Evidence map›Paper›PMID 40510149›Full record

SynthesisFrontiers in oncology2025

Knowledge mapping of global trends in DNA damage repair-related breast cancer research: a bibliometric study.

Yajing Huang, Shumei Wei, Kaimin Hu, Xueping Xiang

Erratum issuedAbstract readSystematic Review
In one paragraph

Synthesis in Frontiers in oncology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. 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

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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

5 · Who and what money

Authors and funding

4 authors.

Yajing HuangDepartment of Pathology, the Second Affiliated Hospital, Zhejiang University, School of Medicine, Hangzhou, China.
Shumei WeiDepartment of Pathology, the Second Affiliated Hospital, Zhejiang University, School of Medicine, Hangzhou, China.
Kaimin HuDepartment of Breast Surgery and Oncology, the Second Affiliated Hospital, Zhejiang University, School of Medicine, Hangzhou, China.
Xueping XiangDepartment of Pathology, the Second Affiliated Hospital, Zhejiang University, School of Medicine, Hangzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Breast cancer remains one of the leading causes of cancer-related morbidity and mortality among women worldwide. Recent advancements in our understanding of DNA damage repair (DDR) mechanisms have shed light on their specific role in the pathogenesis, progression, treatment resistance, and prognosis of breast cancer. In this study, we conducted a bibliometric study to map the global trends in DDR-related breast cancer research. Methodology: A search of publications on DDR in breast cancer from 1990 to 2024 was conducted using the Web of Science Core Collection. A comprehensive bibliometric analysis of the data was performed using CiteSpace, VOSviewer, and Bibliometrix. Additionally, for clinical trial data, the databases ClinicalTrials.gov (https://www.clinicaltrials.gov) and the WHO International Clinical Trials Registry Platform (ICTRP) (https://trialsearch.who.int) were queried. Results: The results revealed a continuous and steady growth in the number of articles published in this area over the past three decades and showed that the USA had produced the highest number of publications in this field, while Harvard University had published the largest number of articles. Jonkers, Jos was found to be the most published author, with 39 documents. Analysis of the journals showed that Conclusion: Overall, this study provides valuable insights into the current research achievements, latest advancements, and emerging global trends in DNA damage repair-related breast cancer research. With sustained clinical focus, more high-quality investigations combining DDR inhibitors with other treatment modalities are needed.

Indexed as

bibliometric studybreast cancerCiteSpaceDNA damage repairglobal trendsVOSviewer

Identifiers

PMID40510149
PMCPMC12159020

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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.