Association of 17q24 rs1859962 gene polymorphism with prostate cancer risk: A systematic review and meta-analysis.

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ID: 96282
2020
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Abstract
Recently, several genome-wide association studies have demonstrated a cumulative association of 17q24 rs1859962 gene variants with prostate cancer (PCa) risk, but conflicting results on this issue have been reported. Hence, we performed a systematic literature review and meta-analysis to assess the association between 17q24 rs1859962 gene and PCa risk.Systematic literature searches were conducted with PubMed, EMBASE, Science Direct/Elsevier, CNKI, and the Cochrane Library up to January 2019 for studies focusing on the association of 17q24 rs1859962 gene polymorphism with PCa risk. Meta-analysis was performed with Review Manager and stata software. Combined OR were identified with 95% confidence intervals (95% CI) in a random or fixed effects model.Eight studies were identified, including 7863 cases of PCa patients and 17122 normal controls. Our results revealed significant associations between the 17q24 rs1859962 gene polymorphism and PCa in all genetic models (P < 0.05). The combined odds ratios and 95% confidence intervals were as follows: Additive model (odds ratios [ORs] 1.44, 95%, confidence interval [CI] [1.32, 1.57]); Codominant model (ORs 1.22, 95% CI [1.08, 1.39]); Dominant model (ORs 1.25, 95%, CI [1.17, 1.34]); recessive model (ORs 1.27, 95% CI [1.18, 1.36]); allele model (ORs 1.32, 95% CI [1.12, 1.55]).The present study supports the proposed association between the 17q24 gene rs1859962 and PCa progression. Specifically, this polymorphism is suggested to be a risk factor of PCa. However, studies with larger sample sizes are needed to better illuminate the correlation between 17q24 rs1859962 gene polymorphism and PCa.
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ren2020associationmedicine Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Ren, Feiqiang;Zhang, Peihai;Ma, Ziyang;Zhang, Ling;Li, Guangsen;Huang, Xiaopeng;Chang, Degui;Yu, Xujun;
Journal Medicine
Year 2020
DOI
10.1097/MD.0000000000018398
URL
Keywords
copd treatment optimization clinical practice adherence to therapy

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