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The skin check of the future: improving early detection of melanoma while avoiding overdiagnosis

  • Susan M. Swetter
  • , Sancy A. Leachman
  • , Raymond L. Barnhill
  • , Laura K. Ferris
  • , Allan C. Halpern
  • , Tammie Ferringer
  • , Jennifer A. Stein
  • , Clara Curiel-Lewandrowski
  • , Justin M. Ko
  • , Veronica Rotemberg
  • , Rebecca I. Hartman
  • , Robert A. Swerlick

Research output: Contribution to journal › Review article › peer-review

Abstract

The past four decades have witnessed a marked increase in melanoma diagnoses, particularly early-stage disease, without proportional decreases in melanoma mortality - a pattern seen across multiple cancer types, termed "overdiagnosis". Overdiagnosis refers to diagnosis of disease that will never cause symptoms or death during a patient’s expected lifetime and requires both the existence of biologically indolent lesions (as are most severely dysplastic nevi, melanomas in situ, and minimally invasive melanomas) and activities leading to their detection (namely, screening). In October 2025, the American Dermatological Association convened leading experts at its annual meeting in Laguna Niguel, California for an unprecedented session titled “The Skin Check of the Future,” bringing together dermatologists, dermatopathologists, and epidemiologists dedicated to melanoma control and technology innovation. The national Melanoma Prevention Working Group contributed additional presentations on skin imaging and artificial intelligence for melanoma early detection and their potential contributions to dermatology workflow. This review synthesizes session presentations and panel discussion, organized around three interconnected themes: the screening conundrum and the critical importance of population risk stratification; the role of pathology in diagnostic uncertainty and emerging approaches to low-risk melanocytic neoplasm relabeling; and the technologies and workflow innovations that may influence future melanoma practice. While robust debate continues about the precise magnitude of overdiagnosis and its implications for individual patient care, this multi-expert synthesis provides a framework for clinicians, researchers, and policymakers to navigate the complex landscape of melanoma detection, while optimizing benefits and minimizing harms across diverse patient populations.

Original languageEnglish (US)
Article number172
JournalArchives of Dermatological Research
Volume318
Issue number1
DOIs
StatePublished - Dec 2026

Keywords

  • Artificial intelligence
  • Diagnostic uncertainty
  • Melanoma
  • Overdiagnosis
  • Risk stratification
  • Screening

ASJC Scopus subject areas

  • Dermatology

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