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
File(s)ComparisonOfPrognosticModels.pdf (2.15 MB)
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Author(s)
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.
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.
Date Issued
2019-03-07
Date Acceptance
2018-03-03
Citation
Gut, 2019, 68 (4), pp.672-683
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/
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
MRC-PHE Centre for Environment and Health and Department of Epidemiology and Biostatistics
Cancer Research UK
Cancer Research UK
Grant Number
MR/M501712/1
C57955/A24390
24390
Subjects
Science & Technology
Life Sciences & Biomedicine
Gastroenterology & Hepatology
RISK SCORE
VALUES
TOOL
cancer prevention
colorectal cancer
colorectal cancer screening
epidemiology
medical statistics
Asymptomatic Diseases
Biological Specimen Banks
Colorectal Neoplasms
Early Detection of Cancer
Europe
Humans
Predictive Value of Tests
Prognosis
Risk Assessment
Risk Factors
United Kingdom
Humans
Colorectal Neoplasms
Prognosis
Risk Assessment
Risk Factors
Predictive Value of Tests
Biological Specimen Banks
Europe
Early Detection of Cancer
Asymptomatic Diseases
United Kingdom
1103 Clinical Sciences
1114 Paediatrics and Reproductive Medicine
Gastroenterology & Hepatology
Publication Status
Published
Date Publish Online
2018-04-03