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@article{Smith:2019:10.1136/gutjnl-2017-315730,
author = {Smith, T and Muller, D and Moons, K and Cross, A and Johansson, M and Ferrari, P and Fagherazzi, G and Peeters, P and Severi, G and Husing, A and Kaaks, R and Tjonneland, A and Olsen, A and Overvad, K and Bonet, C and Rodriguez-Barranco, M and Huerta, JM and Barricarte, Gurrea A and Bradbury, K and Trichopoulou, A and Bamia, C and Orfanos, P and Palli, D and Pala, V and Vineis, P and Bueno-de-Mesquita, B and Ohlsson, B and Harlid, S and Van, Guelpen B and Skeie, G and Weiderpass, E and Jenab, M and Murphy, N and Riboli, E and Gunter, M and Aleksandrova, K and Tzoulaki, I},
doi = {10.1136/gutjnl-2017-315730},
journal = {Gut},
pages = {672--683},
title = {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},
url = {http://dx.doi.org/10.1136/gutjnl-2017-315730},
volume = {68},
year = {2019}
}

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TY  - JOUR
AB  - ObjectiveTo systematically identify and validate published colorectal cancer risk prediction models that do not require invasive testing in two large population-based prospective cohorts.DesignModels 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 versus predicted probability).ResultsThe 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 from 115 to 1,781. 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%CI 0.68-0.72) in the UK Biobank and 0.71 (0.67-0.74) in EPIC. ConclusionSeveral of these non-invasive models exhibited good calibration and discrimination within both external validation populations and are therefore potentially suitable candidates for the facilitation of risk stratification in population-based colorectal screening programmes. Future work should both evaluate this potential, through modelling and impact studies, and ascertain if further enhancement in their performance can be obtained.
AU  - Smith,T
AU  - Muller,D
AU  - Moons,K
AU  - Cross,A
AU  - Johansson,M
AU  - Ferrari,P
AU  - Fagherazzi,G
AU  - Peeters,P
AU  - Severi,G
AU  - Husing,A
AU  - Kaaks,R
AU  - Tjonneland,A
AU  - Olsen,A
AU  - Overvad,K
AU  - Bonet,C
AU  - Rodriguez-Barranco,M
AU  - Huerta,JM
AU  - Barricarte,Gurrea A
AU  - Bradbury,K
AU  - Trichopoulou,A
AU  - Bamia,C
AU  - Orfanos,P
AU  - Palli,D
AU  - Pala,V
AU  - Vineis,P
AU  - Bueno-de-Mesquita,B
AU  - Ohlsson,B
AU  - Harlid,S
AU  - Van,Guelpen B
AU  - Skeie,G
AU  - Weiderpass,E
AU  - Jenab,M
AU  - Murphy,N
AU  - Riboli,E
AU  - Gunter,M
AU  - Aleksandrova,K
AU  - Tzoulaki,I
DO  - 10.1136/gutjnl-2017-315730
EP  - 683
PY  - 2019///
SN  - 0017-5749
SP  - 672
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
T2  - Gut
UR  - http://dx.doi.org/10.1136/gutjnl-2017-315730
UR  - http://hdl.handle.net/10044/1/57830
VL  - 68
ER  -

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