Defining early mycosis fungoides
Open accessAbstract
This editorial review summarizes the results of 5 meetings sponsored by the International Society for Cutaneous Lymphoma at which the clinicopathologic and ancillary features of early mycosis fungoides were critically examined. Based on this analysis, an algorithm was developed for the diagnosis of early mycosis fungoides involving a holistic integration of clinical, histopathologic, immunopathologic, and molecular biological characteristics. A novel aspect of this algorithm is that it relies on multiple types of criteria rather than just one, for example, histopathology. Before its finalization, the proposed diagnostic algorithm will require validation and possibly further refinement at multiple centers during the next several years. It is anticipated that a more standardized approach to the diagnosis of early mycosis fungoides will have a beneficial impact on the epidemiology, prognostication, treatment, and analysis of clinical trials pertaining to this most common type of cutaneous lymphoma.
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Cutaneous TCR clonality is confirmed in only 64% of early-stage patients.
“Cutaneous TCR clonality is confirmed in only 64% of earlystage patients”
From Histological triage of early-stage mycosis fungoides using a weakly supervised deep learning-based model: a multicentre, external validation, and clinical utility study (2026) · cites this paper as [3]
The section ‘Early diagnosis of MF: the role of ancillary techniques’ discusses detecting T-cell clonality in early mycosis fungoides and reports that PCR-method sensitivity varies from 60% to 100%. It does not report that clonality was confirmed in 64% of early-stage patients; the range of test sensitivities does not establish that patient-level figure. (LLM, conf=0.85)
Experimental — accuracy not yet measuredInterobserver variation in early-stage MF diagnosis is reported in approximately 20% of cases, even among specialists.
“with interobserver variation reported in approximately 20% of cases, even among specialists 3 .”
From Histological triage of early-stage mycosis fungoides using a weakly supervised deep learning-based model: a multicentre, external validation, and clinical utility study (2026) · cites this paper as [3]
The section “Early Diagnosis of MF: The Role of Histopathology” reports high interobserver variability and only fair-to-moderate agreement on diagnostic criteria. Its 21.51% figure is a misclassification error rate for a combination of histologic criteria, not the percentage of cases with interobserver variation among specialists. (LLM, conf=0.87)
Experimental — accuracy not yet measuredDetection of aberrant pan-T-cell marker loss carries a sensitivity as low as 10%.
“the detection of aberrant pan-T-cell marker loss carries a sensitivity as low as 10%”
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References 97 · Cited by 550
Research works printed but not linked: 10
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- Authors
- Pimpinelli, N., Olsen, E. A., Santucci, M., Vonderheid, E., Haeffner, A. C., Stevens, S., Burg, G., Cerroni, L., Dreno, B., Glusac, E., Guitart, J., Heald, P. W., Kempf, W., Knobler, R., Lessin, S., Sander, C., Smoller, B. S., Telang, G., Whittaker, S., Iwatsuki, K., Obitz, E., Takigawa, M., Turner, M. L., & Wood, G. S.
- Affiliations
- University of Florence (IT)
- Duke University (US)
- Johns Hopkins University (US)
- University of Zurich (CH)
- Amgen (United States) (US)
- University of Graz (AT)
- Yale University (US)
- Northwestern University (US)
- Medical University of Vienna (AT)
- Fox Chase Cancer Center (US)
- Ludwig-Maximilians-Universität München (DE)
- Brown University (US)
- St Thomas' Hospital (GB)
- Okayama University (JP)
- Aarhus University (DK)
- Hamamatsu University (JP)
- National Cancer Institute (US)
- University of Wisconsin–Madison (US)
- Corresponding author
- Wood, Gary S.
- ORCID
- Venue
- Journal of the American Academy of Dermatology
- Publisher
- Elsevier BV
- Published
- 2005-12
- Volume
- 53
- Issue
- 6
- Pages
- 1053-1063
- ISSN
- 0190-9622 (ISSN-L)
- OpenAlex
- W2015828565
- Cited by
- 550
- References
- 97
- Citations by year
- 2026: 19 · 2025: 26 · 2024: 27 · 2023: 36 · 2022: 18 · 2021: 34 · 2020: 42 · 2019: 39 · 2018: 34 · 2017: 20 · 2016: 27 · 2015: 31 · 2014: 27 · 2013: 26 · 2012: 25
- Type
- journal article
- Language
- en
- Open access
- green
- hdl.handle.net
- Licence
- Locations
- Journal of the American Academy of Dermatology (publishedVersion)
- PubMed (publishedVersion)
- Florence Research (University of Florence) (submittedVersion, other-oa)
- Research Portal (King's College London) (submittedVersion)
- Funders
- U.S. Department of Veterans Affairs
- National Institutes of Health (5k24ar002136-06)
- National Institute of Arthritis and Musculoskeletal and Skin Diseases (AR 02136)
- Topics
- Health Sciences › Medicine › Dermatology › Cutaneous lymphoproliferative disorders research
- Health Sciences › Medicine › Pathology and Forensic Medicine › Lymphoma Diagnosis and Treatment
- Health Sciences › Medicine › Dermatology › Cancer and Skin Lesions
- Keywords
- cutaneous T-cell lymphoma, diagnostic algorithm, clinicopathological features, immunopathology, molecular features, histopathology, diagnostic standardization
- MeSH terms
- Algorithms, Humans, Mycosis Fungoides, Skin Neoplasms, Early Diagnosis
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