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
Li, Kuanrong
Anderson, Garnet
Viallon, Vivian
Arveux, Patrick
Kvaskoff, Marina
Fournier, Agnès
Krogh, Vittorio
Tumino, Rosario
Sánchez, Maria-Jose
Ardanaz, Eva
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Series / Report no.
Open Access
Type
Article
Language
en
Date of publication
2018-12-03
Year of publication
Research Projects
Organizational Units
Journal Issue
Title
Risk prediction for estrogen receptor-specific breast cancers in two large prospective cohorts.
Translated Title
Published in
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.