SynthesisFrontiers in oncology2025
Knowledge graph and bibliometric analysis of inflammatory indicators in ovarian cancer.
Synthesis in Frontiers in oncology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
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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.
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.
Who cites it
4 citing papers in PubMed.
- [Medical prior-guided TabMap deep learning model for ovarian cancer prediction and interpretability analysis].Nan fang yi ke da xue xue bao = Journal of Southern Medical University · 2026Article
- A senescence-based machine learning model prognosticates and personalizes therapy in cervical cancer.Translational cancer research · 2026Article
- Translational Perspectives on Cell-Free Mitochondrial DNA as a Biomarker in Gynecological Cancers: Current Limitations and Future Research Directions.Biomolecules · 2026Review
- Integration of Mendelian randomization and transcriptome wide association studies for causal gene identification in ovarian cancer genetic architecture.Discover oncology · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Chronic inflammation is a type of inflammatory response that lasts for a relatively long period of time. Occurrence and development of many diseases are closely related to chronic inflammation. In the process of the occurrence of certain tumors, chronic inflammation also plays an important role. For example, chronic inflammation of the stomach caused by chronic Helicobacter pylori infection is an important risk factor for gastric cancer. Inflammatory cells can release reactive oxygen species (ROS), cytokines and so on which can induce DNA damage in cells, activate oncogenes and suppress tumor suppressor genes, thus promoting the proliferation, survival, migration and invasion of tumor cells. Recent studies have shown that great progress has been made in understanding the role of chronic inflammation in ovarian cancer. However, there has been no bibliometric analysis in this research field yet. The aim of this study is to review the knowledge structure and research hotspots of inflammatory indicators in ovarian cancer through bibliometric methods. Methods: A computer search was conducted on 595 articles related to inflammatory markers and ovarian cancer in the Web of Science Core Collection (WoSCC) database from 2000 to 2024. Relevant software such as VOSviewer, CiteSpace, R package "bibliometrix" and Microsoft Office Excel 2019 were used to conduct a comprehensive bibliometric analysis on these related articles and analyze the research status and development directions over the past more than 20 years. Results: A total of 595 articles related to inflammatory markers and ovarian cancer were included in this study. Among them, the United States and China had the largest number of published articles. Global publications have been steadily increasing every year with reaching a peak in 2023. The United States had the largest number of publications and followed by China and Italy. Among them, Harvard University in the United States had the largest number of published papers, approximately 100 and followed by the National Institutes of Health (NIH) and the NIH National Cancer Institute (NCI) with 52 each. CHATURVEDI AK ranked first in the total citation number of published articles, with a total of 683 citations and HILDESHEIM A ranked second in the total citation number, with a total of 651 citations. The number citations are highlighting their significant contributions to this field. The two magazines of the CANCER EPIDEMIOLOGY BIOMARKERS & PREVENTION and JOURNAL OF OVARIAN RESEARCH had the most published articles and followed by Cancer and PLOS ONE. The article "COUSSENSLU, 2002, NATURE V420, P860, 00110, 1030/NATURE01322" was the most frequently cited one, with 46 citations. The article "CRVENNKOY SL2010, CELL7140 2883, 00110 016402LL 201001025" was cited 38 times and ranked second. The analysis results of CiteSpace show that ovarian cancer, inflammation and prognosis are identified as the keywords with the highest frequencies, indicating the core research focuses and directions in this area. The results of the research topics in this area show that from 2019 to 2024, the main themes were ovarian cancer, inflammation and so on. Through the analysis of the research trends, it can be known that from 2019 to 2024, ovarian cancer and inflammation were the main trends, which is the analysis of trend topics. All in all, the indicators of ovarian cancer and inflammation represent the frontier research directions in this field. Conclusion: This is the first bibliometric study that comprehensively summarizes the research trends and progress of inflammatory indicators in ovarian cancer. The information in this study has summarized the recent research frontiers and hotspots. The results will provide references for scholars to study the early diagnosis and treatment of inflammatory indicators and ovarian cancer.
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Registered trials
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.