Abstract
ObjectiveWe compared diagnostic accuracy of pleural fluid adenosine deaminase (ADA) and interferon-gamma (IFN-γ) in diagnosing tuberculous pleural effusion (TPE) through systematic review and comparative meta-analysis.MethodsWe queried PubMed and Embase databases to identify studies providing paired data for sensitivity and specificity of both pleural fluid ADA and IFN-γ for diagnosing TPE. We used hierarchical summary receiver operating characteristic (HSROC) plots and HSROC meta-regression to model individual and comparative diagnostic performance of the two tests.ResultsWe retrieved 376 citations and included 45 datasets from 44 publications (4974 patients) in our review. Summary estimates for sensitivity and specificity for ADA were 0.88 (95% CI 0.85–0.91) and 0.91 (95% CI 0.89–0.92), while for IFN-γ they were 0.91 (95% CI 0.89–0.94) and 0.96 (95% CI 0.94–0.97), respectively. HSROC plots showed consistently greater diagnostic accuracy for IFN-γ over ADA across the entire range of observations. HSROC meta-regression using test-type as covariate yielded a relative diagnostic odds ratio of 2.22 (95% CI 1.68–2.94) in favour of IFN-γ, along with better summary sensitivity and specificity figures. No prespecified subgroup variable significantly influenced the summary diagnostic accuracy estimates.ConclusionPleural fluid IFN-γ estimation has better diagnostic accuracy than ADA estimation for diagnosis of TPE.
Highlights
Tuberculosis (TB) remains an important etiology of exudative pleural effusions, especially in regions with high TB burden [1]
Summary estimates for sensitivity and specificity for adenosine deaminase (ADA) were 0.88 and 0.91, while for IFN-γ they were 0.91 and 0.96, respectively
hierarchical summary receiver operating characteristic (HSROC) metaregression using test-type as covariate yielded a relative diagnostic odds ratio of 2.22 in favour of IFN-γ, along with better summary sensitivity and specificity figures
Summary
We used hierarchical summary receiver operating characteristic (HSROC) plots and HSROC meta-regression to model individual and comparative diagnostic performance of the two tests
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