Predicting Risk of Colorectal Cancer After Adenoma Removal in a Large, Community-based Setting

Colonoscopy surveillance guidelines categorize individuals as high or low risk for future colorectal cancer (CRC) based primarily on their prior polyp characteristics, but the approach is imprecise, and consideration of other risk factors may improve post-polypectomy risk stratification. Among patients who underwent a baseline colonoscopy with removal of a conventional adenoma in 2004-2016, we compared the performance for post-polypectomy CRC risk prediction (through 2020) of a comprehensive model featuring patient age, diabetes diagnosis, and baseline colonoscopy indication and prior polyp findings (i.e., adenoma with advanced histology, polyp size ≥10 mm, and sessile serrated adenoma or traditional serrated adenoma) to a polyp model featuring only polyp findings. Models were developed using Cox regression. Performance was assessed using area under the receiver-operating characteristic curve (AUC) and calibration by the Hosmer-Lemeshow goodness-of-fit test. Among 95,001 patients randomly divided 70:30 into model development (n=66,500) and internal validation cohorts (n=28,501); 495 CRCs were subsequently diagnosed, 354 in the development cohort and 141 in the validation cohort. Models demonstrated adequate calibration and the comprehensive model demonstrated superior predictive performance to the polyp model in the development cohort (AUC: 0.71, 95% confidence interval [CI]: 0.68-0.74 vs. AUC: 0.61, 95% CI: 0.58-0.64, respectively) and validation cohort (AUC: 0.70, 95% CI: 0.65-0.75 vs. AUC: 0.62, 95% CI: 0.57-0.67, respectively). A comprehensive CRC risk prediction model featuring patient age, diabetes diagnosis, and baseline colonoscopy indication and polyp findings was more accurate at predicting post-polypectomy CRC diagnosis than a model based on polyp findings alone.

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