RT Journal Article
T1 An epidemiological model for prediction of endometrial cancer risk in Europe.
A1 Hüsing, Anika
A1 Dossus, Laure
A1 Ferrari, Pietro
A1 Tjønneland, Anne
A1 Hansen, Louise
A1 Fagherazzi, Guy
A1 Baglietto, Laura
A1 Schock, Helena
A1 Chang-Claude, Jenny
A1 Boeing, Heiner
A1 Steffen, Annika
A1 Trichopoulou, Antonia
A1 Bamia, Christina
A1 Katsoulis, Michalis
A1 Krogh, Vittorio
A1 Palli, Domenico
A1 Panico, Salvatore
A1 Onland-Moret, N Charlotte
A1 Peeters, Petra H
A1 Bueno-de-Mesquita, H Bas
A1 Weiderpass, Elisabete
A1 Gram, Inger T
A1 Ardanaz, Eva
A1 Obón-Santacana, Mireia
A1 Navarro, Carmen
A1 Sánchez-Cantalejo, Emilio
A1 Etxezarreta, Nerea
A1 Allen, Naomi E
A1 Khaw, Kay Tee
A1 Wareham, Nick
A1 Rinaldi, Sabina
A1 Romieu, Isabelle
A1 Merritt, Melissa A
A1 Gunter, Marc
A1 Riboli, Elio
A1 Kaaks, Rudolf
K1 Endometrial cancer
K1 Epidemiology
K1 Prevention
K1 Risk model
AB Endometrial cancer (EC) is the fourth most frequent cancer in women in Europe, and as its incidence is increasing, prevention strategies gain further pertinence. Risk prediction models can be a useful tool for identifying women likely to benefit from targeted prevention measures. On the basis of data from 201,811 women (mostly aged 30-65 years) including 855 incident EC cases from eight countries in the European Prospective Investigation into Cancer and Nutrition cohort, a model to predict EC was developed. A step-wise model selection process was used to select confirmed predictive epidemiologic risk factors. Piece-wise constant hazard rates in 5-year age-intervals were estimated in a cause-specific competing risks model, five-fold-cross-validation was applied for internal validation. Risk factors included in the risk prediction model were body-mass index (BMI), menopausal status, age at menarche and at menopause, oral contraceptive use, overall and by different BMI categories and overall duration of use, parity, age at first full-term pregnancy, duration of menopausal hormone therapy and smoking status (specific for pre, peri- and post-menopausal women). These variables improved the discriminating capacity to predict risk over 5 years from 71% for a model based on age alone to 77% (overall C statistic), and the model was well-calibrated (ratio of expected to observed cases = 0.99). Our model could be used for the identification of women at increased risk of EC in Western Europe. To achieve an EC-risk model with general validity, a large-scale cohort-consortium approach would be needed to assess and adjust for population variation.
YR 2015
FD 2015-05-13
LK http://hdl.handle.net/10668/9816
UL http://hdl.handle.net/10668/9816
LA en
DS RISalud
RD Apr 14, 2025