Published online Aug 27, 2025. doi: 10.4240/wjgs.v17.i8.109057
Revised: June 17, 2025
Accepted: July 8, 2025
Published online: August 27, 2025
Processing time: 103 Days and 4.2 Hours
Colorectal polyps (CPs) are important precursor lesions of colorectal cancer, and endoscopic surgery remains the primary treatment option. However, the short-term recurrence rate post-surgery is high, and the risk factors for recurrence remain unknown.
To comprehensively explore risk factors for short-term recurrence of CPs after endoscopic surgery and develop a nomogram prediction model.
Overall, 362 patients who underwent endoscopic polypectomy between January 2022 and January 2024 at Nanjing Jiangbei Hospital were included. We screened basic demographic data, clinical and polyp characteristics, surgery-related information, and independent risk factors for CPs recurrence using univariate and multivariate logistic regression analyses. The multivariate analysis results were used to construct a nomogram prediction model, internally validated using Bootstrapping, with performance evaluated using area under the curve (AUC), calibration curve, and decision curve analysis.
CP re-occurred in 166 (45.86%) of the 362 patients within 1 year post-surgery. Multivariate logistic regression analysis showed that age (OR = 1.04, P = 0.002), alcohol consumption (OR = 2.07, P = 0.012), Helicobacter pylori infection (OR = 2.34, P < 0.001), polyp number > 2 (OR = 1.98, P = 0.005), sessile polyps (OR = 2.10, P = 0.006), and adenomatous pathological type (OR = 3.02, P < 0.001) were indepen
We identified multiple independent risk factors for short-term recurrence after endoscopic surgery. The nomogram prediction model showed a certain degree of differentiation, calibration, and potential clinical applicability.
Core Tip: This retrospective study explored risk factors for short-term recurrence of colorectal polyps after endoscopic surgery and developed a nomogram prediction model. We identified key risk factors such as age, alcohol consumption, Helicobacter pylori infection, number of polyps, sessile polyps, and adenomatous pathology. A nomogram prediction model developed based on these factors showed good discriminatory and calibration abilities, offering clinicians a practical tool for individualized recurrence risk assessment to optimize treatment and follow-up strategies.
