An increasing number of clinical trials are enrolling patients with myasthenia gravis (MG). A lack of standardization in the performance of outcome measures leads to confusion among site research teams and is a source of variability in clinical trial data. MGNet, the NIH-supported Rare Disease Clinical Research Network for MG, views standardization of MG outcome measures as a critical need. To address this issue, a group of experts summarized key outcome measures used in MG clinical trials and a symposium was convened to address issues contributing to outcome measure variability. Consensus recommendations resulted in changes to outcome measure instructions and, in some cases, modifications to specific instruments. Recommended changes were posted for public commentary before finalization. Changes to the MG-Activities of Daily Living, MG–Quality of Life–15r, and MG–Impairment Index were limited to adding details to the administration instructions. Recommendations for proper positioning of participants and how to score items that could not be performed because of non-MG reasons were provided for the MG Composite. The Quantitative MG (QMG) score required the most attention, and changes were made both to the instructions and the performance of certain items resulting in the QMG-Revised. The Postintervention Status was believed to have a limited role in clinical trials, except for the concept of minimal manifestation status. As a next step, training materials and revised source documents, which will be freely available to study teams, will be created and posted on the MGNet website. Further studies are needed to validate changes made to the QMG-Revised.

Evidence from preclinical studies suggests that IL-6 signalling has the potential to modulate immunopathogenic mechanisms upstream of autoantibody effector mechanisms in patients with generalised myasthenia gravis. We aimed to assess the safety and efficacy of satralizumab, a humanised monoclonal antibody targeting the IL-6 receptor, in patients with generalised myasthenia gravis. LUMINESCE was a randomised, double-blind, placebo-controlled, multicentre, phase 3 study at 105 sites, including hospitals and clinics, globally. Eligible patients were aged 12 years and older, with seropositive generalised myasthenia gravis (autoantibodies to the acetylcholine receptor [AChR-IgG], muscle-specific kinase [MuSK-IgG], or low-density lipoprotein receptor-related protein 4 [LRP4-IgG]), a Myasthenia Gravis Foundation of America severity class II-IV, a Myasthenia Gravis Activities of Daily Living (MG-ADL) score of 5 or more (non-ocular contribution >50%), and use of stable background therapy. Patients were randomly assigned (1:1) with a permuted-block randomisation method to receive subcutaneous satralizumab (120 mg for bodyweight ≤100 kg; 180 mg for bodyweight >100 kg) or placebo at weeks 0, 2, 4, and every 4 weeks thereafter until week 24. Randomisation was stratified according to background therapy, autoantibody type, and geographical region. The primary efficacy endpoint was mean change from baseline in total MG-ADL score at week 24 in the modified intention-to-treat population (all randomised AChR-IgG-positive patients who completed at least one post-baseline MG-ADL assessment). Safety was assessed in all randomly assigned patients who received at least one dose of study drug. The open-label extension was terminated early because of the sponsor's decision to halt further development of satralizumab for treatment of generalised myasthenia gravis. This trial is registered with ClinicalTrials.gov, NCT04963270, and EudraCT, 2020-004436-21. Between Oct 19, 2021, and Aug 15, 2023, 188 patients were randomly assigned to satralizumab (n=96) or placebo (n=92). 166 AChR-IgG-positive patients (80 in the placebo group and 86 in the satralizumab group) were included in the modified intention-to-treat population. At week 24, statistically significant yet small improvements in MG-ADL score were observed with satralizumab versus placebo (adjusted mean -3·59, 95% CI -4·15 to -3·02 vs -2·57, -3·25 to -1·88; difference -1·02, -1·88 to -0·16; p=0·0120). The proportion of patients with at least one adverse event during the double-blind period was slightly higher in patients treated with satralizumab compared with patients treated with placebo (86 [90%] patients vs 67 [73%] patients). Three serious adverse events (in three [3%] patients) were reported in the satralizumab group (pneumonia, pyelonephritis, and increased lipase) compared with nine (in six [7%] patients) serious adverse events in the placebo group (COVID-19, COVID-19 pneumonia, bacterial urinary tract infection, chest pain, back pain, and rosacea). There were no deaths or adverse events of special interest. Satralizumab was well tolerated and resulted in small improvements in patient-reported and clinician-reported outcomes compared with placebo at week 24 in patients with AChR-IgG-positive generalised myasthenia gravis. Further research analysing the immunological underpinnings of the observed clinical response to IL-6 signalling inhibition in patients with generalised myasthenia gravis and exploring the role of IL-6 in autoantibody-mediated diseases is warranted. F Hoffmann La Roche.

