Evidence map›Paper›PMID 39421747›Full record

ArticleFrontiers in immunology2024

Knowledge mapping and visualization of trends in immunotherapy for ovarian cancer over the past five years: a bibliometric analysis.

Kowthar Mohamed Shaie, Lian Sihan, Wang Yuli, Han Mengfei, Feng Renqian, Hu Yan

Abstract read
In one paragraph

Article in Frontiers in immunology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
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

6 authors.

Kowthar Mohamed ShaieDepartment of Gynecology, First Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, China.
Lian SihanDepartment of Gynecology, First Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, China.
Wang YuliDepartment of Gynecology, First Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, China.
Han MengfeiDepartment of Gynecology, First Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, China.
Feng RenqianDepartment of Gynecology, First Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, China.
Hu YanDepartment of Gynecology, First Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: This study conducts a bibliometric literature analysis to explore trends in immunotherapy for ovarian cancer from 2019 to 2023. Methods: An extensive online literature search was conducted in the Web of Science Core Collection database to identify English-language articles and reviews related to "trends in immunotherapy", and "ovarian cancer". statistical analysis was performed using VOSviewer to visualize and compare nations, institutions, and journals simultaneously. Results: Our findings highlight contributions by 118 nations, led by the People's Republic of China with 3,167 contributions; Germany followed with 558 and Italy having 547. Of all publications made between 2019-2023, "Frontiers Immunology" had the most publications with 546 total records followed by "cancers ", and "frontiers in oncology" being the most heavily relied upon categories. Annually publication trends increased until 2022 but then declined considerably as a peak of highly-cited papers occurring between 2019 and 2022. Conclusions: Our bibliometric analysis not only maps the evolution of immunotherapy research in ovarian cancer but also provides actionable insights for advancing scientific progress. By identifying emerging trends and key areas, future research can strategically enhance treatment strategies and outcomes for ovarian cancer patients.

Indexed as

BibliometricsImmunotherapyOvarian NeoplasmsFemaleHumansbibliometric analysisimmunotherapyknowledge mappingovarian cancerscientific trendsWeb of Science

Identifiers

PMID39421747
PMCPMC11483997

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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.