Genetic and clinical predictors for breast cancer risk assessment and stratification among Chinese women.
BACKGROUND
Most of the genetic variants identified from genome-wide association studies of breast cancer have not been validated in Asian women. No risk assessment model that incorporates both genetic and clinical predictors is currently available to predict breast cancer risk in this population.


METHODS
We analyzed 12 single-nucleotide polymorphisms (SNPs) identified in recent genome-wide association studies mostly of women of European ancestry as being associated with the risk of breast cancer in 3039 case patients and 3082 control subjects who participated in the Shanghai Breast Cancer Study. All participants were interviewed in person to obtain information regarding known and suspected risk factors for breast cancer. The c statistic, a measure of discrimination ability with a value ranging from 0.5 (random classification) to 1.0 (perfect classification), was estimated to evaluate the contribution of genetic and established clinical predictors of breast cancer to a newly established risk assessment model for Chinese women. Clinical predictors included in the model were age at menarche, age at first live birth, waist-to-hip ratio, family history of breast cancer, and a previous diagnosis of benign breast disease. The utility of the models in risk stratification was evaluated by estimating the proportion of breast cancer patients in the general population that could be accounted for above a given risk threshold as predicted by the models. All statistical tests were two-sided.


RESULTS
Eight SNPs (rs2046210, rs1219648, rs3817198, rs8051542, rs3803662, rs889312, rs10941679, and rs13281615), each of which reflected a genetically independent locus, were found to be associated with the risk of breast cancer. A dose-response association was observed between the risk of breast cancer and the genetic risk score, which is an aggregate measure of the effect of these eight SNPs (odds ratio for women in the highest quintile of genetic risk score vs those in the lowest = 1.85, 95% confidence interval = 1.58 to 2.18, P(trend) = 2.5 x 10(-15)). The genetic risk score, the waist-to-hip ratio, and a previous diagnosis of benign breast disease were the top three predictors of the risk of breast cancer, each contributing statistically significantly (P < .001) to the full risk assessment model. The model, with a c statistic of 0.6295 after adjustment for overfitting, showed promise for stratifying women into different risk groups; women in the top 30% risk group accounted for nearly 50% of the breast cancers diagnosed in the general population.


CONCLUSIONS
A risk assessment model that includes both genetic markers and clinical predictors may be useful to classify Asian women into relevant risk groups for cost-efficient screening and other prevention programs.
Zheng
Wei
W
Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, 2525 West End Avenue, Nashville, TN 37203-1738, USA. wei.zheng@vanderbilt.edu
Wen
Wanqing
W
Gao
Yu-Tang
YT
Shyr
Yu
Y
Zheng
Ying
Y
Long
Jirong
J
Li
Guoliang
G
Li
Chun
C
Gu
Kai
K
Cai
Qiuyin
Q
Shu
Xiao-Ou
XO
Lu
Wei
W
D000328:Adult; D017668:Age of Onset; D044466:Asian People / Q000235:genetics* / Q000706:statistics & numerical data*; D001943:Breast Neoplasms / Q000453:epidemiology / Q000209:etiology* / Q000235:genetics; D016022:Case-Control Studies; D002681:China / Q000453:epidemiology; D005260:Female; D020022:Genetic Predisposition to Disease; D055106:Genome-Wide Association Study; D005838:Genotype; D006801:Humans; D050498:Live Birth; D008572:Menarche; D008875:Middle Aged; D015233:Models, Statistical; D020641:Polymorphism, Single Nucleotide; D011237:Predictive Value of Tests; D018570:Risk Assessment; D012307:Risk Factors; D049629:Waist-Hip Ratio; D044465:White People / Q000235:genetics