To describe sentiments, barriers, and drivers related to myasthenia gravis (MG) through comparing conversations by MG serotype

Myasthenia gravis is a rare, autoantibody disorder that affects the neuromuscular junction. Diagnostic testing in MG is for the presence of pathogenic autoantibodies targeting the acetylcholine receptor (AChR) (~85% of cases), muscle-specific receptor tyrosine kinase (MuSK) (~6%), and low-density lipoprotein receptor-related protein 4 (LRP4) (~2%).  Confirmatory diagnostic results indicate “seropositive” MG; inconclusive/undetectable results are considered “seronegative” MG (~7-10%). Given that certain subtypes can be challenging to diagnose and treat, digital conversations can provide insights into patient perceptions and concerns that may differ across subtypes.

US-based public domain patient conversations focusing on MG and posted within topical sites, message boards, social networks, and blogs from August 2022-23 were mined. Content contributors were patients self-identified by MG serostatus (seropositive, seronegative) within the conversations or on public profiles. Advanced search techniques and artificial intelligence powered algorithms were used to extract/organize data by topics into a large, unstructured dataset. Natural language processing was conducted to identify sentiments, mindsets, and drivers/barriers towards treatment.

8,764 conversations were mined from seropositive patients and 2,261 conversations from seronegative patients. All conversations among seronegative posts revealed “uncertain” and “struggling” mindsets, while 28% of seropositive posts were deemed either “pragmatic” or “indomitable”. Virtually no positive drivers of sentiment were seen for either subgroup. Negative drivers centered on “misdiagnosis” and “symptoms” more frequently in seronegative vs. seropositive posts. Seropositive patients seeking advice were more likely to focus on information about treatment options.

Conversations reveal key differences by MG serotype that indicate the burden of misdiagnosis for seronegative MG patients and the difficulty of the diagnostic journey.  This data supports some commonalities across MG serotypes and reveals key differences which can inform clinicians and decision-makers towards improving diagnosis and care.