Abstract
Background
Optimising Tuberculosis (TB) disease testing algorithms is fundamental to ensure the effectiveness and cost-effectiveness of migrant screening programmes, including better understanding of the individual and combined screening test properties. The aim of our study was to estimate pooled TB test properties from the literature and combining them in decision analytical modelling with a focus on whether tests used for the diagnosis of TB infection might add value to these algorithms.
Methods
We performed a systematic review of reviews (RoR) of diagnostic tests for active TB, searching PubMed, Embase, Web of Science and Cochrane library and pooled test properties extracted from original papers included in reviews. We used these pooled results in a decision tree analysis to estimate test properties for common migrant screening algorithms.
Findings
We retrieved 1477 records and included 32 reviews, including data from 437 original studies for 18 TB tests, providing pooled results for 13. Our modelling showed that algorithms with interferon gamma release assays (IGRAs) had the highest diagnostic odds ratios (e.g. QuantiFERON/Chest X-Ray (CXR, TB abnormalities)/Xpert dOR 24?670; 95% confidence intervals 11?630–52?328) and high positive predictive values. Best sensitivities were achieved for combinations with parallel cough/CXR screening followed by Xpert (0.88; CI 0.86–0.90) or Ultra (0.92; 0.90–0.94) as well as T-Spot.TB followed by parallel symptom/CXR screening and Ultra (0.81; 0.78–0.83) or Xpert (0.77; 0.75–0.80).
Interpretation
The significant test accuracy benefit of adding IGRAs to an active TB screening pathway will help inform clinicians and policy makers deciding on the most effective screening algorithms.
