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The added value of genetic information in colorectal cancer risk prediction models: development and evaluation in the UK Biobank prospective cohort study

Colorectal cancer (CRC) risk prediction models could be used to risk-stratify the population to provide individually tailored screening provision. Using participants from the UK Biobank prospective cohort study, we evaluated whether the addition of a genetic risk score (GRS) could improve the perfor...

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Detalles Bibliográficos
Autores principales: Smith, Todd, Gunter, Marc J., Tzoulaki, Ioanna, Muller, David C.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6203780/
https://www.ncbi.nlm.nih.gov/pubmed/30323197
http://dx.doi.org/10.1038/s41416-018-0282-8
Descripción
Sumario:Colorectal cancer (CRC) risk prediction models could be used to risk-stratify the population to provide individually tailored screening provision. Using participants from the UK Biobank prospective cohort study, we evaluated whether the addition of a genetic risk score (GRS) could improve the performance of two previously validated models. Inclusion of the GRS did not appreciably improve discrimination of either model, and led to substantial miscalibration. Following recalibration the discrimination did not change, but good calibration for models incorporating the GRS was recovered. Comparing predictions between models with and without the GRS, 5% of participants or fewer changed their absolute risk by ±0.3% or more in either model. In summary, addition of a GRS did not meaningfully improve the performance of validated CRC-risk prediction models. At present, provision of genetic information is not useful for risk stratification for CRC.