%0 Journal Article
%A Li, Kuanrong
%A Anderson, Garnet
%A Viallon, Vivian
%A Arveux, Patrick
%A Kvaskoff, Marina
%A Fournier, Agnès
%A Krogh, Vittorio
%A Tumino, Rosario
%A Sánchez, Maria-Jose
%A Ardanaz, Eva
%A Chirlaque, María-Dolores
%A Agudo, Antonio
%A Muller, David C
%A Smith, Todd
%A Tzoulaki, Ioanna
%A Key, Timothy J
%A Bueno-de-Mesquita, Bas
%A Trichopoulou, Antonia
%A Bamia, Christina
%A Orfanos, Philippos
%A Kaaks, Rudolf
%A Hüsing, Anika
%A Turzanski-Fortner, Renée
%A Zeleniuch-Jacquotte, Anne
%A Sund, Malin
%A Dahm, Christina C
%A Overvad, Kim
%A Aune, Dagfinn
%A Weiderpass, Elisabete
%A Romieu, Isabelle
%A Riboli, Elio
%A Gunter, Marc J
%A Dossus, Laure
%A Prentice, Ross
%A Ferrari, Pietro
%T Risk prediction for estrogen receptor-specific breast cancers in two large prospective cohorts.
%J Breast cancer research
%V 20
%N 1
%@ 1465-542X
%C London
%I BioMed Central
%M DKFZ-2018-02309
%P 147
%D 2018
%X 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+ (ModelER+) and ER- tumors (ModelER-), respectively, in 281,330 women (51
%F PUB:(DE-HGF)16
%9 Journal Article
%$ pmid:30509329
%2 pmc:PMC6276150
%R 10.1186/s13058-018-1073-0
%U https://inrepo02.dkfz.de/record/142079