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Mantegazza R, Saccà F, Antonini G, Bonifati DM, Evoli A, Habetswallner F, Liguori R, Pegoraro E, Rodolico C, Schenone A, Sgarzi M, Pappagallo G. Therapeutic challenges and unmet needs in the management of myasthenia gravis: an Italian expert opinion. Neurol Sci 2024:10.1007/s10072-024-07577-7. [PMID: 38967883 DOI: 10.1007/s10072-024-07577-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/27/2023] [Accepted: 05/03/2024] [Indexed: 07/06/2024]
Abstract
Myasthenia gravis (MG) is a rare, autoimmune, neurological disorder. Most MG patients have autoantibodies against acetylcholine receptors (AChRs). Some have autoantibodies against muscle-specific tyrosine kinase (MuSK) or lipoprotein-receptor-related protein 4 (LRP4), and some are seronegative. Standard of care, which includes anti-cholinesterase drugs, thymectomy, corticosteroids (CS), and off-label use of non-steroidal immunosuppressive drugs (NSISTs), is bounded by potential side effects and limited efficacy in refractory generalized MG (gMG) patients. This highlights the need for new therapeutic approaches for MG. Eculizumab, a monoclonal antibody that inhibits the complement system, has been recently approved in Italy for refractory gMG. A panel of 11 experts met to discuss unmet therapeutic needs in the acute and chronic phases of the disease, as well as the standard of care for refractory patients. Survival was emphasized as an acute phase outcome. In the chronic phase, persistent remission and early recognition of exacerbations to prevent myasthenic crisis and respiratory failure were considered crucial. Refractory patients require treatments with fast onset of action, improved tolerability, and the ability to slow disease progression and increase life expectancy. The Panel agreed that eculizumab would presumably meet the therapeutic needs of many refractory gMG patients. The panel concluded that the unmet needs of current standard of care treatments for gMG are significant. Evaluating new therapeutic options accurately is essential to find the best balance between efficacy and tolerability for each patient. Collecting real-world data on novel molecules in routine clinical practice is necessary to address unmet needs.
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Affiliation(s)
- Renato Mantegazza
- Neuroimmunology and Neuromuscular Diseases Unit, IRCCS Foundation Carlo Besta Neurological Institute, Milan, Italy.
| | - Francesco Saccà
- NSRO Department, Federico II University of Naples, Naples, Italy
| | - Giovanni Antonini
- Department of Neurosciences, Mental Health and Sensory Organs (NESMOS), Sapienza University of Rome, Rome, Italy
| | - Domenico Marco Bonifati
- Neurology Unit, Cerebro-Cardiovascular Department, Ca' Foncello Hospital Treviso, Piazzale Ospedale 1, 31100, Treviso, Italy
| | - Amelia Evoli
- Neuroscience Department, Facolta Di Medicina E Chirurgia, Università Cattolica del Sacro Cuore, Rome, Italy
- Neurology Institute, Fondazione Policlinico Universitario Agostino Gemelli IRCCS, Rome, Italy
| | | | - Rocco Liguori
- Department of Biomedical and Neuromotor Sciences (DIBINEM), University of Bologna, Bologna, Italy
- IRCCS Istituto Delle Scienze Neurologiche Di Bologna, UOC Clinica Neurologica, Bologna, Italy
| | | | - Carmelo Rodolico
- Department of Clinical and Experimental Medicine, University of Messina, Messina, Italy
| | - Angelo Schenone
- Department of Neurosciences, Rehabilitation, Ophthalmology, Genetic and Maternal and Infantile Sciences (DINOGMI), University and IRCCS San Martino Hospital, Genoa, Italy
| | - Manlio Sgarzi
- Department of Neurology, Papa Giovanni XXIII Hospital, Piazza OMS 1, 24127, Bergamo, Italy
| | - Giovanni Pappagallo
- School of Clinical Methodology, IRCCS "Sacred Heart - Don Calabria", Negrar Di Valpolicella, Italy
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Majigoudra G, Duggal AK, Chowdhury D, Koul A, Todi VK, Roshan S. Clinical Profile and Quality of Life in Myasthenia Gravis Using MGQOL15 R(Hindi): An Indian Perspective. Ann Indian Acad Neurol 2023; 26:441-446. [PMID: 37970285 PMCID: PMC10645219 DOI: 10.4103/aian.aian_945_22] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2022] [Revised: 04/16/2023] [Accepted: 06/13/2023] [Indexed: 11/17/2023] Open
Abstract
Background Myasthenia Gravis (MG) is a chronic fluctuating illness, due to the dysfunction of neuromuscular junction which is autoimmune in nature. The disease severely affects the Quality Of Life (QOL). Objective The primary objective of our study was to assess the QOL in patients with MG using Short Form 36 (SF 36) and MGQOL 15 R (Hindi translated). The secondary objective was to assess the correlation of age, sex, illness duration, clinical characteristics, severity, and treatment with the QOL in MG patients. Methodology A cross sectional study of 55 MG patients was done to analyse and evaluate the clinical status using Hybrid Myasthenia Gravis Foundation of America (HMGFA), Myasthenia gravis composite score (MGCS) and The Myasthenia Gravis Activities of Daily Living (MG - ADL). QOL was assessed by SF 36 and Hindi version of Myasthenia Gravis Quality of Life 15 - Revised (MG-QOL15R) score. Results 78.2% patients had generalized MG. The mean MGC and MG-ADL scores were 5.27 and 3.29 (95% CI: 2.24 -4.34) respectively. The