Related Experiment Video
Updated: Sep 9, 2025

Author Spotlight: Investigating Immune Cell Dynamics in the Tumor Microenvironment — Challenges and Innovations in Cancer Prognosis
Published on: April 12, 2024
Prognostic nomogram for hepatocellular carcinoma with major vascular invasion: a population-based study from the SEER
Jia Fu1,2, Min Liu3, Sirong Chen1
1Department of Radiation Oncology, Guangxi Medical University Cancer Hospital, Nanning, 530021, China.
Background:
Patients with hepatocellular carcinoma (HCC) with major vascular invasion (MaVI) have a poor prognosis. In this study, we aimed to develop a nomogram model for predicting the prognosis of HCC with MaVI.
Methods:
Data of 2211 patients were extracted from the Surveillance, Epidemiology, and End Results (SEER) database on September 25, 2024. We randomly allocated the patients into training and validation cohorts using a 7:3 ratio. Furthermore, an external validation set, comprising 359 patients from Guangxi Medical University Cancer Hospital, was used. Independent variables impacting overall survival (OS) were identified using Cox regression analyses of the training cohort. The variations in OS across groups were compared using Kaplan-Meier curves and log-rank testing. A nomogram model was developed based on the identified factors. Time-dependent receiver operating characteristic curves, C-index values, decision curve analysis, and calibration curves were used to evaluate the model's predictive efficacy.
Results:
Independent indicators of survival for patients with HCC with MaVI included N stage, lung and bone metastases, tumor size, chemotherapy, alpha-fetoprotein (AFP) levels, radiotherapy, and surgery. A nomogram model was constructed using these factors. The C-index values were 0.73 for the training cohort, 0.72 for the internal validation cohort, and 0.72 for Chinese validation set. In training set, the area under the curve (AUC) was 0.81 (95% confidence interval [CI] 0.79-0.83), 0.80 (95% CI 0.77-0.83), and 0.79 (95% CI 0.76-0.82) at 6, 12, and 18 months, respectively. Similarly, the internal validation set had AUC of 0.83 (95% CI 0.80-0.86), 0.80 (95% CI 0.76-0.84), and 0.78 (95% CI 0.74-0.83) and the Chinese validation set had AUC of 0.85 (95% CI 0.78-0.92), 0.82 (95% CI 0.77-0.87), and 0.79 (95% CI 0.74-0.84) at 6, 12, and 18 months, respectively.
Conclusions:
A nomogram model based on N stage, tumor size, AFP levels, lung metastasis, bone metastasis, chemotherapy, radiotherapy, and surgery demonstrated high prediction accuracy and clinical value. Thus, it can serve as a useful reference in clinical practice for patients with HCC having MaVI.
More Related Videos
06:46Competing-Risk Nomogram for Predicting Cancer-Specific Survival in Multiple Primary Colorectal Cancer Patients after Surgery
Published on: September 27, 2024
07:13Comparison of Predictive Performance of Three Lymph Node Staging Systems in Colorectal Signet Ring Cell Carcinoma Based on Machine Learning Model
Published on: April 18, 2025