Accuracy of the interferon-gamma release assay for the diagnosis of tuberculous pleurisy: an updated meta-analysis.

Abstract

Background and Objectives. The best method for diagnosing tuberculous pleurisy (TP) remains controversial. Since a growing number of publications focus on the interferon-gamma release assay (IGRA), we meta-analyzed the available evidence on the overall diagnostic performance of IGRA applied to pleural fluid and peripheral blood. Materials and Methods. PubMed and Embase were searched for relevant English papers up to October 31, 2014. Statistical analyses were performed using Stata and Meta-DiSc. Pooled sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), positive predictive value (PPV), negative predictive value (NPV) and diagnostic odds ratio (DOR) were count. Summary receiver operating characteristic curves and area under the curve (AUC) were used to summarize the overall diagnostic performance. Results. Fifteen publications met our inclusion criteria and were included in the meta analysis. The following pooled estimates for diagnostic parameters of pleural IGRA were obtained: sensitivity, 0.82 (95% CI [0.79-0.85]); specificity, 0.87 (95% CI [0.84-0.90]); PLR, 4.94 (95% CI [2.60-9.39]); NLR, 0.22 (95% CI [0.13-0.38]); PPV, 0.91 (95% CI [0.85-0.96]); NPV, 0.79 (95% CI [0.71-0.85]); DOR, 28.37 (95% CI [10.53-76.40]); and AUC, 0.91. The corresponding estimates for blood IGRA were as follows: sensitivity, 0.80 (95% CI [0.76-0.83]); specificity, 0.70 (95% CI [0.65-0.75]); PLR, 2.48 (95% CI [1.95-3.17]); NLR, 0.30 (95% CI [0.24-0.37]); PPV, 0.79 (95% CI [0.60-0.87]); NPV, 0.75 (95% CI [0.62-0.83]); DOR, 9.96 (95% CI [6.02-16.48]); and AUC, 0.89. Conclusions. This meta analysis suggested that pleural IGRA has potential for serving as a complementary method for diagnosing TP; however, its cost, high turn around time, and sub-optimal performance make it unsuitable as a stand-alone diagnostic tool. Better tests for the diagnosis of TP are required.

• Authors: Cai-Shuang Pang, Yong-Chun Shen, Pan-Wen Tian, Jing Zhu, Mei Feng, Chun Wan, Fu-Qiang Wen
• Journal: PeerJ (PeerJ) Vol. 3 Pg. e951 ( 2015) ISSN: 2167-8359 [Print] United States
• PMID: 26038718 (Publication Type: Journal Article)