Evidence map›Paper›PMID 42350705›Full record

ArticleDiscover oncology2026

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

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

Abstract read
In one paragraph

Article in Discover oncology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Beibei Wu *Department of Oncology, Xiyuan Hospital, China Academy of Chinese Medical Sciences, Beijing, 100091, China.
Rui Li *Department of Oncology, Xiyuan Hospital, China Academy of Chinese Medical Sciences, Beijing, 100091, China.
Mengmeng Wang *Department of Oncology, Xiyuan Hospital, China Academy of Chinese Medical Sciences, Beijing, 100091, China.
Xuejie WangDepartment of Information, Xiyuan Hospital, China Academy of Chinese Medical Science, Beijing, 100091, China.
Chen QiaoDepartment of Information, Xiyuan Hospital, China Academy of Chinese Medical Science, Beijing, 100091, China.
Ding LuoDepartment of Information, Xiyuan Hospital, China Academy of Chinese Medical Science, Beijing, 100091, China.
Jian LiuDepartment of Information, Xiyuan Hospital, China Academy of Chinese Medical Science, Beijing, 100091, China. xyyylj@126.com.

Funding

Science and Technology Innovation Project of Chinese Academy of Traditional Chinese Medicine CI2022C002Special Project of Scientific Research of Capital Health Development 2024-2-4194
6 · The paper itself

Abstract

backgroundResearch 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.

methodsLiterature 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.

resultsThis 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.

conclusionThe 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.

Indexed as

BibliometricsEarly diagnosisHotspotsPancreatic cancer

Identifiers

PMID42350705
PMCPMC13558497

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.