Evidence map›Paper›PMID 26884950›Full record

ArticleInternational journal of clinical and experimental medicine2015

Correlation between PON1 gene polymorphisms and breast cancer risk: a Meta-analysis.

Yayuan Wen, Zemin Huang, Xiaohua Zhang, Bo Gao, Yujun He

Open access · greenAbstract read
In one paragraph

Article in International journal of clinical and experimental medicine, 2015. 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
1.1field-weighted citation impact, top 24% 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, 13 citations in OpenAlex.

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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

5 authors at 2 institutions in 1 country.

Yayuan WenDepartment of General Surgery, Daping Hospital and Research Institute of Surgery, Third Military Medical University Chongqing 400042, P. R. China.
Zemin HuangChinese Astronaut Research and Training Center Beijing 100094, P. R. China.
Xiaohua ZhangDepartment of General Surgery, Daping Hospital and Research Institute of Surgery, Third Military Medical University Chongqing 400042, P. R. China.
Bo GaoDepartment of General Surgery, Daping Hospital and Research Institute of Surgery, Third Military Medical University Chongqing 400042, P. R. China.
Yujun HeDepartment of General Surgery, Daping Hospital and Research Institute of Surgery, Third Military Medical University Chongqing 400042, P. R. China.
Army Medical University · CNChina Astronaut Research and Training Center · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveA number of studies have investigated the relationship between the PON1 gene polymorphisms and breast cancer risk, but the conclusions are not consistent. In this paper, a meta-analysis was conducted to explore the possible reasons for these inconsistencies, expecting to further clarify the correlation between PON1 gene polymorphisms and breast cancer risk.

methodsAfter searches in the database such as MEDLINE, EBSCO, ProQuest, Google Scholar, High-Wire, SID (Scientific Information Database) and PubMed, 7 literatures were collected. RevMan 5.2 software was used to perform the meta-analysis. Random-effects or fixed-effects model was used to analyze the odds ratio (OR) and 95% confidence intervals.

resultsThe analysis of L55M single nucleotide polymorphisms (SNPs) showed that M allele frequency was positively correlated with the incidence risk of breast cancer (OR=1.34, 95% CI: 1.03-1.74). While we did not found Q192R polymorphism associated with the risk of breast cancer (OR=1.0, 95% CI: 0.71-1.42).

conclusionFor PON1 gene, the frequencies of M allele were associated with the incidence risk of breast cancer.

Indexed as

geneticsmeta-analysisParaoxonase

Identifiers

PMID26884950
PMCPMC4723795
OpenAlexW2291289478

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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.