Evaluating the Use of Environmental and Polygenic Risk Scores to Inform Colorectal Cancer Risk-Based Surveillance Intervals

评估利用环境和多基因风险评分指导结直肠癌风险监测间隔的有效性

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Abstract

INTRODUCTION: United States Multi-Society Task Force colonoscopy surveillance intervals are based solely on adenoma characteristics, without accounting for other risk factors. We investigated whether a risk model including demographic, environmental, and genetic risk factors could individualize surveillance intervals under an "equal management of equal risks" framework. METHODS: Using 14,069 individuals from the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial who had a diagnostic colonoscopy following an abnormal flexible sigmoidoscopy, we modeled the risk of colorectal cancer, considering the diagnostic colonoscopy finding, baseline risk factors (e.g., age and sex), 19 lifestyle and environmental risk factors, and a polygenic risk score for colorectal cancer. Ten-year absolute cancer risks for each diagnostic colonoscopy finding (advanced adenomas [N = 2,446], ≥3 non-advanced adenomas [N = 483], 1-2 non-advanced adenomas [N = 4,400], and no adenoma [N = 7,183]) were used as implicit risk thresholds for recommended surveillance intervals. RESULTS: The area under the curve for the model including colonoscopy findings, baseline characteristics, and polygenic risk score was 0.658. Applying the equal management of equal risks framework, 28.2% of individuals with no adenoma and 42.7% of those with 1-2 non-advanced adenomas would be considered high risk and assigned a significantly shorter surveillance interval than currently recommended. Among individuals who developed cancer within 10 years, 52.4% with no adenoma and 48.3% with 1-2 non-advanced adenomas would have been considered high risk and assigned a shorter surveillance interval. DISCUSSION: Using a personalized risk-based model has the potential to identify individuals with no adenoma or 1-2 non-advanced adenomas, who are higher risk and may benefit from shorter surveillance intervals.

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