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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

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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
Authors: Smith, T
Muller, D
Moons, K
Cross, A
Johansson, M
Ferrari, P
Fagherazzi, G
Peeters, P
Severi, G
Husing, A
Kaaks, R
Tjonneland, A
Olsen, A
Overvad, K
Bonet, C
Rodriguez-Barranco, M
Huerta, JM
Barricarte Gurrea, A
Bradbury, K
Trichopoulou, A
Bamia, C
Orfanos, P
Palli, D
Pala, V
Vineis, P
Bueno-de-Mesquita, B
Ohlsson, B
Harlid, S
Van Guelpen, B
Skeie, G
Weiderpass, E
Jenab, M
Murphy, N
Riboli, E
Gunter, M
Aleksandrova, K
Tzoulaki, I
Item Type: Journal Article
Abstract: Objective To systematically identify and validate published colorectal cancer risk prediction models that do not require invasive testing in two large population-based prospective cohorts. Design 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 versus predicted probability). Results 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 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. Conclusion Several 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.
Issue Date: 7-Mar-2019
Date of Acceptance: 3-Mar-2018
URI: http://hdl.handle.net/10044/1/57830
DOI: https://doi.org/10.1136/gutjnl-2017-315730
ISSN: 0017-5749
Publisher: BMJ Publishing Group
Start Page: 672
End Page: 683
Journal / Book Title: Gut
Volume: 68
Issue: 4
Copyright Statement: © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2019. All rights reserved. No commercial use is permitted unless otherwise expressly granted. This is an open access article distributed in accordance with the terms of the Creative Commons Attribution (CC BY 4.0) license, which permits others to distribute, remix, adapt and build upon this work, for commercial use, provided the original work is properly cited. See: http://creativecommons.org/licenses/by/4.0/
Sponsor/Funder: MRC-PHE Centre for Environment and Health and Department of Epidemiology and Biostatistics
Cancer Research UK
Cancer Research UK
Funder's Grant Number: MR/M501712/1
Keywords: Science & Technology
Life Sciences & Biomedicine
Gastroenterology & Hepatology
cancer prevention
colorectal cancer
colorectal cancer screening
medical statistics
Asymptomatic Diseases
Biological Specimen Banks
Colorectal Neoplasms
Early Detection of Cancer
Predictive Value of Tests
Risk Assessment
Risk Factors
United Kingdom
Colorectal Neoplasms
Risk Assessment
Risk Factors
Predictive Value of Tests
Biological Specimen Banks
Early Detection of Cancer
Asymptomatic Diseases
United Kingdom
1103 Clinical Sciences
1114 Paediatrics and Reproductive Medicine
Gastroenterology & Hepatology
Publication Status: Published
Open Access location: http://dx.doi.org/10.1136/
Online Publication Date: 2018-04-03
Appears in Collections:School of Public Health

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