Evidence map›Paper›PMID 25631356›Full record

ReviewSkeletal radiology2015

Focus on Merkel cell carcinoma: diagnosis and staging.

Marion Grandhaye, Pedro Gondim Teixeira, Philippe Henrot, Olivier Morel, Francois Sirveaux, Jean-Luc Verhaeghe, Alain Blum

Abstract readReview
PubMed Publisher
In one paragraph

Review in Skeletal radiology, 2015. 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
0.3field-weighted citation impact, top 38% 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

7 citing papers in PubMed, 10 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Merkel Cell Carcinoma of the Trunk: Two Case Reports and Imaging Review.Journal of the Korean Society of Radiology · 2023
    Article
  5. Review
  6. Review
  7. Computed tomography accelerates staging in patients with Merkel cell carcinoma.European archives of oto-rhino-laryngology : official journal of the European Federation of Oto-Rhino-Laryngological Societies (EUFOS) : affiliated with the German Society for Oto-Rhino-Laryngology - Head and Neck Surgery · 2018
    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

7 authors at 4 institutions in 1 country.

Marion GrandhayeImagerie Guilloz CHU de Nancy Hôpital Central, 29 Avenue de Lattre de Tassigny, 54000, Nancy, France, marion.grandhaye@gmail.com.
Pedro Gondim Teixeira
Philippe Henrot
Olivier Morel
Francois Sirveaux
Jean-Luc Verhaeghe
Alain Blum
Imagerie et Cerveau · FRInstitut de Cancérologie de Lorraine · FRCentre Chirurgical Marie Lannelongue · FRCentre Hospitalier Régional et Universitaire de Nancy · FR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Merkel cell carcinoma is a rare lymphophilic skin tumor of neuroendocrine origin with the potential for rapid progression. Small, localized lesions are diagnosed and treated clinically, but advanced tumors often undergo imaging evaluation. Due to its rarity, radiologists are unaware of evocative imaging features and usually do not consider Merkel cell carcinoma in the differential diagnosis of soft tissue tumors. Appropriate staging is important to determine appropriate treatment and has an impact on patient prognosis. Multimodality imaging is usually needed, and there is no consensus on the optimal imaging strategy. The purpose of this article is to review various aspects of Merkel cell carcinoma imaging and look in detail at how optimal multimodality staging should be carried out.

Indexed as

Carcinoma, Merkel CellHumansMagnetic Resonance ImagingMultimodal ImagingNeoplasm StagingPositron-Emission TomographySkin NeoplasmsTomography, X-Ray Computed

Identifiers

PMID25631356
OpenAlexW2080923065

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.