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Cruciani A, Capone F, Haggiag S, Prosperini L, Santoro F, Ruggieri S, Motolese F, Pilato F, Musumeci G, Pozzilli V, Rossi M, Stampanoni Bassi M, Buttari F, Centonze D, Di Lazzaro V, Gasperini C, Tortorella C. Cortical plasticity in AQP4-positive NMOSD: a transcranial magnetic stimulation study. Cereb Cortex 2024; 34:bhae345. [PMID: 39172095 DOI: 10.1093/cercor/bhae345] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2024] [Revised: 07/31/2024] [Accepted: 08/07/2024] [Indexed: 08/23/2024] Open
Abstract
Aquaporin-4 antibody-positive neuromyelitis optica spectrum disorder (AQP4-NMOSD) is an autoimmune disease characterized by suboptimal recovery from attacks and long-term disability. Experimental data suggest that AQP4 antibodies can disrupt neuroplasticity, a fundamental driver of brain recovery. A well-established method to assess brain LTP is through intermittent theta-burst stimulation (iTBS). This study aimed to explore neuroplasticity in AQP4-NMOSD patients by examining long-term potentiation (LTP) through iTBS. We conducted a proof-of-principle study including 8 patients with AQP4-NMOSD, 8 patients with multiple sclerosis (MS), and 8 healthy controls (HC) in which iTBS was administered to induce LTP-like effects. iTBS-induced LTP exhibited significant differences among the 3 groups (p: 0.006). Notably, AQP4-NMOSD patients demonstrated impaired plasticity compared to both HC (p = 0.01) and pwMS (p = 0.02). This pilot study provides the first in vivo evidence supporting impaired neuroplasticity in AQP4-NMOSD patients. Impaired cortical plasticity may hinder recovery following attacks suggesting a need for targeted rehabilitation strategies.
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Affiliation(s)
- Alessandro Cruciani
- Department of Medicine and Surgery, Unit of Neurology, Neurophysiology, Neurobiology, and Psychiatry, Università Campus Bio-Medico di Roma, Via Alvaro del Portillo 21-00128, Roma, Italy
- Fondazione Policlinico Universitario Campus Bio-Medico, Via Alvaro del Portillo, 21-00128 Roma, Italy
| | - Fioravante Capone
- Department of Medicine and Surgery, Unit of Neurology, Neurophysiology, Neurobiology, and Psychiatry, Università Campus Bio-Medico di Roma, Via Alvaro del Portillo 21-00128, Roma, Italy
- Fondazione Policlinico Universitario Campus Bio-Medico, Via Alvaro del Portillo, 21-00128 Roma, Italy
| | - Shalom Haggiag
- Department of Neurosciences, San Camillo-Forlanini Hospital, C.ne Gianicolense 87, , 00152 Rome, Italy
| | - Luca Prosperini
- Department of Neurosciences, San Camillo-Forlanini Hospital, C.ne Gianicolense 87, , 00152 Rome, Italy
| | - Francesca Santoro
- Department of Medicine and Surgery, Unit of Neurology, Neurophysiology, Neurobiology, and Psychiatry, Università Campus Bio-Medico di Roma, Via Alvaro del Portillo 21-00128, Roma, Italy
- Fondazione Policlinico Universitario Campus Bio-Medico, Via Alvaro del Portillo, 21-00128 Roma, Italy
| | - Serena Ruggieri
- Department of Neurosciences, San Camillo-Forlanini Hospital, C.ne Gianicolense 87, , 00152 Rome, Italy
| | - Francesco Motolese
- Department of Medicine and Surgery, Unit of Neurology, Neurophysiology, Neurobiology, and Psychiatry, Università Campus Bio-Medico di Roma, Via Alvaro del Portillo 21-00128, Roma, Italy
- Fondazione Policlinico Universitario Campus Bio-Medico, Via Alvaro del Portillo, 21-00128 Roma, Italy
| | - Fabio Pilato
- Department of Medicine and Surgery, Unit of Neurology, Neurophysiology, Neurobiology, and Psychiatry, Università Campus Bio-Medico di Roma, Via Alvaro del Portillo 21-00128, Roma, Italy
- Fondazione Policlinico Universitario Campus Bio-Medico, Via Alvaro del Portillo, 21-00128 Roma, Italy
| | - Gabriella Musumeci
- Department of Medicine and Surgery, Unit of Neurology, Neurophysiology, Neurobiology, and Psychiatry, Università Campus Bio-Medico di Roma, Via Alvaro del Portillo 21-00128, Roma, Italy
- Fondazione Policlinico Universitario Campus Bio-Medico, Via Alvaro del Portillo, 21-00128 Roma, Italy
| | - Valeria Pozzilli
- Department of Medicine and Surgery, Unit of Neurology, Neurophysiology, Neurobiology, and Psychiatry, Università Campus Bio-Medico di Roma, Via Alvaro del Portillo 21-00128, Roma, Italy
- Fondazione Policlinico Universitario Campus Bio-Medico, Via Alvaro del Portillo, 21-00128 Roma, Italy
| | - Mariagrazia Rossi
- Department of Medicine and Surgery, Unit of Neurology, Neurophysiology, Neurobiology, and Psychiatry, Università Campus Bio-Medico di Roma, Via Alvaro del Portillo 21-00128, Roma, Italy
- Fondazione Policlinico Universitario Campus Bio-Medico, Via Alvaro del Portillo, 21-00128 Roma, Italy
| | | | - Fabio Buttari
- Unit of Neurology, IRCCS Neuromed, Pozzilli (IS), Italy
- Laboratory of Synaptic Immunopathology, Department of Systems Medicine, University of Tor Vergata, Rome, Italy
| | - Diego Centonze
- Unit of Neurology, IRCCS Neuromed, Pozzilli (IS), Italy
- Laboratory of Synaptic Immunopathology, Department of Systems Medicine, University of Tor Vergata, Rome, Italy
| | - Vincenzo Di Lazzaro
- Department of Medicine and Surgery, Unit of Neurology, Neurophysiology, Neurobiology, and Psychiatry, Università Campus Bio-Medico di Roma, Via Alvaro del Portillo 21-00128, Roma, Italy
- Fondazione Policlinico Universitario Campus Bio-Medico, Via Alvaro del Portillo, 21-00128 Roma, Italy
| | - Claudio Gasperini
- Department of Neurosciences, San Camillo-Forlanini Hospital, C.ne Gianicolense 87, , 00152 Rome, Italy
| | - Carla Tortorella
- Department of Neurosciences, San Camillo-Forlanini Hospital, C.ne Gianicolense 87, , 00152 Rome, Italy
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Rodríguez S. Artificial intelligence in multiple sclerosis management: Challenges in a new era. Mult Scler Relat Disord 2024; 86:105611. [PMID: 38604002 DOI: 10.1016/j.msard.2024.105611] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2024] [Accepted: 04/07/2024] [Indexed: 04/13/2024]
Abstract
Multiple sclerosis poses diagnostic and therapeutic challenges for healthcare professionals, with a high risk of misdiagnosis and difficulties in assessing therapeutic effectiveness. Artificial intelligence, particularly machine learning and deep neural networks, emerges as a promising tool to address these challenges. These technologies have the capability to analyze a wide range of data, from magnetic resonance imaging to genetic information, to provide more accurate diagnoses, classify multiple sclerosis subtypes, and predict disease progression and treatment response with extraordinary precision. However, their implementation raises ethical dilemmas, such as accountability in case of errors and the risk of excessive reliance on healthcare personnel. That said, this manuscript aims to urge healthcare professionals dedicated to the care and research of multiple sclerosis patients to recognize artificial intelligence as a valuable and complementary resource in their clinical practice. It also seeks to emphasize the importance of integrating this type of technology safely and responsibly, thereby ensuring the ethics and welfare of patients.
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Affiliation(s)
- Sebastián Rodríguez
- Universidad Nacional de Colombia, Sede Bogotá. Facultad de Medicina. Departamento de Movimiento Corporal Humano, Maestría en Fisioterapia del Deporte y la Actividad Física, Colombia.
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Pappolla A, Auger C, Sao-Aviles A, Tur C, Rodriguez-Barranco M, Cobo-Calvo Á, Mongay-Ochoa N, Rodríguez-Acevedo B, Zabalza A, Midaglia L, Carbonell-Mirabent P, Carvajal R, Castilló-Justribó J, Braga N, Bollo L, Vidal-Jordana A, Arrambide G, Nos C, Salerno A, Galán I, Comabella M, Sastre-Garriga J, Tintoré M, Rovira A, Montalban X, Río J. Prediction of disease activity and treatment failure in relapsing-remitting MS patients initiating daily oral DMTs. Mult Scler 2024; 30:820-832. [PMID: 38551315 DOI: 10.1177/13524585241240653] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/29/2024]
Abstract
BACKGROUND Limited data exist regarding treatment response prediction to oral disease-modifying therapies (DMTs) in multiple sclerosis (MS). OBJECTIVES We assessed the capacity of available scoring systems to anticipate disease activity parameters in naïve relapsing-remitting MS (RRMS) patients initiating daily oral DMTs, hypothesizing that they exhibit different predictive potentials. METHODS We conducted a retrospective study and applied the Rio Score (RS), modified Rio Score (mRS), and MAGNIMS Score 12 months after DMT initiation. At 36 months, we examined their ability to predict evidence of disease activity (EDA) components and treatment failure by logistic regression analysis. RESULTS Notably, 218 patients (62.4% females) initiating dimethyl fumarate, teriflunomide, and fingolimod were included. At 36 months, the RS high-risk group predicted evidence of clinical activity (odds ratio (OR) 10 [2.7-36.9]) and treatment failure (OR 10.6 [3.4-32.5]) but did not predict radiological activity (OR 1.9 [0.7-5]). The mRS non-responders group did not predict EDA and treatment failure. RS, mRS, and MAGNIMS 0 categories showed significantly lower EDA and treatment failure than the remainder. CONCLUSION Scoring systems present different predictive abilities for disease activity parameters at 36 months in MS patients initiating daily oral therapies, warranting further adjustments (i.e. introduction of fluid biomarkers) to depict disease activity status fully.
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Affiliation(s)
- Agustin Pappolla
- Servei de Neurologia-Neuroimmunologia, Centre d'Esclerosi Múltiple de Catalunya (Cemcat), Vall d'Hebron Institut de Recerca, Vall d'Hebron Hospital Universitari, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Cristina Auger
- Section of Neuroradiology, Department of Radiology, Vall d'Hebron Institut de Recerca, Vall d'Hebron Hospital Universitari, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Augusto Sao-Aviles
- Statistics and Bioinformatics Unit, Vall d'Hebron Institut de Recerca, Vall d'Hebron Hospital Universitari, Barcelona, Spain
| | - Carmen Tur
- Servei de Neurologia-Neuroimmunologia, Centre d'Esclerosi Múltiple de Catalunya (Cemcat), Vall d'Hebron Institut de Recerca, Vall d'Hebron Hospital Universitari, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Marta Rodriguez-Barranco
- Servei de Neurologia-Neuroimmunologia, Centre d'Esclerosi Múltiple de Catalunya (Cemcat), Vall d'Hebron Institut de Recerca, Vall d'Hebron Hospital Universitari, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Álvaro Cobo-Calvo
- Servei de Neurologia-Neuroimmunologia, Centre d'Esclerosi Múltiple de Catalunya (Cemcat), Vall d'Hebron Institut de Recerca, Vall d'Hebron Hospital Universitari, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Neus Mongay-Ochoa
- Servei de Neurologia-Neuroimmunologia, Centre d'Esclerosi Múltiple de Catalunya (Cemcat), Vall d'Hebron Institut de Recerca, Vall d'Hebron Hospital Universitari, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Breogán Rodríguez-Acevedo
- Servei de Neurologia-Neuroimmunologia, Centre d'Esclerosi Múltiple de Catalunya (Cemcat), Vall d'Hebron Institut de Recerca, Vall d'Hebron Hospital Universitari, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Ana Zabalza
- Servei de Neurologia-Neuroimmunologia, Centre d'Esclerosi Múltiple de Catalunya (Cemcat), Vall d'Hebron Institut de Recerca, Vall d'Hebron Hospital Universitari, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Luciana Midaglia
- Servei de Neurologia-Neuroimmunologia, Centre d'Esclerosi Múltiple de Catalunya (Cemcat), Vall d'Hebron Institut de Recerca, Vall d'Hebron Hospital Universitari, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Pere Carbonell-Mirabent
- Servei de Neurologia-Neuroimmunologia, Centre d'Esclerosi Múltiple de Catalunya (Cemcat), Vall d'Hebron Institut de Recerca, Vall d'Hebron Hospital Universitari, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Rene Carvajal
- Servei de Neurologia-Neuroimmunologia, Centre d'Esclerosi Múltiple de Catalunya (Cemcat), Vall d'Hebron Institut de Recerca, Vall d'Hebron Hospital Universitari, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Joaquín Castilló-Justribó
- Servei de Neurologia-Neuroimmunologia, Centre d'Esclerosi Múltiple de Catalunya (Cemcat), Vall d'Hebron Institut de Recerca, Vall d'Hebron Hospital Universitari, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Nathane Braga
- Servei de Neurologia-Neuroimmunologia, Centre d'Esclerosi Múltiple de Catalunya (Cemcat), Vall d'Hebron Institut de Recerca, Vall d'Hebron Hospital Universitari, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Luca Bollo
- Servei de Neurologia-Neuroimmunologia, Centre d'Esclerosi Múltiple de Catalunya (Cemcat), Vall d'Hebron Institut de Recerca, Vall d'Hebron Hospital Universitari, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Angela Vidal-Jordana
- Servei de Neurologia-Neuroimmunologia, Centre d'Esclerosi Múltiple de Catalunya (Cemcat), Vall d'Hebron Institut de Recerca, Vall d'Hebron Hospital Universitari, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Georgina Arrambide
- Servei de Neurologia-Neuroimmunologia, Centre d'Esclerosi Múltiple de Catalunya (Cemcat), Vall d'Hebron Institut de Recerca, Vall d'Hebron Hospital Universitari, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Carlos Nos
- Servei de Neurologia-Neuroimmunologia, Centre d'Esclerosi Múltiple de Catalunya (Cemcat), Vall d'Hebron Institut de Recerca, Vall d'Hebron Hospital Universitari, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Annalaura Salerno
- Section of Neuroradiology, Department of Radiology, Vall d'Hebron Institut de Recerca, Vall d'Hebron Hospital Universitari, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Ingrid Galán
- Servei de Neurologia-Neuroimmunologia, Centre d'Esclerosi Múltiple de Catalunya (Cemcat), Vall d'Hebron Institut de Recerca, Vall d'Hebron Hospital Universitari, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Manuel Comabella
- Servei de Neurologia-Neuroimmunologia, Centre d'Esclerosi Múltiple de Catalunya (Cemcat), Vall d'Hebron Institut de Recerca, Vall d'Hebron Hospital Universitari, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Jaume Sastre-Garriga
- Servei de Neurologia-Neuroimmunologia, Centre d'Esclerosi Múltiple de Catalunya (Cemcat), Vall d'Hebron Institut de Recerca, Vall d'Hebron Hospital Universitari, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Mar Tintoré
- Servei de Neurologia-Neuroimmunologia, Centre d'Esclerosi Múltiple de Catalunya (Cemcat), Vall d'Hebron Institut de Recerca, Vall d'Hebron Hospital Universitari, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Alex Rovira
- Section of Neuroradiology, Department of Radiology, Vall d'Hebron Institut de Recerca, Vall d'Hebron Hospital Universitari, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Xavier Montalban
- Servei de Neurologia-Neuroimmunologia, Centre d'Esclerosi Múltiple de Catalunya (Cemcat), Vall d'Hebron Institut de Recerca, Vall d'Hebron Hospital Universitari, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Jordi Río
- Servei de Neurologia-Neuroimmunologia, Centre d'Esclerosi Múltiple de Catalunya (Cemcat), Vall d'Hebron Institut de Recerca, Vall d'Hebron Hospital Universitari, Universitat Autònoma de Barcelona, Barcelona, Spain
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Hiramatsu K, Maeda H. Adult and pediatric relapsing multiple sclerosis phase II and phase III trial design and their primary end points: A systematic review. Clin Transl Sci 2024; 17:e13794. [PMID: 38708586 PMCID: PMC11070945 DOI: 10.1111/cts.13794] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2023] [Revised: 02/22/2024] [Accepted: 04/01/2024] [Indexed: 05/07/2024] Open
Abstract
No systematic review of trial designs in patients with relapsing multiple sclerosis (RMS) was reported. This systematic review was conducted on the trial designs and primary end points (PEs) of phase II and III trials intended to modify the natural course of the disease in patients with RMS. The purpose of the study is to explore trends/topics and discussion points in clinical trial design and PE, comparing them to regulatory guidelines and expert recommendations. Three trial registration systems, ClinicalTrials.gov, the EU Clinical Trials Register, and the Japan Registry of Clinical Trials, were used and 60 trials were evaluated. The dominant clinical trial design was a randomized controlled parallel-arms trial and other details were as follows: in adult phase III confirmatory trials (n = 32), active-controlled double-blind trial (DBT) (53%) and active-controlled open-label assessor-masking trial (16%); in adult phase II dose-finding trials (n = 9), placebo- and active-controlled DBT (44%), placebo-controlled DBT (22%), and placebo-controlled add-on DBT (22%); and in pediatric phase III confirmatory trials (n = 8), active-controlled DBT (38%) and active-controlled open-label non-masking trial (25%). The most common PEs were as follows: in adult confirmatory trials, annual relapse rate (ARR) (56%) and no evidence of disease activity-3 (NEDA-3) (13%); in adult dose-finding trials, the cumulative number of T1 gadolinium-enhancing lesions (56%), combined unique active lesions (22%), and overall disability response score (22%); and in pediatric confirmatory trials, ARR (38%) and time to first relapse (25%). It was suggested that some parts of the regulatory guidelines and expert recommendations need to be revised.
