Risk Prediction Models for Colorectal Cancer Incorporating Common Genetic Variants: A Systematic Review

Abstract

Colorectal cancer screening reduces colorectal cancer 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 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 on the basis of published genome-wide association studies, in external or split-sample validation the AUROC was 0.56 to 0.57 for models that included SNPs alone, 0.61 to 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 to 0.06. Public health modeling 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 modeling studies to assess the population-level impact of introducing genetic risk-based screening programs.

Prediction of colorectal cancer risk based on profiling with common genetic variants

“…To our knowledge, the best predictive performance achieved by PRS along with age and family history was 0.69 and 0.60 for Korean men and women, 20 but the SNPs were chosen from the same data set used to generate the model, and therefore the reported c‐statistics are likely inflated. Other genetic models showed consistently low to modest discriminatory abilities 21 . Hsu et al developed sex‐specific models by using family history and 27 common genetic variants with adjustment of endoscopy history and obtained a discrimination ability of 0.59 for men and 0.56 for women 22 .…”

Development and validation of a lifestyle-based model for colorectal cancer risk prediction: the LiFeCRC score

“…A number of colorectal cancer risk prediction models have been published over the last decade [ 18 – 21 ]. Most published models have been predominantly developed using data from American and Asian populations [ 18 , 19 ]. We have previously validated several models in European populations based on data from UK Biobank and the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort studies [ 20 ]; however, several gaps remain to be addressed.…”

“…Third, most models focused only on model development and did not address the full continuum of model development, validation and communication recommended in recent methodological guidelines for research on risk prediction (i.e. TRIPOD, Transparent Reporting of a multivariable Prediction model for Individual Prognosis or Diagnosis) [ 19 , 23 ]. Fourth, previous models were mostly developed using logistic regression and did not account for time-to-event.…”

The Impact of a Comprehensive Risk Prediction Model for Colorectal Cancer on a Population Screening Program

“…The CRISP and genomic models, like many risk prediction models, have been developed primarily from data collected from those of Caucasian ethnicity ( 6 , 46 ). There are important efforts to redress this imbalance in new studies, particularly in the development of genomic tests ( 47 , 48 ).…”