Li, Kuanrong; Hüsing, Anika; Fortner, Renée Turzanski; Tjønneland, Anne; Hansen, Louise Seier; Dossus, Laure; Chang-Claude, Jenny; Bergmann, Manuela M.; Steffen, Annika; Bamia, Christina; Trichopoulos, Dimitrios; Trichopoulou, Antonia; Palli, Domenico; Mattiello, Amalia; Agnoli, Claudia; Tumino, Rosaria; Onland-Moret, N. Charlotte; Peeters, Petra H.; Bueno-de-Mesquita, H. Bas; Gram, Inger Torhild; Weiderpass, Elisabete; Sánchez-Cantalejo, Emilio; Chirlaque, María-Dolores; Duell, Eric J.; Ardanaz, Eva; Idahl, Annika; Lundin, Eva; Khaw, Kay-Tee; Travis, Ruth C.; Merritt, Melissa A.; Gunter, Marc J.; Riboli, Elio; Ferrari, Pietro; Terry, Kathryn L.; Cramer, Daniel William; Kaaks, Rudolf (Journal article; Tidsskriftartikkel; Peer reviewed, 2015-03-05)
Background: Ovarian cancer has a high case-fatality ratio, largely due to late diagnosis. Epidemiologic risk prediction models could help identify
women at increased risk who may benefit from targeted prevention measures, such as screening or chemopreventive agents.<p>
<p>Methods: We built an ovarian cancer risk prediction model with epidemiologic risk factors from 202 206 women in the European ...