open access publication

Article, 2024

The Epidemiology of Hospital-Treated Alopecia Areata in Denmark, 1995–2016

Dermatology and Therapy, ISSN 2190-9172, 2193-8210, Volume 14, 4, Pages 993-1006, 10.1007/s13555-024-01145-9

Contributors

Sørensen, Sissel Brandt Toft [1] [2] George, Prethibha [3] Jagun, Oladayo [3] Wolk, Robert M [3] Napatalung, Lynne [3] [4] Zwillich, Samuel H [3] Iversen, Lars Lønsmann 0000-0003-1816-4508 [5] [6] Ehrenstein, Vera 0000-0002-3415-3254 (Corresponding author) [1] [2]

Affiliations

  1. [1] Aarhus University
  2. [NORA names: AU Aarhus University; University; Denmark; Europe, EU; Nordic; OECD];
  3. [2] Aarhus University Hospital
  4. [NORA names: Central Denmark Region; Hospital; Denmark; Europe, EU; Nordic; OECD];
  5. [3] Pfizer (United States)
  6. [NORA names: United States; America, North; OECD];
  7. [4] Icahn School of Medicine at Mount Sinai
  8. [NORA names: United States; America, North; OECD];
  9. [5] Department of Dermatology, Aarhus University Hospital and Aarhus University, Aarhus N, Denmark
  10. [NORA names: Denmark; Europe, EU; Nordic; OECD];

Abstract

IntroductionAlopecia areata (AA) is an autoimmune skin disease presenting as nonscarring hair loss. Information on the epidemiology of AA, especially the occurrence of AA and its subtypes within the general population, is scarce. The study aimed to estimate the incidence rates and prevalence of hospital-treated AA and its subtypes in Denmark and to examine the demographic and clinical characteristics of patients with AA, including comorbidities and use of prescription medications.MethodsThis was a cohort study based on data from administrative and health registers in Denmark in 1995–2016. The study included individuals who were (1) registered with a hospital inpatient or hospital-based outpatient clinic diagnosis of AA between 1995 and 2016 in the Danish National Patient Registry covering encounters at all Danish hospitals, (2) alive and resided in Denmark anytime between 1995 and 2016, (3) aged ≥ 12 years, and (4) resided uninterrupted in Denmark during the 12 months before the first AA diagnosis during the study period.ResultsDuring the study period, 2778 individuals with an incident hospital-based diagnosis of AA were identified; 63.1% were female and 28.7% of the patients were aged ≥ 50 years. Over the study period, the overall incidence rate for any hospital-treated AA per 100,000 person-years was 2.62 (95% confidence interval [CI], 2.53–2.72), and the overall prevalence in 2016 was 71.7 (95% CI 69.4–74.1) per 100,000 persons. Both incidence rate and prevalence increased over time. Prevalence of most hospital-treated comorbidities or history of medication use was below 10% and was similar in the alopecia totalis (AT)/alopecia universalis (AU) and non-AT/AU subtypes of AA.ConclusionThis cohort study reported incidence rates and prevalence over time and characteristics of individuals with hospital-treated AA in Denmark, which are in agreement with those previously reported in this population.

Keywords

AA diagnosis, Au, ConclusionThis, ConclusionThis cohort study, Danish, Danish hospitals, Denmark, IntroductionAlopecia areata, MethodsThis, alopecia, alopecia areata, alopecia totalis, areata, autoimmune skin disease, characteristics, characteristics of individuals, characteristics of patients, clinical characteristics, clinical characteristics of patients, clinical diagnosis of AA, cohort, cohort study, comorbidities, data, diagnosis, diagnosis of AA, disease, encounters, epidemiology, epidemiology of AA, general population, hair loss, health, health registers, history, history of medication use, hospital, incidence, incidence rate, individuals, information, loss, medication, medication use, months, nonscarring hair loss, occurrence, occurrence of AA, overall incidence rate, patients, period, persons, population, prescription, prescription medications, prevalence, rate, register, skin diseases, study, study period, subtype of AA, subtypes, time, totalis, use, years

Funders

  • Pfizer (United States)

Data Provider: Digital Science