Evidence map›Paper›PMID 29340997›Full record

ReviewEndocrine pathology2018

Immunohistochemical Biomarkers of Mesenchymal Neoplasms in Endocrine Organs: Diagnostic Pitfalls and Recent Discoveries.

Yin P Hung, Jason L Hornick

Abstract readReview
PubMed Publisher
In one paragraph

Review in Endocrine pathology, 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
0.7field-weighted citation impact, top 30% 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, 10 citations in OpenAlex.

  1. Review
  2. Review
  3. Article
  4. Adrenal cancer: relevance of different grading systems and subtypes.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2021
    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

2 authors at 1 institution in 1 country.

Yin P HungDepartment of Pathology, Brigham and Women's Hospital and Harvard Medical School, 75 Francis Street, Boston, MA, 02115, USA.
Jason L HornickDepartment of Pathology, Brigham and Women's Hospital and Harvard Medical School, 75 Francis Street, Boston, MA, 02115, USA. jhornick@bwh.harvard.edu.
Harvard University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Mesenchymal neoplasms rarely present in or adjacent to endocrine organs. In this context, the recognition of these rare tumor types can be challenging, with significant potential for misdiagnosis as sarcomatoid carcinomas (i.e., anaplastic thyroid carcinoma and sarcomatoid adrenal cortical carcinoma) or neuroendocrine carcinomas, depending upon the dominant histologic patterns. In this review, we address potential pitfalls in diagnosing selected mesenchymal neoplasms arising within or near endocrine organs, including dedifferentiated liposarcoma, synovial sarcoma, angiosarcoma, PEComa, proximal-type epithelioid sarcoma, Ewing sarcoma, and neuroblastoma. For each of these tumor types, we review clinical and pathologic features, histologic clues to distinguish them from endocrine neoplasms, and recently developed immunohistochemical markers that can be particularly useful for establishing the correct diagnosis.

Indexed as

Biomarkers, TumorDiagnosis, DifferentialEndocrine System DiseasesHumansImmunohistochemistryNeuroblastomaPathology, ClinicalPerivascular Epithelioid Cell NeoplasmsSarcomaBiomarkers, TumorAngiosarcomaDedifferentiated liposarcomaEpithelioid sarcomaEwing sarcomaImmunohistochemistryNeuroblastomaPEComaSarcomaSynovial sarcoma

Identifiers

PMID29340997
OpenAlexW2782789276

What OpenQuestion holds

Textmetadata
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.