Evidence map›Paper›PMID 33240448›Full record

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

Rare ovarian tumours. Other treatments for ovarian cancer.

Marta Gil-Martin, Beatriz Pardo, Maria-Pilar Barretina-Ginesta

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 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.2field-weighted citation impact, top 39% 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

4 citing papers in PubMed, 8 citations in OpenAlex.

  1. Article
  2. Article
  3. Review
  4. Review
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

3 authors at 3 institutions in 1 country.

Marta Gil-MartinMedical Oncology Department, Catalan Institute of Oncology-IDIBELL, L'Hospitalet-Barcelona, Spain.
Beatriz PardoMedical Oncology Department, Catalan Institute of Oncology-IDIBELL, L'Hospitalet-Barcelona, Spain.
Maria-Pilar Barretina-GinestaMedical Oncology Department, Catalan Institute of Oncology (ICO), Girona, Spain.
Catalan Institute for Water Research · ESInstitut Català d'Oncologia · ESInstitut d'Investigació Biomédica de Bellvitge · ES

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

aimThe description of rare malignant ovarian tumours and the most suitable treatments. Alternative therapies different from intravenous chemotherapy are also explained.

methodsLiterature review and ongoing trial information have been used to elaborate this guide.

resultsEach ovarian cancer type must be identified and treated properly from diagnostic to surgery, adjuvant treatment and metastatic disease. Hormonotherapy can be useful as an alternative treatment, especially in low-grade ovarian cancer and endometrioid subtype. Tumour characterisation is appropriated for treatment selection when targeted therapy is indicated. MEK inhibitors, tyrosine-kinase inhibitors, EGFR inhibitors, therapies against integrins, antibody-drug conjugates and other strategies are described. Antiangiogenics, PARP inhibitors and immunotherapy are discussed in other parts of this publication.

conclusionDifferent ovarian cancer types must receive the appropriated treatment. Alternative therapies may be evaluated beyond the standard therapy, frequently in a clinical trial, and an individualised molecular study may help to find the best treatment.

Indexed as

HormonotherapyRare malignant ovarian tumoursTargeted therapy

Identifiers

PMID33240448
PMCPMC7573466
OpenAlexW3081355617

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.