Cancer Epidemiol Biomarkers Prev. 2019 Jul 10. pii: cebp.0059.2019. doi: 10.1158/1055-9965.EPI-19-0059. [Epub ahead of print]
Risk prediction models for colorectal cancer incorporating common genetic variants: a systematic review.
McGeoch L1, Saunders CL2, Griffin SJ3, Emery JD4, Walter FM5, Thompson DJ6, Antoniou AC3, Usher-Smith JA7.
Abstract
Colorectal cancer (CRC) screening reduces CRC incidence and mortality. Risk models based on phenotypic variables have relatively good discrimination in external validation and may improve efficiency of screening. Models incorporating genetic variables may perform better. In this review we updated our previous review by searching Medline and EMBASE from the end date of that review (January 2014) to February 2019 to identify models incorporating at least one single nucleotide polymorphism (SNP) and applicable to asymptomatic individuals in the general population. We identified 23 new models, giving a total of 29. Of those in which the SNP selection was based on published GWASs, in external or split-sample validation the AUROC was 0.56-0.57 for models including SNPs alone, 0.61-0.63 for SNPs in combination with other risk factors and 0.56 to 0.70 when age was included. Calibration was only reported for four. The addition of SNPs to other risk factors increases discrimination by 0.01-0.05. Public health modelling studies suggest that, if determined by risk models, the range of starting ages for screening would be several years greater than using family history alone. Further validation and calibration studies are needed alongside modelling studies to assess the population-level impact of introducing genetic risk-based screening programme.
Copyright ©2019, American Association for Cancer Research.
- PMID:
- 31292139
- DOI:
- 10.1158/1055-9965.EPI-19-0059
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