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Published in: BMC Infectious Diseases 1/2019

Open Access 01-12-2019 | Tuberculosis | Research article

Accumulate evidence for IP-10 in diagnosing pulmonary tuberculosis

Authors: Xia Qiu, Tao Xiong, Xiaojuan Su, Yi Qu, Long Ge, Yan Yue, Yan Zeng, Wenxing Li, Peng Hu, Dezhi Mu

Published in: BMC Infectious Diseases | Issue 1/2019

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Abstract

Backgrounds

Pulmonary tuberculosis (PTB) is a major health and economic burden. Accurate PTB detection is an important step to eliminating TB globally. Interferon gamma-induced protein 10 (IP-10) has been reported as a potential diagnostic marker for PTB since 2007. In this study, a meta-analysis approach was used to assess diagnostic value of IP-10 for PTB.

Methods

Web of Science, PubMed, the Cochrane Library, and Embase databases were searched for studies published in English up to February 2019. The pooled sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds ratio (DOR), the area under the curve (AUC) and hierarchical summary receiver operating characteristic (HSROC) curve were estimated by the HSROC model and random effect model.

Results

Eighteen studies including 2836 total participants met our inclusion criteria. The pooled sensitivity, specificity, PLR, and NLR of IP-10 for PTB detection were 86, 88%, 7.00, and 0.16, respectively. The pooled DOR was 43.01, indicating a very powerful discriminatory ability of IP-10. The AUC was 0.93 (95% CI: 0.91–0.95), showed the accuracy of IP-10 was good. Meta-regression showed that there was no heterogeneity with respect to TB burden, study design type, age, IP-10 assay method, IP-10 condition and HIV-infection status.

Conclusions

Our results showed that IP-10 is a promising marker for differentiating PTB from non-TB.
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Metadata
Title
Accumulate evidence for IP-10 in diagnosing pulmonary tuberculosis
Authors
Xia Qiu
Tao Xiong
Xiaojuan Su
Yi Qu
Long Ge
Yan Yue
Yan Zeng
Wenxing Li
Peng Hu
Dezhi Mu
Publication date
01-12-2019
Publisher
BioMed Central
Published in
BMC Infectious Diseases / Issue 1/2019
Electronic ISSN: 1471-2334
DOI
https://doi.org/10.1186/s12879-019-4466-5

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