A meta-analysis: Is there any association between MiR-608 rs4919510 polymorphism and breast cancer risks?

<div><p>Object</p><p>To combine the data from previously conducted studies about the associations between miR-608 rs4919510 polymorphism (C>G) and breast cancer risks.</p><p>Methods</p><p>According to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, we conducted a systematic review of the related literatures searched from PubMed, Embase, Cochrane Library, Web of Science, and China National Knowledge Internet (CNKI) (time: ~ December 2016). Using DerSimonian-Laird random-effects models [Pooling Model: Mantel Haenszel (MH)], odd ratios (ORs) with 95% confidence intervals (95% CIs) were estimated in the allele model, homozygote model, heterozygote model, dominant model and recessive model. Heterogeneity was analyzed using Labbr plots and I² statistic. Publication bias was analyzed using contour-enhanced funnel plots.</p><p>Results</p><p>We included 5 eligible studies with 7948 patients. The ORs and their 95% CIs in the 5 genetic models mentioned above were 1.009 (95% CI: 0.922, 1.104; p = 0.847), 1.098 (95% CI: 0.954, 1.264; p = 0.194), 1.076 (95% CI: 0.956, 1.211; p = 0.227), 1.043 (95% CI: 0.880, 1.236; p = 0.628), 1.007 (95% CI: 0.906, 1.118; p = 0.899), respectively.</p><p>Conclusion</p><p>In the present meta-analysis, no relationships between miR-608 rs4919510 polymorphism (C>G) and the risk of breast cancer were found. More studies are warranted to further validate the conclusion.</p></div

The results of meta-analysis for various genotype models.

<p>The results of meta-analysis for various genotype models.</p

Scale for methodological quality assessment.

<p>Scale for methodological quality assessment.</p

Literature search and selection of articles.

<p><i>From</i>: Moher D, Liberati A, Tetzlaff J, Altman DG, The PRISMA Group (2009). <i>P</i>referred <i>R</i>eporting <i>I</i>tems for <i>S</i>ystematic Review s and <i>M</i>eta-<i>A</i>nalyses: The PRISMA Statement. PLOS Med 6(6):e1000097. Doi:<a href="https://doi.org/10.1371/journal.pmed1000097" target="_blank">10.1371/journal.pmed1000097</a>. <b>For more information, visit</b><a href="http://www.prisma-statement.org" target="_blank">www.prisma-statement.org</a>.</p

Characteristics of studies included in the meta-analysis.

<p>Characteristics of studies included in the meta-analysis.</p

A timeline of the publications related to breast cancer-related polymorphisms.

<p>Fig 4 was generated through GoPubMed (website: <a href="http://www.gopubmed.com" target="_blank">http://www.gopubmed.com</a>). GoPubMed is a knowledge-based search engine for biomedical texts. The technologies used in GoPubMed are generic and can in general be applied to any kind of texts and any kind of knowledge bases. The system was developed at the Technische Universität Dresden by Michael Schroeder and his team at Transinsight. Creation steps for this timeline: import search items to the Search Box at the home page, then click “Statistics” and download related statistical charts including the timeline and map.</p

Inclusion criteria for study selection in this meta-analysis.

<p>Inclusion criteria for study selection in this meta-analysis.</p

The statistical methods used in this meta-analysis and their explanation.

<p>The statistical methods used in this meta-analysis and their explanation.</p

Excluded studies and the rational for exclusion.

<p>Excluded studies and the rational for exclusion.</p

Labbe plots, sensitivity analysis plots and contour-enhanced funnel plots of the included studies focusing on the association between miR-608 rs4919510 polymorphism and breast cancer risk.

<p>Labbe plots in allele model (<b>A</b>), heterozygote model (<b>B</b>), and dominant model (<b>C</b>). Sensitivity analysis in allele model (<b>D</b>), heterozygote model (<b>E</b>), and dominant model (<b>F</b>). Contour-enhanced funnel plots in allele model (<b>G</b>), heterozygote model (<b>H</b>), and dominant model (<b>I</b>).</p