Evidence map›Paper›PMID 37410149›Full record

ReviewArchives of gynecology and obstetrics2024

It is time to implement molecular classification in endometrial cancer.

Valentina Bruno, Alessandra Logoteta, Benito Chiofalo, Emanuela Mancini, Martina Betti, Luana Fabrizi, Emilio Piccione, Enrico Vizza

Abstract readReview
PubMed Publisher
In one paragraph

Review in Archives of gynecology and obstetrics, 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. Article
  2. Article
  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

8 authors.

Valentina BrunoGynecologic Oncology Unit, Department of Experimental Clinical Oncology, IRCCS "Regina Elena" National Cancer Institute, Via Elio Chianesi 53, 00144, Rome, Italy.
Alessandra LogotetaDepartment of Maternal and Child Health and Urological Sciences, University of Rome "Sapienza", Policlinico "Umberto I", Rome, Italy.
Benito ChiofaloGynecologic Oncology Unit, Department of Experimental Clinical Oncology, IRCCS "Regina Elena" National Cancer Institute, Via Elio Chianesi 53, 00144, Rome, Italy. benito.chiofalo@ifo.it.ORCID 0000-0003-2801-2962
Emanuela ManciniGynecologic Oncology Unit, Department of Experimental Clinical Oncology, IRCCS "Regina Elena" National Cancer Institute, Via Elio Chianesi 53, 00144, Rome, Italy.
Martina BettiBiostatistics, Bioinformatics and Clinical Trial Center, IRCCS-Regina Elena National Cancer Institute, Rome, Italy.
Luana FabriziDepartment of Anesthesiology, IRCCS-Regina Elena National Cancer Institute, Rome, Italy.
Emilio PiccioneDepartment of Surgical Sciences, Catholic University Our Lady of Good Counsel, Tirane, Albania.
Enrico VizzaGynecologic Oncology Unit, Department of Experimental Clinical Oncology, IRCCS "Regina Elena" National Cancer Institute, Via Elio Chianesi 53, 00144, Rome, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A huge effort has been done in redefining endometrial cancer (EC) risk classes in the last decade. However, known prognostic factors (FIGO staging and grading, biomolecular classification and ESMO-ESGO-ESTRO risk classes stratification) are not able to predict outcomes and especially recurrences. Biomolecular classification has helped in re-classifying patients for a more appropriate adjuvant treatment and clinical studies suggest that currently used molecular classification improves the risk assessment of women with EC, however, it does not clearly explain differences in recurrence profiles. Furthermore, a lack of evidence appears in EC guidelines. Here, we summarize the main concepts why molecular classification is not enough in the management of endometrial cancer, by highlighting some promising innovative examples in scientific literature studies with a clinical potential significant impact.

Indexed as

Endometrial NeoplasmsFemaleHumansNeoplasm Recurrence, LocalNeoplasm StagingRetrospective StudiesRisk AssessmentEC biomolecular classificationEC prognosis predictionEC recurrence predictionEC risk stratificationEndometrial cancer

Identifiers

PMID37410149

What OpenQuestion holds

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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.