OBJECTIVES: In Germany, epidemiological data for alopecia areata (AA) are scarce. We describe the epidemiology, physician speciality and comorbidities of patients with AA to better understand the disease burden.

METHODS: This observational cohort study used German health claims data from ∼4.5 million insured patients for the period 01/01/2017–31/12/2020. Two AA populations were identified and analysed using more/less strict criteria as a proxy for illness severity. Severe AA criteria: in different quarters, ≥1 main inpatient ICD-10-German Modification code (L63.0, L63.1) or ≥2 verified outpatient/secondary inpatient diagnoses; or ≥1 main inpatient code (L63.2, L63.8, L63.9) or ≥2 verified outpatient/secondary inpatient diagnoses with a relevant prescription by the diagnosing physician. Total AA criteria: ≥1 main inpatient code (L63.0, L63.1, L63.2, L63.8, L63.9) or ≥2 outpatient/secondary inpatient diagnoses in different quarters. For each study year, the prevalence and perceived incidence of AA stratified by age group (<18, ≥18 years) and sex, extrapolated to the entire population in Germany; clinician speciality visited; and predefined comorbidities of interest were analysed. Results are descriptive

RESULTS: Prevalence of AA appeared similar over 2018–2020: ∼23.3–24.6 per 100,000 patients (severe AA) and ∼95.5–101.6 per 100,000 patients (total AA). Similarly, incidence rates remained constant. Primary care physicians were the most frequently visited clinicians, then dermatologists. The frequencies of the most common predefined comorbidities of interest over the years were: mood (affective) disorders (25.6-31.7%), vasomotor and allergic rhinitis (15.0-17.2%), asthma (11.4-15.7%), other anxiety disorders (10.9-15.6%), autoimmune thyroiditis (8.8-11.1%) and atopic dermatitis (eczema) (10.8-11.2%).

CONCLUSIONS: This study contributes to understanding the substantial burden of AA in Germany, with AA frequently associated with immune, mood and anxiety disorders. Limitations include that analyses were based on health claims data, which have limited clinical information, and no confirmation that prescribed medication was for AA, adding potential for bias.