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Affiliation(s)
- Katsutoshi Hiramatsu
- Department of Regulatory Science, Faculty of PharmacyMeiji Pharmaceutical UniversityTokyoJapan
| | - Hideki Maeda
- Department of Regulatory Science, Faculty of PharmacyMeiji Pharmaceutical UniversityTokyoJapan
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Mahler MR, Magyari M, Pontieri L, Elberling F, Holm RP, Weglewski A, Poulsen MB, Storr LK, Bekyarov PA, Illes Z, Kant M, Sejbaek T, Stilund ML, Rasmussen PV, Brask M, Urbonaviciute I, Sellebjerg F. Prognostic factors for disease activity in newly diagnosed teriflunomide-treated patients with multiple sclerosis: a nationwide Danish study. J Neurol Neurosurg Psychiatry 2024:jnnp-2023-333265. [PMID: 38569873 DOI: 10.1136/jnnp-2023-333265] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/21/2023] [Accepted: 03/17/2024] [Indexed: 04/05/2024]
Abstract
BACKGROUND Clinicians frequently rely on relapse counts, T2 MRI lesion load (T2L) and Expanded Disability Status Scale (EDSS) scores to guide treatment decisions for individuals diagnosed with multiple sclerosis (MS). This study evaluates how these factors, along with age and sex, influence prognosis during treatment with teriflunomide (TFL). METHODS We conducted a nationwide cohort study using data from the Danish Multiple Sclerosis Registry.Eligible participants had relapsing-remitting MS or clinically isolated syndrome and initiated TFL as their first treatment between 2013 and 2019. The effect of age, pretreatment relapses, T2L and EDSS scores on the risk of disease activity on TFL were stratified by sex. RESULTS In total, 784 individuals were included (57.4% females). A high number of pretreatment relapses (≥2) was associated with an increased risk of disease activity in females only (OR and (95% CI): 1.76 (1.11 to 2.81)). Age group 50+ was associated with a lower risk of disease activity in both sexes (OR females=0.28 (0.14 to 0.56); OR males=0.22 (0.09 to 0.55)), while age 35-49 showed a different impact in males and females (OR females=0.79 (0.50 to 1.23); OR males=0.42 (0.24 to 0.72)). EDSS scores and T2L did not show any consistent associations. CONCLUSION A high number of pretreatment relapses was only associated with an increased risk of disease activity in females, while age had a differential impact on the risk of disease activity according to sex. Clinicians may consider age, sex and relapses when deciding on TFL treatment.
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Affiliation(s)
- Mie Reith Mahler
- The Danish Multiple Sclerosis Registry, Danish Multiple Sclerosis Research Center, Copenhagen University Hospital, Glostrup, Denmark
| | - Melinda Magyari
- The Danish Multiple Sclerosis Registry, Danish Multiple Sclerosis Research Center, Copenhagen University Hospital, Glostrup, Denmark
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Luigi Pontieri
- The Danish Multiple Sclerosis Registry, Danish Multiple Sclerosis Research Center, Copenhagen University Hospital, Glostrup, Denmark
| | - Frederik Elberling
- The Danish Multiple Sclerosis Registry, Danish Multiple Sclerosis Research Center, Copenhagen University Hospital, Glostrup, Denmark
| | - Rolf Pringler Holm
- The Danish Multiple Sclerosis Registry, Danish Multiple Sclerosis Research Center, Copenhagen University Hospital, Glostrup, Denmark
| | - Arkadiusz Weglewski
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Department of Neurology, Herlev Hospital, Herlev, Denmark
| | - Mai Bang Poulsen
- Department of Neurology, Nordsjaellands Hospital, Hilleroed, Denmark
| | | | | | - Zsolt Illes
- Department of Neurology, Odense University Hospital, Odense, Denmark
| | - Matthias Kant
- Department of Neurology, Hospital of Southern Jutland Soenderborg Branch, Soenderborg, Denmark
| | - Tobias Sejbaek
- Department of Neurology, Esbjerg Central Hospital, Esbjerg, Denmark
- Department of Regional Health Research, University of Southern Denmark, Odense, Denmark
| | - Morten Leif Stilund
- Department of Neurology, Physiotherapy and Occupational Therapy, Goedstrup Hospital, Herning, Denmark
| | - Peter V Rasmussen
- Department of Neurology, Aarhus University Hospital, Aarhus, Denmark
| | - Maria Brask
- Department of Neurology, Viborg Regional Hospital, Viborg, Denmark
| | | | - Finn Sellebjerg
- The Danish Multiple Sclerosis Registry, Danish Multiple Sclerosis Research Center, Copenhagen University Hospital, Glostrup, Denmark
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
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Cortese R, Testa G, Assogna F, De Stefano N. Magnetic Resonance Imaging Evidence Supporting the Efficacy of Cladribine Tablets in the Treatment of Relapsing-Remitting Multiple Sclerosis. CNS Drugs 2024; 38:267-279. [PMID: 38489020 PMCID: PMC10980660 DOI: 10.1007/s40263-024-01074-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 02/15/2024] [Indexed: 03/17/2024]
Abstract
Numerous therapies are currently available to modify the disease course of multiple sclerosis (MS). Magnetic resonance imaging (MRI) plays a pivotal role in assessing treatment response by providing insights into disease activity and clinical progression. Integrating MRI findings with clinical and laboratory data enables a comprehensive assessment of the disease course. Among available MS treatments, cladribine is emerging as a promising option due to its role as a selective immune reconstitution therapy, with a notable impact on B cells and a lesser effect on T cells. This work emphasizes the assessment of MRI's contribution to MS treatment, particularly focusing on the influence of cladribine tablets on imaging outcomes, encompassing data from pivotal and real-world studies. The evidence highlights that cladribine, compared with placebo, not only exhibits a reduction in inflammatory imaging markers, such as T1-Gd+, T2 and combined unique active (CUA) lesions, but also mitigates the effect on brain volume loss, particularly within grey matter. Importantly, cladribine reveals early action by reducing CUA lesions within the first months of treatment, regardless of a patient's initial conditions. The selective mechanism of action, and sustained efficacy beyond year 2, combined with its early onset of action, collectively position cladribine tablets as a pivotal component in the therapeutic paradigm for MS. Overall, MRI, along with clinical measures, has played a substantial role in showcasing the effectiveness of cladribine in addressing both the inflammatory and neurodegenerative aspects of MS.
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Affiliation(s)
- Rosa Cortese
- Department of Medicine, Surgery and Neuroscience, University of Siena, Viale Bracci 2, 53100, Siena, Italy
| | - Giovanna Testa
- Merck Serono S.p.A. Italy, An Affiliate of Merck KGaA, Rome, Italy
| | | | - Nicola De Stefano
- Department of Medicine, Surgery and Neuroscience, University of Siena, Viale Bracci 2, 53100, Siena, Italy.
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Chaves H, Serra MM, Shalom DE, Ananía P, Rueda F, Osa Sanz E, Stefanoff NI, Rodríguez Murúa S, Costa ME, Kitamura FC, Yañez P, Cejas C, Correale J, Ferrante E, Fernández Slezak D, Farez MF. Assessing robustness and generalization of a deep neural network for brain MS lesion segmentation on real-world data. Eur Radiol 2024; 34:2024-2035. [PMID: 37650967 DOI: 10.1007/s00330-023-10093-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2023] [Revised: 07/01/2023] [Accepted: 07/12/2023] [Indexed: 09/01/2023]
Abstract
OBJECTIVES Evaluate the performance of a deep learning (DL)-based model for multiple sclerosis (MS) lesion segmentation and compare it to other DL and non-DL algorithms. METHODS This ambispective, multicenter study assessed the performance of a DL-based model for MS lesion segmentation and compared it to alternative DL- and non-DL-based methods. Models were tested on internal (n = 20) and external (n = 18) datasets from Latin America, and on an external dataset from Europe (n = 49). We also examined robustness by rescanning six patients (n = 6) from our MS clinical cohort. Moreover, we studied inter-human annotator agreement and discussed our findings in light of these results. Performance and robustness were assessed using intraclass correlation coefficient (ICC), Dice coefficient (DC), and coefficient of variation (CV). RESULTS Inter-human ICC ranged from 0.89 to 0.95, while spatial agreement among annotators showed a median DC of 0.63. Using expert manual segmentations as ground truth, our DL model achieved a median DC of 0.73 on the internal, 0.66 on the external, and 0.70 on the challenge datasets. The performance of our DL model exceeded that of the alternative algorithms on all datasets. In the robustness experiment, our DL model also achieved higher DC (ranging from 0.82 to 0.90) and lower CV (ranging from 0.7 to 7.9%) when compared to the alternative methods. CONCLUSION Our DL-based model outperformed alternative methods for brain MS lesion segmentation. The model also proved to generalize well on unseen data and has a robust performance and low processing times both on real-world and challenge-based data. CLINICAL RELEVANCE STATEMENT Our DL-based model demonstrated superior performance in accurately segmenting brain MS lesions compared to alternative methods, indicating its potential for clinical application with improved accuracy, robustness, and efficiency. KEY POINTS • Automated lesion load quantification in MS patients is valuable; however, more accurate methods are still necessary. • A novel deep learning model outperformed alternative MS lesion segmentation methods on multisite datasets. • Deep learning models are particularly suitable for MS lesion segmentation in clinical scenarios.
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Affiliation(s)
- Hernán Chaves
- Diagnostic Imaging Department, Fleni, Montañeses, 2325 (C1428AQK), Ciudad de Buenos Aires, Argentina.
| | - María M Serra
- Diagnostic Imaging Department, Fleni, Montañeses, 2325 (C1428AQK), Ciudad de Buenos Aires, Argentina
| | - Diego E Shalom
- Department of Physics, University of Buenos Aires (UBA), Buenos Aires, Argentina
- Physics Institute of Buenos Aires (IFIBA) CONICET, Buenos Aires, Argentina
- Laboratorio de Neurociencia, Universidad Torcuato Di Tella, Buenos Aires, Argentina
| | | | - Fernanda Rueda
- Radiology Department, Diagnósticos da América SA (Dasa), Rio de Janeiro, Brazil
| | - Emilia Osa Sanz
- Diagnostic Imaging Department, Fleni, Montañeses, 2325 (C1428AQK), Ciudad de Buenos Aires, Argentina
| | - Nadia I Stefanoff
- Diagnostic Imaging Department, Fleni, Montañeses, 2325 (C1428AQK), Ciudad de Buenos Aires, Argentina
| | - Sofía Rodríguez Murúa
- Center for Research On Neuroimmunological Diseases (CIEN), Fleni, Buenos Aires, Argentina
| | | | - Felipe C Kitamura
- DasaInova, Diagnósticos da América SA (Dasa), São Paulo, São Paulo, Brazil
| | - Paulina Yañez
- Diagnostic Imaging Department, Fleni, Montañeses, 2325 (C1428AQK), Ciudad de Buenos Aires, Argentina
| | - Claudia Cejas
- Diagnostic Imaging Department, Fleni, Montañeses, 2325 (C1428AQK), Ciudad de Buenos Aires, Argentina
| | | | - Enzo Ferrante
- Instituto de Investigación en Señales, Sistemas e Inteligencia Computacional, sinc(i) CONICET-UNL, Santa Fe, Argentina
| | - Diego Fernández Slezak
- Center for Research On Neuroimmunological Diseases (CIEN), Fleni, Buenos Aires, Argentina
- Departamento de Computación, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires (UBA), Buenos Aires, Argentina
- Instituto de Investigación en Ciencias de la Computación (ICC), CONICET-UBA, Buenos Aires, Argentina
| | - Mauricio F Farez
- Radiology Department, Diagnósticos da América SA (Dasa), Rio de Janeiro, Brazil
- Center for Research On Neuroimmunological Diseases (CIEN), Fleni, Buenos Aires, Argentina
- Center for Biostatistics, Epidemiology and Public Health (CEBES), Fleni, Buenos Aires, Argentina
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8
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Yamout B, Al-Jumah M, Sahraian MA, Almalik Y, Khaburi JA, Shalaby N, Aljarallah S, Bohlega S, Dahdaleh M, Almahdawi A, Khoury SJ, Koussa S, Slassi E, Daoudi S, Aref H, Mrabet S, Zeineddine M, Zakaria M, Inshasi J, Gouider R, Alroughani R. Consensus recommendations for diagnosis and treatment of Multiple Sclerosis: 2023 revision of the MENACTRIMS guidelines. Mult Scler Relat Disord 2024; 83:105435. [PMID: 38245998 DOI: 10.1016/j.msard.2024.105435] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2023] [Revised: 12/21/2023] [Accepted: 01/06/2024] [Indexed: 01/23/2024]
Abstract
With evolving diagnostic criteria and the advent of new oral and parenteral therapies for Multiple Sclerosis (MS), most current diagnostic and treatment algorithms need revision and updating. The diagnosis of MS relies on incorporating clinical and paraclinical findings to prove dissemination in space and time and exclude alternative diseases that can explain the findings at hand. The differential diagnostic workup should be guided by clinical and laboratory red flags to avoid unnecessary tests. Appropriate selection of MS therapies is critical to maximize patient benefit. The current guidelines review the current diagnostic criteria for MS and the scientific evidence supporting treatment of acute relapses, radiologically isolated syndrome, clinically isolated syndrome, relapsing remitting MS, progressive MS, pediatric cases and pregnant women. The purpose of these guidelines is to provide practical recommendations and algorithms for the diagnosis and treatment of MS based on current scientific evidence and clinical experience.
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Affiliation(s)
- B Yamout
- Neurology Institute and Multiple Sclerosis Center, Harley Street Medical Center, Abu Dhabi, United Arab Emirates.
| | - M Al-Jumah
- InterHealth hospital, Multiple Sclerosis Center, Riyadh, Saudi Arabia
| | - M A Sahraian
- Multiple Sclerosis Research Center, Neuroscience Institute, Tehran University of Medical Sciences, Tehran, Iran
| | - Y Almalik
- Division of Neurology, College of Medicine, King Saud bin Abdulaziz University for Health Sciences, King Abdullah International Medical Research Center, National Guard Health Affairs, King Abdulaziz Medical City, Riyadh, Saudi Arabia
| | - J Al Khaburi
- Department of Neurology, The Royal Hospital, Sultanate of Oman
| | - N Shalaby
- Neurology Department, Kasr Al-Ainy School of Medicine, Cairo University, Cairo, Egypt
| | | | - S Bohlega
- King Faisal Specialist Hospital and Research Centre, Riyadh, Saudi Arabia
| | | | - A Almahdawi
- Consultant Neurologist, Neurology Unit, Baghdad Teaching Hospital, Medical City Complex, Iraq
| | - S J Khoury
- Nehme and Therese Tohme Multiple Sclerosis Center, American University of Beirut Medical Center, Beirut, Lebanon
| | - S Koussa
- Multiple Sclerosis Center, Geitaoui Lebanese University Hospital, Beirut, Lebanon
| | - E Slassi
- Hôpital Cheikh Khalifa Ibn Zaid, Casablanca, Morocco
| | - S Daoudi
- Hospital Center Nedir Mohamed, Faculty of Medicine, University Mouloud Mammeri Tizi-Ouzou, Algeria
| | - H Aref
- Neurology Department, Ain Shams University, Cairo, Egypt
| | - S Mrabet
- Department of Neurology, CIC, Razi Universitary Hospital, University of Tunis El Manar, Tunis, Tunisia
| | - M Zeineddine
- Middle East and North Africa Committee for Treatment and Research in Multiple Sclerosis (MENACTRIMS), Beirut, Lebanon
| | | | - J Inshasi
- Department of Neurology, Rashid Hospital and Dubai Medical College, Dubai Health Authority, Dubai, United Arab Emirates
| | - R Gouider
- Department of Neurology, CIC, Razi Universitary Hospital, University of Tunis El Manar, Tunis, Tunisia
| | - R Alroughani
- Amiri Hospital, Arabian Gulf Street, Sharq, Kuwait
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9
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Ruggieri S, Prosperini L, Al-Araji S, Annovazzi PO, Bisecco A, Ciccarelli O, De Stefano N, Filippi M, Fleischer V, Evangelou N, Enzinger C, Gallo A, Garjani A, Groppa S, Haggiag S, Khalil M, Lucchini M, Mirabella M, Montalban X, Pozzilli C, Preziosa P, Río J, Rocca MA, Rovira A, Stromillo ML, Zaffaroni M, Tortorella C, Gasperini C. Assessing treatment response to oral drugs for multiple sclerosis in real-world setting: a MAGNIMS Study. J Neurol Neurosurg Psychiatry 2024; 95:142-150. [PMID: 37775266 DOI: 10.1136/jnnp-2023-331920] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/26/2023] [Accepted: 08/09/2023] [Indexed: 10/01/2023]
Abstract
BACKGROUND The assessment of treatment response is a crucial step for patients with relapsing-remitting multiple sclerosis on disease-modifying therapies (DMTs). We explored whether a scoring system developed within the MAGNIMS (MRI in Multiple Sclerosis) network to evaluate treatment response to injectable drugs can be adopted also to oral DMTs. METHODS A multicentre dataset of 1200 patients who started three oral DMTs (fingolimod, teriflunomide and dimethyl fumarate) was collected within the MAGNIMS network. Disease activity after the first year was classified by the 'MAGNIMS' score based on the combination of relapses (0-≥2) and/or new T2 lesions (<3 or ≥3) on brain MRI. We explored the association of this score with the following 3-year outcomes: (1) confirmed disability worsening (CDW); (2) treatment failure (TFL); (3) relapse count between years 1 and 3. The additional value of contrast-enhancing lesions (CELs) and lesion location was explored. RESULTS At 3 years, 160 patients experienced CDW: 12% of them scored '0' (reference), 18% scored '1' (HR=1.82, 95% CI 1.20 to 2.76, p=0.005) and 37% scored '2' (HR=2.74, 95% CI 1.41 to 5.36, p=0.003) at 1 year. The analysis of other outcomes provided similar findings. Considering the location of new T2 lesions (supratentorial vs infratentorial/spinal cord) and the presence of CELs improved the prediction of CDW and TFL, respectively, in patients with minimal MRI activity alone (one or two new T2 lesions). CONCLUSIONS Early relapses and substantial MRI activity in the first year of treatment are associated with worse short-term outcomes in patients treated with some of the oral DMTs.
