AUTHOR=Bai Jianhao , Wan Zhongqi , Wu Zhiyong , Peng Qing 

TITLE=Global research trends in metabolism-related intraocular malignancies: a multi-database bibliometric analysis and cross-validation study

JOURNAL=Frontiers in Molecular Biosciences

VOLUME=Volume 12 - 2025

YEAR=2025

URL=https://www.frontiersin.org/journals/molecular-biosciences/articles/10.3389/fmolb.2025.1683864

DOI=10.3389/fmolb.2025.1683864

ISSN=2296-889X

ABSTRACT=ObjectiveTo systematically characterize the global research landscape of metabolism-related intraocular malignancies and to validate the robustness of findings through a multi-database comparative approach.MethodsPublications from January 1, 1990, to July 31, 2025, were retrieved from the Web of Science Core Collection (WoSCC). To ensure the stability and generalizability of results, equivalent searches were performed in Scopus and PubMed, applying the same keyword set, time frame, and eligibility criteria. Bibliometric analyses were conducted using VOSviewer, CiteSpace, and GraphPad Prism to evaluate publication trends, geographic and institutional contributions, journal and author influence, keyword co-occurrence, co-citation patterns, and emerging research fronts. Cross-database validation assessed concordance in temporal trends, thematic focuses, and country rankings.ResultsA total of 1,745 WoSCC publications were included, authored by researchers from 69 countries. Global output has increased markedly since 2010, peaking in 2021. Uveal melanoma consistently emerged as the dominant intraocular tumor type in metabolic research. Major thematic clusters encompassed oxidative stress, apoptosis, hypoxia, lipid metabolism, and metabolic reprogramming, with recent shifts toward long noncoding RNA, immune infiltration, and metabolomics, signaling a transition to precision oncology. Importantly, multi-database validation demonstrated high concordance in annual publication trends, as well as strong overlap in top keywords and stability in geographical and disease foci.ConclusionThis study provides a multi-database bibliometric assessment of metabolism-related intraocular malignancy research, with offering a reliable foundation for guiding future basic and translational research in ocular oncology.