A Personal Breast Cancer Risk Stratification Model Using Common Variants and Environmental Risk Factors in Japanese Females

Author:

Oze IsaoORCID,Ito HidemiORCID,Kasugai Yumiko,Yamaji Taiki,Kijima Yuko,Ugai Tomotaka,Kasuga Yoshio,Ouellette Tomoyo K.,Taniyama Yukari,Koyanagi Yuriko N.,Imoto IsseiORCID,Tsugane ShoichiroORCID,Koriyama Chihaya,Iwasaki Motoki,Matsuo KeitaroORCID

Abstract

Personalized approaches to prevention based on genetic risk models have been anticipated, and many models for the prediction of individual breast cancer risk have been developed. However, few studies have evaluated personalized risk using both genetic and environmental factors. We developed a risk model using genetic and environmental risk factors using 1319 breast cancer cases and 2094 controls from three case–control studies in Japan. Risk groups were defined based on the number of risk alleles for 14 breast cancer susceptibility loci, namely low (0–10 alleles), moderate (11–16) and high (17+). Environmental risk factors were collected using a self-administered questionnaire and implemented with harmonization. Odds ratio (OR) and C-statistics, calculated using a logistic regression model, were used to evaluate breast cancer susceptibility and model performance. Respective breast cancer ORs in the moderate- and high-risk groups were 1.69 (95% confidence interval, 1.39–2.04) and 3.27 (2.46–4.34) compared with the low-risk group. The C-statistic for the environmental model of 0.616 (0.596–0.636) was significantly improved by combination with the genetic model, to 0.659 (0.640–0.678). This combined genetic and environmental risk model may be suitable for the stratification of individuals by breast cancer risk. New approaches to breast cancer prevention using the model are warranted.

Funder

Japan Agency for Medical Research and Development

Japan Society for the Promotion of Science

Grants-in-Aid for Scientific Research from the Ministry of Education, Science, Sports, Culture and Technology of Japan Priority Areas of Cancer

Publisher

MDPI AG

Subject

Cancer Research,Oncology

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