Clinical Features, Treatment, and Prognostic Factors in Neuronal Surface Antibody-Mediated Severe Autoimmune Encephalitis

Autor: Baojie Wang, Chunjuan Wang, Jianli Feng, Maolin Hao, Shougang Guo
Jazyk: angličtina
Rok vydání: 2022
Předmět:
Zdroj: Frontiers in Immunology, Vol 13 (2022)
Druh dokumentu: article
ISSN: 1664-3224
DOI: 10.3389/fimmu.2022.890656
Popis: ObjectiveThis study aimed to determine the clinical characteristics and evaluate the efficacy of immunotherapy and the long-term prognosis of severe autoimmune encephalitis (AE) in China.MethodsClinical features, laboratory or radiological findings, and treatment outcomes of 60 severe patients with AE from January 1, 2014, to December 31, 2020, were collected. Continuous variables were compared using the t-test and the nonparametric Mann–Whitney U test, as appropriate. Univariate and multivariable logistic regression analyses were performed to assess the correlations between factors, treatment responses, and prognosis of severe AE.ResultsThe median age of symptom onset was 35 years. Tumors were identified in 23.3% of patients, and 36/60 (60%) patients responded to first-line immunotherapy. Second-line immunotherapy was implemented in 26/60 (43.3%) patients. A significant clinical benefit was observed in 19/26 (73.1%) patients treated with lower dosage rituximab; seven patients were still refractory and received bortezomib as an add-on therapy. During the last follow-up, 48/60 (80%) patients achieved good outcomes (mRS, 0–2), and 10 died. Seventeen patients experienced relapses. A high CD19+ B-cell count (OR, 1.197; 95% CI [1.043–1.496]; p = 0.041) and a lower neutrophil-to-lymphocyte ratio (NLR; OR, 0.686; 95% CI [0.472–0.884]; p = 0.015) predict the response to first-line treatment and good prognosis, respectively.ConclusionsPatients with severe AE were in critical condition at baseline but could be salvaged after effective rescue immunotherapy. A lower dosage of rituximab could be an optimal option for severe AE. CD19+ B-cell count and NLR may provide prognostic information for predicting treatment response and outcome of severe AE.
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