Evidence map›Paper›PMID 39220642›Full record

ArticleFrontiers in oncology2024

Case report: Malignant epithelioid angiosarcoma in a Chinese female patient.

Xiaohong Li, Lu Chen, Rong Ye, Chunyan Wu, Wenlei Zhuo

Abstract readCase Reports
In one paragraph

Article in Frontiers in oncology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

5 authors.

Xiaohong LiDepartment of Oncology, Second Affiliated Hospital of Army Military Medical University, Chongqing, China.
Lu ChenDepartment of Oncology, Second Affiliated Hospital of Army Military Medical University, Chongqing, China.
Rong YeDepartment of Oncology, Second Affiliated Hospital of Army Military Medical University, Chongqing, China.
Chunyan WuDepartment of Oncology, Second Affiliated Hospital of Army Military Medical University, Chongqing, China.
Wenlei ZhuoDepartment of Oncology, Second Affiliated Hospital of Army Military Medical University, Chongqing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Perivascular epithelioid cell tumors (PEComas) are mesenchymal tumors that exhibit characteristic epithelioid or spindle cell morphology and typically grow around blood vessels. These tumors are characterized by the expression of melanocytic and smooth muscle markers, such as HMB-45, Melan-A, and smooth muscle actin, indicating a dual differentiation phenotype. PEComas are extremely rare diseases, and patients typically have a very poor prognosis. Here, we report a case of malignant cutaneous PEComa with pulmonary metastasis in a Chinese female and review relevant literature. The patient underwent surgical resection of a soft tissue tumor in the left upper arm under general anesthesia, and the subsequent pathological findings suggested a tumor with perivascular epithelioid cell differentiation (PEComa). The patient received adjuvant chemotherapy and radiotherapy after surgical resection, along with monitoring through computed tomography (CT) scans. Three months later, pulmonary metastasis was detected, but both the cutaneous PEComa in the left upper limb and the pulmonary metastatic lesions were stably controlled under active management and treatment. This is a rare case worth reporting and studying, and therefore, we conducted a long-term follow-up, and we hope to provide help for the clinical treatment of PEComa.

Indexed as

dermatologydermatopathologyimmunohistochemistryPEComaskin tumor

Identifiers

PMID39220642
PMCPMC11361990

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.