Risk prediction for estrogen receptor-specific breast cancers in two large prospective cohorts.
Li, Kuanrong; Anderson, Garnet; Viallon, Vivian; Arveux, Patrick; Kvaskoff, Marina; Fournier, Agnès; Krogh, Vittorio; Tumino, Rosario; Sánchez, Maria-Jose; Ardanaz, Eva; Chirlaque, María-Dolores; Agudo, Antonio; Muller, David C; Smith, Todd; Tzoulaki, Ioanna; Key, Timothy J; Bueno-de-Mesquita, Bas; Trichopoulou, Antonia; Bamia, Christina; Orfanos, Philippos; Kaaks, Rudolf; Hüsing, Anika; Fortner, Renée T; Zeleniuch-Jacquotte, Anne; Sund, Malin; Dahm, Christina C; Overvad, Kim; Aune, Dagfinn; Weiderpass, Elisabete; Romieu, Isabelle; Riboli, Elio; Gunter, Marc J; Dossus, Laure; Prentice, Ross; Ferrari, Pietro
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Open Access
Type
Article
Language
en
Date
2018-12-03
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Title
Risk prediction for estrogen receptor-specific breast cancers in two large prospective cohorts.
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Breast Cancer Res 2018; 20(1):147
Abstract
Few published breast cancer (BC) risk prediction models consider the heterogeneity of predictor variables between estrogen-receptor positive (ER+) and negative (ER-) tumors. Using data from two large cohorts, we examined whether modeling this heterogeneity could improve prediction. We built two models, for ER+ (Model Parity, number of full-term pregnancies, age at first full-term pregnancy and body height were only associated with ER+ tumors. Menopausal status, age at menarche and at menopause, hormone replacement therapy, postmenopausal body mass index, and alcohol intake were homogeneously associated with ER+ and ER- tumors. Internal validation yielded a C-statistic of 0.64 for Model Modeling heterogeneous epidemiological risk factors might yield little improvement in BC risk prediction. Nevertheless, a model specifically predictive of ER+ tumor risk could be more applicable than an omnibus model in risk assessment for chemoprevention.