Autoimmune Glial Fibrillary Acidic Protein Astrocytopathy: To Identify Its Diagnosis, Management and Prognosis (GFAP-AID) Registry: Study Protocol for an Ambispective, Multicenter Registry in China

• Published in: Neuropsychiatric disease and treatment Vol. 18; pp. 1099 - 1105
• Main Authors: Yang, Jie, Jiang, Lihong, Yao, Haiyan, Huang, Li, Long, Youming
• Format: Journal Article
• Language: English
• Published: New Zealand Dove Medical Press Limited 01.06.2022; Dove; Dove Medical Press
• Subjects: antibody; astrocytopathy; Autoimmune diseases; Care and treatment; Central nervous system diseases; Diagnosis; glial fibrillary acidic protein; Medical research; Medicine, Experimental; prognosis; Registries (in medicine); Study Protocol; China; astrocytopathy; diagnosis; antibody; glial fibrillary acidic protein; prognosis
• ISSN: 1176-6328; 1178-2021; 1178-2021
• DOI: 10.2147/ndt.s364246

Currently, no uniform diagnostic criteria or treatment consensus is available for patients with autoimmune glial fibrillary acidic protein astrocytopathy (GFAP-A). The aim of this registry is to develop diagnostic and therapeutic recommendations for GFAP-A based on clinical features, neuroimaging, neuroelectrophysiological examinations, laboratory tests, specific antibody tests, immunotherapy, and prognosis. This multicenter, nationwide ambispective registry includes twenty-seven hospitals in China. From January 2020 to December 2022, consecutive hospitalized patients with symptoms of meningoencephalitis, as well as GFAP-IgG positive cerebrospinal fluid (CSF) or serum will be invited to join this study. It is conservatively estimated that over 300 patients will join the study. Data on demographics, medical history, treatment details and imaging features will be collected after discharge. Outcome events of interest will include modified Rankin Scale (mRS) and Expanded Disability Status Scale (EDSS), readmission with relapsed meningoencephalomyelitis, all-cause mortality, and mortality resulting from complications of GFAP-A. The follow-up will be conducted at six months and twelve months after discharge. Univariate and multivariate regression models will be used to calculate identify independent predictors of outcomes. Stratification analysis will be used to test whether results are similar between key subgroups. This study will describe the risk factors, disease course, response to immunotherapy, and long-term prognosis of a large cohort of GFAP-A patients. By using these data, a relatively rational recommendation process for the diagnosis and treatment of GFAP-A will be developed. ChiCTR2000041291.