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Affiliation(s)
- Serena Ruggieri
- Department of Neurosciences, San Camillo Forlanini Hospital, Rome, Italy
- Department of Human Neurosciences, Sapienza University of Rome, Rome, Italy
| | - Luca Prosperini
- Department of Neurosciences, San Camillo Forlanini Hospital, Rome, Italy
| | - Sarmad Al-Araji
- Department of Neuroinflammation, Queen Square MS Centre, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK
| | - Pietro Osvaldo Annovazzi
- Neuroimmunology Unit-Multiple Sclerosis Center, Hospital of Gallarate, ASST della Valle Olona, Gallarate, Italy
| | - Alvino Bisecco
- Department of Advanced Medical and Surgical Sciences, University of Campania 'Luigi Vanvitelli', Naples, Italy
| | - Olga Ciccarelli
- Department of Neuroinflammation, Queen Square MS Centre, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK
- National Institute for Health Research Biomedical Research Centre, University College London Hospitals, London, UK
| | - Nicola De Stefano
- Department of Medicine, Surgery and Neuroscience, University of Siena, Siena, Italy
| | - Massimo Filippi
- Neurology Unit and Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Vita-Salute San Raffaele University, Milan, Italy
| | - Vinzenz Fleischer
- Department of Neurology and Neuroimaging Center (NIC) of the Focus Program Translational Neuroscience (FTN), University Medical Center of the Johannes Gutenberg University, Mainz, Germany
| | - Nikos Evangelou
- Mental Health & Clinical Neuroscience Unit, University of Nottingham, Nottingham, UK
- Department of Neurology, Nottingham University Hospitals NHS Trust, Nottingham, UK
| | - Christian Enzinger
- Department of Neurology, Medical University of Graz, Graz, Austria
- Department of Radiology (Division of Neuroradiology, Vascular and Interventional Radiology), Medical University of Graz, Graz, Austria
| | - Antonio Gallo
- Department of Advanced Medical and Surgical Sciences, University of Campania 'Luigi Vanvitelli', Naples, Italy
| | - Afagh Garjani
- Mental Health & Clinical Neuroscience Unit, University of Nottingham, Nottingham, UK
- Department of Neurology, Nottingham University Hospitals NHS Trust, Nottingham, UK
| | - Sergiu Groppa
- Department of Neurology and Neuroimaging Center (NIC) of the Focus Program Translational Neuroscience (FTN), University Medical Center of the Johannes Gutenberg University, Mainz, Germany
| | - Shalom Haggiag
- Department of Neurosciences, San Camillo Forlanini Hospital, Rome, Italy
| | - Michael Khalil
- Department of Neurology, Medical University of Graz, Graz, Austria
| | - Matteo Lucchini
- Multiple Sclerosis Center, Fondazione Policlinico Universitario Agostino Gemelli IRCCS, Rome, Italy
- Centro di ricerca Sclerosi Multipla (CERSM), Università Cattolica del Sacro Cuore, Rome, Italy
| | - Massimiliano Mirabella
- Multiple Sclerosis Center, Fondazione Policlinico Universitario Agostino Gemelli IRCCS, Rome, Italy
- Centro di ricerca Sclerosi Multipla (CERSM), Università Cattolica del Sacro Cuore, Rome, Italy
| | - Xavier Montalban
- Centre d'Esclerosi Multiple de Catalunya (Cemcat), Department of Neurology/Neuroimmunology, Hospital Universitari Vall d'Hebron, Universitat Autonoma de Barcelona, Barcelona, Spain
| | - Carlo Pozzilli
- Department of Human Neurosciences, Sapienza University of Rome, Rome, Italy
| | - Paolo Preziosa
- Neurology Unit and Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Vita-Salute San Raffaele University, Milan, Italy
| | - Jordi Río
- Centre d'Esclerosi Multiple de Catalunya (Cemcat), Department of Neurology/Neuroimmunology, Hospital Universitari Vall d'Hebron, Universitat Autonoma de Barcelona, Barcelona, Spain
| | - Maria A Rocca
- Neurology Unit and Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Vita-Salute San Raffaele University, Milan, Italy
| | - Alex Rovira
- Section of Neuroradiology, Department of Radiology, Hospital Universitari Vall d'Hebron, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Maria L Stromillo
- Department of Medicine, Surgery and Neuroscience, University of Siena, Siena, Italy
| | - Mauro Zaffaroni
- Neuroimmunology Unit-Multiple Sclerosis Center, Hospital of Gallarate, ASST della Valle Olona, Gallarate, Italy
| | - Carla Tortorella
- Department of Neurosciences, San Camillo Forlanini Hospital, Rome, Italy
| | - Claudio Gasperini
- Department of Neurosciences, San Camillo Forlanini Hospital, Rome, Italy
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10
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Newsome SD, Binns C, Kaunzner UW, Morgan S, Halper J. No Evidence of Disease Activity (NEDA) as a Clinical Assessment Tool for Multiple Sclerosis: Clinician and Patient Perspectives [Narrative Review]. Neurol Ther 2023; 12:1909-1935. [PMID: 37819598 PMCID: PMC10630288 DOI: 10.1007/s40120-023-00549-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/19/2023] [Accepted: 09/19/2023] [Indexed: 10/13/2023] Open
Abstract
The emergence of high-efficacy therapies for multiple sclerosis (MS), which target inflammation more effectively than traditional disease-modifying therapies, has led to a shift in MS management towards achieving the outcome assessment known as no evidence of disease activity (NEDA). The most common NEDA definition, termed NEDA-3, is a composite of three related measures of disease activity: no clinical relapses, no disability progression, and no radiological activity. NEDA has been frequently used as a composite endpoint in clinical trials, but there is growing interest in its use as an assessment tool to help patients and healthcare professionals navigate treatment decisions in the clinic. Raising awareness about NEDA may therefore help patients and clinicians make more informed decisions around MS management and improve overall MS care. This review aims to explore the potential utility of NEDA as a clinical decision-making tool and treatment target by summarizing the literature on its current use in the context of the expanding treatment landscape. We identify current challenges to the use of NEDA in clinical practice and detail the proposed amendments, such as the inclusion of alternative outcomes and biomarkers, to broaden the clinical information captured by NEDA. These themes are further illustrated with the real-life perspectives and experiences of our two patient authors with MS. This review is intended to be an educational resource to support discussions between clinicians and patients on this evolving approach to MS-specialized care.
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Affiliation(s)
- Scott D Newsome
- Johns Hopkins University School of Medicine, 600 North Wolfe Street, Pathology 627, Baltimore, MD, 21287, USA.
| | - Cherie Binns
- Multiple Sclerosis Foundation, 6520 N Andrews Avenue, Fort Lauderdale, FL, 33309, USA
| | | | - Seth Morgan
- National Multiple Sclerosis Society, 1 M Street SE, Suite 510, Washington, DC, 20003, USA
| | - June Halper
- Consortium of Multiple Sclerosis Centers, 3 University Plaza Drive Suite A, Hackensack, NJ, 07601, USA
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11
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Schroyen G, Sleurs C, Ottenbourgs T, Leenaerts N, Nevelsteen I, Melis M, Smeets A, Deprez S, Sunaert S. Changes in leukoencephalopathy and serum neurofilament after (neo)adjuvant chemotherapy for breast cancer. Transl Oncol 2023; 37:101769. [PMID: 37651891 PMCID: PMC10480307 DOI: 10.1016/j.tranon.2023.101769] [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: 03/31/2023] [Revised: 08/21/2023] [Accepted: 08/21/2023] [Indexed: 09/02/2023] Open
Abstract
BACKGROUND Previous case studies have provided evidence for chemotherapy-induced leukoencephalopathy in patients with breast cancer. However, prospective research is lacking. Hence, we investigated leukoencephalopathy before and after chemotherapy and its association with a serum neuroaxonal damage marker. METHODS This prospective cohort study included 40 patients receiving chemotherapy for breast cancer, and two age- and education-matched control groups, recruited between 2018 and 2021 (31-64 years of age). The latter control groups consisted of 39 chemotherapy-naïve patients and 40 healthy women. Fluid-attenuated inversion-recovery magnetic resonance imaging was used for lesion volumetry (total, juxtacortical, periventricular, infratentorial, and deep white matter) and blood serum to measure neurofilament light chain (NfL) levels. Acquisition took place pre-chemotherapy and three months and one-year post-chemotherapy, or at corresponding intervals. Within/between group differences were compared using robust mixed-effects modeling, and associations between total lesion volume and serum-NfL with linear regression. RESULTS Stronger increases in deep white matter lesion volumes were observed shortly post-chemotherapy, compared with healthy women (ßstandardized=0.09, pFDR<0.001). Increases in total lesion volume could mainly be attributed to enlargement of existing lesions (mean±SD, 0.12±0.16 mL), rather than development of new lesions (0.02±0.02 mL). A stronger increase in serum-NfL concentration was observed shortly post-chemotherapy compared with both control groups (ß>0.70, p<0.004), neither of which showed any changes over time, whereas a decrease was observed compared with healthy women one-year post-chemotherapy (ß=-0.54, p = 0.002). Serum-NfL concentrations were associated with lesion volume one-year post-chemotherapy (or at matched timepoint; ß=0.36, p = 0.010), whereas baseline or short-term post-therapy levels or changes were not. CONCLUSION These results underscore the possibility of chemotherapy-induced leukoencephalopathy months post-treatment, as well as the added value of serum-NfL as a prognostic marker for peripheral/central neurotoxicity. TRANSLATIONAL RELEVANCE Previous case studies have provided evidence of chemotherapy-induced leukoencephalopathy in patients with breast cancer. However, prospective studies to estimate longitudinal changes are currently missing. In this study, we used longitudinal fluid-attenuated inversion-recovery magnetic resonance imaging to assess white matter lesion volumes in patients treated for non-metastatic breast cancer and healthy women. Our findings demonstrate that chemotherapy-treated patients exhibit stronger increases in lesion volumes compared with healthy women, specifically in deep white matter, at three months post-chemotherapy. Increases could mainly be attributed to enlargement of existing lesions, rather than development of new lesions. Last, serum concentrations of neurofilament light chain, a neuroaxonal damage marker, increased shortly after chemotherapy and long-term post-chemotherapy levels were associated with lesion volumes. These findings highlight the potential of this non-invasive serum marker as a prognostic marker for peripheral and/or central neurotoxicity. Implementation in clinical practice could aid in therapeutic decisions, assessing disease activity, or monitoring treatment response.
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Affiliation(s)
- Gwen Schroyen
- KU Leuven, Leuven Brain Institute, Leuven, Belgium; University Hospitals Leuven, Leuven Cancer Institute, Leuven, Belgium; KU Leuven, Department of Imaging and Pathology, Translational MRI, Leuven, Belgium
| | - Charlotte Sleurs
- KU Leuven, Leuven Brain Institute, Leuven, Belgium; University Hospitals Leuven, Leuven Cancer Institute, Leuven, Belgium; Tilburg University, Department of Cognitive Neuropsychology, Tilburg, the Netherlands; KU Leuven, Department of Oncology, Leuven, Belgium
| | - Tine Ottenbourgs
- KU Leuven, Department of Imaging and Pathology, Translational MRI, Leuven, Belgium
| | - Nicolas Leenaerts
- KU Leuven, Leuven Brain Institute, Leuven, Belgium; KU Leuven, Department of Neurosciences, Mind-Body Research, Leuven, Belgium; KU Leuven, University Psychiatric Center, Leuven, Belgium; University Hospitals Leuven, Department of Psychiatry, Leuven, Belgium
| | - Ines Nevelsteen
- University Hospitals Leuven, Leuven Cancer Institute, Leuven, Belgium; KU Leuven, Department of Oncology, Leuven, Belgium; University Hospitals Leuven, Department of Oncology, Surgical Oncology, Leuven, Belgium
| | - Michelle Melis
- KU Leuven, Leuven Brain Institute, Leuven, Belgium; University Hospitals Leuven, Leuven Cancer Institute, Leuven, Belgium; KU Leuven, Department of Imaging and Pathology, Translational MRI, Leuven, Belgium
| | - Ann Smeets
- University Hospitals Leuven, Leuven Cancer Institute, Leuven, Belgium; KU Leuven, Department of Oncology, Leuven, Belgium; University Hospitals Leuven, Department of Oncology, Surgical Oncology, Leuven, Belgium
| | - Sabine Deprez
- KU Leuven, Leuven Brain Institute, Leuven, Belgium; University Hospitals Leuven, Leuven Cancer Institute, Leuven, Belgium; KU Leuven, Department of Imaging and Pathology, Translational MRI, Leuven, Belgium.
| | - Stefan Sunaert
- KU Leuven, Leuven Brain Institute, Leuven, Belgium; KU Leuven, Department of Imaging and Pathology, Translational MRI, Leuven, Belgium; University Hospitals Leuven, Department of Radiology, Leuven, Belgium
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12
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Bazzurri V, Fiore A, Curti E, Tsantes E, Franceschini A, Granella F. Prevalence of 2-year "No evidence of disease activity" (NEDA-3 and NEDA-4) in relapsing-remitting multiple sclerosis. A real-world study. Mult Scler Relat Disord 2023; 79:105015. [PMID: 37769430 DOI: 10.1016/j.msard.2023.105015] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2023] [Revised: 09/08/2023] [Accepted: 09/17/2023] [Indexed: 09/30/2023]
Abstract
BACKGROUND No evidence of disease activity (NEDA) is becoming a gold standard in the evaluation of disease modifying therapies (DMT) in relapsing-remitting multiple sclerosis (RRMS). NEDA-3 status is the absence of relapses, new activity on brain MRI, and disability progression. NEDA-4 meets all NEDA-3 criteria plus lack of brain atrophy. OBJECTIVE Aim of this study was to investigate the prevalence of two-year NEDA-3, NEDA-4, six-month delayed NEDA-3 (6mdNEDA-3), and six-month delayed NEDA-4 (6mdNEDA-4) in a cohort of patients with RRMS. Six-month delayed measures were introduced to consider latency of action of drugs. METHODS Observational retrospective monocentric study. All the patients with RRMS starting DMT between 2015 and 2018, and with 2-year of follow-up, were included. Annualized brain volume loss (a-BVL) was calculated by SIENA software. RESULTS We included 108 patients, the majority treated with first line DMT. At 2-year follow-up, 35 % of patients were NEDA-3 (50 % 6mdNEDA-3), and 17 % NEDA-4 (28 % 6mdNEDA-4). Loss of NEDA-3 status was mainly driven by MRI activity (70 %), followed by relapses (56 %), and only minimally by disability progression (7 %). CONCLUSION In our cohort 2-year NEDA status, especially including lack of brain atrophy, was hard to achieve. Further studies are needed to establish the prognostic value of NEDA-3 and NEDA4 in the long-term follow-up.
