A Retrospective Cohort Study and Clinical Classification System of Acne Keloidalis Nuchae.

J Clin Aesthet Dermatol

Dr. Umar is with the Department of Medicine at the University of California at Los Angeles in Los Angeles, California; the Division of Dermatology, Harbor-UCLA Medical Center in Torrance, California; and the Dr. U Hair and Skin Clinic in Manhattan Beach, California.

Published: April 2021

Although many treatments are available for acne keloidalis nuchae (AKN), no systematic classification scheme exists to evaluate the outcomes of these treatments. This study aimed to propose an AKN classification scheme. A retrospective data analysis of several parameters, including lesion distribution, lesion type, and scalp disease association, was conducted in 108 men diagnosed with AKN between July 2009 and November 2020 in an outpatient dermatology setting. A three-tier classification system was developed as follows: Tier 1, lesion distribution relative to an area demarcated by two horizontal lines on the occipital prominences and tips of the mastoid processes and lesion sagittal width defined using Classes I through IV; Tier 2, lesion types including papules/nodules (discrete/merged), plaques, and tumorous masses; and Tier 3, the presence or absence of folliculitis decalvans (FD) or dissecting cellulitis (DC). All patients were non-white men, with most being of African (58%) or Hispanic (37%) descent. The most prevalent Tier 1 AKN presentation was Class II (58%). The mean sagittal width for Classes I through III were 2.4cm (I), 4.5cm (II), and 8.0cm (III), with Class IV characterized by widespread scalp disease. Plaques were most common in Tier 2-type lesions. FD or DC was found in seven percent of the study participants. Patients of African descent had a greater tendency to develop tumorous masses (p<0.02). The retrospective study design and possible selection bias. We proposed an AKN classification scheme as a tool for objectively describing AKN lesions and evaluating treatment outcomes.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8142833PMC

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