Predictive model for immunotherapy of alopecia areata with diphencyprone.

BACKGROUND Immunotherapy with diphencyprone (diphenylcyclopropenone) is used in the treatment of alopecia areata (AA). Response rates have varied in the literature. OBJECTIVES To determine the efficacy of diphencyprone therapy for AA in the largest reported cohort of patients; to identify patient and treatment factors predictive of therapeutic success; and to develop a practical model for predicting patient response. METHODS The medical records of 148 consecutive patients treated with diphencyprone were reviewed. A clinically significant response to diphencyprone therapy was defined as a cosmetically acceptable response or greater than 75% terminal hair regrowth. Survival analyses using the Kaplan-Meier method and the Cox proportional hazards model were performed to determine significant factors predictive of regrowth and relapse. RESULTS Using a survival analysis model, the cumulative patient response at 32 months was 77.9% (95% confidence interval, 56.8%-98.9%). Variables independently associated with clinically significant regrowth were age at onset of disease and baseline extent of AA. Older age at onset of AA portended a better prognosis. A cosmetically acceptable end point was obtained in 17.4% of patients with alopecia totalis/universalis, 60.3% with 75% to 99% AA, 88.1% with 50% to 74% AA, and 100% with 25% to 49% AA. A lag of 3 months was present between initiation of therapy and development of significant hair regrowth in the first responders. Relapse after achieving significant regrowth developed in 62.6% of patients. CONCLUSIONS Response to diphencyprone treatment in AA is affected by baseline extent of AA and age at disease onset. A prolonged treatment course might be necessary. A predictive model has been developed to assist with patient prognostication and counseling.