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Affiliation(s)
- V Bazzurri
- Neurology Unit, Emergency Department, Guglielmo da Saliceto Hospital, Piacenza, Italy.
| | - A Fiore
- Department of Biomedical Metabolic and Neurosciences, University of Modena and Reggio Emilia, Italy
| | - E Curti
- Multiple Sclerosis Centre, Neurology Unit, Department of General Medicine, Parma University Hospital, Parma, Italy
| | - E Tsantes
- Multiple Sclerosis Centre, Neurology Unit, Department of General Medicine, Parma University Hospital, Parma, Italy
| | - A Franceschini
- Unit of Neurosciences, Department of Medicine and Surgery, University of Parma, Parma, Italy
| | - F Granella
- Multiple Sclerosis Centre, Neurology Unit, Department of General Medicine, Parma University Hospital, Parma, Italy; Unit of Neurosciences, Department of Medicine and Surgery, University of Parma, Parma, Italy
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13
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Amato MP, Bergamaschi R, Centonze D, Mirabella M, Marfia GA, Totaro R, Lus G, Brescia Morra V, Aguglia U, Comi C, Cavalla P, Zaffaroni M, Rovaris M, Grimaldi LM, Leoni S, Malucchi S, Baldi E, Romano M, Falcini M, Perini P, Assetta M, Portaccio E, Sommacal S, Olivieri N, Parodi F, Todaro DS, Grassivaro N, Farina A, Mondino MM, Filippi M, Trojano M. Effectiveness of teriflunomide on No Evidence of Disease Activity and cognition in relapsing remitting multiple sclerosis: results of the NEDA3PLUS study. J Neurol 2023; 270:4687-4696. [PMID: 37405689 PMCID: PMC10511573 DOI: 10.1007/s00415-023-11820-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2023] [Revised: 06/08/2023] [Accepted: 06/11/2023] [Indexed: 07/06/2023]
Abstract
BACKGROUND Cognitive impairment (CI) is a prevalent and debilitating manifestation of multiple sclerosis (MS); however, it is not included in the widely used concept of No Evidence of Disease Activity (NEDA-3). We expanded the NEDA-3 concept to NEDA-3 + by encompassing CI assessed through the Symbol Digit Modality Test (SDMT) and evaluated the effect of teriflunomide on NEDA3 + in patients treated in a real-world setting. The value of NEDA-3 + in predicting disability progression was also assessed. METHODS This 96-weeks observational study enrolled patients already on treatment with teriflunomide for ≥ 24 weeks. The predictiveness of NEDA-3 and NEDA-3 + at 48 weeks on the change in motor disability at 96 weeks was compared through a two-sided McNemar test. RESULTS The full analysis set (n = 128; 38% treatment naïve) featured relatively low level of disability (baseline EDSS = 1.97 ± 1.33). NEDA-3 and NEDA-3 + statuses were achieved by 82.8% and 64.8% of patients, respectively at 48 weeks vs. baseline, and by 57.0% and 49.2% of patients, respectively at 96 weeks vs. baseline. All patients except one were free of disability progression at Week 96, and NEDA-3 and NEDA-3 + were equally predictive. Most patients were free of relapse (87.5%), disability progression (94.5%) and new MRI activity (67.2%) comparing 96 weeks with baseline. SDMT scores were stable in patients with baseline score ˃35 and improved significantly in those with baseline score ≤ 35. Treatment persistence was high (81.0% at Week 96). CONCLUSION Teriflunomide confirmed its real-world efficacy and was found to have a potentially beneficial effect on cognition.
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Affiliation(s)
- Maria Pia Amato
- Department of NEUROFARBA, Section of Neurosciences, University of Florence, Florence, Italy
- IRCCS Fondazione Don Carlo Gnocchi, Florence, Italy
| | | | - Diego Centonze
- Unit of Neurology and Neurorehabilitation, IRCCS Neuromed, Pozzilli, Italy
| | - Massimiliano Mirabella
- Fondazione Policlinico Universitario 'Agostino Gemelli' IRCCS, Neurology Unit, Rome, Italy
- Centro di Ricerca Sclerosi Multipla (CERSM), Università Cattolica del Sacro Cuore, Rome, Italy
| | - Girolama Alessandra Marfia
- Multiple Sclerosis Clinical and Research Unit, Department of Systems Medicine, University of Rome Tor Vergata, Rome, Italy
| | - Rocco Totaro
- Demyelinating Disease Center, San Salvatore Hospital, L'Aquila, Italy
| | - Giacomo Lus
- Department of Advanced Medical and Surgical Sciences, University of Campania Luigi Vanvitelli, Naples, Italy
| | - Vincenzo Brescia Morra
- Department of Neuroscience, Reproductive Science and Odontostomatology, University Federico II, Multiple Sclerosis Clinical Care and Research Centre, Naples, Italy
| | - Umberto Aguglia
- Department of Medical and Surgical Sciences, "Magna Graecia" University, Catanzaro, Italy
- Regional Epilepsy Centre, Great Metropolitan Hospital, Reggio Calabria, Italy
| | - Cristoforo Comi
- Department of Translational Medicine and Interdisciplinary Research Center of Autoimmune Diseases, University of Piemonte Orientale, Novara, Italy
| | - Paola Cavalla
- Department of Neuroscience and Mental Health, City of Health and Science University Hospital of Turin, Multiple Sclerosis Center, Turin, Italy
| | - Mauro Zaffaroni
- ASST della Valle Olona, Hospital of Gallarate, Neuroimmunology Unit, Gallarate, Italy
| | - Marco Rovaris
- IRCCS Fondazione Don Carlo Gnocchi Onlus, Multiple Sclerosis Center, Milan, Italy
| | | | | | - Simona Malucchi
- University Hospital San Luigi Gonzaga, SCDO Neurologia-CRESM, Orbassano, Turin, Italy
| | - Eleonora Baldi
- Department of Neuroscience and Rehabilitation, S. Anna Hospital, Multiple Sclerosis Center, Ferrara, Italy
| | - Marcello Romano
- Neurology and Stroke Unit, Villa Sofia Cervello Hospital, Palermo, Italy
| | - Mario Falcini
- Santo Stefano Hospital, Neurology Unit, Prato, Italy
| | - Paola Perini
- University Hospital of Padua, Multiple Sclerosis Centre of the Veneto Region (CeSMuV), Padua, Italy
| | | | - Emilio Portaccio
- Department of NEUROFARBA, Section of Neurosciences, University of Florence, Florence, Italy
| | | | | | | | | | | | | | | | - Massimo Filippi
- IRCCS San Raffaele Scientific Institute, Neurology Unit, Milan, Italy
- IRCCS San Raffaele Scientific Institute, Neurorehabilitation Unit, Milan, Italy
- IRCCS San Raffaele Scientific Institute, Neurophysiology Service, Milan, Italy
- Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Neuroimaging Research Unit, Milan, Italy
- Vita-Salute San Raffaele University, Milan, Italy
| | - Maria Trojano
- School of Medicine, University "Aldo Moro" of Bari, Bari, Italy.
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Freeman SA, Lemarchant B, Alberto T, Boucher J, Outteryck O, Labalette M, Rogeau S, Dubucquoi S, Zéphir H. Assessing Sustained B-Cell Depletion and Disease Activity in a French Multiple Sclerosis Cohort Treated by Long-Term IV Anti-CD20 Antibody Therapy. Neurotherapeutics 2023; 20:1707-1722. [PMID: 37882961 PMCID: PMC10684468 DOI: 10.1007/s13311-023-01446-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 09/22/2023] [Indexed: 10/27/2023] Open
Abstract
Few studies have investigated sustained B-cell depletion after long-term intravenous (IV) anti-CD20 B-cell depleting therapy (BCDT) in multiple sclerosis (MS) with respect to strict and/or minimal disease activity. The main objective of this study was to investigate how sustained B-cell depletion after BCDT influences clinical and radiological stability as defined by "no evidence of disease activity" (NEDA-3) and "minimal evidence of disease activity" (MEDA) status in MS patients at 12 and 18 months. Furthermore, we assessed the frequency of serious adverse events (SAE), and the influence of prior lymphocytopenia-inducing treatment (LIT) on lymphocyte subset counts and gammaglobulins in MS patients receiving long-term BCDT. We performed a retrospective, prospectively collected, study in a cohort of 192 MS patients of all clinical phenotypes treated by BCDT between January 2014 and September 2021. Overall, 84.2% and 96.9% of patients attained NEDA-3 and MEDA status at 18 months, respectively. Sustained CD19+ depletion was observed in 85.8% of patients at 18 months. No significant difference was observed when comparing patients achieving either NEDA-3 or MEDA at 18 months and sustained B-cell depletion. Compared to baseline levels, IgM and IgG levels on BCDT significantly decreased at 6 months and 30 months, respectively. Patients receiving LIT prior to BCDT showed significant CD4+ lymphocytopenia and lower IgG levels compared to non-LIT patients. Grade 3 or above SAEs were rare. As nearly all patients achieved MEDA at 18 months, we suggest tailoring IV BCDT after 18 months given the occurrence of lymphocytopenia, hypogammaglobulinemia, and SAE after this time point.
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Affiliation(s)
- Sean A Freeman
- Department of Neurology, CRC-SEP, CHU of Lille, Lille, France.
| | - Bruno Lemarchant
- Department of Neurology, CRC-SEP, CHU of Lille, Lille, France
- Laboratory of Neuroinflammation and Multiple Sclerosis (NEMESIS), Univ. Lille, INSERM, CHU Lille, U1172, Lille, France
| | - Tifanie Alberto
- Department of Neurology, CRC-SEP, CHU of Lille, Lille, France
| | - Julie Boucher
- Department of Neurology, CRC-SEP, CHU of Lille, Lille, France
| | - Olivier Outteryck
- Laboratory of Neuroinflammation and Multiple Sclerosis (NEMESIS), Univ. Lille, INSERM, CHU Lille, U1172, Lille, France
- Department of Neuroradiology, CHU Lille, Roger Salengro Hospital, Lille, France
| | - Myriam Labalette
- Univ. Lille, INSERM, CHU Lille, U1286 - INFINITE - Institute for Translational Research in Inflammation, Lille, France
| | - Stéphanie Rogeau
- Univ. Lille, INSERM, CHU Lille, U1286 - INFINITE - Institute for Translational Research in Inflammation, Lille, France
| | - Sylvain Dubucquoi
- Univ. Lille, INSERM, CHU Lille, U1286 - INFINITE - Institute for Translational Research in Inflammation, Lille, France
| | - Hélène Zéphir
- Department of Neurology, CRC-SEP, CHU of Lille, Lille, France
- Laboratory of Neuroinflammation and Multiple Sclerosis (NEMESIS), Univ. Lille, INSERM, CHU Lille, U1172, Lille, France
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15
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Voigt I, Inojosa H, Wenk J, Akgün K, Ziemssen T. Building a monitoring matrix for the management of multiple sclerosis. Autoimmun Rev 2023; 22:103358. [PMID: 37178996 DOI: 10.1016/j.autrev.2023.103358] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2023] [Accepted: 05/09/2023] [Indexed: 05/15/2023]
Abstract
Multiple sclerosis (MS) has a longitudinal and heterogeneous course, with an increasing number of therapy options and associated risk profiles, leading to a constant increase in the number of parameters to be monitored. Even though important clinical and subclinical data are being generated, treating neurologists may not always be able to use them adequately for MS management. In contrast to the monitoring of other diseases in different medical fields, no target-based approach for a standardized monitoring in MS has been established yet. Therefore, there is an urgent need for a standardized and structured monitoring as part of MS management that is adaptive, individualized, agile, and multimodal-integrative. We discuss the development of an MS monitoring matrix which can help facilitate data collection over time from different dimensions and perspectives to optimize the treatment of people with MS (pwMS). In doing so, we show how different measurement tools can combined to enhance MS treatment. We propose to apply the concept of patient pathways to disease and intervention monitoring, not losing track of their interrelation. We also discuss the use of artificial intelligence (AI) to improve the quality of processes, outcomes, and patient safety, as well as personalized and patient-centered care. Patient pathways allow us to track the patient's journey over time and can always change (e.g., when there is a switch in therapy). They therefore may assist us in the continuous improvement of monitoring in an iterative process. Improving the monitoring process means improving the care of pwMS.
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Affiliation(s)
- Isabel Voigt
- Center of Clinical Neuroscience, Department of Neurology, Faculty of Medicine and University Hospital Carl Gustav Carus, TU Dresden, Dresden, Germany
| | - Hernan Inojosa
- Center of Clinical Neuroscience, Department of Neurology, Faculty of Medicine and University Hospital Carl Gustav Carus, TU Dresden, Dresden, Germany
| | - Judith Wenk
- Center of Clinical Neuroscience, Department of Neurology, Faculty of Medicine and University Hospital Carl Gustav Carus, TU Dresden, Dresden, Germany
| | - Katja Akgün
- Center of Clinical Neuroscience, Department of Neurology, Faculty of Medicine and University Hospital Carl Gustav Carus, TU Dresden, Dresden, Germany
| | - Tjalf Ziemssen
- Center of Clinical Neuroscience, Department of Neurology, Faculty of Medicine and University Hospital Carl Gustav Carus, TU Dresden, Dresden, Germany.
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16
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Amin NS, Abd El-Aziz MK, Hamed M, Moustafa RR, El Tayebi HM. Rs205764 and rs547311 in linc00513 may influence treatment responses in multiple sclerosis patients: A pharmacogenomics Egyptian study. Front Immunol 2023; 14:1087595. [PMID: 36883100 PMCID: PMC9985893 DOI: 10.3389/fimmu.2023.1087595] [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: 11/02/2022] [Accepted: 01/26/2023] [Indexed: 02/21/2023] Open
Abstract
Background Multiple sclerosis (MS) is characterized by a complex etiology that is reflected in the lack of consistently predictable treatment responses across patients of seemingly similar characteristics. Approaches to demystify the underlying predictors of aberrant treatment responses have made use of genome-wide association studies (GWAS), with imminent progress made in identifying single nucleotide polymorphisms (SNPs) associated with MS risk, disease progression, and treatment response. Ultimately, such pharmacogenomic studies aim to utilize the approach of personalized medicine to maximize patient benefit and minimize rate of disease progression. Objective Very limited research is available around the long intergenic non-coding RNA (linc)00513, recently being reported as a novel positive regulator of the type-1 interferon (IFN) pathway, following its overexpression in the presence of two polymorphisms: rs205764 and rs547311 in the promoter region of this gene. We attempt to provide data on the prevalence of genetic variations at rs205764 and rs547311 in Egyptian MS patients, and correlate these polymorphisms with the patients' responses to disease-modifying treatments. Methods Genomic DNA from 144 RRMS patients was isolated and analyzed for genotypes at the positions of interest on linc00513 using RT-qPCR. Genotype groups were compared with regards to their response to treatment; additional secondary clinical parameters including the estimated disability status score (EDSS), and onset of the disease were examined in relation to these polymorphisms. Results Polymorphisms at rs205764 were associated with a significantly higher response to fingolimod and a significantly lower response to dimethylfumarate. Moreover, the average EDSS of patients carrying polymorphisms at rs547311 was significantly higher, whereas no correlation appeared to exist with the onset of MS. Conclusion Understanding the complex interplay of factors influencing treatment response is pivotal in MS. One of the factors contributing to a patient's response to treatment, as well as disease disability, may be polymorphisms on non-coding genetic material, such as rs205764 and rs547311 on linc00513. Through this work, we propose that genetic polymorphisms may partially drive disease disability and inconsistent responses to treatment in MS; we also aim to draw attention towards genetic approaches, such as screening for specific polymorphisms, to possibly direct treatment choices in such a complex disease.
