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External validation of risk prediction models for incident colorectal cancer using UK Biobank

BACKGROUND: This study aimed to compare and externally validate risk scores developed to predict incident colorectal cancer (CRC) that include variables routinely available or easily obtainable via self-completed questionnaire. METHODS: External validation of fourteen risk models from a previous sys...

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Autores principales: Usher-Smith, J A, Harshfield, A, Saunders, C L, Sharp, S J, Emery, J, Walter, F M, Muir, K, Griffin, S J
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5846069/
https://www.ncbi.nlm.nih.gov/pubmed/29381683
http://dx.doi.org/10.1038/bjc.2017.463
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author Usher-Smith, J A
Harshfield, A
Saunders, C L
Sharp, S J
Emery, J
Walter, F M
Muir, K
Griffin, S J
author_facet Usher-Smith, J A
Harshfield, A
Saunders, C L
Sharp, S J
Emery, J
Walter, F M
Muir, K
Griffin, S J
author_sort Usher-Smith, J A
collection PubMed
description BACKGROUND: This study aimed to compare and externally validate risk scores developed to predict incident colorectal cancer (CRC) that include variables routinely available or easily obtainable via self-completed questionnaire. METHODS: External validation of fourteen risk models from a previous systematic review in 373 112 men and women within the UK Biobank cohort with 5-year follow-up, no prior history of CRC and data for incidence of CRC through linkage to national cancer registries. RESULTS: There were 1719 (0.46%) cases of incident CRC. The performance of the risk models varied substantially. In men, the QCancer10 model and models by Tao, Driver and Ma all had an area under the receiver operating characteristic curve (AUC) between 0.67 and 0.70. Discrimination was lower in women: the QCancer10, Wells, Tao, Guesmi and Ma models were the best performing with AUCs between 0.63 and 0.66. Assessment of calibration was possible for six models in men and women. All would require country-specific recalibration if estimates of absolute risks were to be given to individuals. CONCLUSIONS: Several risk models based on easily obtainable data have relatively good discrimination in a UK population. Modelling studies are now required to estimate the potential health benefits and cost-effectiveness of implementing stratified risk-based CRC screening.
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spelling pubmed-58460692018-03-14 External validation of risk prediction models for incident colorectal cancer using UK Biobank Usher-Smith, J A Harshfield, A Saunders, C L Sharp, S J Emery, J Walter, F M Muir, K Griffin, S J Br J Cancer Epidemiology BACKGROUND: This study aimed to compare and externally validate risk scores developed to predict incident colorectal cancer (CRC) that include variables routinely available or easily obtainable via self-completed questionnaire. METHODS: External validation of fourteen risk models from a previous systematic review in 373 112 men and women within the UK Biobank cohort with 5-year follow-up, no prior history of CRC and data for incidence of CRC through linkage to national cancer registries. RESULTS: There were 1719 (0.46%) cases of incident CRC. The performance of the risk models varied substantially. In men, the QCancer10 model and models by Tao, Driver and Ma all had an area under the receiver operating characteristic curve (AUC) between 0.67 and 0.70. Discrimination was lower in women: the QCancer10, Wells, Tao, Guesmi and Ma models were the best performing with AUCs between 0.63 and 0.66. Assessment of calibration was possible for six models in men and women. All would require country-specific recalibration if estimates of absolute risks were to be given to individuals. CONCLUSIONS: Several risk models based on easily obtainable data have relatively good discrimination in a UK population. Modelling studies are now required to estimate the potential health benefits and cost-effectiveness of implementing stratified risk-based CRC screening. Nature Publishing Group 2018-03-06 2018-01-30 /pmc/articles/PMC5846069/ /pubmed/29381683 http://dx.doi.org/10.1038/bjc.2017.463 Text en Copyright © 2018 The Author(s) http://creativecommons.org/licenses/by/4.0/ This work is licensed under the Creative Commons Attribution 4.0 International License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/
spellingShingle Epidemiology
Usher-Smith, J A
Harshfield, A
Saunders, C L
Sharp, S J
Emery, J
Walter, F M
Muir, K
Griffin, S J
External validation of risk prediction models for incident colorectal cancer using UK Biobank
title External validation of risk prediction models for incident colorectal cancer using UK Biobank
title_full External validation of risk prediction models for incident colorectal cancer using UK Biobank
title_fullStr External validation of risk prediction models for incident colorectal cancer using UK Biobank
title_full_unstemmed External validation of risk prediction models for incident colorectal cancer using UK Biobank
title_short External validation of risk prediction models for incident colorectal cancer using UK Biobank
title_sort external validation of risk prediction models for incident colorectal cancer using uk biobank
topic Epidemiology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5846069/
https://www.ncbi.nlm.nih.gov/pubmed/29381683
http://dx.doi.org/10.1038/bjc.2017.463
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