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UK Study on Clinical and Genetic Features of Giant Cell Arteritis and Polymyalgia Rheumatica in Adults Over 50
Led by University of Leeds · Updated on 2025-03-30
4500
Participants Needed
76
Research Sites
N/A
Total Duration
AI-Summary
What this Trial Is About
Researchers are conducting a multi-centre observational study to better understand giant cell arteritis GCA and polymyalgia rheumatica PMR, conditions mainly affecting people over 50 years old. The study aims to identify genetic factors that influence susceptibility to these diseases to provide new insights into how they develop. It includes both retrospective participants with confirmed diagnoses and prospective participants suspected of having these conditions, with some patients also enrolled in a registry monitoring tocilizumab treatment for relapsing or refractory GCA. The study collects detailed clinical, imaging, and molecular data, including genetic and proteomic analyses, from participants to characterize disease subtypes and impacts. Researchers also assess quality of life through patient-reported outcomes and track long-term prognosis by linking to health records. The study explores environmental factors and co-existing conditions to improve diagnosis, prognosis, and monitoring of disease activity, especially for patients receiving synthetic or biological disease-modifying anti-rheumatic drugs. Participants provide information during baseline assessments, including blood and urine samples for analysis, and complete questionnaires about their symptoms and quality of life. Follow-up occurs through health record review over an average of one year to evaluate diagnosis and disease outcomes. The primary measure is genetic susceptibility, with secondary outcomes focusing on disease characteristics, life impact, diagnosis, and disease activity. The study is sponsored by the University of Leeds and started in 2005, continuing through 2028.
CONDITIONS
Brief Title
Clinical and Immunogenetic Characterization of Giant Cell Arteritis (GCA) and Polymyalgia Rheumatica (PMR)
Research Team
L
Louise Sorensen
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