mean MGQOL15R score was 6.52 ± 7.7 and the score correlated with the symptoms. The SF 36 scores were the best and the worst in the bodily pain (93.72 ± 13.52) and general health subset (61.81 ± 39.64) respectively. Except for steroid dose, there was no significant correlation between SF36 and other factors. Conclusion QOL in MG was found to be affected due to the disease. The MGQOL 15 R scores correlated with the clinical features, remission or active status, steroid use and thymectomy. No Significant association was observed between MG QOL scores and various lab parameters and repetitive nerve stimulation (RNS) test results. Higher dose of steroid was associated with poor QOL, while thymectomy was associated with better QOL scores. MGQOL15R (Hindi) is a quick and simple tool to assess the QOL in MG patients.
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Affiliation(s)
- Ganeshgouda Majigoudra
- Department of Neurology, Govind Ballabh Pant Postgraduate Institute of Medical Education and Research, New Delhi, India
| | - Ashish K. Duggal
- Department of Neurology, Govind Ballabh Pant Postgraduate Institute of Medical Education and Research, New Delhi, India
| | - Debashish Chowdhury
- Department of Neurology, Govind Ballabh Pant Postgraduate Institute of Medical Education and Research, New Delhi, India
| | - Arun Koul
- Department of Neurology, Govind Ballabh Pant Postgraduate Institute of Medical Education and Research, New Delhi, India
| | - Vineet K. Todi
- Department of Neurology, Govind Ballabh Pant Postgraduate Institute of Medical Education and Research, New Delhi, India
| | - Sujata Roshan
- Department of Neurology, Govind Ballabh Pant Postgraduate Institute of Medical Education and Research, New Delhi, India
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Sanders DB, Raja SM, Guptill JT, Hobson‐Webb LD, Juel VC, Massey JM. The
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uke myasthenia gravis clinic registry:
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escription and demographics. Muscle Nerve 2020; 63:209-216. [DOI: 10.1002/mus.27120] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2020] [Revised: 11/12/2020] [Accepted: 11/13/2020] [Indexed: 12/22/2022]
Affiliation(s)
- Donald B. Sanders
- Neuromuscular Division, Department of Neurology Duke University Medical Center Durham North Carolina USA
| | - Shruti M. Raja
- Neuromuscular Division, Department of Neurology Duke University Medical Center Durham North Carolina USA
| | - Jeffrey T. Guptill
- Neuromuscular Division, Department of Neurology Duke University Medical Center Durham North Carolina USA
| | - Lisa D. Hobson‐Webb
- Neuromuscular Division, Department of Neurology Duke University Medical Center Durham North Carolina USA
| | - Vern C. Juel
- Neuromuscular Division, Department of Neurology Duke University Medical Center Durham North Carolina USA
| | - Janice M. Massey
- Neuromuscular Division, Department of Neurology Duke University Medical Center Durham North Carolina USA
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Anil R, Kumar A, Alaparthi S, Sharma A, Nye JL, Roy B, O'Connor KC, Nowak RJ. Exploring outcomes and characteristics of myasthenia gravis: Rationale, aims and design of registry - The EXPLORE-MG registry. J Neurol Sci 2020; 414:116830. [PMID: 32388060 DOI: 10.1016/j.jns.2020.116830] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2019] [Revised: 02/22/2020] [Accepted: 04/07/2020] [Indexed: 11/19/2022]
Abstract
OBJECTIVES Though much information exists about the diagnosis, treatment, and epidemiology of myasthenia gravis (MG), a comprehensive data registry and biorepository is critical to better understand disease mechanisms, treatment outcomes, and the impact of treatment strategies. We aimed to design and implement the "Exploring Outcomes and Characteristics of Myasthenia Gravis (EXPLORE-MG) Registry" to address these knowledge gaps. METHODS A web-based, non-interventional, longitudinal, observational disease and outcomes registry was developed; incorporating NIH recommended common data elements for the study of MG. Individuals diagnosed with MG based on prespecified criteria were eligible to participate. The registry was further strengthened by a complementary biorepository. An interim analysis was completed on registry data collected through data-lock in 2017. RESULTS A total of 232 MG patients, followed at the Yale MG Clinic from 2011 to 2017, were enrolled, which included 2142 total visit entries. Of the 232 MG patients (mean age 60 years, range 17-99; female:male, 1.04:1), 165 were acetylcholine receptor antibody-positive, 20 were muscle-specific kinase antibody-positive, and 47 were seronegative. This cohort consisted of 64 patients with ocular disease, 168 patients with generalized disease, and 65 patients post-thymectomy, including 20 with thymoma-associated MG. CONCLUSIONS Identification of key clinical features that may predict treatment responsiveness or provide insight into patient outcomes is essential to improve patient care. As current research focuses on the development of patient-tailored, targeted-treatment regimens, this registry can help provide important clinical and epidemiological data from a large contemporary patient cohort with long-term follow-up. REGISTRATION ClinicalTrials.gov Identifier: NCT03792659.
