Meta-Analysis:
Vitamin D receptor Taq I polymorphism and the risk of prostate cancer: a meta-analysis
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Abstract
Shaosan Kang1,*, Yansheng Zhao2,*, Lei Wang1, Jian Liu1, Xi Chen1, Xiaofeng Liu3, Zhijie Shi4, Weixing Gao1 and Fenghong Cao1
1Department of Urology, North China University of Science and Technology Affiliated Hospital, Tangshan 063000, China
2Department of Imaging, KaiLuan General Hospital, Tangshan 063000, China
3Department of Surgery, LaoTing Traditional Chinese Medicine Hospital, Tangshan 063600, China
4Department of Urology, TangShan Gongren Hospital, Tangshan 063000, China
*These authors contributed equally to this work
Correspondence to:
Shaosan Kang, email: [email protected]
Keywords: Taq I; prostate cancer; vitamin D receptor; polymorphisms; meta-analysis
Received: September 11, 2017 Accepted: December 15, 2017 Published: December 22, 2017
ABSTRACT
Numerous previous studies reported the association of Vitamin D receptor gene Taq Ipolymorphism with prostate cancer risk, however these results were controversial. In order to provide a relatively comprehensive description of this relationship, we conducted this meta-analysis by searching PubMed, Embase, and China National Knowledge Infrastructure. Finally, 36 studies with 8,423 cases and 8,887 controls were included. Taq I polymorphism was found to marginally increase the prostate cancer risk in recessive genetic model (tt/Tt vs. TT: Odds Ratio (OR) = 0.89, 95% Confidence Interval (CI) = 0.80–1.00, p = 0.05) and allele genetic model (t vs. T allele: OR = 0.91, 95% CI = 0.84–0.99, p = 0.003) in the overall analysis. Subgroup analyses showed that significant increased risk was found in Asians in homozygote model (tt vs. TT: OR = 0.63, 95% CI = 0.41–0.95, p = 0.029) and allele genetic model (t vs. T: OR = 0.78, 95% CI = 0.67–0.90, p = 0.002), and in the subgroup of population-based controls in all the genetic models. These results suggest that Taq Ipolymorphism might be a risk factor of prostate cancer risk, especially in Asians. It could be considered as a promising target to predict the prostate cancer risk for clinical practice.
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