Evidence map›Paper›PMID 40903746›Full record

ArticleEuropean journal of medical research2025

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

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

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Article in European journal of medical research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1citing papers in PubMed
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1 · What the graph read from it

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3 · Its place in the literature

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1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Jia FuDepartment of Radiation Oncology, Guangxi Medical University Cancer Hospital, Nanning, 530021, China.
Min LiuDepartment of Oncology, Zhuzhou Central Hospital, Zhuzhou, 412000, China.
Sirong ChenDepartment of Radiation Oncology, Guangxi Medical University Cancer Hospital, Nanning, 530021, China.
LiJun ChenDepartment of Radiation Oncology, Guangxi Medical University Cancer Hospital, Nanning, 530021, China. lijanchen@sr.gxmu.edu.cn.
Shixiong LiangDepartment of Radiation Oncology, Guangxi Medical University Cancer Hospital, Nanning, 530021, China. liangshixiong@sr.gxmu.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPatients 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.

methodsData 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.

resultsIndependent 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.

conclusionsA 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.

Indexed as

Carcinoma, HepatocellularLiver NeoplasmsNomogramsAdultAgedChinaCohort StudiesEast Asian PeopleFemaleHumansMaleMiddle AgedNeoplasm InvasivenessPrognosisSEER ProgramHepatocellular carcinomaMajor vascular invasionNomogramOverall survivalSEER database

Identifiers

PMID40903746
PMCPMC12406567

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