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Myasthenia GravisMay 2023

What the MycarinG Trial Found — Rozanolixizumab for Myasthenia Gravis

MycarinG tested rozanolixizumab, a weekly under-the-skin antibody infusion that lowers harmful antibodies, in 200 adults with generalized myasthenia gravis. Both doses produced a meaningful reduction in daily-life symptoms.

What the trial was testing

The MycarinG enrolled 200 patients with myasthenia gravis. The study was sponsored by UCB Biopharma and tracked outcomes across the full group of patients who matched the trial's eligibility profile.

It was a large trial designed to confirm whether the treatment works well enough for wider use. Trials at this stage are designed to produce evidence regulators and physicians can act on — not just observations to follow up later.

What the results showed

2.6-point greater drop in daily-life symptoms vs. inactive comparison.

The Lancet Neurology · 2023 · NCT03971422

These findings — that in daily-life symptoms on rozanolixizumab vs. inactive comparison over 6 weeks — were published in the The Lancet Neurology and represent the headline result of the study.

Researchers tracked outcomes across 200 patients enrolled in the trial. The result was consistent enough across the group that the team felt confident reporting it.

What this means for patients

For patients with myasthenia gravis, this result changes the calculus on what to ask their care team about. Whether it changes day-to-day care depends on factors like disease subtype, prior treatments, and where the patient is in their care journey.

What you can do now

Rozanolixizumab (Rystiggo) is FDA-approved and available now for generalized myasthenia gravis in adults with the AChR or MuSK antibody. It is given as a weekly under-the-skin infusion in cycles. Ask a neurologist about access — most cases that meet criteria are covered.

Eligibility for the treatments mentioned above depends on specific test results and clinical history. Bring this summary, the trial name, and your most recent labs or pathology report to your next visit.

Open myasthenia gravis trials

RecruitingObservational study

A Prospective Cohort Study of Myasthenia Gravis in China

The goal of this prospective cohort study is to investigate long-term therapeutic strategies for myasthenia gravis (MG) and identify potential biomarkers. The main questions it aims to answer are: 1. Whether low-dose oral steroids may lead to a reduction in the recurrence rate among patients with MG. 2. To identify potential biomarkers that can predict disease progression and prognosis. This study recruits well-controlled patients with MG. Based on patient preferences and considerations such as coexisting conditions (e.g., uncontrolled hypertension, diabetes, severe osteoporosis, obesity), the participants will be non-randomly divided into two groups: a maintenance steroid therapy group and a withdrawal group (withdraw all immunosuppresants). Subsequently, these groups of patients will undergo long-term follow-up assessments.

Beijing, Beijing Municipality, China
RecruitingObservational study

FLOWER: Following Longitudinal Outcomes With Epidemiology for Rare Diseases

FLOWER is a completely virtual, nationwide, real-world observational study to collect, annotate, standardize, and report clinical data for rare diseases. Patients participate in the study by electronic consent (eConsent) and sign a medical records release to permit data collection. Medical records are accessed from institutions directly via eFax or paper fax, online from patient electronic medical record (EMR) portals, direct from DNA/RNA sequencing and molecular profiling vendors, and via electronic health information exchanges. Patients and their treating physicians may also optionally provide medical records. Medical records are received in or converted to electronic/digitized formats (CCDA, FHIR, PDF), sorted by medical record type (clinic visit, in-patient hospital, out-patient clinic, infusion and out-patient pharmacies, etc.) and made machine-readable to support data annotation, full text searches, and natural language processing (NLP) algorithms to further facilitate feature identification.

Los Altos, California, United States