Construction of a diagnostic nomogram model for predicting the risk of lymph node metastasis in clinical T1 or T2 colon cancer based on the SEER database

Background: There are few methods related to predicting lymph node metastasis (LNM) in patients with clinically staged T1 or T2 colon cancer. In this study, we aimed to discover independent risk factors for patients with pathologic T-stage 1 (pT1) or pT2 colon cancer with LNM and to develop a nomogram for predicting the probability of LNM for patients with clinically staged T1 or T2 colon cancer. Methods: All data were drawn from the Surveillance, Epidemiology, and End Results (SEER) database. Independent risk factors for LNM were identified using univariate and multivariate logistic regression analyses, and these factors were used to construct a nomogram. The discriminatory power, accuracy, and clinical utility of the model were evaluated using receiver operating characteristic (ROC), calibration, and decision curve analysis (DCA), respectively. Results: According to the inclusion and exclusion criteria, 32,803 patients with stage pT1 or pT2 colon cancer who had undergone surgery were selected from the SEER database. The data showed that the incidence of LNM in patients with pT1 and pT2 colon cancer was 17.11%. The age, histological grade, histological type, T classification, M classification, and tumour location were independent risk factors identified through univariate and multivariate analyses, and these factors were used to construct a nomogram. The ROC curve analysis showed that the area under the curve (AUC) of the ROC of the predictive nomogram for LNM risk was 0.6714 [95% confidence interval (CI): 0.6621-0.6806] in the training set and 0.6567 (95% CI: 0.6422-0.6712) in the validation set, indicative of good discriminatory power of the model. Calibration curve analysis demonstrated good agreement between the nomogram prediction and actual observation. DCA showed excellent clinical utility of the prediction model. Conclusions: The incidence of LNM was high in patients with pT1 and pT2 colon cancer. The nomogram established in this study can accurately predict the risk of LNM in patients with clinically staged T1 or T2 colon cancer before further clinical intervention, which allows clinicians to develop optimal treatment.