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Affiliation(s)
- Nada Sherif Amin
- Clinical Pharmacology and Pharmacogenomics Research Group, Department of Pharmacology and Toxicology, Faculty of Pharmacy and Biotechnology, German University in Cairo, Cairo, Egypt
| | - Mostafa K Abd El-Aziz
- Clinical Pharmacology and Pharmacogenomics Research Group, Department of Pharmacology and Toxicology, Faculty of Pharmacy and Biotechnology, German University in Cairo, Cairo, Egypt
| | - Mohamed Hamed
- Department of Neurology, Faculty of Medicine, Al-Azhar University, Cairo, Egypt
| | - Ramez Reda Moustafa
- Department of Neurology, Faculty of Medicine, Ain Shams University, Cairo, Egypt
| | - Hend M El Tayebi
- Clinical Pharmacology and Pharmacogenomics Research Group, Department of Pharmacology and Toxicology, Faculty of Pharmacy and Biotechnology, German University in Cairo, Cairo, Egypt
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17
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Camacho-Toledano C, Machín-Díaz I, Calahorra L, Cabañas-Cotillas M, Otaegui D, Castillo-Triviño T, Villar LM, Costa-Frossard L, Comabella M, Midaglia L, García-Domínguez JM, García-Arocha J, Ortega MC, Clemente D. Peripheral myeloid-derived suppressor cells are good biomarkers of the efficacy of fingolimod in multiple sclerosis. J Neuroinflammation 2022; 19:277. [PMCID: PMC9675277 DOI: 10.1186/s12974-022-02635-3] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2022] [Accepted: 10/30/2022] [Indexed: 11/21/2022] Open
Abstract
Background The increasing number of treatments that are now available to manage patients with multiple sclerosis (MS) highlights the need to develop biomarkers that can be used within the framework of individualized medicine. Fingolimod is a disease-modifying treatment that belongs to the sphingosine-1-phosphate receptor modulators. In addition to inhibiting T cell egress from lymph nodes, fingolimod promotes the immunosuppressive activity of myeloid-derived suppressor cells (MDSCs), whose monocytic subset (M-MDSCs) can be used as a biomarker of disease severity, as well as the degree of demyelination and extent of axonal damage in the experimental autoimmune encephalomyelitis (EAE) model of MS. In the present study, we have assessed whether the abundance of circulating M-MDSCs may represent a useful biomarker of fingolimod efficacy in EAE and in the clinical context of MS patients. Methods Treatment with vehicle or fingolimod was orally administered to EAE mice for 14 days in an individualized manner, starting the day when each mouse began to develop clinical signs. Peripheral blood from EAE mice was collected previous to treatment and human peripheral blood mononuclear cells (PBMCs) were collected from fingolimod to treat MS patients’ peripheral blood. In both cases, M-MDSCs abundance was analyzed by flow cytometry and its relationship with the future clinical affectation of each individual animal or patient was assessed. Results Fingolimod-treated animals presented a milder EAE course with less demyelination and axonal damage, although a few animals did not respond well to treatment and they invariably had fewer M-MDSCs prior to initiating the treatment. Remarkably, M-MDSC abundance was also found to be an important and specific parameter to distinguish EAE mice prone to better fingolimod efficacy. Finally, in a translational effort, M-MDSCs were quantified in MS patients at baseline and correlated with different clinical parameters after 12 months of fingolimod treatment. M-MDSCs at baseline were highly representative of a good therapeutic response to fingolimod, i.e., patients who met at least two of the criteria used to define non-evidence of disease activity-3 (NEDA-3) 12 months after treatment. Conclusion Our data indicate that M-MDSCs might be a useful predictive biomarker of the response of MS patients to fingolimod. Supplementary Information The online version contains supplementary material available at 10.1186/s12974-022-02635-3.
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Affiliation(s)
- Celia Camacho-Toledano
- grid.414883.20000 0004 1767 1847Neuroimmuno-Repair Group, Hospital Nacional de Parapléjicos-SESCAM, Finca La Peraleda s/n, 45071 Toledo, Spain
| | - Isabel Machín-Díaz
- grid.414883.20000 0004 1767 1847Neuroimmuno-Repair Group, Hospital Nacional de Parapléjicos-SESCAM, Finca La Peraleda s/n, 45071 Toledo, Spain
| | - Leticia Calahorra
- grid.414883.20000 0004 1767 1847Neuroimmuno-Repair Group, Hospital Nacional de Parapléjicos-SESCAM, Finca La Peraleda s/n, 45071 Toledo, Spain
| | - María Cabañas-Cotillas
- grid.414883.20000 0004 1767 1847Neuroimmuno-Repair Group, Hospital Nacional de Parapléjicos-SESCAM, Finca La Peraleda s/n, 45071 Toledo, Spain
| | - David Otaegui
- grid.432380.eMultiple Sclerosis Unit, Biodonostia Health Institute, 20014 Donostia-San Sebastián, Spain
| | - Tamara Castillo-Triviño
- grid.432380.eMultiple Sclerosis Unit, Biodonostia Health Institute, 20014 Donostia-San Sebastián, Spain ,grid.414651.30000 0000 9920 5292Neurology Department, Hospital Universitario Donostia, San Sebastián, Spain
| | - Luisa María Villar
- grid.411347.40000 0000 9248 5770Immunology Department, Hospital Universitario Ramón y Cajal, Instituto Ramón y Cajal de Investigación Sanitaria (IRYCIS), Madrid, Spain
| | - Lucienne Costa-Frossard
- grid.411347.40000 0000 9248 5770Immunology Department, Hospital Universitario Ramón y Cajal, Instituto Ramón y Cajal de Investigación Sanitaria (IRYCIS), Madrid, Spain ,grid.411347.40000 0000 9248 5770Multiple Sclerosis Unit, Neurology, Ramón y Cajal University Hospital, Madrid, Spain
| | - Manuel Comabella
- grid.411083.f0000 0001 0675 8654Neurology-Neuroimmunology Service, Centre d’Esclerosi Múltiple de Catalunya (Cemcat), Institut de Recerca Vall d’Hebron, Hospital Universitari Vall d’Hebron, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Luciana Midaglia
- grid.411083.f0000 0001 0675 8654Neurology-Neuroimmunology Service, Centre d’Esclerosi Múltiple de Catalunya (Cemcat), Institut de Recerca Vall d’Hebron, Hospital Universitari Vall d’Hebron, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - José Manuel García-Domínguez
- grid.410526.40000 0001 0277 7938Multiple Sclerosis Unit, Department of Neurology, Hospital General Universitario Gregorio Marañón, Madrid, Spain
| | - Jennifer García-Arocha
- grid.414883.20000 0004 1767 1847Neuroimmuno-Repair Group, Hospital Nacional de Parapléjicos-SESCAM, Finca La Peraleda s/n, 45071 Toledo, Spain
| | - María Cristina Ortega
- grid.414883.20000 0004 1767 1847Neuroimmuno-Repair Group, Hospital Nacional de Parapléjicos-SESCAM, Finca La Peraleda s/n, 45071 Toledo, Spain
| | - Diego Clemente
- grid.414883.20000 0004 1767 1847Neuroimmuno-Repair Group, Hospital Nacional de Parapléjicos-SESCAM, Finca La Peraleda s/n, 45071 Toledo, Spain
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Simonsen CS, Flemmen HØ, Broch L, Brekke K, Brunborg C, Berg-Hansen P, Celius EG. Rebaseline no evidence of disease activity (NEDA-3) as a predictor of long-term disease course in a Norwegian multiple sclerosis population. Front Neurol 2022; 13:1034056. [PMID: 36452173 PMCID: PMC9702815 DOI: 10.3389/fneur.2022.1034056] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2022] [Accepted: 10/24/2022] [Indexed: 08/15/2023] Open
Abstract
INTRODUCTION No evidence of disease activity with three components (NEDA-3) is achieved if the person with MS (pwMS) has no new MRI lesions, no new relapses and no change in Expanded disability status scale (EDSS) over 1 year. Whether NEDA-3 is a good tool in measuring disease activity is up for discussion, but it is superior to the individual parameters separately and user-friendly. There is disagreement on whether NEDA-3 is a good predictor of long-term disability. METHODS This is a retrospective cohort study using real-world data with limited selection bias from the complete MS population at two hospitals in the southeast of Norway. We included pwMS diagnosed between 2006 and 2017 who had enough information to determine time to failure of NEDA-3 after diagnosis. RESULTS Of 536 pwMS, only 38% achieved NEDA 1 year after diagnosis. PwMS achieving NEDA were more likely to be started on a high efficacy drug as the initial drug, but there were no demographic differences. Mean time to NEDA failure was 3.3 (95% CI 2.9-3.7) years. Starting a high efficiacy therapy was associated with an increased risk of sustaining NEDA as compared to those receiving moderate efficacy therapy. PwMS who achieved NEDA at year one had a mean time to EDSS 6 of 33.8 (95% CI 30.9-36.8) years vs. 30.8 (95% CI 25.0-36.6) years in pwMS who did not achieve NEDA, p < 0.001. When rebaselining NEDA 1 year after diagnosis, 52.2% achieved NEDA in the 1st year after rebaseline, mean time to NEDA failure was 3.4 (95% CI 3.0-3.7) years and mean time to EDSS 6 was 44.5 (95% CI 40.4-48.5) years in pwMS achieving NEDA vs. 29.6 (95% CI 24.2-35.0) years in pwMS not achieving NEDA, p < 0.001. After rebaseline, pwMS with a high efficacy therapy as the initial drug had a mean time from diagnosis to NEDA fail of 4.8 years (95% CI 3.9-5.8) vs. 3.1 years (95% CI 2.7-3.5) in pwMS started on a moderate efficacy therapy, p < 0.001. In pwMS with NEDA failure at year one, 70% failed one, 28% failed two and 2% failed three components. New MRI lesions were the most common cause of NEDA failure (63%), followed by new relapses (50%) and EDSS change (25%). CONCLUSION NEDA-3 from rebaseline after 1 year, once treatment is stabilized, can predict the long-term disease course in MS. Starting a high efficacy DMT is associated with longer time to NEDA failure than moderate therapies. Finally, most pwMS only fail one component and new MRI lesions are the most likely cause of NEDA failure.
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Affiliation(s)
| | - Heidi Øyen Flemmen
- Department of Neurology, Hospital Telemark HF, Skien, Norway
- Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Line Broch
- Department of Neurology, Vestre Viken Hospital Trust, Drammen, Norway
- Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Department of Neurology, Oslo University Hospital, Oslo, Norway
| | - Kamilla Brekke
- Department of Neurology, Vestre Viken Hospital Trust, Drammen, Norway
- Department of Neurology, Hospital Vestfold, Tønsberg, Norway
| | - Cathrine Brunborg
- Oslo Centre for Biostatistics and Epidemiology, Research Support Services, Oslo University Hospital, Oslo, Norway
| | - Pål Berg-Hansen
- Department of Neurology, Oslo University Hospital, Oslo, Norway
| | - Elisabeth Gulowsen Celius
- Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Department of Neurology, Oslo University Hospital, Oslo, Norway
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19
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Rotstein D, Solomon JM, Sormani MP, Montalban X, Ye XY, Dababneh D, Muccilli A, Saab G, Shah P. Association of NEDA-4 With No Long-term Disability Progression in Multiple Sclerosis and Comparison With NEDA-3: A Systematic Review and Meta-analysis. NEUROLOGY(R) NEUROIMMUNOLOGY & NEUROINFLAMMATION 2022; 9:9/6/e200032. [PMID: 36224046 PMCID: PMC9558627 DOI: 10.1212/nxi.0000000000200032] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/22/2022] [Accepted: 08/02/2022] [Indexed: 11/06/2022]
Abstract
Background and Objectives No evidence of disease activity (NEDA)-4 has been suggested as a treatment target for disease-modifying therapy (DMT) in relapsing-remitting multiple sclerosis (RRMS). However, the ability of NEDA-4 to discriminate long-term outcomes in MS and how its performance compares with NEDA-3 remain uncertain. We conducted a systematic review and meta-analysis to evaluate (1) the association between NEDA-4 and no long-term disability progression in MS and (2) the comparative performance of NEDA-3 and NEDA-4 in predicting no long-term disability progression. Methods English-language abstracts and manuscripts were systematically searched in MEDLINE, Embase, and the Cochrane databases from January 2006 to November 2021 and reviewed independently by 2 investigators. We selected studies that assessed NEDA-4 at 1 or 2 years after DMT start and had at least 4 years of follow-up for determination of no confirmed disability progression. We conducted a meta-analysis using random-effects model to determine the pooled odds ratio (OR) for no disability progression with NEDA-4 vs EDA-4. For the comparative analysis, we selected studies that evaluated both NEDA-3 and NEDA-4 with at least 4 years of follow-up and examined the difference in the association of NEDA-3 and NEDA-4 with no disability progression. Results Five studies of 1,000 patients (3 interferon beta and 2 fingolimod) met inclusion criteria for both objectives. The median duration of follow-up was 6 years (interquartile range: 4–6 years). The prevalence of NEDA-4 ranged from 4.2% to 13.9% on interferon beta therapy and 24.9% to 25.1% on fingolimod therapy. The pooled OR for no long-term confirmed disability progression with NEDA-4 vs EDA-4 was 2.14 (95% confidence interval: 1.36–3.37; I2 = 0). We did not observe any significant difference between NEDA-4 and NEDA-3 in the comparative analyses. Discussion In patients with RRMS, NEDA-4 at 1–2 years was associated with 2 times higher odds of no long-term disability progression, at 6 years compared with EDA-4, but offered no advantage over NEDA-3.
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Affiliation(s)
- Dalia Rotstein
- From the Department of Medicine, (D.R., A.M., G.S.), University of Toronto, Ontario, Canada; St. Michael's Hospital (D.R., A.M., G.S.), Toronto, Ontario, Canada; Department of Medicine, (J.M.S.), McMaster University, Hamilton, Ontario, Canada; Department of Health Sciences (M.P.S.), Section of Biostatistics, University of Genova, Italy; IRCCS Ospedale Policlinico San Martino (M.P.S.), Genova, Italy; Department of Neurology and Cemcat (X.M.), Hospital Universitari Vall d'Hebron, Universitat Autonoma de Barcelona, Barcelona; Department of Pediatrics (X.Y.Y., P.S.), Mount Sinai Hospital, Toronto, Canada; Columbia University Irving Medical Center (D.D.), Department of Neurology, New York City; York Presbyterian Hospital (NYP) (D.D.), New York City; and Institute of Health (P.S.), Policy, Management and Evaluation, University of Toronto, Canada.
