Comorbidities, Healthcare Utilization, and Costs Associated With Alopecia Totalis and Alopecia Universalis in the United States

Main Article Content

Carolyn Maskin
Arash Mostaghimi
Aster Meche
Markqayne Ray
Kavita Gandhi
David Gruben
Vanja Sikirica


Alopecia areata, Alopecia totalis, Alopecia universalis, cost, healthcare burden, US claims database, healthcare resource utilization


Background: Alopecia areata (AA) is an autoimmune disease characterized by nonscarring hair loss. Extensive forms of AA include alopecia totalis (AT; complete scalp hair loss) or alopecia universalis (AU; complete scalp, face, and body hair loss). Limited information exists about the cost and healthcare burden of AT and AU.

Methods: Using a large US administrative healthcare claims database, two mutually exclusive patient cohorts were identified: AA cohort: ≥1 diagnosis of AA; AT/AU cohort: ≥1 diagnosis of AT/AU between January 1 and December 31, 2017. Baseline characteristics measured at first AA diagnosis (index date) and all-cause healthcare utilization and costs identified in the 1-year post-index period were compared between AT/AU and non-AT/AU AA cohorts.

Results: 14,340 patients with AA were identified, including 1,224 patients with AT or AU. Compared with patients with non-AT/AU AA (n=13,116), patients with AT/AU were older (mean age 43.1 vs 40.6 years, P<0.0001) and more were female (68.1% vs 62.9%, P<0.0001). More patients with AT/AU had baseline comorbidities (atopic disease [28.3% vs 24.1%], anemia [10.4% vs 7.4%], autoimmune disorders [9.6% vs 5.5%]; P≤0.001 for all). Post-index patients with AT/AU had higher per person per policy year healthcare resource utilization and costs (P≤0.001) and total adjusted annual mean costs (P<0.05). Over 50% more patients with AT/AU received immunosuppressive agents than patients with non-AT/AU AA.

Conclusion: Patients with AT/AU had higher rates of comorbidities and greater healthcare resource utilization medical costs than patients with non-AT/AU AA, suggesting that improved insight into the patterns of specific comorbid conditions is needed.


1. Alkhalifah A, Alsantali A, Wang E, McElwee KJ, Shapiro J. Alopecia areata update: part I. Clinical picture, histopathology, and pathogenesis. J Am Acad Dermatol 2010a;62(2):177-88.

2. Alkhalifah A, Alsantali A, Wang E, McElwee KJ, Shapiro J. Alopecia areata update: part II. Treatment. J Am Acad Dermatol 2010b;62(2):191-202.

3. IQVIA. US Claims - IQVIA PharMetrics Plus,; [accessed January 11, 2021].

4. Lai VWY, Chen G, Gin D, Sinclair R. Systemic treatments for alopecia areata: A systematic review. Australas J Dermatol 2019;60(1):e1-e13.

5. Lavian J, Li SJ, Lee EY, Bordone LA, Polubriaginof FCG, Christiano AM, et al. Validation of Case Identification for Alopecia Areata Using International Classification of Diseases Coding. Int J Trichology 2020;12(5):234-7.

6. Lee S, Lee H, Lee CH, Lee WS. Comorbidities in alopecia areata: a systematic review and meta-analysis. J Am Acad Dermatol 2019;80(2):466-77 e16.

7. MacDonald Hull SP, Wood ML, Hutchinson PE, Sladden M, Messenger AG, British Association of Dermatologists. Guidelines for the management of alopecia areata. Br J Dermatol 2003;149(4):692-9.

8. Mostaghimi A, Xenakis J, Meche A, Smith TW, Gruben D, Sikirica V. Economic burden and healthcare resource use of alopecia areata in an insured population in the USA. Dermatol Ther (Heidelb). 2022 Apr;12(4):1027-1040.

9. Quan H, Li B, Couris CM, Fushimi K, Graham P, Hider P, et al. Updating and validating the Charlson comorbidity index and score for risk adjustment in hospital discharge abstracts using data from 6 countries. Am J Epidemiol 2011;173(6):676-82.

10. Safavi KH, Muller SA, Suman VJ, Moshell AN, Melton LJ, 3rd. Incidence of alopecia areata in Olmsted County, Minnesota, 1975 through 1989. Mayo Clin Proc 1995;70(7):628-33.

11. Villasante Fricke AC, Miteva M. Epidemiology and burden of alopecia areata: a systematic review. Clin Cosmet Investig Dermatol 2015;8:397-403.