TY - JOUR
T1 - A personal breast cancer risk stratification model using common variants and environmental risk factors in japanese females
AU - Oze, Isao
AU - Ito, Hidemi
AU - Kasugai, Yumiko
AU - Yamaji, Taiki
AU - Kijima, Yuko
AU - Ugai, Tomotaka
AU - Kasuga, Yoshio
AU - Ouellette, Tomoyo K.
AU - Taniyama, Yukari
AU - Koyanagi, Yuriko N.
AU - Imoto, Issei
AU - Tsugane, Shoichiro
AU - Koriyama, Chihaya
AU - Iwasaki, Motoki
AU - Matsuo, Keitaro
N1 - Funding Information:
Funding: This research was supported by AMED under Grant Number JP17ck0106177 and JP20ck010 6553. The Nagano study was supported by Grants-in-Aid for Research on Risk of Chemical Substances and the Third Term Comprehensive Ten-Year Strategy for Cancer Control from the Ministry of Health, Labor and Welfare of Japan. The Kagoshima study was supported by JSPS KAKENHI Grants (JP20590650). The Aichi study was funded by Grants-in-Aid for Scientific Research from the Ministry of Education, Science, Sports, Culture and Technology of Japan Priority Areas of Cancer (No. 17015018), Innovative Areas (No. 221S0001), JSPS KAKENHI Grants (JP16H06277), Grant-in-Aid for the Third Term Comprehensive 10-year Strategy for Cancer Control from the Ministry of Health, Labour and Welfare of Japan.
Publisher Copyright:
© 2021 by the authors. Licensee MDPI, Basel, Switzerland.
PY - 2021/8/1
Y1 - 2021/8/1
N2 - 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.
AB - 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.
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U2 - 10.3390/cancers13153796
DO - 10.3390/cancers13153796
M3 - Article
AN - SCOPUS:85111246426
SN - 2072-6694
VL - 13
JO - Cancers
JF - Cancers
IS - 15
M1 - 3796
ER -