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Affiliation(s)
- Rahul Anil
- Department of Neurology, Yale School of Medicine, New Haven, CT, USA
| | - Aditya Kumar
- Department of Neurology, Yale School of Medicine, New Haven, CT, USA
| | - Sneha Alaparthi
- Department of Neurology, Yale School of Medicine, New Haven, CT, USA
| | - Aditi Sharma
- Department of Neurology, Yale School of Medicine, New Haven, CT, USA
| | - Joan L Nye
- Department of Neurology, Yale School of Medicine, New Haven, CT, USA
| | - Bhaskar Roy
- Department of Neurology, Yale School of Medicine, New Haven, CT, USA
| | - Kevin C O'Connor
- Department of Neurology, Yale School of Medicine, New Haven, CT, USA; Department of Immunobiology, Yale School of Medicine, New Haven, CT, USA
| | - Richard J Nowak
- Department of Neurology, Yale School of Medicine, New Haven, CT, USA.
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Barnett C, Herbelin L, Dimachkie MM, Barohn RJ. Measuring Clinical Treatment Response in Myasthenia Gravis. Neurol Clin 2019; 36:339-353. [PMID: 29655453 DOI: 10.1016/j.ncl.2018.01.006] [Citation(s) in RCA: 45] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022]
Abstract
In this article we provide an overview of health-related outcome measurement-to better understand what different outcomes used in myasthenia actually measure-and to provide some guidance when choosing measures based on the clinical context and question. In myasthenia, the most commonly used outcome measures are aimed at assessing the signs and symptoms. In this review, we provide a summary of the most commonly used outcome measures. We discuss instruments that gauge disease overall health impact, such as on disability and quality of life. Finally, we discuss other relevant outcomes such as steroid-sparing effects and the role of surrogate markers.
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Affiliation(s)
- Carolina Barnett
- Neurology (Medicine), University of Toronto, University Health Network, Toronto, Ontario, Canada.
| | - Laura Herbelin
- Department of Neurology, University of Kansas Medical Center, 3901 Rainbow Boulevard, Kansas City, KS 66160, USA
| | - Mazen M Dimachkie
- Department of Neurology, University of Kansas Medical Center, 3901 Rainbow Boulevard, Kansas City, KS 66160, USA
| | - Richard J Barohn
- Department of Neurology, University of Kansas Medical Center, 3901 Rainbow Boulevard, Kansas City, KS 66160, USA
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Carter J, Tribe RM, Sandall J, Shennan AH. The Preterm Clinical Network (PCN) Database: a web-based systematic method of collecting data on the care of women at risk of preterm birth. BMC Pregnancy Childbirth 2018; 18:335. [PMID: 30119660 PMCID: PMC6098573 DOI: 10.1186/s12884-018-1967-y] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2017] [Accepted: 08/06/2018] [Indexed: 11/10/2022] Open
Abstract
Background Despite much research effort, there is a paucity of conclusive evidence in the field of preterm birth prediction and prevention. The methods of monitoring and prevention strategies offered to women at risk vary considerably around the UK and depend on local maternity care provision. It is becoming increasingly recognised that this experience and knowledge, if captured on a larger scale, could be a utilized as a valuable source of evidence for others. The UK Preterm Clinical Network (UKPCN) was established with the aim of improving care and outcomes for women at risk of preterm birth through the sharing of a wealth of experience and knowledge, as well as the building of clinical and research collaboration. The design and development of a bespoke internet-based database was fundamental to achieving this aim. Method Following consultation with UKPCN members and agreement on a minimal dataset, the Preterm Clinical Network (PCN) Database was constructed to collect data from women at risk of preterm birth and their children. Information Governance and research ethics committee approval was given for the storage of historical as well as prospectively collected data. Collaborating centres have instant access to their own records, while use of pooled data is governed by the PCN Database Access Committee. Applications are welcomed from UKPCN members and other established research groups. The results of investigations using the data are expected to provide insights into the effectiveness of current surveillance practices and preterm birth interventions on a national and international scale, as well as the generation of ideas for innovation and research. To date, 31 sites are registered as Data Collection Centres, four of which are outside the UK. Conclusion This paper outlines the aims of the PCN Database along with the development process undertaken from the initial idea to live launch.
