Competing-Risk Nomogram for Predicting Cancer- Specific Survival in Multiple Primary Colorectal Cancer Patients after Surgery

Cancer-specific survival (CSS) in multiple primary colorectal cancer (MPCC) patients is competitively affected by death from other causes. This study aimed to investigate CSS and associated risk factors by competing risk analysis in MPCC patients. The data of this study is from the SEER database. Using univariable and multivariable analysis of the competitive risk model to weaken the impact of competitive events, it explores the risk factors of CSS and develops a nomogram model. Then, the performance of the model is verified by the ROC curve, calibration curve, and DCA. The study encompasses a total of 8931 patients, with 6255 in the training cohort and 2676 in the validation cohort. Univariable and multivariable analyses showed that sex, Tumor Node Metastasis (TNM) stage, and tumor grade are independent risk factors for cancer-specific survival in MPCC patients. Based on the risk factors, we developed a diagram model to predict CSS. ROC curve, calibration curve, and DCA also show good results. In conclusion, a nomogram is developed that serves as a valuable tool for predicting CSS in MPCC patients, providing clinicians with crucial insights for personalized treatment planning.