Developing an Alopecia Areata Disease Activity Index (ALADIN)

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DESCRIPTION (provided by applicant): The goal of this application is to develop a new outcome instrument, the Alopecia Areata Disease Activity Index (ALADIN) that has the potential for use in the determination of clinically relevant endpoints for Alopecia Areata (AA). AA is one of the most common autoimmune diseases, with a lifetime risk of approximately 2%, affecting 5.3 million individuals in the United States alone, including males and females of all ages and ethnic groups. AA represents the second most common form of human hair loss, and causes significant disfigurement and psychological distress to affected individuals. AA carries one of the highest burdens among any skin diseases, particularly among children and adolescents whose self-image is so closely linked to their appearance. Integration of patient reported outcomes (PROs) as disease endpoints is needed in the determination of drug efficacy and in the comparison of outcomes across drug trials for AA. Because of the high psychological burden associated with AA, it is essential that the patient's perspective be considered as a core outcome in the development of new treatments for AA. For this reason, PROs need to be developed that can capture the emotional and psychological impact of the disease. To our knowledge, the emotional and psychological impacts of AA on patients' health related quality of life have not yet been included in any completed RCT studies. In order to incorporate an AA specific PRO into the assessment of disease progression/status, there needs to exist a reliable and valid instrument that measures a uniform set of outcomes in clinical trials for AA. In the context of our ongoing clinical trials in AA at Columbia University Medical Center, we have the unique opportunity to develop and deploy the Alopecia Areata Disease Activity Index (ALADIN) into clinical trials for AA, where we will be able to assess its psychometric properties in an AA population. ALADIN will be constructed by integrating a patient reported health-related quality of life instrument; physician reported hair loss assessments, clinical measures, a genotype risk score, and gene expression analysis and serum biomarkers. ALADIN will be modeled after the well-accepted and extensively validated Crohn's disease activity index (CDAI) which similarly contains patient reported measures; physician reported measures, and biological data. We will apply innovative statistical approaches in developing ALADIN, to create a classifier that quantitatively distinguishes disease state, prognosis and therapeutic response. The final instrument will be a single index that can be used to monitor disease activity in AA, and will be easily adaptable to multiple clinical trial sites and allow comparison across trials.