Evidence map›Paper›PMID 38415064›Full record

ArticleRadiology case reports2024

Metastatic sclerosing epithelioid fibrosarcoma.

Ryan C Rizk, Mohammad Yasrab, Linda C Chu, Edmund M Weisberg, Elliot K Fishman

Open access · goldAbstract readCase Reports
PubMed Full text at PMC Publisher
In one paragraph

Article in Radiology case reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.4field-weighted citation impact, top 40% 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

0 citing papers in PubMed, 1 citations in OpenAlex.

No citing paper in PubMed yet.

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 at 1 institution in 1 country.

Ryan C RizkThe Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, 601 North Caroline St, Baltimore, MD 21287 USA.
Mohammad YasrabThe Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, 601 North Caroline St, Baltimore, MD 21287 USA.
Linda C ChuThe Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, 601 North Caroline St, Baltimore, MD 21287 USA.
Edmund M WeisbergThe Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, 601 North Caroline St, Baltimore, MD 21287 USA.
Elliot K FishmanThe Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, 601 North Caroline St, Baltimore, MD 21287 USA.
Johns Hopkins University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Sclerosing epithelioid fibrosarcoma is a rare fibrosarcoma variant in which more than half of patients experience local recurrence or metastatic spread. In the current literature, there is limited and nonspecific imaging data, contributing to frequent misdiagnosis and delays in treatment intervention. Given the poor prognosis associated with this malignancy and the high probability of metastases, accurate and prompt diagnoses are critical. In this article, we report the case of a 27-year-old female diagnosed with metastatic sclerosing epithelioid fibrosarcoma following the discovery of a growing palpable mass on her right gluteus maximus muscle. We focus on the use of radiological imaging modalities in optimizing diagnosis and correlate our imaging and pathological findings.

Indexed as

Computed tomographyFibrosarcomaMagnetic resonance imagingMetastasisMisdiagnosisSclerosing epithelioid fibrosarcoma

Identifiers

PMID38415064
PMCPMC10897837
OpenAlexW4392010131

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.