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Factors Influencing the Association between CYP17 T34C Polymorphism and the Risk of Breast Cancer: Meta-regression and Subgroup Analysis
Chen Yun 1 *,Pei Jianpin 2
1.School of Pharmacy,NanJing Medical University,Nanjing 210000
2.School of Integrated Transport,Jiangsu Provincial jiaotong Plan and Design Institute
*Correspondence author
#Submitted by
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Funding: Jiangsu natural science fund (No.BK2009419) Doctoral Fund)
Opened online:24 December 2012
Accepted by: none
Citation: Chen Yun,Pei Jianpin.Factors Influencing the Association between CYP17 T34C Polymorphism and the Risk of Breast Cancer: Meta-regression and Subgroup Analysis[OL]. [24 December 2012] http://en.paper.edu.cn/en_releasepaper/content/4500293
 
 
A number of studies have investigated the association between CYP17 T34C polymorphism and the risk of breast cancer; the results of these studies are inconsistent, however. This fact implies that the effect of CYP17 T34C polymorphism on susceptibility to breast cancer may be modified by other risk factors. To provide a more definitive conclusion, a full meta-analysis combining and summarizing 24 studies was first performed. Both traditional method and Bayesian approach were applied. Odds ratio was estimated using a dominant mode of inheritance after a biological justification for the choice of genetic model. The results of homogeneity analysis (H = 1.16, I2 = 25.4% and p = 0.127) suggested the presence of heterogeneity across the studies. Thus random effects models simulated by the DerSimonian-Laird method were employed. The capability of a Bayesian approach was highlighted in the estimation of a pooled odds ratio and 95% confidence interval. The results of meta-analysis (OR =1.001, CI=0.832-1.208) suggest no significant association in the combined populations. Furthermore, Bayesian meta-regression and subgroup analysis were conducted to investigate the sources of heterogeneity. The risk factors evaluated in the study were menopausal status, ethnicity, age at menarche, age at first birth, parity, use of oral contraceptives, body mass index (BMI) and use of hormone repair therapy (HRT). After these population stratifications, there was evidence indicating a possible impact of menopausal status, age at menarche and BMI on the association between CYP17 T34C polymorphism and the risk of breast cancer.
Keywords:CYP17;Polymorphism;Breast Cancer;Bayesian Meta-regression;Subgroup Meta-analysis
 
 
 

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