To describe overall sentiments towards Myasthenia Gravis (MG) and compare males and females on the most frequent themes.
MG is a rare, chronic autoantibody neuromuscular disease with profound patient burden. Data from digital conversations can provide an unprovoked view of MG disease burden and highlight areas of greatest concern to patients.
One year (8/2021 - 8/2022) of conversations focused on MG in the public domain originating from US internet protocol addresses were tagged based on self-identification in the conversations or on public profiles. Advanced search techniques together with artificial intelligence powered algorithms were used to extract and organize data by topics into a large, unstructured dataset. Sentiment analysis via natural language processing was conducted to categorize conversations as positive, negative or neutral and analyzed to derive the most frequent drivers of sentiment.
Digital conversations reveal a high degree of concern among patients with MG most specifically related to symptoms, life impact, misdiagnosis and treatments (for MG). Therapies that provide better symptom control could positively affect many aspects of patient’s lives.