| | - Jacqueline M Solomon
- From the Department of Medicine, (D.R., A.M., G.S.), University of Toronto, Ontario, Canada; St. Michael's Hospital (D.R., A.M., G.S.), Toronto, Ontario, Canada; Department of Medicine, (J.M.S.), McMaster University, Hamilton, Ontario, Canada; Department of Health Sciences (M.P.S.), Section of Biostatistics, University of Genova, Italy; IRCCS Ospedale Policlinico San Martino (M.P.S.), Genova, Italy; Department of Neurology and Cemcat (X.M.), Hospital Universitari Vall d'Hebron, Universitat Autonoma de Barcelona, Barcelona; Department of Pediatrics (X.Y.Y., P.S.), Mount Sinai Hospital, Toronto, Canada; Columbia University Irving Medical Center (D.D.), Department of Neurology, New York City; York Presbyterian Hospital (NYP) (D.D.), New York City; and Institute of Health (P.S.), Policy, Management and Evaluation, University of Toronto, Canada
| | - Maria Pia Sormani
- From the Department of Medicine, (D.R., A.M., G.S.), University of Toronto, Ontario, Canada; St. Michael's Hospital (D.R., A.M., G.S.), Toronto, Ontario, Canada; Department of Medicine, (J.M.S.), McMaster University, Hamilton, Ontario, Canada; Department of Health Sciences (M.P.S.), Section of Biostatistics, University of Genova, Italy; IRCCS Ospedale Policlinico San Martino (M.P.S.), Genova, Italy; Department of Neurology and Cemcat (X.M.), Hospital Universitari Vall d'Hebron, Universitat Autonoma de Barcelona, Barcelona; Department of Pediatrics (X.Y.Y., P.S.), Mount Sinai Hospital, Toronto, Canada; Columbia University Irving Medical Center (D.D.), Department of Neurology, New York City; York Presbyterian Hospital (NYP) (D.D.), New York City; and Institute of Health (P.S.), Policy, Management and Evaluation, University of Toronto, Canada
| | - Xavier Montalban
- From the Department of Medicine, (D.R., A.M., G.S.), University of Toronto, Ontario, Canada; St. Michael's Hospital (D.R., A.M., G.S.), Toronto, Ontario, Canada; Department of Medicine, (J.M.S.), McMaster University, Hamilton, Ontario, Canada; Department of Health Sciences (M.P.S.), Section of Biostatistics, University of Genova, Italy; IRCCS Ospedale Policlinico San Martino (M.P.S.), Genova, Italy; Department of Neurology and Cemcat (X.M.), Hospital Universitari Vall d'Hebron, Universitat Autonoma de Barcelona, Barcelona; Department of Pediatrics (X.Y.Y., P.S.), Mount Sinai Hospital, Toronto, Canada; Columbia University Irving Medical Center (D.D.), Department of Neurology, New York City; York Presbyterian Hospital (NYP) (D.D.), New York City; and Institute of Health (P.S.), Policy, Management and Evaluation, University of Toronto, Canada
| | - Xiang Y Ye
- From the Department of Medicine, (D.R., A.M., G.S.), University of Toronto, Ontario, Canada; St. Michael's Hospital (D.R., A.M., G.S.), Toronto, Ontario, Canada; Department of Medicine, (J.M.S.), McMaster University, Hamilton, Ontario, Canada; Department of Health Sciences (M.P.S.), Section of Biostatistics, University of Genova, Italy; IRCCS Ospedale Policlinico San Martino (M.P.S.), Genova, Italy; Department of Neurology and Cemcat (X.M.), Hospital Universitari Vall d'Hebron, Universitat Autonoma de Barcelona, Barcelona; Department of Pediatrics (X.Y.Y., P.S.), Mount Sinai Hospital, Toronto, Canada; Columbia University Irving Medical Center (D.D.), Department of Neurology, New York City; York Presbyterian Hospital (NYP) (D.D.), New York City; and Institute of Health (P.S.), Policy, Management and Evaluation, University of Toronto, Canada
| | - Dina Dababneh
- From the Department of Medicine, (D.R., A.M., G.S.), University of Toronto, Ontario, Canada; St. Michael's Hospital (D.R., A.M., G.S.), Toronto, Ontario, Canada; Department of Medicine, (J.M.S.), McMaster University, Hamilton, Ontario, Canada; Department of Health Sciences (M.P.S.), Section of Biostatistics, University of Genova, Italy; IRCCS Ospedale Policlinico San Martino (M.P.S.), Genova, Italy; Department of Neurology and Cemcat (X.M.), Hospital Universitari Vall d'Hebron, Universitat Autonoma de Barcelona, Barcelona; Department of Pediatrics (X.Y.Y., P.S.), Mount Sinai Hospital, Toronto, Canada; Columbia University Irving Medical Center (D.D.), Department of Neurology, New York City; York Presbyterian Hospital (NYP) (D.D.), New York City; and Institute of Health (P.S.), Policy, Management and Evaluation, University of Toronto, Canada
| | - Alexandra Muccilli
- From the Department of Medicine, (D.R., A.M., G.S.), University of Toronto, Ontario, Canada; St. Michael's Hospital (D.R., A.M., G.S.), Toronto, Ontario, Canada; Department of Medicine, (J.M.S.), McMaster University, Hamilton, Ontario, Canada; Department of Health Sciences (M.P.S.), Section of Biostatistics, University of Genova, Italy; IRCCS Ospedale Policlinico San Martino (M.P.S.), Genova, Italy; Department of Neurology and Cemcat (X.M.), Hospital Universitari Vall d'Hebron, Universitat Autonoma de Barcelona, Barcelona; Department of Pediatrics (X.Y.Y., P.S.), Mount Sinai Hospital, Toronto, Canada; Columbia University Irving Medical Center (D.D.), Department of Neurology, New York City; York Presbyterian Hospital (NYP) (D.D.), New York City; and Institute of Health (P.S.), Policy, Management and Evaluation, University of Toronto, Canada
| | - Georges Saab
- From the Department of Medicine, (D.R., A.M., G.S.), University of Toronto, Ontario, Canada; St. Michael's Hospital (D.R., A.M., G.S.), Toronto, Ontario, Canada; Department of Medicine, (J.M.S.), McMaster University, Hamilton, Ontario, Canada; Department of Health Sciences (M.P.S.), Section of Biostatistics, University of Genova, Italy; IRCCS Ospedale Policlinico San Martino (M.P.S.), Genova, Italy; Department of Neurology and Cemcat (X.M.), Hospital Universitari Vall d'Hebron, Universitat Autonoma de Barcelona, Barcelona; Department of Pediatrics (X.Y.Y., P.S.), Mount Sinai Hospital, Toronto, Canada; Columbia University Irving Medical Center (D.D.), Department of Neurology, New York City; York Presbyterian Hospital (NYP) (D.D.), New York City; and Institute of Health (P.S.), Policy, Management and Evaluation, University of Toronto, Canada
| | - Prakesh Shah
- From the Department of Medicine, (D.R., A.M., G.S.), University of Toronto, Ontario, Canada; St. Michael's Hospital (D.R., A.M., G.S.), Toronto, Ontario, Canada; Department of Medicine, (J.M.S.), McMaster University, Hamilton, Ontario, Canada; Department of Health Sciences (M.P.S.), Section of Biostatistics, University of Genova, Italy; IRCCS Ospedale Policlinico San Martino (M.P.S.), Genova, Italy; Department of Neurology and Cemcat (X.M.), Hospital Universitari Vall d'Hebron, Universitat Autonoma de Barcelona, Barcelona; Department of Pediatrics (X.Y.Y., P.S.), Mount Sinai Hospital, Toronto, Canada; Columbia University Irving Medical Center (D.D.), Department of Neurology, New York City; York Presbyterian Hospital (NYP) (D.D.), New York City; and Institute of Health (P.S.), Policy, Management and Evaluation, University of Toronto, Canada
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Taloni A, Farrelly FA, Pontillo G, Petsas N, Giannì C, Ruggieri S, Petracca M, Brunetti A, Pozzilli C, Pantano P, Tommasin S. Evaluation of Disability Progression in Multiple Sclerosis via Magnetic-Resonance-Based Deep Learning Techniques. Int J Mol Sci 2022; 23:ijms231810651. [PMID: 36142563 PMCID: PMC9505100 DOI: 10.3390/ijms231810651] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2022] [Revised: 09/02/2022] [Accepted: 09/05/2022] [Indexed: 11/16/2022] Open
Abstract
Short-term disability progression was predicted from a baseline evaluation in patients with multiple sclerosis (MS) using their three-dimensional T1-weighted (3DT1) magnetic resonance images (MRI). One-hundred-and-eighty-one subjects diagnosed with MS underwent 3T-MRI and were followed up for two to six years at two sites, with disability progression defined according to the expanded-disability-status-scale (EDSS) increment at the follow-up. The patients’ 3DT1 images were bias-corrected, brain-extracted, registered onto MNI space, and divided into slices along coronal, sagittal, and axial projections. Deep learning image classification models were applied on slices and devised as ResNet50 fine-tuned adaptations at first on a large independent dataset and secondly on the study sample. The final classifiers’ performance was evaluated via the area under the curve (AUC) of the false versus true positive diagram. Each model was also tested against its null model, obtained by reshuffling patients’ labels in the training set. Informative areas were found by intersecting slices corresponding to models fulfilling the disability progression prediction criteria. At follow-up, 34% of patients had disability progression. Five coronal and five sagittal slices had one classifier surviving the AUC evaluation and null test and predicted disability progression (AUC > 0.72 and AUC > 0.81, respectively). Likewise, fifteen combinations of classifiers and axial slices predicted disability progression in patients (AUC > 0.69). Informative areas were the frontal areas, mainly within the grey matter. Briefly, 3DT1 images may give hints on disability progression in MS patients, exploiting the information hidden in the MRI of specific areas of the brain.
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Affiliation(s)
- Alessandro Taloni
- Institute for Complex Systems, National Research Council (ISC-CNR), 00185 Rome, Italy
| | | | - Giuseppe Pontillo
- Department of Advanced Biomedical Sciences, Federico II University of Naples, 80131 Naples, Italy
- Department of Electrical Engineering and Information Technology, Federico II University of Naples, 80125 Naples, Italy
| | - Nikolaos Petsas
- Department of Radiology, IRCCS NEUROMED, 86077 Pozzilli, Italy
| | - Costanza Giannì
- Department of Human Neurosciences, Sapienza University of Rome, 00185 Rome, Italy
| | - Serena Ruggieri
- Department of Human Neurosciences, Sapienza University of Rome, 00185 Rome, Italy
- Neuroimmunology Unit, IRCSS Fondazione Santa Lucia, 00179 Rome, Italy
| | - Maria Petracca
- Department of Human Neurosciences, Sapienza University of Rome, 00185 Rome, Italy
- Department of Neuroscience, Reproductive Sciences and Odontostomatology, Federico II University of Naples, 80131 Naples, Italy
| | - Arturo Brunetti
- Department of Advanced Biomedical Sciences, Federico II University of Naples, 80131 Naples, Italy
| | - Carlo Pozzilli
- Department of Human Neurosciences, Sapienza University of Rome, 00185 Rome, Italy
| | - Patrizia Pantano
- Department of Radiology, IRCCS NEUROMED, 86077 Pozzilli, Italy
- Department of Human Neurosciences, Sapienza University of Rome, 00185 Rome, Italy
| | - Silvia Tommasin
- Department of Human Neurosciences, Sapienza University of Rome, 00185 Rome, Italy
- Correspondence:
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21
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Rotstein D, Solomon JM, Sormani MP, Montalban X, Ye XY, Dababneh D, Muccilli A, Shah P. Association of No Evidence of Disease Activity With No Long-term Disability Progression in Multiple Sclerosis: A Systematic Review and Meta-analysis. Neurology 2022; 99:e209-e220. [PMID: 35473761 DOI: 10.1212/wnl.0000000000200549] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2021] [Accepted: 03/02/2022] [Indexed: 11/15/2022] Open
Abstract
BACKGROUND AND OBJECTIVES We conducted a systematic review and meta-analysis to evaluate the relationship between no evidence of disease activity (NEDA) and no long-term disability progression on low- and high-efficacy therapy in relapsing-remitting multiple sclerosis (RRMS). METHODS MEDLINE, Embase, and the Cochrane Database were searched from January 1, 2006, to January 26, 2021. We selected studies that evaluated NEDA-3 (no relapse, new MRI lesion, or confirmed disability progression) at 1 or 2 years and had a minimum of 4 years of follow-up for determination of disability progression. Data were extracted by 2 independent reviewers and were meta-analyzed with a random-effects model. Primary outcome of no disability progression was defined as no confirmed progression on the Expanded Disability Status Scale during follow-up. We assessed the odds ratio (OR) for no disability progression with NEDA vs evidence of disease activity (EDA). Positive predictive value (PPV) of NEDA for no disability progression was summarized for studies with prevalence of no progression >80% vs ≤80% separately. RESULTS We included 29 studies in our qualitative synthesis, of which 27 (16 low efficacy, 11 high efficacy) were included in the meta-analysis (N = 10,935 participants). Median follow-up was 5.6 years (interquartile range 4.3-8.0 years). The pooled ORs for no progression with NEDA-3 vs EDA were 2.32 (95% CI 1.58-3.42; I 2 = 73%) for low-efficacy therapy and 3.19 (95% CI 1.86-5.47; I 2 = 86%) for high-efficacy therapy. Among studies with prevalence of no progression at follow-up >80%, the pooled PPV for low efficacy therapy was 91% (95% CI 89%-93%) and for high-efficacy therapy was 92% (95% CI 88%-94%). Among studies with prevalence of no progression ≤80%, the pooled PPV for low-efficacy therapy was 81% (95% CI 75%-86%) and for high-efficacy therapy was 86% (95% CI 80%-90%). DISCUSSION NEDA-3 is associated with no long-term disability progression in RRMS on both low- and high-efficacy therapies. Further studies of early composite outcome measures incorporating easily measurable biomarkers and longer follow-up may help to improve the prognostic value of NEDA-3 in RRMS. TRIAL REGISTRATION INFORMATION International Prospective Register of Systematic Reviews Identifier: CRD42020189316.
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Affiliation(s)
- Dalia Rotstein
- From the Department of Medicine (D.R., A.M.), University of Toronto; St. Michael's Hospital (D.R., A.M.), Toronto; Department of Medicine (J.M.S.), McMaster University, Hamilton, Ontario, Canada; Section of Biostatistics (M.P.S.), Department of Health Sciences, University of Genova; IRCCS Ospedale Policlinico San Martino (M.P.S.), Genova, Italy; Department of Neurology (X.M.), Cemcat, Hospital Universitari Vall d-Hebron, Universitat Autonoma de Barcelona, Spain; Department of Pediatrics (X.Y.Y., P.S.), Mount Sinai Hospital, Toronto, Ontario, Canada; Department of Neurology (D.D.), Columbia University Irving Medical Center; New York Presbyterian Hospital (D.D.), New York City; and Institute of Health, Policy, Management and Evaluation (P.S.), University of Toronto, Ontario, Canada.
| | - Jacqueline Madeleine Solomon
- From the Department of Medicine (D.R., A.M.), University of Toronto; St. Michael's Hospital (D.R., A.M.), Toronto; Department of Medicine (J.M.S.), McMaster University, Hamilton, Ontario, Canada; Section of Biostatistics (M.P.S.), Department of Health Sciences, University of Genova; IRCCS Ospedale Policlinico San Martino (M.P.S.), Genova, Italy; Department of Neurology (X.M.), Cemcat, Hospital Universitari Vall d-Hebron, Universitat Autonoma de Barcelona, Spain; Department of Pediatrics (X.Y.Y., P.S.), Mount Sinai Hospital, Toronto, Ontario, Canada; Department of Neurology (D.D.), Columbia University Irving Medical Center; New York Presbyterian Hospital (D.D.), New York City; and Institute of Health, Policy, Management and Evaluation (P.S.), University of Toronto, Ontario, Canada
| | - Maria Pia Sormani
- From the Department of Medicine (D.R., A.M.), University of Toronto; St. Michael's Hospital (D.R., A.M.), Toronto; Department of Medicine (J.M.S.), McMaster University, Hamilton, Ontario, Canada; Section of Biostatistics (M.P.S.), Department of Health Sciences, University of Genova; IRCCS Ospedale Policlinico San Martino (M.P.S.), Genova, Italy; Department of Neurology (X.M.), Cemcat, Hospital Universitari Vall d-Hebron, Universitat Autonoma de Barcelona, Spain; Department of Pediatrics (X.Y.Y., P.S.), Mount Sinai Hospital, Toronto, Ontario, Canada; Department of Neurology (D.D.), Columbia University Irving Medical Center; New York Presbyterian Hospital (D.D.), New York City; and Institute of Health, Policy, Management and Evaluation (P.S.), University of Toronto, Ontario, Canada
| | - Xavier Montalban
- From the Department of Medicine (D.R., A.M.), University of Toronto; St. Michael's Hospital (D.R., A.M.), Toronto; Department of Medicine (J.M.S.), McMaster University, Hamilton, Ontario, Canada; Section of Biostatistics (M.P.S.), Department of Health Sciences, University of Genova; IRCCS Ospedale Policlinico San Martino (M.P.S.), Genova, Italy; Department of Neurology (X.M.), Cemcat, Hospital Universitari Vall d-Hebron, Universitat Autonoma de Barcelona, Spain; Department of Pediatrics (X.Y.Y., P.S.), Mount Sinai Hospital, Toronto, Ontario, Canada; Department of Neurology (D.D.), Columbia University Irving Medical Center; New York Presbyterian Hospital (D.D.), New York City; and Institute of Health, Policy, Management and Evaluation (P.S.), University of Toronto, Ontario, Canada
| | - Xiang Y Ye
- From the Department of Medicine (D.R., A.M.), University of Toronto; St. Michael's Hospital (D.R., A.M.), Toronto; Department of Medicine (J.M.S.), McMaster University, Hamilton, Ontario, Canada; Section of Biostatistics (M.P.S.), Department of Health Sciences, University of Genova; IRCCS Ospedale Policlinico San Martino (M.P.S.), Genova, Italy; Department of Neurology (X.M.), Cemcat, Hospital Universitari Vall d-Hebron, Universitat Autonoma de Barcelona, Spain; Department of Pediatrics (X.Y.Y., P.S.), Mount Sinai Hospital, Toronto, Ontario, Canada; Department of Neurology (D.D.), Columbia University Irving Medical Center; New York Presbyterian Hospital (D.D.), New York City; and Institute of Health, Policy, Management and Evaluation (P.S.), University of Toronto, Ontario, Canada
| | - Dina Dababneh
- From the Department of Medicine (D.R., A.M.), University of Toronto; St. Michael's Hospital (D.R., A.M.), Toronto; Department of Medicine (J.M.S.), McMaster University, Hamilton, Ontario, Canada; Section of Biostatistics (M.P.S.), Department of Health Sciences, University of Genova; IRCCS Ospedale Policlinico San Martino (M.P.S.), Genova, Italy; Department of Neurology (X.M.), Cemcat, Hospital Universitari Vall d-Hebron, Universitat Autonoma de Barcelona, Spain; Department of Pediatrics (X.Y.Y., P.S.), Mount Sinai Hospital, Toronto, Ontario, Canada; Department of Neurology (D.D.), Columbia University Irving Medical Center; New York Presbyterian Hospital (D.D.), New York City; and Institute of Health, Policy, Management and Evaluation (P.S.), University of Toronto, Ontario, Canada
| | - Alexandra Muccilli
- From the Department of Medicine (D.R., A.M.), University of Toronto; St. Michael's Hospital (D.R., A.M.), Toronto; Department of Medicine (J.M.S.), McMaster University, Hamilton, Ontario, Canada; Section of Biostatistics (M.P.S.), Department of Health Sciences, University of Genova; IRCCS Ospedale Policlinico San Martino (M.P.S.), Genova, Italy; Department of Neurology (X.M.), Cemcat, Hospital Universitari Vall d-Hebron, Universitat Autonoma de Barcelona, Spain; Department of Pediatrics (X.Y.Y., P.S.), Mount Sinai Hospital, Toronto, Ontario, Canada; Department of Neurology (D.D.), Columbia University Irving Medical Center; New York Presbyterian Hospital (D.D.), New York City; and Institute of Health, Policy, Management and Evaluation (P.S.), University of Toronto, Ontario, Canada
| | - Prakesh Shah
- From the Department of Medicine (D.R., A.M.), University of Toronto; St. Michael's Hospital (D.R., A.M.), Toronto; Department of Medicine (J.M.S.), McMaster University, Hamilton, Ontario, Canada; Section of Biostatistics (M.P.S.), Department of Health Sciences, University of Genova; IRCCS Ospedale Policlinico San Martino (M.P.S.), Genova, Italy; Department of Neurology (X.M.), Cemcat, Hospital Universitari Vall d-Hebron, Universitat Autonoma de Barcelona, Spain; Department of Pediatrics (X.Y.Y., P.S.), Mount Sinai Hospital, Toronto, Ontario, Canada; Department of Neurology (D.D.), Columbia University Irving Medical Center; New York Presbyterian Hospital (D.D.), New York City; and Institute of Health, Policy, Management and Evaluation (P.S.), University of Toronto, Ontario, Canada
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22
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Lehnert T, Röver C, Köpke S, Rio J, Chard D, Fittipaldo AV, Friede T, Heesen C, Rahn AC. Immunotherapy for people with clinically isolated syndrome or relapsing-remitting multiple sclerosis: treatment response by demographic, clinical, and biomarker subgroups (PROMISE)-a systematic review protocol. Syst Rev 2022; 11:134. [PMID: 35778721 PMCID: PMC9250266 DOI: 10.1186/s13643-022-01997-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/07/2021] [Accepted: 05/28/2022] [Indexed: 11/18/2022] Open
Abstract
BACKGROUND Multiple sclerosis (MS) is an inflammatory and degenerative disease of the central nervous system with an increasing worldwide prevalence. Since 1993, more than 15 disease-modifying immunotherapies (DMTs) have been licenced and have shown moderate efficacy in clinical trials. Based on the heterogeneity of the disease and the partial effectiveness of therapies, a personalised medicine approach would be valuable taking individual prognosis and suitability of a chosen therapy into account to gain the best possible treatment effect. The primary objective of this review is to assess the differential treatment effects of all approved DMTs in subgroups of adults with clinically isolated syndrome or relapsing forms of MS. We will analyse possible treatment effect modifiers (TEM) defined by baseline demographic characteristics (gender, age), and diagnostic (i.e. MRI measures) and clinical (i.e. relapses, disability level) measures of MS disease activity. METHODS We will include all published and accessible unpublished primary and secondary analyses of randomised controlled trials (RCTs) with a follow-up of at least 12 months investigating the efficacy of at least one approved DMT, with placebo or other approved DMTs as control intervention(s) in subgroups of trial participants. As the primary outcome, we will address disability as defined by the Expanded Disability Status Scale or multiple sclerosis functional composite scores followed by relapse frequency, quality of life measures, and side effects. MRI data will be analysed as secondary outcomes. MEDLINE, EMBASE, CINAHL, LILACS, CENTRAL and major trial registers will be searched for suitable studies. Titles and abstracts and full texts will be screened by two persons independently using Covidence. The risk of bias will be analysed based on the Cochrane "Risk of Bias 2" tool, and the certainty of evidence will be assessed using GRADE. Treatment effects will be reported as rate ratio or odds ratio. Primary analyses will follow the intention-to-treat principle. Meta-analyses will be carried out using random-effects models. DISCUSSION Given that individual patient data from clinical studies are often not available, the review will allow to analyse the evidence on TEM in MS immunotherapy and thus support clinical decision making in individual cases. SYSTEMATIC REVIEW REGISTRATION PROSPERO CRD42021279665 .
