Risk prediction for estrogen receptor-specific breast cancers in two large prospective cohorts

Risk prediction for estrogen receptor-specific breast cancers in two large prospective cohorts

Abstract Background 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 predictio...

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Bibliografische gegevens
Hoofdauteurs: Kuanrong Li, Garnet Anderson, Vivian Viallon, Patrick Arveux, Marina Kvaskoff, Agnès Fournier, Vittorio Krogh, Rosario Tumino, Maria-Jose Sánchez, Eva Ardanaz, María-Dolores Chirlaque, Antonio Agudo, David C. Muller, Todd Smith, Ioanna Tzoulaki, Timothy J. Key, Bas Bueno-de-Mesquita, Antonia Trichopoulou, Christina Bamia, Philippos Orfanos, Rudolf Kaaks, Anika Hüsing, Renée T. Fortner, Anne Zeleniuch-Jacquotte, Malin Sund, Christina C. Dahm, Kim Overvad, Dagfinn Aune, Elisabete Weiderpass, Isabelle Romieu, Elio Riboli, Marc J. Gunter, Laure Dossus, Ross Prentice, Pietro Ferrari
Formaat: Artikel
Taal:English
Gepubliceerd in: BMC 2018-12-01
Reeks:Breast Cancer Research
Onderwerpen:
Breast cancer
Risk prediction
Estrogen receptor
Prospective cohort
EPIC
WHI
Online toegang:http://link.springer.com/article/10.1186/s13058-018-1073-0

Internet

http://link.springer.com/article/10.1186/s13058-018-1073-0

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