TY  - JOUR
AU  - Li, Kuanrong
AU  - Anderson, Garnet
AU  - Viallon, Vivian
AU  - Arveux, Patrick
AU  - Kvaskoff, Marina
AU  - Fournier, Agnès
AU  - Krogh, Vittorio
AU  - Tumino, Rosario
AU  - Sánchez, Maria-Jose
AU  - Ardanaz, Eva
AU  - Chirlaque, María-Dolores
AU  - Agudo, Antonio
AU  - Muller, David C
AU  - Smith, Todd
AU  - Tzoulaki, Ioanna
AU  - Key, Timothy J
AU  - Bueno-de-Mesquita, Bas
AU  - Trichopoulou, Antonia
AU  - Bamia, Christina
AU  - Orfanos, Philippos
AU  - Kaaks, Rudolf
AU  - Hüsing, Anika
AU  - Turzanski-Fortner, Renée
AU  - Zeleniuch-Jacquotte, Anne
AU  - Sund, Malin
AU  - Dahm, Christina C
AU  - Overvad, Kim
AU  - Aune, Dagfinn
AU  - Weiderpass, Elisabete
AU  - Romieu, Isabelle
AU  - Riboli, Elio
AU  - Gunter, Marc J
AU  - Dossus, Laure
AU  - Prentice, Ross
AU  - Ferrari, Pietro
TI  - Risk prediction for estrogen receptor-specific breast cancers in two large prospective cohorts.
JO  - Breast cancer research
VL  - 20
IS  - 1
SN  - 1465-542X
CY  - London
PB  - BioMed Central
M1  - DKFZ-2018-02309
SP  - 147
PY  - 2018
AB  - 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
LB  - PUB:(DE-HGF)16
C6  - pmid:30509329
C2  - pmc:PMC6276150
DO  - DOI:10.1186/s13058-018-1073-0
UR  - https://inrepo02.dkfz.de/record/142079
ER  -