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Affiliation(s)
- Thomas Lehnert
- Institute of Neuroimmunology and Multiple Sclerosis, University Medical Center Hamburg-Eppendorf (UKE), Hamburg, Germany
| | - Christian Röver
- Department of Medical Statistics, University Medical Center Göttingen, Göttingen, Germany
| | - Sascha Köpke
- Institute of Nursing Science, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
| | - Jordi Rio
- Neurology/Neuroimmunology, Centre d’Esclerosi Multiple de Catalunya (Cemcat), Hospital Universitari Vall d’Hebron, Universitat Autonoma de Barcelona, Barcelona, Spain
| | - Declan Chard
- Department of Neuroinflammation, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, UK
- National Institute for Health Research (NIHR), University College London Hospitals (UCLH) Biomedical Research Centre, London, UK
| | - Andrea V. Fittipaldo
- Department of Oncology, Istituto Ricerche Farmacologiche “Mario Negri” IRCCS, Milano, Italy
| | - Tim Friede
- Department of Medical Statistics, University Medical Center Göttingen, Göttingen, Germany
| | - Christoph Heesen
- Institute of Neuroimmunology and Multiple Sclerosis, University Medical Center Hamburg-Eppendorf (UKE), Hamburg, Germany
| | - Anne C. Rahn
- Institute of Neuroimmunology and Multiple Sclerosis, University Medical Center Hamburg-Eppendorf (UKE), Hamburg, Germany
- Institute for Social Medicine and Epidemiology, Nursing Research Unit, University of Lübeck, Lübeck, Germany
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23
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Basu S, Munafo A, Ben‐Amor A, Roy S, Girard P, Terranova N. Predicting disease activity in patients with multiple sclerosis: An explainable machine‐learning approach in the Mavenclad trials. CPT Pharmacometrics Syst Pharmacol 2022; 11:843-853. [PMID: 35521742 PMCID: PMC9286719 DOI: 10.1002/psp4.12796] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2021] [Revised: 02/04/2022] [Accepted: 03/09/2022] [Indexed: 11/09/2022] Open
Abstract
Multiple sclerosis (MS) is among the most common autoimmune disabling neurological conditions of young adults and affects more than 2.3 million people worldwide. Predicting future disease activity in patients with MS based on their pathophysiology and current treatment is pivotal to orientate future treatment. In this respect, we used machine learning to predict disease activity status in patients with MS and identify the most predictive covariates of this activity. The analysis is conducted on a pooled population of 1935 patients enrolled in three cladribine tablets clinical trials with different outcomes: relapsing–remitting MS (from CLARITY and CLARITY‐Extension trials) and patients experiencing a first demyelinating event (from the ORACLE‐MS trial). We applied gradient‐boosting (from XgBoost library) and Shapley Additive Explanations (SHAP) methods to identify patients' covariates that predict disease activity 3 and 6 months before their clinical observation, including patient baseline characteristics, longitudinal magnetic resonance imaging readouts, and neurological and laboratory measures. The most predictive covariates for early identification of disease activity in patients were found to be treatment duration, higher number of new combined unique active lesion count, higher number of new T1 hypointense black holes, and higher age‐related MS severity score. The outcome of this analysis improves our understanding of the mechanism of onset of disease activity in patients with MS by allowing their early identification in clinical settings and prompting preventive measures, therapeutic interventions, or more frequent patient monitoring.
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Affiliation(s)
- Sreetama Basu
- Merck Institute for Pharmacometrics, Merck Serono S.A. (an affiliate of Merck KGaA, Darmstadt, Germany) Lausanne Switzerland
| | - Alain Munafo
- Merck Institute for Pharmacometrics, Merck Serono S.A. (an affiliate of Merck KGaA, Darmstadt, Germany) Lausanne Switzerland
| | | | - Sanjeev Roy
- Ares Trading SA (an affiliate of Merck KGaA, Darmstadt, Germany) Eysins Switzerland
| | - Pascal Girard
- Merck Institute for Pharmacometrics, Merck Serono S.A. (an affiliate of Merck KGaA, Darmstadt, Germany) Lausanne Switzerland
| | - Nadia Terranova
- Merck Institute for Pharmacometrics, Merck Serono S.A. (an affiliate of Merck KGaA, Darmstadt, Germany) Lausanne Switzerland
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Hirata T, Itokazu T, Sasaki A, Sugihara F, Yamashita T. Humanized Anti-RGMa Antibody Treatment Promotes Repair of Blood-Spinal Cord Barrier Under Autoimmune Encephalomyelitis in Mice. Front Immunol 2022; 13:870126. [PMID: 35784362 PMCID: PMC9241446 DOI: 10.3389/fimmu.2022.870126] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2022] [Accepted: 05/10/2022] [Indexed: 11/13/2022] Open
Abstract
The lack of established biomarkers which reflect dynamic neuropathological alterations in multiple sclerosis (MS) makes it difficult to determine the therapeutic response to the tested drugs and to identify the key biological process that mediates the beneficial effect of them. In the present study, we applied high-field MR imaging in locally-induced experimental autoimmune encephalomyelitis (EAE) mice to evaluate dynamic changes following treatment with a humanized anti-repulsive guidance molecule-a (RGMa) antibody, a potential drug for MS. Based on the longitudinal evaluation of various MRI parameters including white matter, axon, and myelin integrity as well as blood-spinal cord barrier (BSCB) disruption, anti-RGMa antibody treatment exhibited a strong and prompt therapeutic effect on the disrupted BSCB, which was paralleled by functional improvement. The antibody’s effect on BSCB repair was also suggested via GeneChip analysis. Moreover, immunohistochemical analysis revealed that EAE-induced vascular pathology which is characterized by aberrant thickening of endothelial cells and perivascular type I/IV collagen deposits were attenuated by anti-RGMa antibody treatment, further supporting the idea that the BSCB is one of the key therapeutic targets of anti-RGMa antibody. Importantly, the extent of BSCB disruption detected by MRI could predict late-phase demyelination, and the predictability of myelin integrity based on the extent of acute-phase BSCB disruption was compromised following anti-RGMa antibody treatment. These results strongly support the concept that longitudinal MRI with simultaneous DCE-MRI and DTI analysis can be used as an imaging biomarker and is useful for unbiased prioritization of the key biological process that mediates the therapeutic effect of tested drugs.
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Affiliation(s)
- Takeshi Hirata
- Department of Neuro-Medical Science, Graduate School of Medicine, Osaka University, Suita, Japan
- Sohyaku, Innovative Research Division, Mitsubishi Tanabe Pharma Corporation, Yokohama, Japan
| | - Takahide Itokazu
- Department of Neuro-Medical Science, Graduate School of Medicine, Osaka University, Suita, Japan
- Department of Molecular Neuroscience, Graduate School of Medicine, Osaka University, Suita, Japan
- *Correspondence: Toshihide Yamashita, ; Takahide Itokazu,
| | - Atsushi Sasaki
- Department of Neuro-Medical Science, Graduate School of Medicine, Osaka University, Suita, Japan
- Sohyaku, Innovative Research Division, Mitsubishi Tanabe Pharma Corporation, Yokohama, Japan
| | - Fuminori Sugihara
- Central Instrumentation Laboratory, Research Institute for Microbial Diseases, Osaka University, Suita, Japan
| | - Toshihide Yamashita
- Department of Neuro-Medical Science, Graduate School of Medicine, Osaka University, Suita, Japan
- Department of Molecular Neuroscience, Graduate School of Medicine, Osaka University, Suita, Japan
- Department of Molecular Neuroscience, World Premier International Research Center Initiative (WPI)-Immunology Frontier Research Center, Osaka University, Suita, Japan
- *Correspondence: Toshihide Yamashita, ; Takahide Itokazu,
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25
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Danieli L, Roccatagliata L, Distefano D, Prodi E, Riccitelli GC, Diociasi A, Carmisciano L, Cianfoni A, Bartalena T, Kaelin-Lang A, Gobbi C, Zecca C, Pravatà E. Nonlesional Sources of Contrast Enhancement on Postgadolinium "Black-Blood" 3D T1-SPACE Images in Patients with Multiple Sclerosis. AJNR Am J Neuroradiol 2022; 43:872-880. [PMID: 35618421 DOI: 10.3174/ajnr.a7529] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2021] [Accepted: 04/08/2022] [Indexed: 11/07/2022]
Abstract
BACKGROUND AND PURPOSE We hypothesized that 3D T1-TSE "black-blood" images may carry an increased risk of contrast-enhancing lesion misdiagnosis in patients with MS because of the misinterpretation of intraparenchymal vein enhancement. Thus, the occurrence of true-positive and false-positive findings was compared between standard MPRAGE and volumetric interpolated brain examination techniques. MATERIALS AND METHODS Sampling perfection with application-optimized contrasts by using different flip-angle evolution (SPACE) images obtained from 232 patients with MS, clinically isolated syndrome, or radiologically isolated syndrome were compared with standard MPRAGE and volumetric interpolated brain examination images. The intraparenchymal vein contrast-to-noise ratio was estimated at the level of the thalami. Contrast-enhancing lesions were blindly detected by 2 expert readers and 1 beginner reader. True- and false-positives were determined by senior readers' consensus. True-positive and false-positive frequency differences and patient-level diagnosis probability were tested with the McNemar test and OR. The contrast-to-noise ratio and morphology were compared using the Mann-Whitney U and χ2 tests. RESULTS The intraparenchymal vein contrast-to-noise ratio was higher in SPACE than in MPRAGE and volumetric interpolated brain examination images (P < .001, both). There were 66 true-positives and 74 false-positives overall. SPACE detected more true-positive and false-positive results (P range < .001-.07) but did not increase the patient's true-positive likelihood (OR = 1 1.29, P = .478-1). However, the false-positive likelihood was increased (OR = 3.03-3.55, P = .008-.027). Venous-origin false-positives (n = 59) with contrast-to-noise ratio and morphology features similar to small-sized (≤14 mm3 P = .544) true-positives occurred more frequently in SPACE images (P < .001). CONCLUSIONS Small intraparenchymal veins may confound the diagnosis of enhancing lesions on postgadolinium black-blood SPACE images.
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Affiliation(s)
- L Danieli
- Form the Department of Neuroradiology (L.D., E. Prodi, A.C., E. Pravatà), Neurocenter of Southern Switzerland, Ente Ospedaliero Cantonale, Lugano, Switzerland
| | - L Roccatagliata
- Dipartimento di Scienze della Salute (L.R., A.D.), Università degli Studi di Genova, Genoa, Italy
| | | | - E Prodi
- Form the Department of Neuroradiology (L.D., E. Prodi, A.C., E. Pravatà), Neurocenter of Southern Switzerland, Ente Ospedaliero Cantonale, Lugano, Switzerland
| | - G C Riccitelli
- Department of Neurology (G.C.R., A.K.-L., C.G., C.Z., E. Pravatà), Neurocenter of Southern Switzerland, Ente Ospedaliero Cantonale, Lugano, Switzerland.,Faculty of Biomedical Sciences (G.C.R., A.C., A.K.-L., C.G., C,Z., E. Pravatà), Università della Svizzera Italiana, Lugano, Switzerland
| | - A Diociasi
- Dipartimento di Scienze della Salute (L.R., A.D.), Università degli Studi di Genova, Genoa, Italy
| | - L Carmisciano
- Department of Health Sciences, Section of Biostatistics (L.C.), Università degli Studi di Genova, Genoa, Italy
| | - A Cianfoni
- Form the Department of Neuroradiology (L.D., E. Prodi, A.C., E. Pravatà), Neurocenter of Southern Switzerland, Ente Ospedaliero Cantonale, Lugano, Switzerland.,Faculty of Biomedical Sciences (G.C.R., A.C., A.K.-L., C.G., C,Z., E. Pravatà), Università della Svizzera Italiana, Lugano, Switzerland
| | - T Bartalena
- Department of Radiology (T.B.), Pol. Zappi Bartalena, Imola, Italy
| | - A Kaelin-Lang
- Department of Neurology (G.C.R., A.K.-L., C.G., C.Z., E. Pravatà), Neurocenter of Southern Switzerland, Ente Ospedaliero Cantonale, Lugano, Switzerland.,Faculty of Biomedical Sciences (G.C.R., A.C., A.K.-L., C.G., C,Z., E. Pravatà), Università della Svizzera Italiana, Lugano, Switzerland
| | - C Gobbi
- Department of Neurology (G.C.R., A.K.-L., C.G., C.Z., E. Pravatà), Neurocenter of Southern Switzerland, Ente Ospedaliero Cantonale, Lugano, Switzerland.,Faculty of Biomedical Sciences (G.C.R., A.C., A.K.-L., C.G., C,Z., E. Pravatà), Università della Svizzera Italiana, Lugano, Switzerland
| | - C Zecca
- Department of Neurology (G.C.R., A.K.-L., C.G., C.Z., E. Pravatà), Neurocenter of Southern Switzerland, Ente Ospedaliero Cantonale, Lugano, Switzerland.,Faculty of Biomedical Sciences (G.C.R., A.C., A.K.-L., C.G., C,Z., E. Pravatà), Università della Svizzera Italiana, Lugano, Switzerland
| | - E Pravatà
- Form the Department of Neuroradiology (L.D., E. Prodi, A.C., E. Pravatà), Neurocenter of Southern Switzerland, Ente Ospedaliero Cantonale, Lugano, Switzerland .,Faculty of Biomedical Sciences (G.C.R., A.C., A.K.-L., C.G., C,Z., E. Pravatà), Università della Svizzera Italiana, Lugano, Switzerland
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26
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Versteegh MM, Huygens SA, Wokke BWH, Smolders J. Effectiveness and Cost-Effectiveness of 360 Disease-Modifying Treatment Escalation Sequences in Multiple Sclerosis. VALUE IN HEALTH : THE JOURNAL OF THE INTERNATIONAL SOCIETY FOR PHARMACOECONOMICS AND OUTCOMES RESEARCH 2022; 25:984-991. [PMID: 35667786 DOI: 10.1016/j.jval.2021.11.1363] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/14/2021] [Revised: 10/28/2021] [Accepted: 11/12/2021] [Indexed: 06/15/2023]
Abstract
OBJECTIVES The rapid expansion in treatment options for relapsing-remitting multiple sclerosis (RRMS) of the past decade requires clinical decision making on the sequential prescription of these treatments. Here, we compare 360 treatment escalation sequences for patients with RRMS in terms of health outcomes and societal costs in The Netherlands. METHODS We use a microsimulation model with a societal perspective, developed in collaboration with MS neurologists, to estimate the effectiveness and cost-effectiveness of 360 treatment sequences starting with first-line therapies in RRMS. This model integrated data on disease progression, disease-modifying treatment efficacy, clinical decision rules, age-dependent relapse rates, quality of life, healthcare, and societal costs. RESULTS Costs and health outcomes were overlapping among different treatment escalation sequences. In our model for RRMS treatment, optimal lifetime health outcomes (20.24 ± 1.43 quality-adjusted life-years [QALYs], 6.11 ± 0.30 relapses) were achieved with the sequence peginterferon-dimethyl fumarate-ocrelizumab-natalizumab-alemtuzumab. The most cost-effective sequence (peginterferon-glatiramer acetate-ocrelizumab-cladribine-alemtuzumab) yielded numerically worse health outcomes per patient (19.59 ± 1.43 QALYs, 6.64 ± 0.43 relapses), but resulted in €98 127 ± €19 134 less costs than the most effective treatment sequence. CONCLUSIONS Effectiveness estimates of treatments have overlapping confidence intervals but the treatment sequence that yields most QALYs is not the most cost-effective option, also when taking uncertainty into account. It is important that neurologists are aware of cost constraints and its relationship with prescription behavior, but treatment decisions should be individually tailored.
