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Patient journey and treatment pattern in myasthenia gravis: real-world data from the Brazilian public health system
Renata Andrade1, Wilson Marques Junior2, Luiza Vasconcelos3
1Hospital Metropolitano Oeste Pelópidas Silveira, Real Hospital Português, Divisão de Doenças Raras, Recife PE, Brazil.
Abstract:
Myasthenia gravis (MG) is a rare neurological disease and the most common autoimmune disorder, characterized by muscle weakness. In Brazil, there is limited data on these patients within the Brazilian public healthcare system (SUS, from Sistema Único de Saúde, in Portuguese).To assess patients with MG in the Brazilian public healthcare system to understand their characteristics, patient journey, and treatment patterns.A retrospective observational study using real-world data from SUS to analyze patients with MG from January 2010 to December 2023. Data were extracted from the DATASUS, focusing on the Outpatient Procedure (SIA) and Hospital Admissions (SIH) information systems. Probabilistic record linkage compiled longitudinal patient data, assessing epidemiology, demographics, clinical characteristics, and treatment patterns, including medications, doses, and lines of treatment (LOT).A total of 13,476 patients with MG were identified. Admissions in healthcare units increased over the years, with 30.4% experiencing exacerbations and 9% crises. The mean age was 45.6 years, with a majority being female (65.4%) and white (53.4%). The case-fatality rate rose from 0.76% in 2011 to 1.90% in 2023. Treatment patterns showed frequent transitions between LOT, indicating constant instability and inadequate symptom control, with azathioprine and pyridostigmine being the most used medications. Some patients started treatment with intravenous immunoglobulin (IVIg), used in combination with other medications, and continued it continuously.The study highlights the increasing burden of MG on SUS, emphasizing the challenges of disease management and the need for continuous advancements in diagnostic and therapeutic strategies to improve patient outcomes.
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