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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.
Afiliação
  • Usher-Smith JA; The Primary Care Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge CB2 0SR, UK.
  • Harshfield A; The Primary Care Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge CB2 0SR, UK.
  • Saunders CL; The Primary Care Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge CB2 0SR, UK.
  • Sharp SJ; MRC Epidemiology Unit, University of Cambridge, Institute of Metabolic Science, Cambridge CB2 0QQ, UK.
  • Emery J; Department of General Practice, Centre for Cancer Research, Faculty of Medicine, Dentistry and Health Sciences, The University of Melbourne, Victorian Comprehensive Cancer Centre, Melbourne, VIC 3010, Australia.
  • Walter FM; The Primary Care Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge CB2 0SR, UK.
  • Muir K; Institute of Population Health, University of Manchester, Manchester M13 9PL, UK.
  • Griffin SJ; The Primary Care Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge CB2 0SR, UK.
Br J Cancer ; 118(5): 750-759, 2018 03 06.
Article em En | MEDLINE | ID: mdl-29381683
ABSTRACT

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.
Assuntos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Neoplasias Colorretais / Medição de Risco Tipo de estudo: Diagnostic_studies / Etiology_studies / Incidence_studies / Prognostic_studies / Risk_factors_studies / Screening_studies Limite: Aged / Female / Humans / Male / Middle aged País como assunto: Europa Idioma: En Ano de publicação: 2018 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Neoplasias Colorretais / Medição de Risco Tipo de estudo: Diagnostic_studies / Etiology_studies / Incidence_studies / Prognostic_studies / Risk_factors_studies / Screening_studies Limite: Aged / Female / Humans / Male / Middle aged País como assunto: Europa Idioma: En Ano de publicação: 2018 Tipo de documento: Article