A statistical method was used for the meta-analysis of tests for latent TB in the absence of a gold standard, combining random-effect and latent-class methods to estimate test accuracy

ObjectiveBecause of the lack of a gold standard, the diagnostic performance of tests for the detection of latent tuberculosis infection (LTBI) is not known. However, statistical methods can be used to estimate the accuracy from the studies reporting the concordance among the tests.Study Design and SettingWe developed a random-effect latent-class model to estimate performance characteristics of three LTBI diagnostic tests: tuberculin skin test (TST, at 10-mm cutoff), QuantiFERON-TB gold (QFG), and TSPOT-TB from the studies evaluating agreement among the tests.ResultsNineteen studies were included. QFG had a sensitivity of 0.642 (95% confidence interval [CI]: 0.593–0.691) and specificity of 0.996 (95% CI: 0.989–1.000), TSPOT-TB had a sensitivity of 0.500 (95% CI: 0.334–0.666) and specificity of 0.906 (95% CI: 0.882–0.929), and TST had a sensitivity of 0.709 (95% CI: 0.658–0.761) and specificity of 0.683 (95% CI: 0.522–0.844). Results were not sensitive to the inclusion of any single study. When only the three studies that reported on TSPOT were removed, estimates for the other two tests varied minimally.ConclusionsStatistical methods can help estimate the accuracy of LTBI tests. Although the specificities were close to their reported values in the literature, the estimates for sensitivities were low; a finding that should be carefully evaluated.