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Background <p>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.</p> Methods <p>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.&#xa0;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.</p> Results <p>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.&#xa0;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&#xa0;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&#xa0;months, respectively.</p> Conclusions <p>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.</p>

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Prognostic nomogram for hepatocellular carcinoma with major vascular invasion: a population-based study from the SEER database and a Chinese cohort

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年9月3日

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  • Jia Fu,
  • Min Liu,
  • Sirong Chen,
  • LiJun Chen,
  • Shixiong Liang

摘要

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.