The Ratio of Typical Clubbing in Pulled-Out Hairs as a Useful Marker in Predicting the Course of Alopecia Areata

ANNALS OF DERMATOLOGY(2024)

Cited 0|Views9
No score
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 [Delta SALT]). 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 Delta SALT (p<0.05). Strong activity group (pulled-out hair >= 10, n=33) showed difference in clinical course (maximal score, Delta SALT) 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.
More
Translated text
Key words
Alopecia,Alopecia areata,Hair loss,Microscopy,Risk assessment
AI Read Science
Must-Reading Tree
Example
Generate MRT to find the research sequence of this paper
Chat Paper
Summary is being generated by the instructions you defined