Identifying Small Clinical Characteristics to Facilitate Early Myasthenia Gravis Diagnosis: Judith Thompson, PharmD, MPH, CPHQ

WATCH TIME: 3 minutes

"It’s difficult with the fluctuating symptoms of MG for non-specialists to recognize and diagnose accurately and timely."

The diagnosis of myasthenia gravis (MG) can be difficult, as it can mimic other diseases, including certain infectious diseases, systemic diseases, central nervous system diseases, and muscular dystrophies, among others. At the 2024 American Association of Neuromuscular & Electrodiagnostic Medicine (AANEM) meeting, held October 15-18, in Savannah, Georgia, a study focused on evaluating whether social determinants of health (SDoH) are associated with misdiagnosis in MG.

Led by Judith Thompson, PharmD, MPH, CPHQ, the retrospective observational cohort study was conducted using insurance claims from 3873 adults diagnosed with MG between September 2018 and August 2020. Possible misdiagnosis, defined by select conditions with 1 or more claims prior to index and no claims following index, was found in 425 (11%) of individuals. The most common condition was stroke (5.5%), followed by chronic obstructive pulmonary disease (4.5%), chronic fatigue (2.2%), Graves’ disease (1.5%), multiple sclerosis (1.4%), and Guillain-Barré syndrome (1.1%). In addition, 6 high-risk SDoH measures had an elevated unadjusted odds ratio for misdiagnosis, with the highest OR for social connectedness (1.40) and housing risk (1.24).

Thompson, rare disease population health strategy lead at UCB, sat down with NeurologyLive^® at the conference to discuss the data, including the difficulty of diagnosing MG. She spoke on how the variability in symptoms, combined with a lack of specific MG awareness, particularly among primary care providers and other non-specialist fields such as emergency medicine, ophthalmology, pulmonology, and psychology, contributes significantly to delayed diagnosis. In addition, she stressed the need to enhance foundational MG knowledge during medical education so that future providers across specialties can recognize MG’s hallmark symptoms early and make appropriate referrals.

Click here for more AANEM 2024 coverage.

REFERENCE
1. Thompson J, Zhang B, Liberman JN, Darer J. Evidence of misdiagnosis in administrative claims data for individuals with myasthenia gravis. Presented at: 2024 AANEM Annual Meeting; October 15-18; Savannah, GA. ABSTRACT 288