Abstract
BACKGROUND: To construct a prognostic model for predicting cancer-specific survival in lymph node-positive colorectal cancer patients treated with adjuvant chemotherapy after surgery. METHODS: Data were collected from the 2010-2015 SEER database and from CRC patients at the Second Affiliated Hospital of Bengbu Medical University (2017-2023). Lasso regression and random survival forest methods were used to screen ten clinicopathologic features. Cox regression analysis identified independent prognostic factors for CRC. Nomogram plot model was used to predict 1-, 3-, and 5-year survival rates, with its accuracy verified through ROC curves, calibration curves, and decision curve analysis (DCA). The X-tile software differentiated between high and low-risk groups and illustrated survival differences using Kaplan-Meier curves. RESULTS: Age, histologic grade, stage, CEA, nerve invasion, and LNR were independent prognostic risk factors for colorectal cancer (P < 0.001); and LNR were the five variables used to construct the Nomogram. The area under the curve (AUC) was 0.83, 0.85, and 0.84 at 1, 3, and 5 years for the training cohort; 0.83, 0.85, and 0.84 at 1, 3, and 5 years for the internal validation cohort; and 0.83, 0.85, and 0.84 at 1, 3, and 5 years for the external validation cohort, respectively. calibration curves, C-indexes, and DCA curves validated the accuracy of the model, respectively. The survival prognosis of the high-risk group was lower than that of the low-risk group in all three data sets. (HR = 6.37, CI:6.05-6.71, P < 0.05; HR = 7.05, CI:6.52-7.64, P < 0.05; HR = 2.69, CI:1.66-4.37, P < 0.05). CONCLUSIONS: LNR represents a new independent prognostic factor for lymph node-positive CRC. The optimal threshold determined by the Nomogram method effectively categorizes subgroups of lymph node-positive CRC cases after surgical chemotherapy, crucial for guiding clinical treatment strategy selection.