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Background <p>Research on the early detection of pancreatic cancer has grown rapidly in recent years; however, existing bibliometric studies in this field have focused on broad research landscapes or treatment modalities, with no systematic analysis specifically mapping the knowledge structure and emerging frontiers of early detection.</p> Methods <p>Literature published between January 1, 1986, and December 31, 2025, was retrieved from the Web of Science Core Collection database. Co-occurrence analysis, cluster analysis, and burst analysis were carried out using bibliometric tools such as VOSviewer, CiteSpace, and R-bibliometrix to evaluate publication trends, main contributors, and the dynamic evolution of the research topic.</p> Results <p>This study included original papers and reviews (<i>n</i> = 7,353). The analysis reveals that the volume of publications has shown a strong upward trend since 2004. The United States dominates global output; Johns Hopkins University emerged as the institution with the largest number of publications and the highest number of citations; <i>Pancreas</i> is the most productive journal in this field, while the <i>American Journal of Surgical Pathology</i> received the highest total citations. Six keyword clusters were identified: molecular biology and biomarkers, imaging and endoscopic techniques, pathological classification of mucinous neoplasms, precancerous lesion characteristics, clinical management strategies, and epidemiology/risk factors/artificial intelligence. Current research hotspots focus on the surveillance of high-risk populations (new-onset diabetes, genetic susceptibility syndromes, and precancerous lesions), as well as innovative screening models, including multi-omics liquid biopsies, artificial intelligence, and cyst fluid molecular classifiers. In addition, the study identified barriers to clinical translation in this field, such as insufficient research on cost-effectiveness and psychological outcomes, alongside inadequate funding.</p> Conclusion <p>The field of early detection of pancreatic cancer is shifting from passive, single-modality imaging to active, risk-assessment-based multimodal surveillance. In the future, large-scale prospective population trials are still necessary, and cost-benefit assessments alongside patient-reported psychological outcomes remain critical to accelerate the clinical application of multi-omics marker platforms and AI models.</p>

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A bibliometric analysis of research trends and future directions in early detection of pancreatic cancer

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年6月25日

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  • Beibei Wu,
  • Rui Li,
  • Mengmeng Wang,
  • Xuejie Wang,
  • Chen Qiao,
  • Ding Luo,
  • Jian Liu

摘要

Background

Research on the early detection of pancreatic cancer has grown rapidly in recent years; however, existing bibliometric studies in this field have focused on broad research landscapes or treatment modalities, with no systematic analysis specifically mapping the knowledge structure and emerging frontiers of early detection.

Methods

Literature published between January 1, 1986, and December 31, 2025, was retrieved from the Web of Science Core Collection database. Co-occurrence analysis, cluster analysis, and burst analysis were carried out using bibliometric tools such as VOSviewer, CiteSpace, and R-bibliometrix to evaluate publication trends, main contributors, and the dynamic evolution of the research topic.

Results

This study included original papers and reviews (n = 7,353). The analysis reveals that the volume of publications has shown a strong upward trend since 2004. The United States dominates global output; Johns Hopkins University emerged as the institution with the largest number of publications and the highest number of citations; Pancreas is the most productive journal in this field, while the American Journal of Surgical Pathology received the highest total citations. Six keyword clusters were identified: molecular biology and biomarkers, imaging and endoscopic techniques, pathological classification of mucinous neoplasms, precancerous lesion characteristics, clinical management strategies, and epidemiology/risk factors/artificial intelligence. Current research hotspots focus on the surveillance of high-risk populations (new-onset diabetes, genetic susceptibility syndromes, and precancerous lesions), as well as innovative screening models, including multi-omics liquid biopsies, artificial intelligence, and cyst fluid molecular classifiers. In addition, the study identified barriers to clinical translation in this field, such as insufficient research on cost-effectiveness and psychological outcomes, alongside inadequate funding.

Conclusion

The field of early detection of pancreatic cancer is shifting from passive, single-modality imaging to active, risk-assessment-based multimodal surveillance. In the future, large-scale prospective population trials are still necessary, and cost-benefit assessments alongside patient-reported psychological outcomes remain critical to accelerate the clinical application of multi-omics marker platforms and AI models.