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Impact of known risk factors on endometrial cancer burden in Chinese women.

ABSTRACT: This study aimed to provide data on the impact of known risk factors on endometrial cancer burden. Using data on 1199 endometrial cancer cases and 1212 frequency matched controls from a population-based case-control study carried out in urban Shanghai, China from 1997 to 2003, multivariable adjusted odds ratios were obtained from unconditional logistic regression analyses. Partial population-attributable risks were calculated and corresponding 95% confidence intervals were estimated using a bootstrap method. An estimated 16.94% of endometrial cancer cases were attributed to overweight or obesity; 8.39% to meat intake; 5.45% to nonregular tea drinking; 5.23% to physical inactivity; and 1.77% to family history of endometrial, breast, or colorectal cancers. Overall, these risk factors accounted for 36.01% (95% confidence interval: 28.55-43.11%) of total endometrial cancer cases. Similar results were observed when analysis was restricted to postmenopausal women. Among modifiable lifestyle factors, overweight and obesity accounted for the largest proportion of endometrial cancer in the study population. Lifestyle alterations, such as maintenance of healthy weight, regular exercise, consumption of less meat, and tea drinking, could potentially reduce endometrial cancer by more than one-third.

SUBMITTER: Gao J

PROVIDER: S-EPMC4676733 | biostudies-literature | 2016 Jul

REPOSITORIES: biostudies-literature

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Impact of known risk factors on endometrial cancer burden in Chinese women.

Gao Jing J Yang Gong G Wen Wanqing W Cai Qiu-Yin QY Zheng Wei W Shu Xiao-Ou XO Xiang Yong-Bing YB

European journal of cancer prevention : the official journal of the European Cancer Prevention Organisation (ECP) 20160701 4

This study aimed to provide data on the impact of known risk factors on endometrial cancer burden. Using data on 1199 endometrial cancer cases and 1212 frequency matched controls from a population-based case-control study carried out in urban Shanghai, China from 1997 to 2003, multivariable adjusted odds ratios were obtained from unconditional logistic regression analyses. Partial population-attributable risks were calculated and corresponding 95% confidence intervals were estimated using a boot ...[more]

PMID: 26075656

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Project description:INTRODUCTION: Recently, several genome-wide association studies (GWAS) have identified novel single nucleotide polymorphisms (SNPs) associated with breast cancer risk. However, most of the studies were conducted among Caucasians and only one from Chinese. METHODS: In the current study, we first tested whether 15 SNPs identified by previous GWAS were also breast cancer marker SNPs in this Chinese population. Then, we grouped the marker SNPs, and modeled them with clinical risk factors, to see the usage of these factors in breast cancer risk assessment. Two methods (risk factors counting and odds ratio (OR) weighted risk scoring) were used to evaluate the cumulative effects of the five significant SNPs and two clinical risk factors (age at menarche and age at first live birth). RESULTS: Five SNPs located at 2q35, 3p24, 6q22, 6q25 and 10q26 were consistently associated with breast cancer risk in both testing set (878 cases and 900 controls) and validation set (914 cases and 967 controls) samples. Overall, all of the five SNPs contributed to breast cancer susceptibility in a dominant genetic model (2q35, rs13387042: adjusted OR = 1.26, P = 0.006; 3q24.1, rs2307032: adjusted OR = 1.24, P = 0.005; 6q22.33, rs2180341: adjusted OR = 1.22, P = 0.006; 6q25.1, rs2046210: adjusted OR = 1.51, P = 2.40 × 10-8; 10q26.13, rs2981582: adjusted OR = 1.31, P = 1.96 × 10-4). Risk score analyses (area under the curve (AUC): 0.649, 95% confidence interval (CI): 0.631 to 0.667; sensitivity = 62.60%, specificity = 57.05%) presented better discrimination than that by risk factors counting (AUC: 0.637, 95% CI: 0.619 to 0.655; sensitivity = 62.16%, specificity = 60.03%) (P < 0.0001). Absolute risk was then calculated by the modified Gail model and an AUC of 0.658 (95% CI = 0.640 to 0.676) (sensitivity = 61.98%, specificity = 60.26%) was obtained for the combination of five marker SNPs, age at menarche and age at first live birth. CONCLUSIONS: This study shows that five GWAS identified variants were also consistently validated in this Chinese population and combining these genetic variants with other risk factors can improve the risk predictive ability of breast cancer. However, more breast cancer associated risk variants should be incorporated to optimize the risk assessment.

Dataset Information

Impact of known risk factors on endometrial cancer burden in Chinese women.

Publications

Impact of known risk factors on endometrial cancer burden in Chinese women.

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