Evidence map›Paper›PMID 34439142›Full record

ReviewCancers2021

Endometrial Cancer Molecular Characterization: The Key to Identifying High-Risk Patients and Defining Guidelines for Clinical Decision-Making?

Regina Esi Mensimah Baiden-Amissah, Daniela Annibali, Sandra Tuyaerts, Frederic Amant

Open access · goldAbstract readReview
In one paragraph

Review in Cancers, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
2.8field-weighted citation impact, top 9% 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

17 citing papers in PubMed, 22 citations in OpenAlex.

  1. Article
  2. Article
  3. Review
  4. Management of endometrial cancer in Latin America: raising the standard of care and optimizing outcomes.International journal of gynecological cancer : official journal of the International Gynecological Cancer Society · 2024
    Review
  5. Review
  6. Article
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  8. Article
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  14. 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

4 authors at 3 institutions in 2 countries.

Regina Esi Mensimah Baiden-AmissahDepartment of Oncology, Leuven Cancer Institute (LKI), KU Leuven (University of Leuven), 3000 Leuven, Belgium.ORCID 0000-0003-3071-7726
Daniela AnnibaliDepartment of Oncology, Leuven Cancer Institute (LKI), KU Leuven (University of Leuven), 3000 Leuven, Belgium.ORCID 0000-0001-8413-7669
Sandra TuyaertsLaboratory of Medical and Molecular Oncology (LMMO), Department of Medical Oncology, Vrije Universiteit Brussel (VUB), Universitair Ziekenhuis Brussel (UZ Brussel), 1090 Brussels, Belgium.ORCID 0000-0003-1255-8071
Frederic AmantDepartment of Oncology, Leuven Cancer Institute (LKI), KU Leuven (University of Leuven), 3000 Leuven, Belgium.ORCID 0000-0002-5452-4905
KU Leuven · BEUniversitair Ziekenhuis Leuven · BEVrije Universiteit Brussel · BE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Endometrial carcinomas (EC) are the sixth most common cancer in women worldwide and the most prevalent in the developed world. ECs have been historically sub-classified in two major groups, type I and type II, based primarily on histopathological characteristics. Notwithstanding the usefulness of such classification in the clinics, until now it failed to adequately stratify patients preoperatively into low- or high-risk groups. Pieces of evidence point to the fact that molecular features could also serve as a base for better patients' risk stratification and treatment decision-making. The Cancer Genome Atlas (TCGA), back in 2013, redefined EC into four main molecular subgroups. Despite the high hopes that welcomed the possibility to incorporate molecular features into practice, currently they have not been systematically applied in the clinics. Here, we outline how the emerging molecular patterns can be used as prognostic factors together with tumor histopathology and grade, and how they can help to identify high-risk EC subpopulations for better risk stratification and treatment strategy improvement. Considering the importance of the use of preclinical models in translational research, we also discuss how the new patient-derived models can help in identifying novel potential targets and help in treatment decisions.

Indexed as

adjuvant therapyendometrial cancergenetic alterationsmolecular risk stratificationpreclinical modelstargeted therapy

Identifiers

PMID34439142
PMCPMC8391655
OpenAlexW3188764068

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.