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Based on 32 histological attributes, a hypothesis\u2010free prediction model was developed and validated on an independent patient's cohort.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>A reduced set of two histological features (presence of atypical lymphocytes in either epidermis or dermis) was trained. In an independent validation cohort, this model showed high predictive power (95% sensitivity and 100% specificity) to differentiate MF from AD and robustness against inter\u2010individual investigator differences.<\/jats:p><\/jats:sec><jats:sec><jats:title>Limitations.<\/jats:title><jats:p>The study investigated a limited number of cases and the classifier is based on subjectively evaluated histological criteria.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusion<\/jats:title><jats:p>Aiming at distinguishing early MF from AD, the proposed binary classifier performed well in an independent cohort and across observers. Combining this histological classifier with immunohistochemical and\/or molecular techniques (such as clonality analysis or molecular classifiers) could further promote differentiation of early MF and AD.<\/jats:p><\/jats:sec>","DOI":"10.1111\/jdv.19325","type":"journal-article","created":{"date-parts":[[2023,7,9]],"date-time":"2023-07-09T09:18:42Z","timestamp":1688894322000},"page":"2284-2292","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":15,"title":["Histology\u2010based classifier to distinguish early mycosis fungoides from atopic dermatitis"],"prefix":"10.1111","volume":"37","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3252-1700","authenticated-orcid":false,"given":"Sophie","family":"Roenneberg","sequence":"first","affiliation":[{"name":"Department of Dermatology and Allergy Technical University of Munich  Munich 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