Evidence map›Paper›PMID 36765848›Full record

ReviewCancers2023

Lymph Node Involvement in Recurrent Serous Borderline Ovarian Tumors: Current Evidence, Controversies, and a Review of the Literature.

Laureline Wetterwald, Apostolos Sarivalasis, Aikaterini Liapi, Patrice Mathevet, Chahin Achtari

Abstract readReview
In one paragraph

Review in Cancers, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Article
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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

5 authors.

Laureline WetterwaldOncology Department, Lausanne University Hospital, University of Lausanne, 1011 Lausanne, Switzerland.ORCID 0000-0001-7935-743X
Apostolos SarivalasisOncology Department, Lausanne University Hospital, University of Lausanne, 1011 Lausanne, Switzerland.ORCID 0000-0002-3153-297X
Aikaterini LiapiOncology Department, Lausanne University Hospital, University of Lausanne, 1011 Lausanne, Switzerland.
Patrice MathevetDepartment of Obstetrics and Gynecology, Lausanne University Hospital, University of Lausanne, 1011 Lausanne, Switzerland.
Chahin AchtariDepartment of Obstetrics and Gynecology, Lausanne University Hospital, University of Lausanne, 1011 Lausanne, Switzerland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Borderline ovarian tumors (BOTs) account for 10-20% of epithelial ovarian neoplasms. They are characterized by their lack of destructive stromal invasion. In comparison to invasive ovarian cancers, BOTs occur in younger patients and have better outcome. Serous borderline ovarian tumor (SBOT) represents the most common subtype of BOT. Complete surgical staging is the current standard management but fertility-sparing surgery is an option for SBOT patients who are at reproductive age. While most cases of SBOTs have an indolent course with favorable prognosis, late recurrence and malignant transformation can occur, usually in the form of low-grade serous carcinoma (LGSC). Thus, assessment of the recurrence risk is essential for the management of those patients. SBOTs can be associated with lymph node involvement (LNI) in up to 30% of patients who undergo lymph node dissection at diagnosis, and whether LNI affects prognosis is controversial. The present review suggests that recurrent SBOTs with LNI have poorer oncological outcomes and highlights the biases due to the scarcity of reports in the literature. Preventing SBOTs from recurring and becoming invasive overtime and a more profound understanding of the underlying mechanisms at play are necessary.

Indexed as

borderline ovarian tumorhormonal treatmentlow malignant potential ovarian tumorlymph nodeprognosisrecurrenceserous borderline ovarian tumor

Identifiers

PMID36765848
PMCPMC9913328

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Registered trials

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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.