Evidence map›Paper›PMID 33123697›Full record

ArticleFacts, views & vision in ObGyn2020

Treatment algorithm in patients with ovarian cancer.

I Vergote, H Denys, J De Greve, C Gennigens, K Van De Vijver, J Kerger, P Vuylsteke, J F Baurain

Open access · greenAbstract read
In one paragraph

Article in Facts, views & vision in ObGyn, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed
2.4field-weighted citation impact, top 11% 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

18 citing papers in PubMed, 21 citations in OpenAlex.

  1. Article
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  8. Pregnancy after advanced ovarian cancer with spontaneous uterine rupture in second trimester: A case report and review of the literature.International journal of gynaecology and obstetrics: the official organ of the International Federation of Gynaecology and Obstetrics · 2025
    Review
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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

8 authors at 2 institutions in 1 country.

I VergoteDepartment of Oncology, University Hospitals Leuven, Herestraat 49, 3000 Leuven, Belgium.
H DenysDepartment of Medical Oncology, Ghent University Hospital, C. Heymanslaan 10, 9000 Ghent, Belgium.
J De GreveDepartment of Medical Genetics, University Hospitals Brussels, Laarbeeklaan 101, 1090, Brussels, Belgium.
C GennigensDepartment of Medical Oncology, Liège University Hospital, Avenue de l'Hôpital 1, 4000 Liège, Belgium.
K Van De VijverDepartment of Pathology, Ghent University Hospital, C. Heymanslaan 10, 9000 Ghent, Belgium.
J KergerJules Bordet Institute, Brussels University Hospital,Boulevard de Waterloo 121, 1000 Brussels, Belgium.
P VuylstekeDepartment of Oncology, UCLouvain, CHU UCL Namur Hospital, Site St-Elisabeth, Place Louise Godin 15, 5000 Namur, Belgium.
J F BaurainDepartment of Oncology, UCLouvain, CHU UCL Namur Hospital, Site St-Elisabeth, Place Louise Godin 15, 5000 Namur, Belgium.
Ghent University Hospital · BEKU Leuven · BE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Most ovarian cancer patients are diagnosed only at advanced stages when survival outcomes are worse, andwhen therapeutic decisions might prove challenging. The fundamental treatment for women with ovarian cancerincludes debulking surgery whenever possible and appropriate systemic therapy (chemotherapy, targeted andantiangiogenic agents). In the last few years, knowledge about histological and molecular characteristics of ovariancancer subtypes and stages has increased considerably. This has enabled the development and improvement ofseveral options for the diagnosis and treatment of ovarian cancer in a patient-tailored approach. Accordingly,therapeutic decisions are guided by the characteristics of the patient and the tumour, especially the molecularfeatures of the cancer subtype and disease stage. Particularly relevant are the advances in early genetic testing ofgermline and somatic mutations involved in DNA repair, and the clinical development of targeted agents. In orderto implement the best individual medical strategies, in this article, we present an algorithm of treatment options,including recently developed targeted agents, for primary and recurrent ovarian cancer patients in Belgium.

Indexed as

Epithelial ovarian cancergenetic testingtargeted agentstreatment algorithm

Identifiers

PMID33123697
PMCPMC7580261
OpenAlexW3095511752

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.