Evidence map›Paper›PMID 33604556›Full record

ArticleCytokine: X2020

Value of serum cytokine biomarkers TNF-α, IL-4, sIL-2R and IFN-γ for use in monitoring bacterial load and anti-tuberculosis treatment progress.

Wenjuan Nie, Jun Wang, Wei Jing, Wenhui Shi, Qingfeng Wang, Xuerui Huang, Baoyun Cai, Qiping Ge, Lihui Nie, Xiqin Han and 4 more

Open access · hybridAbstract read
In one paragraph

Article in Cytokine: X, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 1 pooled it
0.2field-weighted citation impact, top 35% 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

11 citing papers in PubMed, 1 synthesis or guideline pooled it, 17 citations in OpenAlex.

  1. Pooled it
  2. Review
  3. Article
  4. Article
  5. Article
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  10. Review
  11. Delamanid suppresses CXCL10 expressionFrontiers in immunology · 2022
    Article
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

14 authors at 1 institution in 1 country.

Wenjuan NieTuberculosis Department, Beijing Chest Hospital Affiliated to Capital Medical University, No 9, Beiguan Street, Tongzhou District, Beijing 101149, PR China.
Jun WangTuberculosis Department, Beijing Chest Hospital Affiliated to Capital Medical University, No 9, Beiguan Street, Tongzhou District, Beijing 101149, PR China.
Wei JingTuberculosis Department, Beijing Chest Hospital Affiliated to Capital Medical University, No 9, Beiguan Street, Tongzhou District, Beijing 101149, PR China.
Wenhui ShiTuberculosis Department, Beijing Chest Hospital Affiliated to Capital Medical University, No 9, Beiguan Street, Tongzhou District, Beijing 101149, PR China.
Qingfeng WangTuberculosis Department, Beijing Chest Hospital Affiliated to Capital Medical University, No 9, Beiguan Street, Tongzhou District, Beijing 101149, PR China.
Xuerui HuangTuberculosis Department, Beijing Chest Hospital Affiliated to Capital Medical University, No 9, Beiguan Street, Tongzhou District, Beijing 101149, PR China.
Baoyun CaiTuberculosis Department, Beijing Chest Hospital Affiliated to Capital Medical University, No 9, Beiguan Street, Tongzhou District, Beijing 101149, PR China.
Qiping GeTuberculosis Department, Beijing Chest Hospital Affiliated to Capital Medical University, No 9, Beiguan Street, Tongzhou District, Beijing 101149, PR China.
Lihui NieTuberculosis Department, Beijing Chest Hospital Affiliated to Capital Medical University, No 9, Beiguan Street, Tongzhou District, Beijing 101149, PR China.
Xiqin HanTuberculosis Department, Beijing Chest Hospital Affiliated to Capital Medical University, No 9, Beiguan Street, Tongzhou District, Beijing 101149, PR China.
Yadong DuTuberculosis Department, Beijing Chest Hospital Affiliated to Capital Medical University, No 9, Beiguan Street, Tongzhou District, Beijing 101149, PR China.
Jing WangTuberculosis Department, Beijing Chest Hospital Affiliated to Capital Medical University, No 9, Beiguan Street, Tongzhou District, Beijing 101149, PR China.
Ru GuoTuberculosis Department, Beijing Chest Hospital Affiliated to Capital Medical University, No 9, Beiguan Street, Tongzhou District, Beijing 101149, PR China.
Naihui ChuTuberculosis Department, Beijing Chest Hospital Affiliated to Capital Medical University, No 9, Beiguan Street, Tongzhou District, Beijing 101149, PR China.
Capital Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Tuberculosis (TB) patient serum cytokine levels may be predictive of anti-tuberculosis treatment progress. Here, serum levels of cytokines TNF-α, IL-4, sIL-2R and IFN-γ were measured then correlated to clinical TB manifestations, bacterial burden, chest imaging findings and clinical course. Study subjects included 67 newly diagnosed pulmonary TB (PTB) patients with active disease admitted to Beijing Chest Hospital for anti-TB chemotherapeutic treatment. Blood was drawn at 0 months (pre-treatment), 1-2 months (at any time between 1 and 2 month) and after 6 months completion of treatment and serum TNF-α, IL-4, sIL-2R and IFN-γ levels were measured in duplicate using enzyme-linked immunosorbent assays (ELISAs). Correlation analysis was conducted to evaluate sensitivity and specificity of cytokine levels as predictors of disease activity and treatment progress. The results indicated that the pre-treatment serum TNF-α level of the smear-negative group was lower than that of the smear 1+ group, while serum TNF-α after 6 months completion of treatment and IFN-γ levels at 1-2 months and after 6 months completion of treatment were significantly lower, respectively, than at 0 months (before treatment) (P < 0.05). Using a cut-off value of 845 pg/ml, serum TNF-α level was predictive of treatment progress, with a sensitivity of 51%, specificity of 60% and AUC of 0.594 (P = 0.013). Meanwhile, using a cut-off value of 393 pg/ml, serum IFN-γ provided superior monitoring efficacy, with a sensitivity of 60%, specificity of 64% and AUC of 0.651 (P = 0.017). In conclusion, both serum TNF-α and IFN-γ levels might be useful biomarkers for monitoring treatment progress.

Indexed as

BiomarkerIFN-γIL-4Serum cytokinesIL-2RTNF-αTuberculosis

Identifiers

PMID33604556
PMCPMC7885884
OpenAlexW3024648440

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.