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Affiliation(s)
- Jenny Carter
- Department of Women and Children's Health, School of Life Course Sciences, Faculty of Life Sciences and Medicine, King's College London, London, UK.
| | - Rachel M Tribe
- Department of Women and Children's Health, School of Life Course Sciences, Faculty of Life Sciences and Medicine, King's College London, London, UK
| | - Jane Sandall
- Department of Women and Children's Health, School of Life Course Sciences, Faculty of Life Sciences and Medicine, King's College London, London, UK
| | - Andrew H Shennan
- Department of Women and Children's Health, School of Life Course Sciences, Faculty of Life Sciences and Medicine, King's College London, London, UK
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Li HF, Hong Y, Xie Y, Hao HJ, Sun RC. Precision medicine in myasthenia graves: begin from the data precision. ANNALS OF TRANSLATIONAL MEDICINE 2016; 4:106. [PMID: 27127759 DOI: 10.21037/atm.2016.02.16] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
Myasthenia gravis (MG) is a prototypic autoimmune disease with overt clinical and immunological heterogeneity. The data of MG is far from individually precise now, partially due to the rarity and heterogeneity of this disease. In this review, we provide the basic insights of MG data precision, including onset age, presenting symptoms, generalization, thymus status, pathogenic autoantibodies, muscle involvement, severity and response to treatment based on references and our previous studies. Subgroups and quantitative traits of MG are discussed in the sense of data precision. The role of disease registries and scientific bases of precise analysis are also discussed to ensure better collection and analysis of MG data.
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Affiliation(s)
- Hai-Feng Li
- 1 Department of Neurology, Qilu Hospital of Shandong University, Jinan 250012, China ; 2 Department of Clinical Medicine, University of Bergen, Bergen, Norway ; 3 Department of Neurology, The George Washington University, Washington, DC, USA ; 4 Department of Neurology, Peking University First Hospital, Beijing 100034, China ; 5 College of Information and Engineering, Qingdao University, Qingdao 266071, China
| | - Yu Hong
- 1 Department of Neurology, Qilu Hospital of Shandong University, Jinan 250012, China ; 2 Department of Clinical Medicine, University of Bergen, Bergen, Norway ; 3 Department of Neurology, The George Washington University, Washington, DC, USA ; 4 Department of Neurology, Peking University First Hospital, Beijing 100034, China ; 5 College of Information and Engineering, Qingdao University, Qingdao 266071, China
| | - Yanchen Xie
- 1 Department of Neurology, Qilu Hospital of Shandong University, Jinan 250012, China ; 2 Department of Clinical Medicine, University of Bergen, Bergen, Norway ; 3 Department of Neurology, The George Washington University, Washington, DC, USA ; 4 Department of Neurology, Peking University First Hospital, Beijing 100034, China ; 5 College of Information and Engineering, Qingdao University, Qingdao 266071, China
| | - Hong-Jun Hao
- 1 Department of Neurology, Qilu Hospital of Shandong University, Jinan 250012, China ; 2 Department of Clinical Medicine, University of Bergen, Bergen, Norway ; 3 Department of Neurology, The George Washington University, Washington, DC, USA ; 4 Department of Neurology, Peking University First Hospital, Beijing 100034, China ; 5 College of Information and Engineering, Qingdao University, Qingdao 266071, China
| | - Ren-Cheng Sun
- 1 Department of Neurology, Qilu Hospital of Shandong University, Jinan 250012, China ; 2 Department of Clinical Medicine, University of Bergen, Bergen, Norway ; 3 Department of Neurology, The George Washington University, Washington, DC, USA ; 4 Department of Neurology, Peking University First Hospital, Beijing 100034, China ; 5 College of Information and Engineering, Qingdao University, Qingdao 266071, China
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