The Ratio of Typical Clubbing in Pulled-Out Hairs as a Useful Marker in Predicting the Course of Alopecia Areata
- Author:
So Hee PARK
1
;
Hyojin KIM
;
Jong Uk KIM
;
Seong Min HONG
;
Sang Woo AHN
Author Information
- Publication Type:Original Article
- From:Annals of Dermatology 2024;36(1):29-34
- CountryRepublic of Korea
- Language:English
-
Abstract:
Background:Analysis of hair microscopic morphology is a simple and less invasive method to differentiate alopecia areata (AA) from other alopecic diseases. However, there is limited information on the distribution of the microscopic characteristics.
Objective:This study evaluated the microscopic morphological characteristics of pulled-out hair and their correlation with disease course in AA.
Methods:Morphological characteristics of pulled-out hair were classified into 5 categories:the presence of typical clubbing, surface undulation, tapering, breakage, and depigmentation in proximal hair shaft. Clinical course of AA was investigated through assessment of Severity of Alopecia Tool (SALT) score (initial score, maximal score and difference of them [ΔSALT]).
Results:Among 1,272 pulled-out hairs (n=179) obtained at initial visit, depigmentation (59.5%) was the most common, followed by loss of typical clubbing (57.2%) and surface undulation (55.2%). The percentage of loss of typical clubbing and proximal tapering was significantly higher in severe type of AA, younger age of onset and shorter disease duration. The ratio of typical clubbing (<50% vs. ≥50%) was associated with difference in maximal score and ΔSALT (p<0.05). Strong activity group (pulled-out hair ≥10, n=33) showed difference in clinical course (maximal score, ΔSALT) as well as distribution of microscopic features (loss of typical clubbing) compared with those in non-strong activity group. The ratio of typical clubbing significantly increased at follow-up than initially in strong activity group (p<0.05).
Conclusion:Microscopic hair morphology, especially loss of typical clubbing and proximal tapering, could be useful tool to predict the course of AA.
