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Updated: Apr 24, 2026

Competing-Risk Nomogram for Predicting Cancer-Specific Survival in Multiple Primary Colorectal Cancer Patients after Surgery
Published on: September 27, 2024
Development and validation of a novel nomogram for predicting long-term survival in patients with decompensated
Zhimeng Jiang1,2, Wencai Lai1,2, Jianguo Chu2
1Graduate School of Hebei North University, Zhangjiakou, Hebei, China.
Background And Aims:
Transjugular intrahepatic portosystemic shunt (TIPS) is a critical intervention for complications of decompensated cirrhosis. However, traditional scoring systems like MELD and CTP have limitations in predicting long-term post-TIPS survival, particularly in populations with viral hepatitis. This study aimed to develop and validate a novel nomogram to predict 1-, 3-, and 5-year overall survival (OS) in patients with decompensated cirrhosis undergoing TIPS.
Methods:
We conducted a single-center retrospective study enrolling 409 patients with decompensated cirrhosis who received their first TIPS treatment between January 2017 and December 2023. Patients were randomly assigned to a training cohort (n = 286) and a validation cohort (n = 123). Independent prognostic factors were identified using multivariate Cox proportional hazards regression to construct a nomogram. Model performance was evaluated using time-dependent receiver operating characteristic (ROC) curves, calibration plots, and decision curve analysis (DCA), and compared with MELD-Na and CTP scores.
Results:
Six independent predictors were identified: age, serum ammonia, total cholesterol, total bilirubin, albumin, and creatinine. The nomogram demonstrated superior discrimination, the areas under the ROC curve (AUCs) for 1-, 3-, and 5-year OS were 0.79, 0.82, and 0.84 in the training cohort, and 0.81, 0.75, and 0.80 in the validation cohort, respectively. Calibration curves showed excellent agreement between predicted and observed survival, and DCA indicated significant clinical net benefit.
Conclusion:
We developed a robust nomogram integrating hepatic, renal, and metabolic indicators to predict long-term survival in post-TIPS patients. This model offers superior accuracy compared to traditional scoring systems, facilitating better risk stratification and individualized clinical decision-making.
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