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Predictive model for immunotherapy of alopecia areata with diphencyprone.
Arch Dermatol. 2001 Aug; 137(8):1063-8.AD

Abstract

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.

Authors+Show Affiliations

Division of Dermatology, Vancouver General Hospital, University of British Columbia, 835 W 10th Ave, Vancouver, British Columbia, Canada V5Z 4E8.No affiliation info availableNo affiliation info availableNo affiliation info available

Pub Type(s)

Journal Article
Research Support, Non-U.S. Gov't

Language

eng

PubMed ID

11493099

Citation

Wiseman, M C., et al. "Predictive Model for Immunotherapy of Alopecia Areata With Diphencyprone." Archives of Dermatology, vol. 137, no. 8, 2001, pp. 1063-8.
Wiseman MC, Shapiro J, MacDonald N, et al. Predictive model for immunotherapy of alopecia areata with diphencyprone. Arch Dermatol. 2001;137(8):1063-8.
Wiseman, M. C., Shapiro, J., MacDonald, N., & Lui, H. (2001). Predictive model for immunotherapy of alopecia areata with diphencyprone. Archives of Dermatology, 137(8), 1063-8.
Wiseman MC, et al. Predictive Model for Immunotherapy of Alopecia Areata With Diphencyprone. Arch Dermatol. 2001;137(8):1063-8. PubMed PMID: 11493099.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - Predictive model for immunotherapy of alopecia areata with diphencyprone. AU - Wiseman,M C, AU - Shapiro,J, AU - MacDonald,N, AU - Lui,H, PY - 2001/10/6/pubmed PY - 2001/10/12/medline PY - 2001/10/6/entrez SP - 1063 EP - 8 JF - Archives of dermatology JO - Arch Dermatol VL - 137 IS - 8 N2 - 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. SN - 0003-987X UR - https://www.unboundmedicine.com/medline/citation/11493099/Predictive_model_for_immunotherapy_of_alopecia_areata_with_diphencyprone_ L2 - https://jamanetwork.com/journals/jamadermatology/fullarticle/vol/137/pg/1063 DB - PRIME DP - Unbound Medicine ER -