Literature DB >> 29128463

Objective outcome measures: Collecting meaningful data on alopecia areata.

Elise A Olsen1, Janet Roberts2, Leonard Sperling3, Antonella Tosti4, Jerry Shapiro5, Amy McMichael6, Wilma Bergfeld7, Valerie Callender8, Paradi Mirmirani9, Ken Washenik10, David Whiting11, George Cotsarelis12, Maria Hordinsky13.   

Abstract

BACKGROUND: Although alopecia areata is a common disorder, it has no US Food and Drug Administration-approved treatment and evidence-based therapeutic data are lacking.
OBJECTIVE: To develop guidelines for the diagnosis, evaluation, assessment, response criteria, and end points for alopecia areata.
METHODS: Literature review and expert opinion of a group of dermatologists specializing in hair disorders.
RESULTS: Standardized methods of assessing and tracking hair loss and growth, including new scoring techniques, response criteria, and end points in alopecia areata are presented. LIMITATIONS: The additional time to perform the assessments is the primary limitation to use of the methodology in clinical practice.
CONCLUSION: Use of these measures will facilitate collection of standardized outcome data on therapeutic agents used in alopecia areata both in clinical practice and in clinical trials.
Copyright © 2017 American Academy of Dermatology, Inc. All rights reserved.

Entities:  

Keywords:  ALODEX score; SALT score; alopecia areata; assessment measures; outcome measures; response criteria

Mesh:

Year:  2017        PMID: 29128463     DOI: 10.1016/j.jaad.2017.10.048

Source DB:  PubMed          Journal:  J Am Acad Dermatol        ISSN: 0190-9622            Impact factor:   11.527


  5 in total

1.  Clinically Applicable Deep Learning Framework for Measurement of the Extent of Hair Loss in Patients With Alopecia Areata.

Authors:  Solam Lee; Jong Won Lee; Sung Jay Choe; Sejung Yang; Sang Baek Koh; Yeon Soon Ahn; Won-Soo Lee
Journal:  JAMA Dermatol       Date:  2020-09-01       Impact factor: 10.282

2.  Topographic Phenotypes of Alopecia Areata and Development of a Prognostic Prediction Model and Grading System: A Cluster Analysis.

Authors:  Solam Lee; Beom Jun Kim; Chung-Hyeok Lee; Won-Soo Lee
Journal:  JAMA Dermatol       Date:  2019-05-01       Impact factor: 10.282

3.  Consensus on the treatment of alopecia areata - Brazilian Society of Dermatology.

Authors:  Paulo Müller Ramos; Alessandra Anzai; Bruna Duque-Estrada; Daniel Fernandes Melo; Flavia Sternberg; Leopoldo Duailibe Nogueira Santos; Lorena Dourado Alves; Fabiane Mulinari-Brenner
Journal:  An Bras Dermatol       Date:  2020-10-08       Impact factor: 1.896

Review 4.  Platelet-Rich Plasma in Alopecia Areata-A Steroid-Free Treatment Modality: A Systematic Review and Meta-Analysis of Randomized Clinical Trials.

Authors:  Fanni Adél Meznerics; Kata Illés; Fanni Dembrovszky; Péter Fehérvári; Lajos Vince Kemény; Kata Dorottya Kovács; Norbert Miklós Wikonkál; Dezső Csupor; Péter Hegyi; András Bánvölgyi
Journal:  Biomedicines       Date:  2022-07-29

5.  The Alopecia Areata Investigator Global Assessment scale: a measure for evaluating clinically meaningful success in clinical trials.

Authors:  K W Wyrwich; H Kitchen; S Knight; N V J Aldhouse; J Macey; F P Nunes; Y Dutronc; N Mesinkovska; J M Ko; B A King
Journal:  Br J Dermatol       Date:  2020-04-03       Impact factor: 9.302

  5 in total

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