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

Todd Smith, David C Muller, Karel G M Moons, Amanda J Cross, Mattias Johansson, Pietro Ferrari, Guy Fagherazzi, Petra H M Peeters, Gianluca Severi, Anika Hüsing, Rudolf Kaaks, Anne Tjonneland, Anja Olsen, Kim Overvad, Catalina Bonet, Miguel Rodriguez-Barranco, Jose Maria Huerta, Aurelio Barricarte Gurrea, Kathryn E Bradbury, Antonia TrichopoulouChristina Bamia, Philippos Orfanos, Domenico Palli, Valeria Pala, Paolo Vineis, Bas Bueno-de-Mesquita, Bodil Ohlsson, Sophia Harlid, Bethany Van Guelpen, Guri Skeie, Elisabete Weiderpass, Mazda Jenab, Neil Murphy, Elio Riboli, Marc J Gunter, Krasimira Jekova Aleksandrova, Ioanna Tzoulaki

Research output: Contribution to journalReview articlepeer-review

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 vs 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 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% CI 0.68 to 0.72) in the UK Biobank and 0.71 (95% CI 0.67 to 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.

Original languageEnglish
Pages (from-to)672-683
Number of pages12
JournalGut
Volume68
Issue number4
Early online date3 Apr 2018
DOIs
Publication statusPublished - Apr 2019

Keywords

  • epidemiology
  • colorectal cancer
  • cancer prevention
  • medical statistics
  • colorectal cancer screening
  • Colorectal Neoplasms/epidemiology
  • Predictive Value of Tests
  • Prognosis
  • Risk Assessment
  • Early Detection of Cancer
  • Humans
  • Risk Factors
  • Asymptomatic Diseases
  • United Kingdom/epidemiology
  • Europe/epidemiology
  • Biological Specimen Banks

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