Construction and evaluation of the prediction model for advanced disease in well-differentiated colorectal neuroendocrine neoplasms less than 2 cm in diameter

Advanced lesions are often ignored in well-differentiated colorectal neuroendocrine neoplasms (NENs) smaller than 2 cm, and we aimed to develop an effective nomogram for these lesions. We extracted data from the Surveillance, Epidemiology, and End Results (SEER) database and used a logistic regression model to identify independent risk factors for advanced disease. All these identified factors were included to construct the prediction model, and the receiver operating characteristic (ROC) curve, calibration plot and DCA curve were utilized to assess the predictive value. The data obtained from the National Cancer Center were utilized for external validation. In total, 3223 patients were enrolled in the training set, including 2947 (91.4 %) with early disease and 276 (8.6 %) with advanced disease. The logistic analysis showed that age (odds ratio (OR) = 1.486, 95 % confidence interval (CI): 1.102–2.003, P = 0.009), tumor size (OR = 11.071, 95 % CI: 8.229–14.893, P