Evidence map›Paper›PMID 28548958›Full record

SynthesisOncotarget2017

Interleukin-6-174G>C gene promoter polymorphism and prognosis in patients with cancer.

Kan Zhai, Yong Yang, Zhi-Gang Gao, Jie Ding

Abstract readMeta-Analysis
In one paragraph

Synthesis in Oncotarget, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed, 1 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

9 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  3. Article
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  8. American journal of translational research · 2019
    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

4 authors.

Kan ZhaiMedical Research Center, Beijing Chao-Yang Hospital, Capital Medical University, Beijing 100020, China.
Yong YangDepartment of General Surgery, Beijing Chao-Yang Hospital, Capital Medical University, Beijing 100020, China.
Zhi-Gang GaoDepartment of General Surgery, Beijing Chao-Yang Hospital, Capital Medical University, Beijing 100020, China.
Jie DingMedical Research Center, Beijing Chao-Yang Hospital, Capital Medical University, Beijing 100020, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Interleukin-6 (IL-6) is known to be involved in the pathogenesis of cancer progression. IL-6-174G>C polymorphism has shown several results in association studies. In this study, we evaluated the association the IL-6-174G>C polymorphism and overall survival (OS) of cancer using 17 eligible studies with 4,304 patients. Our meta-analysis indicated that IL-6-174G>C polymorphism is not associated with OS when assessed using 3 genotype comparison including GG/(GC+CC), CC/(GC+GG) and CC/GG. Interestingly, compared to GG carrier, patients with IL-6-174GC genotype showed a decreased hazard of poor OS (hazard ratio = 0.81, 95% confidence interval: 0.68-0.96, P = 0.018; I2 = 34.5%, Phet = 0.107). However, for GG/(GC+CC) genotype comparison, this SNP is affect patients' OS obviously in bladder cancer, ovarian and peritoneal cancer, neuroblastoma, gastric cancer and osteosarcoma, though pooled results showing negative association because adverse and protective effect on different type of cancer balance each other. These results suggest IL-6-174G>C polymorphism might play a role in modulating OS in different type of cancer and might contribute to individual treatment in the future.

Indexed as

AllelesPolymorphism, Single NucleotidePromoter Regions, GeneticGenetic Association StudiesGenetic Predisposition to DiseaseHumansInterleukin-6NeoplasmsPrognosisPublication BiasInterleukin-6cancerInterleukin-6meta-analysispolymorphismprognosis

Identifiers

PMID28548958
PMCPMC5546496

What OpenQuestion holds

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Registered trials

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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.