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dc.contributor.authorSmith, T
dc.contributor.authorMuller, DC
dc.contributor.authorMoons, KGM
dc.contributor.authorCross, AJ
dc.contributor.authorJohansson, M
dc.contributor.authorFerrari, P
dc.contributor.authorFagherazzi, G
dc.contributor.authorPeeters, PHM
dc.contributor.authorSeveri, G
dc.contributor.authorHuesing, A
dc.contributor.authorKaaks, R
dc.contributor.authorTjonneland, A
dc.contributor.authorOlsen, A
dc.contributor.authorOvervad, K
dc.contributor.authorBonet, C
dc.contributor.authorRodriguez-Barranco, M
dc.contributor.authorHuerta, JM
dc.contributor.authorGurrea, AB
dc.contributor.authorBradbury, KE
dc.contributor.authorTrichopoulou, A
dc.contributor.authorBamia, C
dc.contributor.authorOrfanos, P
dc.contributor.authorPalli, D
dc.contributor.authorPala, V
dc.contributor.authorVineis, P
dc.contributor.authorBueno-de-Mesquita, B
dc.contributor.authorOhlsson, B
dc.contributor.authorHarlid, S
dc.contributor.authorVan Guelpen, B
dc.contributor.authorSkeie, G
dc.contributor.authorWeiderpass, E
dc.contributor.authorJenab, M
dc.contributor.authorMurphy, N
dc.contributor.authorRiboli, E
dc.contributor.authorGunter, MJ
dc.contributor.authorAleksandrova, KJ
dc.contributor.authorTzoulaki, I
dc.date.accessioned2020-12-17T03:16:24Z
dc.date.available2020-12-17T03:16:24Z
dc.date.issued2019-04-01
dc.identifierpii: gutjnl-2017-315730
dc.identifier.citationSmith, T., Muller, D. C., Moons, K. G. M., Cross, A. J., Johansson, M., Ferrari, P., Fagherazzi, G., Peeters, P. H. M., Severi, G., Huesing, A., Kaaks, R., Tjonneland, A., Olsen, A., Overvad, K., Bonet, C., Rodriguez-Barranco, M., Huerta, J. M., Gurrea, A. B., Bradbury, K. E. ,... Tzoulaki, I. (2019). 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. GUT, 68 (4), pp.672-683. https://doi.org/10.1136/gutjnl-2017-315730.
dc.identifier.issn0017-5749
dc.identifier.urihttp://hdl.handle.net/11343/254815
dc.description.abstractOBJECTIVE: 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.
dc.languageEnglish
dc.publisherBMJ PUBLISHING GROUP
dc.titleComparison 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
dc.typeJournal Article
dc.identifier.doi10.1136/gutjnl-2017-315730
melbourne.affiliation.departmentMelbourne School of Population and Global Health
melbourne.source.titleGut
melbourne.source.volume68
melbourne.source.issue4
melbourne.source.pages672-683
dc.rights.licenseCC BY
melbourne.elementsid1323176
melbourne.contributor.authorSeveri, Gianluca
dc.identifier.eissn1468-3288
melbourne.accessrightsOpen Access


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