Evidence map›Paper›PMID 31666025›Full record

SynthesisBMC infectious diseases2019

Accumulate evidence for IP-10 in diagnosing pulmonary tuberculosis.

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

Abstract readMeta-Analysis
In one paragraph

Synthesis in BMC infectious diseases, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed, 2 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

22 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
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  14. MedComm · 2024
    Review
  15. Review
  16. Evaluation of theFrontiers in cellular and infection microbiology · 2023
    Article
  17. Evaluation ofFrontiers in cellular and infection microbiology · 2023
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  18. Diagnostic Performance of a NovelFrontiers in microbiology · 2022
    Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Xia QiuDepartment of Pediatrics, West China Second University Hospital, Sichuan University, Chengdu, 610041, Sichuan, China.
Tao XiongDepartment of Pediatrics, West China Second University Hospital, Sichuan University, Chengdu, 610041, Sichuan, China.
Xiaojuan SuKey Laboratory of Obstetric & Gynecologic and Pediatric Diseases and Birth Defects of Ministry of Education, Sichuan University, Chengdu, China.
Yi QuDepartment of Pediatrics, West China Second University Hospital, Sichuan University, Chengdu, 610041, Sichuan, China.
Long GeEvidence Based Social Science Research Center, School of Public Health, Lanzhou University, Lanzhou, China.
Yan YueDepartment of Pediatrics, West China Second University Hospital, Sichuan University, Chengdu, 610041, Sichuan, China.
Yan ZengDepartment of Pediatrics, West China Second University Hospital, Sichuan University, Chengdu, 610041, Sichuan, China.
Wenxing LiDepartment of Pediatrics, West China Second University Hospital, Sichuan University, Chengdu, 610041, Sichuan, China.
Peng HuDepartment of Pediatrics, West China Second University Hospital, Sichuan University, Chengdu, 610041, Sichuan, China.
Dezhi MuDepartment of Pediatrics, West China Second University Hospital, Sichuan University, Chengdu, 610041, Sichuan, China. mudz@scu.edu.cn.

Funding

Institute for NanoScience and NanoTechnology, Sharif University of Technology (IR) 2016TD0002National Key R&D Program of China 2017YFA 0104200National Science Foundation of China 81330016, 81630038, 81771634, 81842011the grant from the clinical discipline program (Neonatology) from the Ministry of Health of China 1311200003303the grants from the Ministry of Education of China IRT0935
6 · The paper itself

Abstract

backgroundsPulmonary 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.

methodsWeb 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.

resultsEighteen 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.

conclusionsOur results showed that IP-10 is a promising marker for differentiating PTB from non-TB.

Indexed as

Area Under CurveBiomarkersChemokine CXCL10Clinical Trials as TopicHumansOdds RatioROC CurveSensitivity and SpecificityTuberculosis, PulmonaryBiomarkersChemokine CXCL10CXCL10 protein, humanDiagnosisInterferon gamma-induced protein 10Meta-analysisPulmonary tuberculosis

Identifiers

PMID31666025
PMCPMC6822474

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.