Evidence map›Paper›PMID 25428147›Full record

ArticleJournal of clinical microbiology2015

Discrimination between active and latent tuberculosis based on ratio of antigen-specific to mitogen-induced IP-10 production.

Yun Hee Jeong, Yun-Gyoung Hur, Hyejon Lee, Sunghyun Kim, Jang-Eun Cho, Jun Chang, Sung Jae Shin, Hyeyoung Lee, Young Ae Kang, Sang-Nae Cho and 1 more

Open access · bronzeAbstract readEvaluation Study
In one paragraph

Article in Journal of clinical microbiology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers, 6 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
35citing papers in PubMed, 6 pooled it
2.9field-weighted citation impact, top 9% of its field
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

35 citing papers in PubMed, 6 syntheses or guidelines pooled it, 67 citations in OpenAlex.

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  17. Ferrets as a model for tuberculosis transmission.Frontiers in cellular and infection microbiology · 2022
    Article
  18. Elevated IP-10 at the Protein and Gene Level Associates With Pulmonary TB.Frontiers in cellular and infection microbiology · 2022
    Article
  19. Review
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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

11 authors at 3 institutions in 1 country.

Yun Hee JeongDepartment of Biochemistry, College of Life Science and Biotechnology, Yonsei University, Seoul, Republic of Korea.
Yun-Gyoung HurDepartment of Microbiology, Yonsei University College of Medicine, Seoul, Republic of Korea.
Hyejon LeeDepartment of Microbiology, Yonsei University College of Medicine, Seoul, Republic of Korea.
Sunghyun KimDepartment of Biomedical Laboratory Science, College of Health Sciences, Yonsei University, Wonju, Gangwon, Republic of Korea.
Jang-Eun ChoDepartment of Biomedical Laboratory Science, Daegu Health College, Daegu, Republic of Korea.
Jun ChangDivision of Life and Pharmaceutical Sciences, College of Pharmacy, Ewha Woman's University, Seoul, Republic of Korea.
Sung Jae ShinDepartment of Microbiology, Yonsei University College of Medicine, Seoul, Republic of Korea.
Hyeyoung LeeDepartment of Biomedical Laboratory Science, College of Health Sciences, Yonsei University, Wonju, Gangwon, Republic of Korea.
Young Ae KangDivision of Pulmonology, Department of Internal Medicine, Yonsei University College of Medicine, Seoul, Republic of Korea.
Sang-Nae ChoDepartment of Microbiology, Yonsei University College of Medicine, Seoul, Republic of Korea.
Sang-Jun HaDepartment of Biochemistry, College of Life Science and Biotechnology, Yonsei University, Seoul, Republic of Korea sjha@yonsei.ac.kr.
Yonsei University · KRDaegu Health College · KREwha Womans University · KR

Funding

NHLBI NIH HHS HI13C0833PHS HHS A101750
6 · The paper itself

Abstract

Mycobacterium tuberculosis is the major causative agent of tuberculosis (TB). The gamma interferon (IFN-γ) release assay (IGRA) has been widely used to diagnose TB by testing cell-mediated immune responses but has no capacity for distinguishing between active TB and latent TB infection (LTBI). This study aims to identify a parameter that will help to discriminate active TB and LTBI. Whole-blood samples from 33 active TB patients, 20 individuals with LTBI, and 26 non-TB controls were applied to the commercial IFN-γ release assay, QuantiFERON-TB Gold In-Tube, and plasma samples were analyzed for interleukin-2 (IL-2), IL-6, IL-8, IL-10, IL-13, tumor necrosis factor-alpha (TNF-α), IFN-γ, monokine induced by IFN-γ (MIG), interferon gamma inducible protein 10 (IP-10), interferon-inducible T cell alpha chemoattractant (I-TAC), and monocyte chemoattractant protein 1 (MCP-1) by using a commercial cytometric bead array. The Mycobacterium tuberculosis antigen-specific production of most of the assayed cytokines and chemokines was higher in the active TB than in the LTBI group. The mitogen-induced responses were lower in the active TB than in the LTBI group. When the ratio of TB-specific to mitogen-induced responses was calculated, IL-2, IL-6, IL-10, IL-13, TNF-α, IFN-γ, MIG, and IP-10 were more useful in discriminating active TB from LTBI. In particular, most patients showed higher IP-10 production to Mycobacterium tuberculosis antigens than to mitogen at the individual level, and the ratio for IP-10 was the strongest indicator of active infection versus LTBI with 93.9% sensitivity and 90% specificity. In conclusion, the ratio of the TB-specific to the mitogen-induced IP-10 responses showed the most promising accuracy for discriminating active TB versus LTBI and should be further studied to determine whether it can serve as a biomarker that might help clinicians administer appropriate treatments.

Indexed as

AdultAntigens, BacterialChemokine CXCL10Diagnosis, DifferentialFemaleHumansInterferon-gamma Release TestsLeukocytes, MononuclearMaleMiddle AgedMitogensMycobacterium tuberculosisTuberculosisYoung AdultAntigens, BacterialChemokine CXCL10CXCL10 protein, humanMitogens

Identifiers

PMID25428147
PMCPMC4298513
OpenAlexW2123799872

What OpenQuestion holds

Textmetadata
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.