Population-based analysis on predictors for lymph node metastasis in T1 colon cancer
Xin Xu1, Chihao Zhang1, Xiaochun Ni1
1Department of General Surgery, Shanghai Ninth People's Hospital, School of Medicine, Shanghai Jiao Tong University, 280 Mohe Road, Shanghai, 201999, China.
Background:
In this study, we aimed to identify independent predictive factors for lymph node metastasis (LNM) in T1 colon cancer.
Methods:
Data of 8056 eligible patients were retrospectively collected from the Surveillance, Epidemiology, and End Results (SEER) database during 2004-2012. We performed logistic regression analysis to identify predictive factors for LNM. Both unadjusted and adjusted Cox regression analyses were used to determine the association between LNM and patient survival. Finally, we used competing risks analysis and the cumulative incidence function (CIF) to further confirm the prognostic role of LNM in cancer-specific survival (CSS).
Results:
The overall risk of LNM in patients with T1 colon cancer was 12.0% (N = 967). Adjusted logistic regression models revealed that mucinous carcinoma [odds ratio (OR) = 2.26, P < 0.001], moderately differentiated (OR 1.74, P < 0.001), poorly differentiated (OR 5.16, P < 0.001), and undifferentiated carcinoma (OR 3.01, P = 0.003); older age (OR 0.66, P < 0.001 for age 65-79 years, OR 0.44, P < 0.001 for age over 80 years); and carcinoma located in the ascending colon (OR 0.77, P = 0.018) and sigmoid colon (OR 1.24, P = 0.014) were independent predictive factors for LNM. Adjusted Cox regression analysis showed that positive lymph node involvement was significantly associated with CSS [hazard ratio (HR) = 3.02, P < 0.001], which was further robustly confirmed using a competing risks model and the CIF.
Conclusions:
This population-based study showed that mucinous carcinoma, tumor grade, age, and primary tumor location were independent predictive factors for LNM in T1 colon cancer. The risk of LNM should be carefully evaluated in patients with T1 colon cancer, before clinical management.
