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Colon cancer is the third most incident and life-threatening cancer in Taiwan. A comprehensive survival prediction system would greatly benefit clinical practice in this area. This study was designed to develop an accurate prognostic model for colon cancer patients by using clinicopathological variables obtained from the Taiwan Cancer Registry database. We analyzed 20,218 colon cancer patients from the Taiwan Cancer Registry database, who were diagnosed between 2007 and 2015, were followed up until December 31, 2017, and had undergone curative surgery. We proposed two prognostic models, with different combinations of predictors. The first model used only traditional clinical features. The second model included several colon cancer site-specific factors (circumferential resection margin, perineural invasion, obstruction, and perforation), in addition to the traditional features. Both prediction models were developed by using a Cox proportional hazards model. Furthermore, we investigated whether race is a significant predictor of survival in colon cancer patients by using Model 1 on the Surveillance, Epidemiology, and End Results (SEER) cancer registry dataset. The proposed models displayed a robust prediction performance (all Harrell's c-index >0.8). For both the calibration and validation steps, the differences between the predicted and observed mortality were mostly less than 5%. The prediction model (Model 1) is an effective predictor of survival regardless of the ethnic background of patients and can potentially help to provide better prediction of colon cancer-specific survival outcomes, thus allowing physicians to improve treatment plans.

Colon cancer is the third most incident and life-threatening cancer in Taiwan. A comprehensive survival prediction system would greatly benefit clinical practice in this area. This study was designed to develop an accurate prognostic model for colon cancer patients by using clinicopathological variables obtained from the Taiwan Cancer Registry database.We analyzed 20,218 colon cancer patients from the Taiwan Cancer Registry database, who were diagnosed between 2007 and 2015, were followed up until December 31, 2017, and had undergone curative surgery. We proposed two prognostic models, with different combinations of predictors. The first model used only traditional clinical features. The second model included several colon cancer site-specific factors (circumferential resection margin, perineural invasion, obstruction, and perforation), in addition to the traditional features. Both prediction models were developed by using a Cox proportional hazards model. Furthermore, we investigated whether race is a significant predictor of survival in colon cancer patients by using Model 1 on the Surveillance, Epidemiology, and End Results (SEER) cancer registry dataset.The proposed models displayed a robust prediction performance (all Harrell's c-index0.8). For both the calibration and validation steps, the differences between the predicted and observed mortality were mostly less than 5%.The prediction model (Model 1) is an effective predictor of survival regardless of the ethnic background of patients and can potentially help to provide better prediction of colon cancer-specific survival outcomes, thus allowing physicians to improve treatment plans.