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Updated: Jan 12, 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 nomogram for predicting postoperative survival in patients with multifocal
Bojun Liu1,2, Gongming Zhang1,3, Guangming Li4,5
1Beijing YouAn Hospital, Capital Medical University, 8 Xitoutiao, Youanmenwai Street, Fengtai District, Beijing, China.
Background:
Hepatocellular carcinoma (HCC) is the fifth most common malignant tumor and the third leading cause of cancer-related death worldwide. Despite the significance of multifocality in HCC (M-HCC), most studies have predominantly treated it as a prognostic factor, lacking in-depth investigation into its prognostic implications. This retrospective study aims to integrate clinical and laboratory examinations to construct a predictive model that more accurately forecasts the prognosis of patients with M-HCC. This aims to guide personalized treatment strategies and improve overall survival rates.
Methods:
We applied the Lasso and cross-validated Lasso (CV-Lasso) combined with Random Forest analysis to explore the prognostic factors influencing M-HCC. Simultaneously, we utilized the identified prognostic factors to construct a Nomogram. This Nomogram assigns scores based on the magnitude of the impact of each factor on prognosis, enabling the prediction of postoperative survival rates for patients. Subsequently, the model-derived risk scores categorized patients into low-risk and high-risk groups, and Kaplan-Meier curves were generated.
Results:
The patients, who were enrolled, were divided into training and validation sets. Factors influencing the prognosis of M-HCC were identified through Lasso, cross-validated Lasso, and Random Forest analyses, revealing seven key factors: Age, Antiviral, Child-Pugh, Cirrhosis, White Blood Cell (WBC), Platelets (PLT), and Thrombin Time (TT). Nomograms were constructed based on these factors to predict 3-year, 5-year, and 8-year survival rates. ROC curves confirmed the predictive capability of various factors, with larger areas under the curve at 5 (AUC = 0.653) and 8 years (AUC = 0.733). Kaplan-Meier curves stratified patients into low-risk and high-risk groups, showing significantly higher survival times in the low-risk group (p < 0.0001).
Conclusions:
Postoperative antiviral treatment for patients with M-HCC, aimed at enhancing immune function and protecting liver function, has been shown to extend patient survival. Simultaneously, factors such as Child-Pugh, age, and Cirrhosis in patients with M-HCC have been associated with a decrease in postoperative survival time.
