Development of a scoring system to predict outcomes of i.v. corticosteroid pulse therapy in rapidly progressive alopecia areata adopting digital image analysis of hair recovery

Alopecia areata (AA) is a common autoimmune disease manifesting varying degrees of hair loss. Rapidly progressive AA (RP‐AA) is a severe subtype of AA and often resistant to skin‐directed treatments. i.v. corticosteroid pulse therapy has been applied for RP‐AA; however, the treatment outcome can only become evaluable several months after the intervention, discomposing the patients. In this study, we attempted to develop a scoring system to predict treatment outcomes based on statistical correlations between newly identified predictors and the recovery rates calculated by digital image analysis. Thirty RP‐AA patients (15 men and 15 women) who underwent pulse therapy and demonstrated total hair loss during the clinical course were included. The percentages of hair regrowth (%HR) at 6 months after the treatment were quantitatively calculated by image analysis software. The correlation between %HR and clinicopathological and immunological variables were statistically assessed. The analysis identified four confirmatory contributors including female sex (P = 0.015), absence of previous AA history (P = 0.02), lower peripheral blood eosinophil count (P = 0.02) and mild to moderate cell infiltration around the hair bulb (P = 0.034), together with a potential contributor, namely absence of atopic dermatitis in their medical history (P = 0.08). The scoring system was developed by double counting confirmatory variables and single counting a potential variable. Importantly, the scores obtained by this system demonstrated significant correlation with %HR (r = 0.61, P