Shuanhu Wang1, Yakui Liu1, Yi Shi1, Jiajia Guan1, Mulin Liu1, Wenbin Wang2. 1. Department of Gastrointestinal Surgery, The First Affiliated Hospital of Bengbu Medical College, Bengbu, Anhui, China. 2. Department of General Surgery, The Fourth Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China.
Abstract
OBJECTIVE: To develop and externally validate a prognostic nomogram to predict overall survival (OS) in patients with resectable colon cancer. METHODS: Data for 50,996 patients diagnosed with non-metastatic colon cancer were retrieved from the Surveillance, Epidemiology, and End Results (SEER) database. Patients were assigned randomly to the training set (n = 34,168) or validation set (n = 16,828). Independent prognostic factors were identified by multivariate Cox proportional hazards regression analysis and used to construct the nomogram. Harrell's C-index and calibration plots were calculated using the SEER validation set. Additional external validation was performed using a Chinese dataset (n = 342). RESULTS: Harrell's C-index of the nomogram for OS in the SEER validation set was 0.71, which was superior to that using the 7th edition of the American Joint Committee on Cancer TNM staging (0.59). Calibration plots showed consistency between actual observations and predicted 1-, 3-, and 5-year survival. Harrell's C-index (0.72) and calibration plot showed excellent predictive accuracy in the external validation set. CONCLUSIONS: We developed a nomogram to predict OS after curative resection for colon cancer. Validation using the SEER and external datasets revealed good discrimination and calibration. This nomogram may help predict individual survival in patients with colon cancer.
OBJECTIVE: To develop and externally validate a prognostic nomogram to predict overall survival (OS) in patients with resectable colon cancer. METHODS: Data for 50,996 patients diagnosed with non-metastatic colon cancer were retrieved from the Surveillance, Epidemiology, and End Results (SEER) database. Patients were assigned randomly to the training set (n = 34,168) or validation set (n = 16,828). Independent prognostic factors were identified by multivariate Cox proportional hazards regression analysis and used to construct the nomogram. Harrell's C-index and calibration plots were calculated using the SEER validation set. Additional external validation was performed using a Chinese dataset (n = 342). RESULTS: Harrell's C-index of the nomogram for OS in the SEER validation set was 0.71, which was superior to that using the 7th edition of the American Joint Committee on CancerTNM staging (0.59). Calibration plots showed consistency between actual observations and predicted 1-, 3-, and 5-year survival. Harrell's C-index (0.72) and calibration plot showed excellent predictive accuracy in the external validation set. CONCLUSIONS: We developed a nomogram to predict OS after curative resection for colon cancer. Validation using the SEER and external datasets revealed good discrimination and calibration. This nomogram may help predict individual survival in patients with colon cancer.