Real-world survival of colon cancer after radical surgery: A single-institutional retrospective analysis
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Updated: Aug 27, 2025

Competing-Risk Nomogram for Predicting Cancer-Specific Survival in Multiple Primary Colorectal Cancer Patients after Surgery
Published on: September 27, 2024
Xiangyi Pang1, Benjie Xu1, Jie Lian1
1Department of Outpatient Chemotherapy, Harbin Medical University Cancer Hospital, Harbin, China.
Abstract:
The survival rate for colon cancer after radical surgery has been the focus of extensive debate. To assess the postoperative survival and prognostic factors for overall survival (OS), we collected clinicopathological information for 2,655 patients. The survival time and potential risk factors for OS were analyzed by using Kaplan-Meier curves, Cox proportional hazards models, best subset regression (BSR), and least absolute shrinkage and selection operator (LASSO). The 5-year survival rates of stage I-IV colon cancer were 96.6%, 88.7%, 69.9%, and 34.3%, respectively. Adjuvant chemotherapy improved the survival rate (90.4% vs. 82.4%, with versus without adjuvant chemotherapy, respectively) in stage II patients with high-risk factors. Elevated preoperative carcinoembryonic antigen (CEA) and carbohydrate antigen 19-9 (CA19-9) were significantly associated with worse OS compared with patients without these elevations. Less than 12 versus more than 12 harvested lymph nodes (LNs) affected prognosis (84.6% vs. 89.7%, respectively). Regarding the lymph node ratio (LNR), the 5-year OS rate was 89.2%, 71.5%, 55.8%, and 34.5% in patients with LNR values of 0, 0.3, 0.3-0.7, and >0.7, respectively. We constructed a nomogram comprising the independent factors associated with survival to better predict prognosis. On the basis of these findings, we propose that stage II colon cancer patients without high-risk factors and with both elevated preoperative CEA and CA199 should receive adjuvant therapy. Furthermore, the LNR could complement TNM staging in patients with <12 harvested LNs. Our nomogram might be useful as a new prognosis prediction system for colon cancer patients.
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