Comprehensive Bibliometric Analysis of Prediction Models for HCC: Current Trends and Future Prospects

Hepatocellular carcinoma (HCC) is the most common primary malignant liver tumor, with rising incidence and mortality rates posing a significant threat to global public health. Accurate prediction of liver cancer occurrence and progression is essential for improving patient prognosis. This study uses bibliometric methods to analyze the current state and future trends in liver cancer prediction research.

A search was conducted in the Web of Science (WOS) database on October 22, 2023, identifying 1092 articles on liver cancer prediction. These articles were quantitatively analyzed using CiteSpace 6.2 software, with a focus on research hotspots, authors, countries, and keywords.

The study involved 114 countries, 4254 institutions, and 280 journals, with 48,788 citations. China (826 papers) and the USA (96 papers) dominate the field. Leading institutions include Sun Yat-sen University, Fudan University, Zhejiang University, and Yonsei University. The most cited journals were Hepatology (2209 citations) and Journal of Hepatology (946 citations). Frontiers in Oncology had the highest H-index (14). Key authors include Kim Seung Up (23 papers) and Ahn Sang Hoon (H-index = 14). Early research focused on risk factors and staging, while recent studies emphasize DNA methylation, immune microenvironments, and tumor metastasis. Future research will focus on multi-omics data integration and AI-driven predictive model optimization.

This study provides a comprehensive overview of liver cancer prediction research, highlighting key trends and the potential of multi-omics data and machine learning to enhance predictive models and clinical outcomes.