Background: Amyloidosis, a rare multisystem condition, often requires complex, multidisciplinary care. Its low prevalence underscores the importance of efforts to ensure the availability of high-quality patient education materials for better outcomes. ChatGPT (OpenAI) is a large language model powered by artificial intelligence that offers a potential avenue for disseminating accurate, reliable, and accessible educational resources for both patients and providers. Its user-friendly interface, engaging conversational responses, and the capability for users to ask follow-up questions make it a promising future tool in delivering accurate and tailored information to patients. Objective: We performed a multidisciplinary assessment of the accuracy, reproducibility, and readability of ChatGPT in answering questions related to amyloidosis. Methods: In total, 98 amyloidosis questions related to cardiology, gastroenterology, and neurology were curated from medical societies, institutions, and amyloidosis Facebook support groups and inputted into ChatGPT-3.5 and ChatGPT-4. Cardiology- and gastroenterology-related responses were independently graded by a board-certified cardiologist and gastroenterologist, respectively, who specialize in amyloidosis. These 2 reviewers (RG and DCK) also graded general questions for which disagreements were resolved with discussion. Neurology-related responses were graded by a board-certified neurologist (AAH) who specializes in amyloidosis. Reviewers used the following grading scale: (1) comprehensive, (2) correct but inadequate, (3) some correct and some incorrect, and (4) completely incorrect. Questions were stratified by categories for further analysis. Reproducibility was assessed by inputting each question twice into each model. The readability of ChatGPT-4 responses was also evaluated using the Textstat library in Python (Python Software Foundation) and the Textstat readability package in R software (R Foundation for Statistical Computing). Results: ChatGPT-4 (n=98) provided 93 (95%) responses with accurate information, and 82 (84%) were comprehensive. ChatGPT-3.5 (n=83) provided 74 (89%) responses with accurate information, and 66 (79%) were comprehensive. When examined by question category, ChatGTP-4 and ChatGPT-3.5 provided 53 (95%) and 48 (86%) comprehensive responses, respectively, to “general questions” (n=56). When examined by subject, ChatGPT-4 and ChatGPT-3.5 performed best in response to cardiology questions (n=12) with both models producing 10 (83%) comprehensive responses. For gastroenterology (n=15), ChatGPT-4 received comprehensive grades for 9 (60%) responses, and ChatGPT-3.5 provided 8 (53%) responses. Overall, 96 of 98 (98%) responses for ChatGPT-4 and 73 of 83 (88%) for ChatGPT-3.5 were reproducible. The readability of ChatGPT-4’s responses ranged from 10th to beyond graduate US grade levels with an average of 15.5 (SD 1.9). Conclusions: Large language models are a promising tool for accurate and reliable health information for patients living with amyloidosis. However, ChatGPT’s responses exceeded the American Medical Association’s recommended fifth- to sixth-grade reading level. Future studies focusing on improving response accuracy and readability are warranted. Prior to widespread implementation, the technology’s limitations and ethical implications must be further explored to ensure patient safety and equitable implementation.

