Introduction: Tuberculosis (TB) is among the 10 most common causes of death worldwide and it is the leading cause of mortality in people with human immunodeficiency virus (HIV). Clinical scoring systems have the potential to improve case finding and to prioritize patients for TB testing. Areas covered: This systematic review investigated the utility of prediction models to improve pulmonary tuberculosis (pTB) case finding. Studies were searched through PubMed until 15th of August 2018 and 20 studies were eligible according to the inclusion criteria. Data on study population, outcome measurements, predictors, and performance were extracted. Many studies showed promising results but lacked external validation. Furthermore, head-to-head studies are needed to compare the different prediction models. Sensitivities of the prediction models ranged from 26% to 96% and specificities from 18% to 92%, negative likelihood ratios (LR-) from 0.22 to 0.8 and positive likelihood ratios(LR+) 1.07 to 7.32. Composite scores including paraclinical measures added to sensitivity. Expert opinion: TB case finding is of utmost importance to advance the quest for global TB elimination, and simple measures to identify high-risk populations or persons to undergo further diagnostic evaluation are highly needed. A number of clinical scores are available and could be implemented in practice to improve case finding.
Keywords: Clinical prediction model; case finding; clinical prediction rule; clinical score; pulmonary tuberculosis.