TY  - JOUR
AU  - Smith, Todd
AU  - Muller, David C
AU  - Moons, Karel G M
AU  - Cross, Amanda J
AU  - Johansson, Mattias
AU  - Ferrari, Pietro
AU  - Fagherazzi, Guy
AU  - Peeters, Petra H M
AU  - Severi, Gianluca
AU  - Hüsing, Anika
AU  - Kaaks, Rudolf
AU  - Tjonneland, Anne
AU  - Olsen, Anja
AU  - Overvad, Kim
AU  - Bonet, Catalina
AU  - Rodriguez-Barranco, Miguel
AU  - Huerta, Jose Maria
AU  - Barricarte Gurrea, Aurelio
AU  - Bradbury, Kathryn E
AU  - Trichopoulou, Antonia
AU  - Bamia, Christina
AU  - Orfanos, Philippos
AU  - Palli, Domenico
AU  - Pala, Valeria
AU  - Vineis, Paolo
AU  - Bueno-de-Mesquita, Bas
AU  - Ohlsson, Bodil
AU  - Harlid, Sophia
AU  - Van Guelpen, Bethany
AU  - Skeie, Guri
AU  - Weiderpass, Elisabete
AU  - Jenab, Mazda
AU  - Murphy, Neil
AU  - Riboli, Elio
AU  - Gunter, Marc J
AU  - Aleksandrova, Krasimira Jekova
AU  - Tzoulaki, Ioanna
TI  - Comparison of prognostic models to predict the occurrence of colorectal cancer in asymptomatic individuals: a systematic literature review and external validation in the EPIC and UK Biobank prospective cohort studies.
JO  - Gut
VL  - 68
IS  - 4
SN  - 1468-3288
CY  - London
PB  - BMJ Publishing Group
M1  - DKFZ-2018-01979
SP  - 672-683
PY  - 2019
AB  - To systematically identify and validate published colorectal cancer risk prediction models that do not require invasive testing in two large population-based prospective cohorts.Models were identified through an update of a published systematic review and validated in the European Prospective Investigation into Cancer and Nutrition (EPIC) and the UK Biobank. The performance of the models to predict the occurrence of colorectal cancer within 5 or 10 years after study enrolment was assessed by discrimination (C-statistic) and calibration (plots of observed vs predicted probability).The systematic review and its update identified 16 models from 8 publications (8 colorectal, 5 colon and 3 rectal). The number of participants included in each model validation ranged from 41 587 to 396 515, and the number of cases ranged from 115 to 1781. Eligible and ineligible participants across the models were largely comparable. Calibration of the models, where assessable, was very good and further improved by recalibration. The C-statistics of the models were largely similar between validation cohorts with the highest values achieved being 0.70 (95
LB  - PUB:(DE-HGF)16
C6  - pmid:29615487
DO  - DOI:10.1136/gutjnl-2017-315730
UR  - https://inrepo02.dkfz.de/record/141708
ER  -