A retrospective study based on SEER database: not all high-risk factors are equal for stage II colon cancer

BACKGROUND: For stage II colon cancer, understanding of high-risk factors (HRFs) that affect the overall survival (OS) and the benefit of chemotherapy is limited. Meanwhile, no stable predictor can effectively predict OS of stage II colon cancer to date. Our study is aimed to identify HRFs associated with OS of stage II colon cancer, to quantify the risk conferred by each HRF, and to evaluate OS benefit gained by chemotherapy. Meanwhile, we attempt to establish a nomogram model for stage II colon cancer. METHODS: The clinical variables of patients with stage II colon cancer between 2000 and 2018 were retrieved from the Surveillance, Epidemiology, and End Results (SEER) database. Univariate and multivariate analysis were performed to filtered out all the HRFs. We calculated the hazard ratios (HR) and evaluated the survival benefit of adjuvant chemotherapy for each HRF and combinations of HRFs. Then, a nomogram model based on all HRFs was established and verified. RESULTS: A total of 39,103 patients with stage II colon cancer were included. T4b tumors were the highest risk for reduced OS [HR =2.821; 95% confidence interval (CI): 1.949–4.082], mucin-producing tumors (HR =2.412; 95% CI: 1.326–4.388) the second, and lymph node (LN) examined less than 12 (HR =2.200; 95% CI: 1.786–2.710) the third. T4 tumors (HR =0.790; 95% CI: 0.542–1.151), poorly/undifferentiated tumors (HR =0.468; 95% CI: 0.237–0.924), and some combinations of HRFs containing either could benefit from adjuvant chemotherapy. Meanwhile, we established an effective nomogram model based on the identified HRFs. CONCLUSIONS: The study has identified several novel HRFs for stage II colon cancer. Adjuvant chemotherapy has considerable OS benefit for stage II colon cancers with some specific HRFs, and treatment plans need to be individualized. Type and number of HRFs should be taken into consideration when recommending adjuvant chemotherapy. Our new nomogram model has better predictive ability and stability than the tumor-node-metastasis (TNM) stage system of American Joint Committee on Cancer (AJCC) staging system.