Evidence map›Paper›PMID 39588300›Full record

SynthesisFrontiers in oncology2024

Drug resistance biomarkers in ovarian cancer: a bibliometric study from 2017 to 2022.

Sindy Cabarca, Carmen Ili, Carlos Vanegas, Laura Gil, Melba Vertel-Morrinson, Priscilla Brebi

Abstract readSystematic Review
In one paragraph

Synthesis in Frontiers in oncology, 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. Review
  2. Review
  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.

Sindy CabarcaMillennium Institute on Immunology and Immunotherapy. Laboratory of Integrative Biology (LIBi), Centro de Excelencia en Medicina Traslacional (CEMT), Scientific and Technological Bioresource Nucleus (BIOREN), Universidad de La Frontera, Temuco, Chile.
Carmen IliMillennium Institute on Immunology and Immunotherapy. Laboratory of Integrative Biology (LIBi), Centro de Excelencia en Medicina Traslacional (CEMT), Scientific and Technological Bioresource Nucleus (BIOREN), Universidad de La Frontera, Temuco, Chile.
Carlos VanegasGrupo de Investigación Estadística y Modelamiento Matemático Aplicado (GEMMA), Departamento de Matemáticas, Facultad de Educación y Ciencias, Universidad de Sucre, Sincelejo, Colombia.
Laura GilGrupo de Investigación Estadística y Modelamiento Matemático Aplicado (GEMMA), Departamento de Matemáticas, Facultad de Educación y Ciencias, Universidad de Sucre, Sincelejo, Colombia.
Melba Vertel-MorrinsonGrupo de Investigación Estadística y Modelamiento Matemático Aplicado (GEMMA), Departamento de Matemáticas, Facultad de Educación y Ciencias, Universidad de Sucre, Sincelejo, Colombia.
Priscilla BrebiMillennium Institute on Immunology and Immunotherapy. Laboratory of Integrative Biology (LIBi), Centro de Excelencia en Medicina Traslacional (CEMT), Scientific and Technological Bioresource Nucleus (BIOREN), Universidad de La Frontera, Temuco, Chile.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Late diagnosis and patient relapse, mainly due to chemoresistance, are the key reasons for the high mortality rate of ovarian cancer patients. Hence, the search for biomarkers of high predictive value within the phenomenon of chemoresistance is vital. This study performs a bibliometric analysis of the scientific literature concerning biomarkers of drug resistance in ovarian cancer, considering the period from 2017 to 2022. Methods: The terms "drug resistance biomarker" and "ovarian cancer" were linked by the Boolean operator "AND". The search was done in PubMed, selecting documents published over the last 5 years (2017-2022), which were analyzed with the open-source tool Bibliometrix developed in the R package. The language of the publications was restricted to English. Several types of papers such as case reports, clinical trials, comparative studies, and original articles were considered. Results: A total of 335 scientific articles were analyzed. The United States and China were the leading contributors and established the largest number of scientific collaborations. The Huazhong University of Science and Technology and the University of Texas MD Anderson Cancer Center were the most influential institutions. The Journal of Ovarian Research, International Journal of Molecular Science, and Scientific Reports are among the most relevant journals. The study identified high-profile, relevant thematic niches and important descriptors that indicate topics of interest, including studies on women, cell lines, solid tumors, and gene expression regulation. As well as studies involving middle-aged and adult participants, and those focusing on prognosis evaluation. Descriptors such as "drug resistance," "neoplasm," "genetics," "biomarker," "gene expression profile," and "drug therapy" would indicate new research trends. In addition, we propose that BCL-2, CHRF, SNAIL, miR-363, iASPP, ALDH1, Fzd7, and EZH2 are potential biomarkers of drug resistance. Conclusions: This paper contributes to the global analysis of the scientific investigation related to drug resistance biomarkers in ovarian cancer to facilitate further studies and collaborative networks, which may lead to future improvements in therapy for this lethal disease.

Indexed as

bibliometric analysisbibliometrixbiblioshinybiomarkerschemoresistancedescriptordrug resistanceovarian cancer

Identifiers

PMID39588300
PMCPMC11586235

What OpenQuestion holds

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LicenceCC BY
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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.