Evidence map›Paper›PMID 33240440›Full record

ArticleEJC supplements : EJC : official journal of EORTC, European Organization for Research and Treatment of Cancer ... [et al.]2020

The hallmarks of ovarian cancer: proliferation and cell growth.

Raquel López-Reig, José Antonio López-Guerrero

Open access · goldAbstract read
In one paragraph

Article in EJC supplements : EJC : official journal of EORTC, European Organization for Research and Treatment of Cancer ... [et al.], 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed, 1 pooled it
2.0field-weighted citation impact, top 14% of its field
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

15 citing papers in PubMed, 1 synthesis or guideline pooled it, 22 citations in OpenAlex.

  1. Pooled it
  2. Review
  3. Article
  4. Article
  5. Review
  6. Article
  7. Article
  8. Article
  9. Review
  10. Could cannabinoids provide a new hope for ovarian cancer patients?Pharmacology research & perspectives · 2023
    Review
  11. Molecular-Based Immunohistochemical Algorithm for Uterine Leiomyosarcoma Diagnosis.Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc · 2023
    Article
  12. Molecular Management of High-Grade Serous Ovarian Carcinoma.International journal of molecular sciences · 2022
    Review
  13. Article
  14. Review
  15. 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

2 authors at 2 institutions in 1 country.

Raquel López-ReigLaboratory of Molecular Biology, Fundación Instituto Valenciano de Oncología (IVO), 46009 Valencia, Spain.
José Antonio López-GuerreroLaboratory of Molecular Biology, Fundación Instituto Valenciano de Oncología (IVO), 46009 Valencia, Spain.
Fundación Instituto Valenciano de Oncología · ESUniversitat de València · ES

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Epithelial ovarian cancer (EOC) is a heterogeneous group of diseases with distinct biological and clinical behaviour. Despite the differences between them, the capability of tumour cells to continuously proliferate and avoid death is maintained among histotypes. This ability is the result of alterations at different levels, causing the deregulation of cell cycle and proliferative-related pathways. Even if the leading role is played by RB and TP53, changes in other molecular pathways are involved in the development of EOC. This ability can be exploited to generate

Indexed as

Animal modelsCell growthCell proliferationEpithelial ovarian cancer

Identifiers

PMID33240440
PMCPMC7573473
OpenAlexW3081245281

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.