Abstract: Objective To establish a nomogram model for efficiently predicting overall survival (OS) and cancer-specific survival (CSS) in patients with CRCHBM.Method 2239 patients from 2010 to 2019 were retrospectively analyzed from the Surveillance,Epidemiology,and End Results Program (SEER) databases and Wuhan Union Hospital Cancer Center.SEER is randomly assigned to the training and internal validation cohorts,and the Wuhan database serves as the external validation.Cox regression analyses were used to determine the independent clinicopathological prognosis factors affecting OS and CSS,and a nomogram was constructed to predict OS and CSS.The clinical utility of columnar plots was assessed using calibration curves,area under the curve (AUC),and decision curve analysis (DCA).Result OS column line graphs were constructed based on nine independent predictors:age,tumor location,degree of differentiation,tumor size,TNM stage,chemotherapy,primary focus surgery,number of lymph nodes sampled,and serum carcinoembryonic antigen (CEA) level.The C-index of the nomogram to predict the 1 -,3 -,and 5-year OS were 0.764,0.790,and 0.805 in the training group,0.754,0.760,and 0.801 in the internal validation group,and 0.822,0.874,and 0.906 in the external validation group.CSS column line graphs were constructed based on 3 independent predictors of TNM staging,radiotherapy and chemotherapy.The 1 -,3 -,and 5-year CSS AUROC values of the training group were 0.791,0.757,and 0.782,respectively.0.682,0.709,0.625 in the internal validation group and 0.759,0.702,0.755 in the external validation group,respectively.The results of receiver operating characteristic curve(ROC),ROC and DCA showed that the use of our model was more effective in predicting OS and CSS than other single clinicopathological features.Conclusion In summary,the nomogram based on significant clinicopathological features can be conveniently used to predict OS and CSS individually in patients with CRCHBM.

Key words: colorectal cancer；hepato-bone metastasis；nomogram；overall survival；cancer-specific survival；prognosis