Evidence map›Paper›PMID 37667131›Full record

ArticleAmerican journal of clinical dermatology2024

Relationship of Histopathologic Parameters and Gene Expression Profiling in Malignant Melanoma.

Alexis G Strahan, Ivan Švagelj, Drazen Jukic

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Article in American journal of clinical dermatology, 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
–field-weighted citation impact, top 55% 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, 0 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

3 authors at 1 institution in 1 country.

Alexis G StrahanMercer University School of Medicine, Savannah, GA, USA.ORCID http://orcid.org/0000-0003-4763-0950
Ivan ŠvageljDepartment of Pathology and Cytology, General County Hospital Vinkovci, Vinkovci, Croatia.
Drazen JukicDepartment of Pathology and Clinical Sciences Education, Mercer University School of Medicine, 900 Mohawk St suite E, Savannah, GA, 31419, USA. jukic_dm@mercer.edu.
Mercer University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundHistopathologic characteristics (HC) are a mainstay in melanoma prognosis; gene expression profiling (GEP) has emerged as a potential additional independent value.

objectiveTo elucidate HC predictive of groups obtained via GEP of malignant melanoma.

methodsA retrospective study analyzing HC of 265 melanomas submitted for GEP over the course of 8 years. GEP was conducted as a part of regular clinicopathologic workup through Castle Biosciences Decision Dx

resultsOf the 265 cases, the major HC found to have an association with reported gene expression profiles were melanoma histology subtype, depth of invasion, and presence of ulcer. LIMITATIONS: This study is limited by its cross-sectional nature. Causation and long-term related outcomes of the use of GEP versus American Joint Committee on Cancer histopathologic staging cannot be ascertained by this design.

conclusionsAn association, but no definitive prediction, exists between histopathologic categories of depth of invasion, melanoma subtype, and presence or absence of ulcer and gene expression profiles. GEP adds valuable data to the evaluation of malignant melanomas that cannot be definitively predicted by conventional models. The findings add to needed groundwork for comparison of traditional markers and molecular genotyping and begins to build a robust predictive model for better outcomes in patients with malignant melanoma.

Indexed as

MelanomaSkin NeoplasmsCross-Sectional StudiesGene Expression ProfilingHumansPrognosisRetrospective StudiesUlcer

Identifiers

PMID37667131
OpenAlexW4386415547

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Registered trials

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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.