Evidence map›Paper›PMID 36336975›Full record

ArticleCancer2023

Prognostic modeling of cutaneous melanoma stage I patients using cancer registry data identifies subsets with very-low melanoma mortality.

Megan M Eguchi, David E Elder, Raymond L Barnhill, Michael W Piepkorn, Stevan R Knezevich, Joann G Elmore, Kathleen F Kerr

Open access · greenAbstract read
In one paragraph

Article in Cancer, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
2.0field-weighted citation impact, top 11% 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

9 citing papers in PubMed, 21 citations in OpenAlex.

  1. Article
  2. Article
  3. Cutaneous melanoma in Kazakhstan: epidemiological trends and economic burden on the healthcare system.Archives of public health = Archives belges de sante publique · 2026
    Article
  4. Melanoma Diagnosis in the Mihm Era-And Beyond.Journal of cutaneous pathology · 2026
    Review
  5. Article
  6. Review
  7. Review
  8. Article
  9. Review
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 5 institutions in 2 countries.

Megan M EguchiDepartment of Medicine, University of California, Los Angeles, David Geffen School of Medicine, Los Angeles, California, USA.ORCID 0000-0002-0485-077X
David E ElderDepartment of Pathology and Laboratory Medicine, Hospital of the University of Pennsylvania, Philadelphia, Pennsylvania, USA.
Raymond L BarnhillDepartment of Translational Research, Institut Curie, Paris, France.
Michael W PiepkornDivision of Dermatology, Department of Medicine, University of Washington School of Medicine, Seattle, Washington, USA.
Stevan R KnezevichPathology Associates, Clovis, California, USA.
Joann G ElmoreDepartment of Medicine, University of California, Los Angeles, David Geffen School of Medicine, Los Angeles, California, USA.ORCID 0000-0002-7311-6835
Kathleen F KerrDepartment of Biostatistics, University of Washington, Seattle, Washington, USA.ORCID 0000-0002-6438-9583
University of California, Los Angeles · USUniversity of Washington · USClovis Oncology (United States) · USHospital of the University of Pennsylvania · USUniversité Paris Cité · FR

Funding

Reducing Errors in the Diagnosis of Melanoma and Melanocytic LesionsR01CA201376 · NCI · UNIVERSITY OF WASHINGTON · PI ELMORE, JOANN G, KERR, KATHLEEN F. · 2016 to 2020
$3.2M
NCI NIH HHS R01 CA201376
6 · The paper itself

Abstract

backgroundEvidence exists that escalating melanoma incidence is due in part to overdiagnosis, the diagnosis of lesions that will not lead to symptoms or death. The authors aimed to characterize subsets of melanoma patients with very-low risk of death that may be contributing to overdiagnosis.

methodsMelanoma patients diagnosed in 2010 and 2011 with stage I lesions ≤1.0 mm thick and negative clinical lymph nodes from the Surveillance, Epidemiology, and End Results database were selected. Classification and regression tree and logistic regression models were developed and validated to identify patients with very-low risk of death from melanoma within 7 years. Logistic models were also used to identify patients at higher risk of death among this group of stage I patients.

resultsCompared to an overall 7-year mortality from melanoma of 2.5% in these patients, a subset comprising 25% had a risk below 1%. Younger age at diagnosis and Clark level II were associated with low risk of death in all models. Breslow thickness below 0.4 mm, absence of mitogenicity, absence of ulceration, and female sex were also associated with lower mortality. A small subset of high-risk patients with >20% risk of death was also identified.

conclusionPatients with very-low risk of dying from melanoma within 7 years of diagnosis were identified. Such cases warrant further study and consensus discussion to develop classification criteria, with the potential to be categorized using an alternative term such as "melanocytic neoplasms of low malignant potential." LAY SUMMARY: Although melanoma is the most serious skin cancer, most melanoma patients have high chances of survival. There is evidence that some lesions diagnosed as melanoma would never have caused symptoms or death, a phenomenon known as overdiagnosis. In this study, we used cancer registry data to identify a subset of early-stage melanoma patients with almost no melanoma deaths. Using two statistical approaches, we identified patients with <1% risk of dying from melanoma in 7 years. Such patients tended to be younger with minimal invasion into the skin. We also identified a very small patient subset with higher mortality risk.

Indexed as

MelanomaSkin NeoplasmsHumansPrognosisRegistriesRoutinely Collected Health Datamelanomaoverdiagnosisprognosisregression analysisSEER program

Identifiers

PMID36336975
PMCPMC10367581
OpenAlexW4308369842

What OpenQuestion holds

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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.