepheid®, California, USA)), a lateral-flow urine-based test for lipoarabinomannan (LF-LAM), and digital chest X-rays with artificial intelligence-based computer-aided detection (CXR-CAD). A microbiological reference standard of positive culture using the mycobacteria growth indicator tube will be used to confirm TB disease.

We will compare the cost and effectiveness of concurrent and sequential positive serial combinations (screening algorithms) of CRP, CXR-CAD, LF-LAM, individual and pooled Xpert Ultra. Diagnostic performance will be estimated using sensitivity, specificity, predictive values and proportions of positive results, with Bayesian inference used to derive these estimates. The analysis will include adults (15 years and older) only and will be stratified by HIV status and level of care, including facility and community-based case finding. Effectiveness will be assessed based on the number of people with TB detected. Cost analysis will be conducted from the provider perspective, incorporating commodity and implementation costs. A decision tree model will be developed to assess the cost per number of persons with confirmed TB detected across all countries. Probabilistic sensitivity analysis will be conducted to account for uncertainty in model parameters, incorporating willingness-to-pay and willingness-to-accept thresholds.

WHO ethical review committee approval ERC.0003921. Data will be available on reasonable request to the principal investigator of the consortium.

NCT05845112.