Myasthenia gravis (MG) is a rare neuromuscular disorder where IgG antibodies damage the communication between nerves and muscles, leading to muscle weakness that can be severe and have a significant impact on patients' lives. MG exacerbations include myasthenic crisis with respiratory failure, the most serious manifestation of MG. Recent studies have found MG prevalence increasing, especially in older patients. This study examined trends in hospital admissions and in-hospital mortality for adult patients with MG and readmissions and postdischarge mortality in older (65 years or older) adults with MG. Data from the Nationwide Inpatient Sample (NIS), an all-payer national database of hospital discharges, were used to characterize trends in hospitalizations and in-hospital mortality related to MG exacerbations and MG crisis among adult patients aged 18 years or older. The Medicare Limited Data Set, a deidentified, longitudinal research database with demographic, enrollment, and claims data was used to assess hospitalizations, length of stay (LOS), readmissions, and 30-day postdischarge mortality among fee-for-service Medicare beneficiaries aged 65 years or older. The study period was 2010-2019. Multinomial logit models and Poisson regression were used to test for significance of trends. Hospitalization rates for 19,715 unique adult patients and 56,822 admissions increased from 2010 to 2019 at an average annualized rate of 4.9% (MG noncrisis: 4.4%; MG crisis: 6.8%; all p < 0.001). Readmission rates were approximately 20% in each study year for both crisis and noncrisis hospitalizations; the in-hospital mortality rate averaged 1.8%. Among patients aged 65 years or older, annualized increases in hospitalizations were estimated at 5.2%, 4.2%, and 7.7% for all, noncrisis, and crisis hospitalizations, respectively (all p < 0.001). The average LOS was stable over the study period, ranging from 11.3 to 13.1 days, but was consistently longer for MG crisis admissions. Mortality among patients aged 65 years or older was higher compared with that in all patients, averaging 5.0% across each of the study years. Increasing hospitalization rates suggest a growing burden associated with MG, especially among older adults. While readmission and mortality rates have remained stable, the increasing hospitalization rates indicate that the raw numbers of readmissions-and deaths-are also increasing. Mortality rates are considerably higher in older patients hospitalized with MG.

Introduction Accurate measurement of myasthenia gravis (MG) severity is required for appropriate clinical monitoring of patients with MG and assessment of the benefit of new treatments in clinical trials. Our objective was to explore how MG severity can be measured and to determine how the newly developed MG Symptoms Patient-Reported Outcome (PRO) instrument complements the available measures of MG severity. Methods The conceptual coverage of the Quantitative MG (QMG), MG Composite (MGC), MG-Activities of Daily Living (MG-ADL), and MG Symptoms PRO was scrutinized against core symptoms of MG: muscle weakness in three muscle groups (ocular, bulbar, and respiratory), muscle weakness fatigability, and physical fatigue. Post hoc analyses of the MG0002 study, a Phase 2a clinical trial of rozanolixizumab in adults with moderate to severe generalized MG, included correlation and Rasch model analyses. Results The qualitative appraisal highlighted that only the MG Symptoms PRO captured physical fatigue. Data from 541 assessments (43 unique patients) were used for the analyses. Correlations ranged between 0.56 and 0.74 for the MG-ADL, QMG, MGC, and MG Symptoms PRO Muscle Weakness Fatigability score, and between 0.20 and 0.71 for the MG Symptoms PRO scores focusing on independent muscle groups. Analyses with the Rasch model estimated a meaningful continuum of severity of MG, including all items, except ocular muscles, from the four instruments. The QMG and MG Symptoms PRO had the broadest coverage of the MG severity continuum. Muscle fatigability and physical fatigue were more characteristic of low severity while bulbar weakness indicated more severe MG. Conclusion The severity of MG can be reflected in a meaningful continuum underpinned by the MG-specific outcome measures. Only ocular muscle manifestations were shown to reflect a possibly different facet of MG severity. With its modular nature and comprehensive content, the MG Symptoms PRO provides complementary information to the outcome measures widely used in MG. Trial Registration ClinicalTrials.gov identifier: NCT03052751.