Faculty Bibliography

Alopecia areata (AA) is an autoimmune disease characterized by nonscarring hair loss. As a clinically heterogeneous disease, various classification systems have evolved for defining its severity. In this high-level review of the literature, we discuss the traditional classification systems for AA severity and their strengths and weaknesses. Most recent classifications have focused on the extent of scalp hair loss as a defining feature, but additional clinical aspects of the disease, including location, pattern, and duration of hair loss as well as impact on the patient's quality of life, are also relevant. These various components have typically been used unidimensionally to classify patients. We propose a multidimensional framework to define AA severity that incorporates multiple patient- and illness-related domains. Using such a framework, dermatologists may better assess the severity of the disease for the individual patient beyond the extent of hair loss.

INTRODUCTION/BACKGROUND:Alopecia areata (AA) is an autoimmune disease characterized by hair loss. Patients with AA experience a range of social and emotional impacts, and the lack of effective treatments and multiple affected locations can deepen the burden of illness. The objective of the current study was to assess health-related quality of life (HRQL) among patients with AA, and to evaluate the relationship between patient-reported AA severity, HRQL and treatment patterns. METHODS:A web survey was completed by participants recruited through the National Alopecia Areata Foundation. The survey included questions on disease characteristics, burden and impact (evaluated by the Skindex-16 for AA and items on work/school and sexual relationships), healthcare utilization and treatment experience. Analyses were conducted for the overall sample and by key subgroups, including AA severity and disease duration. RESULTS:A total of 1327 participants with AA completed the survey. The mean age was 39.7 [standard deviation (SD) 12.3] years and 58.4% were female. On average, participants had experienced signs and symptoms of AA for 11.5 years (SD 12.5) and were diagnosed by a healthcare provider (HCP) 10.5 (SD 12.2) years ago. Participants reported a range of severity of current scalp hair loss, including 0% (2.6%), 1-20% (39.8%), 21-49% (26.2%), 50-94% (10.2%) and 95-100% (21.3%). Participants reporting 95-100% of scalp hair missing were less likely to be currently seeing an HCP and to currently be on treatments for AA. There was a non-linear relationship between HRQL and current AA severity. Participants with 1-20% to 50-94% of current scalp hair missing reported higher symptom, functioning and emotional impacts due to AA than participants with 0% missing scalp hair and/or 95-100% missing scalp hair. Similar findings were observed for current eyebrow and eyelash severity, except for emotional impacts. CONCLUSION/CONCLUSIONS:Severity of AA plays an important role in understanding the burden of illness and healthcare patterns of people living with AA.

BACKGROUND:The current classification for alopecia areata (AA) does not provide a consistent assessment of disease severity. OBJECTIVE:To develop an AA severity scale based on expert experience. METHODS:A modified Delphi process was utilized. An advisory group of 22 AA clinical experts from the United States was formed to develop this AA scale. Representatives from the pharmaceutical industry provided feedback during its development. RESULTS:Survey responses were used to draft severity criteria, aspiring to develop a simple scale that may be easily applied in clinical practice. A consensus vote was held to determine the final AA severity statement, with all AA experts agreeing to adopt the proposed scale. LIMITATIONS/CONCLUSIONS:The scale is a static assessment intended to be used in clinical practice and not clinical trials. CONCLUSION/CONCLUSIONS:The final AA disease severity scale, anchored in the extent of hair loss, captures key features commonly used by AA experts in clinical practice. This scale will better aid clinicians in appropriately assessing severity in patients with this common disease.

BACKGROUND:Minoxidil is a widely used over-the-counter topical treatment for hair loss. The response rate for topical minoxidil is relatively low. Minoxidil is a pro-drug, converted to its active form, minoxidil sulfate, by SULT1A1 enzymes located in the scalp. Recently, a novel topical formula that increases the activity of SULT1A1 in hair follicles was reported. AIMS/OBJECTIVE:To evaluate any benefit of applying the SULT1A1 enzyme booster prior to daily 5% minoxidil treatment. METHODS:Male androgenic alopecia patients were recruited to a randomized blinded placebo-controlled study. Patients were randomized to receive 5% topical minoxidil plus the novel formula or minoxidil plus a sham adjuvant. Patient's hair growth was monitored using global photography over 60 days. RESULTS:Twenty-four males with androgenic alopecia (Norwood scale average 4.4, range 2-6) were randomized and completed the trial: 12 in the active arm and 12 in placebo. 75% of the subjects who used the SULT1A1 adjuvant with their daily minoxidil treatments for 60 days regrew hair versus 33% of those using the placebo adjuvant (p = 0.023). CONCLUSIONS:In a small cohort of androgenetic alopecia men, adding the SULT1A1 adjuvant to their daily minoxidil treatment regimen improved hair regrowth.

BACKGROUND:Although many hair disorders can be readily diagnosed based on their clinical appearance, their progression and response to treatment are often difficult to monitor, particularly in quantitative terms. We introduce an innovative technique utilizing a smartphone and computerized image analysis to expeditiously and automatically measure and compute hair density and diameter in patients in real time. METHODS:A smartphone equipped with a dermatoscope lens wirelessly transmits trichoscopy images to a computer for image processing. A black-and-white binary mask image representing hair and skin is produced, and the hairs are thinned into single-pixel-thick fiber skeletons. Further analysis based on these fibers allows morphometric characteristics such as hair shaft number and diameters to be computed rapidly. The hair-bearing scalps of fifty participants were imaged to assess the precision of our automated smartphone-based device in comparison with a specialized trichometry device for hair shaft density and diameter measurement. The precision and operation time of our technique relative to manual trichometry, which is commonly used by hair disorder specialists, is determined. RESULTS:An equivalence test, based on two 1-sided t tests, demonstrates statistical equivalence in hair density and diameter values between this automated technique and manual trichometry within a 20% margin. On average, this technique actively required 24 seconds of the clinician's time whereas manual trichometry necessitated 9.2 minutes. CONCLUSION/CONCLUSIONS:Automated smartphone-based trichometry is a rapid, precise, and clinically feasible technique which can significantly facilitate the assessment and monitoring of hair loss. Its use could be easily integrated into clinical practice to improve standard trichoscopy.