Evidence map›Paper›PMID 32541494›Full record

SynthesisMedicine2020

Association between HIF-1α gene polymorphisms and lung cancer: A meta-analysis.

Shuguang Xu, Kejing Ying

Open access · goldAbstract readMeta-Analysis
In one paragraph

Synthesis in Medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.6field-weighted citation impact, top 41% 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

5 citing papers in PubMed, 9 citations in OpenAlex.

  1. Article
  2. Article
  3. Review
  4. Article
  5. 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

2 authors at 2 institutions in 1 country.

Shuguang XuDepartment of Respiratory Medicine, Sir Run Run Shaw Hospital, College of Medicine, Zhejiang University, Hangzhou.
Kejing YingDepartment of Respiratory Medicine, Sir Run Run Shaw Hospital, College of Medicine, Zhejiang University, Hangzhou.
Sir Run Run Shaw Hospital · CNZhejiang University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Hypoxia-inducible factor-1 (HIF-1), an important component of angiogenesis, is activated as a response to tumor hypoxia and facilitates tumor survival. Several case-control articles stressed the connection between lung cancer danger and HIF-1α gene polymorphism, but the conclusions were conflicting. Thus, this meta-analysis was carried out to assess the connection between HIF-1α gene polymorphisms (rs11549467, rs11549465, and rs2057482) and lung cancer risk.PubMed, Embase, Cochrane Library, and Google Scholar were systematically searched up to November 1, 2018. The study quality was quantified by the c. The odds ratios (ORs) and 95% confidence intervals (CIs) were pooled in 5 genetic models for assessment under a fixed- or random-effect model. Subgroup analyses were carried out by ethnicity and genotype method. Sensitivity analysis and publication bias were tested. Five eligible articles were enrolled.The rs11549467 significantly increased the lung cancer risk (OR [95% CI]: A vs G, 1.68 [1.03-2.76]; AA + AG vs GG, 1.70 [1.14-2.54]; AA vs GG, 1.59 [1.21-2.10]), whereas neither rs11549465 nor rs2057482 was related with the lung cancer risk. Subgroup analysis showed rs11549465 and rs11549467 increased lung cancer risk among Asians, but not whites. HIF-1α rs2057482 was unrelated to the risk of lung cancer in Asians and whites.HIF-1α gene rs11549465 and rs11549467, but not rs2057482, increased the risk of lung cancer among Asians.

Indexed as

Polymorphism, Single NucleotideHumansHypoxia-Inducible Factor 1, alpha SubunitLung NeoplasmsRisk AssessmentHIF1A protein, humanHypoxia-Inducible Factor 1, alpha Subunit

Identifiers

PMID32541494
PMCPMC7302596
OpenAlexW3035611763

What OpenQuestion holds

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LicenceCC BY-NC
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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.