Evidence map›Paper›PMID 29881291›Full record

ArticleOncoTargets and therapy2018

A large and aggressive fibromatosis in the axilla: a rare case report and review of the literature.

Mingyue Duan, Hua Xing, Keren Wang, Chunbo Niu, Chengwei Jiang, Lijuan Zhang, Shereen Ezzat, Le Zhang

Open access · goldAbstract readCase Reports
In one paragraph

Article in OncoTargets and therapy, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
1.0field-weighted citation impact, top 24% 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

5 citing papers in PubMed, 7 citations in OpenAlex.

  1. Review
  2. Article
  3. Article
  4. Article
  5. 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 at 2 institutions in 3 countries.

Mingyue DuanDepartment of Breast Surgery, China-Japan Union Hospital, Jilin University, Changchun, Jilin, People's Republic of China.
Hua XingDepartment of Breast Surgery, China-Japan Union Hospital, Jilin University, Changchun, Jilin, People's Republic of China.
Keren WangDepartment of Breast Surgery, China-Japan Union Hospital, Jilin University, Changchun, Jilin, People's Republic of China.
Chunbo NiuDepartment of Pathology, China-Japan Union Hospital, Jilin University, Changchun, Jilin, People's Republic of China.
Chengwei JiangDepartment of Pathology, China-Japan Union Hospital, Jilin University, Changchun, Jilin, People's Republic of China.
Lijuan ZhangDepartment of Breast Surgery, China-Japan Union Hospital, Jilin University, Changchun, Jilin, People's Republic of China.
Shereen EzzatOntario Cancer Institute and The Endocrine Oncology Site Group, Princess Margaret Hospital, University Health Network, Toronto, ON, Canada.
Le ZhangDepartment of Breast Surgery, China-Japan Union Hospital, Jilin University, Changchun, Jilin, People's Republic of China.
Union Hospital · CNUniversity Health Network · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Aggressive fibromatosis (AF) is a rare benign tumor, which occurs in the deep part of bone and muscle fibrous tissue. Clinical and pathological features can be challenging for definitive diagnosis. Here, we report a rare case of a large AF in the axilla. Interestingly, 18 F-fluorodeoxyglucose-positron emission tomography/computed tomography showed significant increase in standard uptake value. Surgical resection yielded a spindle cell tumor likely of fibromatosis origin which was positive for β-catenin expression.

Indexed as

18 F-fluorodeoxyglucoseaggressive fibromatosisaxilladesmoid-type fibromatosisPET/CTβ-catenin

Identifiers

PMID29881291
PMCPMC5983020
OpenAlexW2804093461

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.