Evidence map›Paper›PMID 35847944›Full record

ArticleFrontiers in oncology2022

Low-Grade Uterine Endometrial Stromal Sarcoma: Prognostic Analysis of Clinico-Pathological Characteristics, Surgical Management, and Adjuvant Treatments. Experience From Two Referral Centers.

Fulvio Borella, Luca Bertero, Paola Cassoni, Elisa Piovano, Niccolò Gallio, Mario Preti, Stefano Cosma, Domenico Ferraioli, Luca Pace, Luca Mariani and 2 more

Open access · goldAbstract read
In one paragraph

Article in Frontiers in oncology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
3.3field-weighted citation impact, top 7% 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, 20 citations in OpenAlex.

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  15. Utero-ovarian low grade endometrial stromal sarcoma, a case report.International journal of surgery case reports · 2023
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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

12 authors at 3 institutions in 2 countries.

Fulvio BorellaDivision of Gynecology and Obstetrics 1, "City of Health and Science University Hospital", University of Turin, Turin, Italy.
Luca BerteroPathology Unit, Department of Medical Sciences, "City of Health and Science University Hospital", University of Turin, Turin, Italy.
Paola CassoniPathology Unit, Department of Medical Sciences, "City of Health and Science University Hospital", University of Turin, Turin, Italy.
Elisa PiovanoDivision of Gynecology and Obstetrics 3, "City of Health and Science University Hospital", Turin, Italy.
Niccolò GallioDivision of Gynecology and Obstetrics 1, "City of Health and Science University Hospital", University of Turin, Turin, Italy.
Mario PretiDivision of Gynecology and Obstetrics 1, "City of Health and Science University Hospital", University of Turin, Turin, Italy.
Stefano CosmaDivision of Gynecology and Obstetrics 1, "City of Health and Science University Hospital", University of Turin, Turin, Italy.
Domenico FerraioliDepartment of Oncology Surgery, Centre Léon Berard (CLB), Lyon, France.
Luca PaceDepartment of Surgical Sciences, University of Turin, Turin, Italy.
Luca MarianiDepartment of Surgical Sciences, University of Turin, Turin, Italy.
Nicoletta BigliaDepartment of Surgical Sciences, University of Turin, Turin, Italy.
Chiara BenedettoDivision of Gynecology and Obstetrics 1, "City of Health and Science University Hospital", University of Turin, Turin, Italy.
University of Turin · ITCentre Léon Bérard · FRPiedmont Reference Center for Epidemiology and Cancer Prevention · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: Low-grade uterine endometrial stromal sarcoma (LG-ESS) is a rare tumor characterized by an overall good survival but showing a indolent behavior and a variable risk of recurrence. There is no clear consensus on the optimal management of these tumors and no prognostic or predictive factors have been established. With this study, we evaluated the prognostic relevance of several clinical, surgical, and pathological features in patients affected by LG-ESS to identify risk factors associated with recurrence. Methods: We retrospectively analyzed 52 LG-ESS cases, treated from January 1st, 1994, to May 31st, 2020, in two referral centers. The relationship between recurrence and clinicopathological characteristics as well as surgical treatment was investigated. Risk of recurrence and disease-free survival (DFS) were estimated by Cox regression and the Kaplan-Meier analysis, respectively. Results: Of 52 patients with LG-ESS, 8 experienced recurrence (15%). The median follow-up was 100 months (SD ± 96, range: 15-336). By univariate analysis, fragmentation/morcellation, tumor size, FIGO stage, higher mitotic count, presence of necrosis, and lymphovascular space invasion (LSVI) resulted associated with a poorer outcome. Conversely, the surgical modality (laparotomic vs laparoscopic and hysterectomy with bilateral salpingo-oophorectomy vs local excision) and pelvic lymphadenectomy were not. Even the different modalities of adjuvant therapy (hormonal therapy, radiotherapy, and chemotherapy) showed no prognostic significance. Tumor fragmentation/morcellation and higher mitotic count resulted independent prognostic variables at multivariate analysis. Conclusions: This data supports the avoidance of any type of morcellation if LG-ESS is suspected preoperatively. Higher mitotic count and, possibly, tumor size, advanced FIGO stage, necrosis, and LVSI could be exploited to tailor the adjuvant therapy, but these results need to be confirmed in larger prospective studies.

Indexed as

endometrial stroma sarcomamorcellationsurvivaltreatmentuterine sarcoma

Identifiers

PMID35847944
PMCPMC9280128
OpenAlexW4283719016

What OpenQuestion holds

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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.