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Endometrial cancer risk prediction including serum-based biomarkers: results from the EPIC cohort

Authors :
Kim Overvad
Marc J. Gunter
Inger T. Gram
Giovanna Masala
Agnès Fournier
Salma Butt
Kay-Tee Khaw
J. Ramón Quirós
Sabina Rinaldi
Carlotta Sacerdote
Tilman Kühn
José María Huerta
Meric Konar
H. Bas Bueno-de-Mesquita
Gianluca Severi
Renée T. Fortner
Eva Ardanaz
Leila Lujan-Barroso
Claudia Agnoli
Vasiliki Benetou
Rosario Tumino
Amalia Mattiello
Anika Hüsing
Oxana Gavrilyuk
Marie-Christine Boutron-Ruault
Elio Riboli
Antonia Trichopoulou
Rudolf Kaaks
Nerea Larrañaga
Petra H.M. Peeters
Eva Lundin
Emilio Sánchez-Cantalejo
Elisabete Weiderpass
Louise Hansen
Signe Borgquist
Ioanna Tzoulaki
Philippos Orfanos
Naomi E. Allen
Annika Idahl
Melissa A. Merritt
Anne Tjønneland
Laure Dossus
Heiner Boeing
Source :
International Journal of Cancer. 140:1317-1323
Publication Year :
2017
Publisher :
Wiley, 2017.

Abstract

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 process; biomarkers were retained at p

Details

ISSN :
00207136
Volume :
140
Database :
OpenAIRE
Journal :
International Journal of Cancer
Accession number :
edsair.doi...........143cda7317c37c8b693aa71744697481
Full Text :
https://doi.org/10.1002/ijc.30560