Value of the log odds of positive lymph nodes for prognostic assessment of colon mucinous adenocarcinoma: Analysis and external validation

PURPOSE: To evaluate the impact of the log odds of positive lymph nodes (LODDS) on cancer‐specific survival (CSS) in colon mucinous adenocarcinoma (MAC) patients, compared with pN stage and the lymph nodes ratio (LNR). METHODS: A total of 10,182 colon MAC patients from the Surveillance, Epidemiology, and End Results database were divided into the training group. The external validation group included 153 patients from Fujian Medical University Union Hospital. The Cox regression method was used to identify prognostic risk factors. Nomograms were evaluated by Harrell's concordance index (C‐index) and calibration curves. Recursive partitioning analysis (RPA) was used to develop a novel staging system. RESULTS: Time‐dependent receiver operating characteristic curves (ROC) to predict CSS showed the areas under the ROC curve of LODDS were always higher than pN stage and LNR. LNR and LODDS classifications can well distinguish the prognosis of patients with the same pN stage. Cox analyses indicated that age, tumor size, pT stage, pN stage, LNR, and LODDS were independent predictors of CSS (p < 0.05). Based on three lymph nodes classifications, we constructed three prognostic nomograms models for CSS. The C‐index of the pN, LNR, and LODDS classification nomograms were 0.746 (95% confidence interval [95% CI]: 0.736–0.756), 0.750 (95% CI: 0.740–0.760), and 0.758 (95% CI: 0.748–0.768), respectively. In external validation, we observed the C‐index of LODDS classification nomograms was 0.787 (95% CI: 0.648–0.926). RPA stage, including four stages, was constructed successfully based on pT stage and LNR or LODDS, respectively. The 3‐, 5‐, and 8‐year areas under the ROC curve of LNR‐RPA stage and LODDS‐RPA stage were superior to tumor‐node‐metastasis stage. CONCLUSION: LODDS to be a better prognostic factor of CSS for colon MAC patients than pN stage and LNR. A nomogram and RPA stage base on LODDS can provide accurate information for personalized cancer treatment.