Endometrial cancer risk prediction including serum-based biomarkers: results from the EPIC cohort.
- Fortner, Renée T
- Hüsing, Anika
- Kühn, Tilman
- Konar, Meric
- Overvad, Kim
- Tjønneland, Anne
- Hansen, Louise
- Boutron-Ruault, Marie-Christine
- Severi, Gianluca
- Fournier, Agnès
- Boeing, Heiner
- Trichopoulou, Antonia
- Benetou, Vasiliki
- Orfanos, Philippos
- Masala, Giovanna
- Agnoli, Claudia
- Mattiello, Amalia
- Tumino, Rosario
- Sacerdote, Carlotta
- Bueno-de-Mesquita, H B As
- Peeters, Petra H M
- Weiderpass, Elisabete
- Gram, Inger T
- Gavrilyuk, Oxana
- Quirós, J Ramón
- Maria Huerta, José
- Ardanaz, Eva
- Larrañaga, Nerea
- Lujan-Barroso, Leila
- Sánchez-Cantalejo, Emilio
- Butt, Salma Tunå
- Borgquist, Signe
- Idahl, Annika
- Lundin, Eva
- Khaw, Kay-Tee
- Allen, Naomi E
- Rinaldi, Sabina
- Dossus, Laure
- Gunter, Marc
- Merritt, Melissa A
- Tzoulaki, Ioanna
- Riboli, Elio
- Kaaks, Rudolf
DOIAbstract
Endometrial cancer risk prediction models including lifestyle, anthropometric and reproductive factors have limited discrimination. Adding biomarker data to these models may improve predictive capacity; to our knowledge, this has not been investigated for endometrial cancer. Using a nested case-control study within the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort, we investigated the improvement in discrimination gained by adding serum biomarker concentrations to risk estimates derived from an existing risk prediction model based on epidemiologic factors. Serum concentrations of sex steroid hormones, metabolic markers, growth factors, adipokines and cytokines were evaluated in a step-wise backward selection pro...
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