Evidence map›Paper›PMID 25792844›Full record

ArticleOncoTargets and therapy2015

The association between the migration inhibitory factor -173G/C polymorphism and cancer risk: a meta-analysis.

Xiao Zhang, Wenhao Weng, Wen Xu, Yulan Wang, Wenjun Yu, Xun Tang, Lifang Ma, Qiuhui Pan, Jiayi Wang, Fenyong Sun

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in OncoTargets and therapy, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
–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

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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. Review
  2. Article
  3. Review
  4. Article
  5. Genetic Variants of thePharmacogenomics and personalized medicine · 2021
    Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. 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.

Xiao ZhangDepartment of Clinical laboratory medicine, Shanghai Tenth People's Hospital of Tongji University, Shanghai, People's Republic of China.
Wenhao WengDepartment of Clinical laboratory medicine, Shanghai Tenth People's Hospital of Tongji University, Shanghai, People's Republic of China.
Wen XuDepartment of Clinical laboratory medicine, Zhongshan Hospital, Fudan University, Shanghai, People's Republic of China.
Yulan WangDepartment of Clinical laboratory medicine, Shanghai Tenth People's Hospital of Tongji University, Shanghai, People's Republic of China.
Wenjun YuDepartment of Clinical laboratory medicine, Shanghai Tenth People's Hospital of Tongji University, Shanghai, People's Republic of China.
Xun TangDepartment of Clinical laboratory medicine, Shanghai Tenth People's Hospital of Tongji University, Shanghai, People's Republic of China.
Lifang MaDepartment of Clinical laboratory medicine, Shanghai Tenth People's Hospital of Tongji University, Shanghai, People's Republic of China.
Qiuhui PanDepartment of Central Laboratory, Shanghai Tenth People's Hospital of Tongji University, Shanghai, People's Republic of China.
Jiayi WangDepartment of Clinical laboratory medicine, Shanghai Tenth People's Hospital of Tongji University, Shanghai, People's Republic of China.
Fenyong SunDepartment of Clinical laboratory medicine, Shanghai Tenth People's Hospital of Tongji University, Shanghai, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Previous studies have suggested that macrophage migration inhibitory factor (MIF) -173G/C polymorphism may be associated with cancer risk. However, previous research has demonstrated conflicting results. Therefore, we followed the preferred reporting items for systematic reviews and meta-analyses (PRISMA) guidelines and the meta-analysis on genetic association studies checklist, and performed a meta-analysis to investigate the association between MIF -173G/C polymorphisms and the risk of cancer. Odds ratios (ORs) and corresponding 95% confidence intervals (CIs) were combined to measure the association between MIF promoter polymorphisms and cancer risk. The pooled ORs were performed for the dominant model, recessive model, allelic model, homozygote comparison, and heterozygote comparison. The publication bias was examined by Begg's funnel plots and Egger's test. A total of ten studies enrolling 2,203 cases and 2,805 controls met the inclusion criteria. MIF (-173G/C) polymorphism was significantly associated with increased cancer risk under the dominant model (OR=1.32, 95%, CI=1.00-1.74, P=0.01) and the heterozygote comparison (OR=1.38, CI=1.01-1.87, P=0.04). In subgroup analysis, MIF polymorphism and prostate were related to increased risk of prostate and non-solid cancer. In conclusion, MIF polymorphism was significantly associated with cancer risk in heterozygote comparison. The MIF -173G/C polymorphism may be associated with increased cancer risk.

Indexed as

cancer susceptibilityMIFSNPsystematic review

Identifiers

PMID25792844
PMCPMC4360805

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