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Affiliation(s)
- Matthijs M Versteegh
- Institute for Medical Technology Assessment, Erasmus University Rotterdam, Rotterdam, The Netherlands.
| | - Simone A Huygens
- Institute for Medical Technology Assessment, Erasmus University Rotterdam, Rotterdam, The Netherlands
| | - Beatrijs W H Wokke
- MS Center ErasMS, Departments of Neurology and Immunology, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Joost Smolders
- MS Center ErasMS, Departments of Neurology and Immunology, Erasmus University Medical Center, Rotterdam, The Netherlands
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27
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Filippi M, Amato MP, Centonze D, Gallo P, Gasperini C, Inglese M, Patti F, Pozzilli C, Preziosa P, Trojano M. Early use of high-efficacy disease‑modifying therapies makes the difference in people with multiple sclerosis: an expert opinion. J Neurol 2022; 269:5382-5394. [PMID: 35608658 PMCID: PMC9489547 DOI: 10.1007/s00415-022-11193-w] [Citation(s) in RCA: 46] [Impact Index Per Article: 23.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2022] [Revised: 05/12/2022] [Accepted: 05/13/2022] [Indexed: 11/05/2022]
Abstract
Multiple sclerosis (MS) is a chronic and progressive neurological disease that is characterized by neuroinflammation, demyelination and neurodegeneration occurring from the earliest phases of the disease and that may be underestimated. MS patients accumulate disability through relapse-associated worsening or progression independent of relapse activity. Early intervention with high-efficacy disease-modifying therapies (HE-DMTs) may represent the best window of opportunity to delay irreversible central nervous system damage and MS-related disability progression by hindering underlying heterogeneous pathophysiological processes contributing to disability progression. In line with this, growing evidence suggests that early use of HE-DMTs is associated with a significant greater reduction not only of inflammatory activity (clinical relapses and new lesion formation at magnetic resonance imaging) but also of disease progression, in terms of accumulation of irreversible clinical disability and neurodegeneration compared to delayed HE-DMT use or escalation strategy. These beneficial effects seem to be associated with acceptable long-term safety risks, thus configuring this treatment approach as that with the most positive benefit/risk profile. Accordingly, it should be mandatory to treat people with MS early with HE-DMTs in case of prognostic factors suggestive of aggressive disease, and it may be advisable to offer an HE-DMT to MS patients early after diagnosis, taking into account drug safety profile, disease severity, clinical and/or radiological activity, and patient-related factors, including possible comorbidities, family planning, and patients’ preference in agreement with the EAN/ECTRIMS and AAN guidelines. Barriers for an early use of HE-DMTs include concerns for long-term safety, challenges in the management of treatment initiation and monitoring, negative MS patients’ preferences, restricted access to HE-DMTs according to guidelines and regulatory rules, and sustainability. However, these barriers do not apply to each HE-DMT and none of these appear insuperable.
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Affiliation(s)
- Massimo Filippi
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Via Olgettina, 60, 20132, Milan, Italy. .,Neurology Unit, IRCCS San Raffaele Scientific Institute, Via Olgettina, 60, 20132, Milan, Italy. .,Neurorehabilitation Unit, IRCCS San Raffaele Scientific Institute, Via Olgettina, 60, 20132, Milan, Italy. .,Neurophysiology Service, IRCCS San Raffaele Scientific Institute, Via Olgettina, 60, 20132, Milan, Italy. .,Vita-Salute San Raffaele University, Milan, Italy.
| | - Maria Pia Amato
- Department NEUROFARBA, University of Florence, Florence, Italy.,IRCCS Fondazione Don Carlo Gnocchi, Florence, Italy
| | - Diego Centonze
- Department of Systems Medicine, Tor Vergata University, Rome, Italy.,Unit of Neurology, IRCCS Neuromed, Pozzilli, IS, Italy
| | - Paolo Gallo
- Department of Neuroscience, University of Padova, Padua, Italy
| | - Claudio Gasperini
- Department of Neurosciences, S Camillo Forlanini Hospital Rome, Rome, Italy
| | - Matilde Inglese
- Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health (DINOGMI), University of Genoa, Genoa, Italy.,IRCCS Ospedale Policlinico San Martino, Genoa, Italy
| | - Francesco Patti
- Department GF Ingrassia, Medical, Surgical Science and Advanced Technologies, University of Catania, Catania, Italy.,Center for Multiple Sclerosis, Policlinico "G Rodolico", University of Catania, Catania, Italy
| | | | - Paolo Preziosa
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Via Olgettina, 60, 20132, Milan, Italy.,Neurology Unit, IRCCS San Raffaele Scientific Institute, Via Olgettina, 60, 20132, Milan, Italy
| | - Maria Trojano
- Department of Basic Medical Sciences, Neuroscience, and Sense Organs, University of Bari "Aldo Moro", Bari, Italy
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28
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Masanneck L, Rolfes L, Regner-Nelke L, Willison A, Räuber S, Steffen F, Bittner S, Zipp F, Albrecht P, Ruck T, Hartung HP, Meuth SG, Pawlitzki M. Detecting ongoing disease activity in mildly affected multiple sclerosis patients under first-line therapies. Mult Scler Relat Disord 2022; 63:103927. [DOI: 10.1016/j.msard.2022.103927] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2022] [Revised: 05/19/2022] [Accepted: 05/27/2022] [Indexed: 12/12/2022]
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29
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Azizian M, Ghasemi Darestani N, Aliabadi A, Afzali M, Tavoosi N, Fosouli M, Khataei J, Aali H, Nourian SMA. Predictive value of number and volume of demyelinating plaques in treatment response in patients with multiple sclerosis treated with INF-B. AMERICAN JOURNAL OF NEURODEGENERATIVE DISEASE 2022; 11:10-16. [PMID: 35600511 PMCID: PMC9123433] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Received: 12/16/2021] [Accepted: 03/27/2022] [Indexed: 06/15/2023]
Abstract
BACKGROUND Multiple Sclerosis (MS) is an autoimmune, inflammatory disease of the central nervous system. Magnetic resonance imaging (MRI) findings are associated with disease clinical activity and response to treatment. This study aimed to evaluate the future value of plaque number and volume in MRI as radiological criteria in determining the treatment response to INF-B in patients with MS. METHODS This is a cross-sectional study performed in 2016-2021 in Iran on patients with the newly diagnosed (less than one year) relapsing-remitting MS. Brain MRI was taken for all patients. The number and volumes of the MS plaques were evaluated from FLAIR images by the two radiologists. Patients were treated with INF-B1a with a dosage of 12 million units equal to 44 micrograms subcutaneously, three times per week. Patients were visited monthly by neurologists to examine their clinical status. After one year, the brain MRI was conducted with the similar characteristics to the beginning of the study, and the number and volume of MS plaques were measured again. RESULTS The study population consisted of 33 males and 90 females with a mean age of 28.37 ± 6.29 years. The mean Expanded Disability Status Scale (EDSS) of the patients was 3.16 ± 0.23 at the beginning of the study. The specificity for a 50% reduction in the number and volume of plaques as two separate criteria was the same and equal to 100%. The sensitivity of the number and volume of plaques were 65.5% and 90.6%, respectively. In addition, considering 10% as the cut-off point of the number of plaques, the sensitivity of the number of plaques as a criterion was equal to the sensitivity of the plaque volume. CONCLUSION The results of this study showed that imaging criteria provide a more objective tool for evaluating the effectiveness of treatment. These findings indicate that the number and volume of plaques could be two reliable MRI imaging criteria for assessing therapy response. The number of plaques was less accurate than the volume of plaques.
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Affiliation(s)
- Maryam Azizian
- School of Medicine, Kerman University of Medical SciencesKerman, Iran
| | | | - Athena Aliabadi
- Advanced Diagnostic and Interventional Radiology Research Center, Tehran University of Medical ScienceTehran, Iran
| | - Mahdieh Afzali
- Department of Neurology, School of Medicine, Yas Hospital, Tehran University of Medical SciencesTehran, Iran
| | - Nooshin Tavoosi
- Department of Midwifery, School of Nursing and Midwifery, Islamic Azad University Shahrekord BranchShahrekord, Iran
| | - Mahnaz Fosouli
- Department of Radiology, Isfahan University of Medical SciencesIsfahan, Iran
| | - Jalil Khataei
- Department of Radiology, Isfahan University of Medical SciencesIsfahan, Iran
| | - Halimeh Aali
- Department of Internal Medicine, University of Medical SciencesZabol, Iran
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30
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Miscioscia A, Puthenparampil M, Miante S, Pengo M, Rinaldi F, Perini P, Gallo P. Retinal inner nuclear layer thinning is decreased and associates with the clinical outcome in ocrelizumab-treated primary progressive multiple sclerosis. J Neurol 2022; 269:5436-5442. [PMID: 35648233 PMCID: PMC9467948 DOI: 10.1007/s00415-022-11183-y] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2022] [Revised: 05/07/2022] [Accepted: 05/11/2022] [Indexed: 02/06/2023]
Abstract
BACKGROUND Ocrelizumab was found to decrease brain atrophy rate in primary progressive multiple sclerosis (PPMS), but no data are currently available on the effect of ocrelizumab on retinal layer thicknesses in the PPMS population. OBJECTIVE To assess retinal layer changes in ocrelizumab-treated PPMS and test their possible application as biomarkers of therapy response. METHODS 36 PPMS patients, treated with ocrelizumab for at least 6 months, and 39 sex- and age-matched healthy controls (HC) were included in a blind, longitudinal study. Spectrum-domain optical coherence tomography (SD-OCT) was performed at study entry (T0) and after 6 (T6) and 12 months (T12). At month 24 (T24), patients were divided into responders (no evidence of 1-year confirmed disability progression, 1y-CDP) and non-responders (evidence of 1y-CDP). RESULTS At T24, 23/36 (64%) patients were considered responders and 13/36 (36%) non-responders. At T0, peripapillary retinal nerve fiber layer (pRNFL) thickness, macular ganglion cell-inner plexiform layer (GCIPL) and inner retinal layer (IRL) volume were significantly lower in PPMS compared to HC (p = 0.001 for all comparisons). At T6 and T12, non-responders significantly differed in the inner nuclear layer (INL) thinning rate compared to responders (p = 0.005 at both time-points). CONCLUSIONS Ocrelizumab significantly slows down INL thinning rate in PPMS responders. The longitudinal analysis of retina layer changes by means of OCT may be a promising prognostic test, and merits further investigations.
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Affiliation(s)
- Alessandro Miscioscia
- Department of Neuroscience DNS, School of Medicine, University of Padua, Via Giustiniani, 5, 35128 Padua, Veneto Region Italy ,Multiple Sclerosis Centre, University Hospital of Padua, Padua, Veneto Region Italy
| | - Marco Puthenparampil
- Department of Neuroscience DNS, School of Medicine, University of Padua, Via Giustiniani, 5, 35128 Padua, Veneto Region Italy ,Multiple Sclerosis Centre, University Hospital of Padua, Padua, Veneto Region Italy
| | - Silvia Miante
- Department of Neuroscience DNS, School of Medicine, University of Padua, Via Giustiniani, 5, 35128 Padua, Veneto Region Italy ,Multiple Sclerosis Centre, University Hospital of Padua, Padua, Veneto Region Italy ,Present Address: Neurology Unit, Ospedale dell’Angelo, Mestre, Italy
| | - Marta Pengo
- Department of Neuroscience DNS, School of Medicine, University of Padua, Via Giustiniani, 5, 35128 Padua, Veneto Region Italy ,Multiple Sclerosis Centre, University Hospital of Padua, Padua, Veneto Region Italy ,Present Address: Department of Molecular and Translational Medicine, University of Brescia, Brescia, Italy
| | - Francesca Rinaldi
- Multiple Sclerosis Centre, University Hospital of Padua, Padua, Veneto Region Italy
| | - Paola Perini
- Multiple Sclerosis Centre, University Hospital of Padua, Padua, Veneto Region Italy
| | - Paolo Gallo
- Department of Neuroscience DNS, School of Medicine, University of Padua, Via Giustiniani, 5, 35128 Padua, Veneto Region Italy ,Multiple Sclerosis Centre, University Hospital of Padua, Padua, Veneto Region Italy
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Treatment response scoring systems to assess long-term prognosis in self-injectable DMTs relapsing-remitting multiple sclerosis patients. J Neurol 2022; 269:452-459. [PMID: 34596743 DOI: 10.1007/s00415-021-10823-z] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2021] [Revised: 09/15/2021] [Accepted: 09/24/2021] [Indexed: 10/20/2022]
Abstract
BACKGROUND AND OBJECTIVES Different treatment response scoring systems in treated MS patients exist. The objective was to assess the long-term predictive value of these systems in RRMS patients treated with self-injectable DMTs. METHODS RRMS-treated patients underwent brain MRI before the onset of therapy and 12 months thereafter, and neurological assessments every 6 months. Clinical and demographic characteristics were collected at baseline. After the first year of treatment, several scoring systems [Rio score (RS), modified Rio score (MRS), MAGNIMS score (MS), and ROAD score (RoS)] were calculated. Cox-Regression and survival analyses were performed to identify scores predicting long-term disability. RESULTS We included 319 RRMS patients. Survival analyses showed that patients with RS > 1 and RoS > 3 had a significant risk of reaching an EDSS of 4.0 and 6.0 The score with the best sensitivity (61%) was the RoS, while the MRS showed the best specificity (88%). The RS showed the best positive predictive value (42%) and the best accuracy (81%). CONCLUSIONS The combined measures integrated into different scores have an acceptable prognostic value for identifying patients with long-term disability. Thus, these data reinforce the concept of early treatment optimization to minimize the risk of long-term disability.
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32
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Rovira A, Corral JF, Auger C, Valverde S, Vidal-Jordana A, Oliver A, de Barros A, Ng Wong YK, Tintoré M, Pareto D, Aymerich FX, Montalban X, Lladó X, Alonso J. Assessment of automatic decision-support systems for detecting active T2 lesions in multiple sclerosis patients. Mult Scler 2021; 28:1209-1218. [PMID: 34859704 DOI: 10.1177/13524585211061339] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
BACKGROUND Active (new/enlarging) T2 lesion counts are routinely used in the clinical management of multiple sclerosis. Thus, automated tools able to accurately identify active T2 lesions would be of high interest to neuroradiologists for assisting in their clinical activity. OBJECTIVE To compare the accuracy in detecting active T2 lesions and of radiologically active patients based on different visual and automated methods. METHODS One hundred multiple sclerosis patients underwent two magnetic resonance imaging examinations within 12 months. Four approaches were assessed for detecting active T2 lesions: (1) conventional neuroradiological reports; (2) prospective visual analyses performed by an expert; (3) automated unsupervised tool; and (4) supervised convolutional neural network. As a gold standard, a reference outcome was created by the consensus of two observers. RESULTS The automated methods detected a higher number of active T2 lesions, and a higher number of active patients, but a higher number of false-positive active patients than visual methods. The convolutional neural network model was more sensitive in detecting active T2 lesions and active patients than the other automated method. CONCLUSION Automated convolutional neural network models show potential as an aid to neuroradiological assessment in clinical practice, although visual supervision of the outcomes is still required.
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Affiliation(s)
- Alex Rovira
- Neuroradiology Section, Department of Radiology (IDI), Vall d'Hebron University Hospital, Barcelona, Spain/Neuroradiology Research Group, Vall d'Hebron Research Institute (VHIR), Barcelona, Spain/Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Juan Francisco Corral
- Neuroradiology Section, Department of Radiology (IDI), Vall d'Hebron University Hospital, Barcelona, Spain/Neuroradiology Research Group, Vall d'Hebron Research Institute (VHIR), Barcelona, Spain
| | - Cristina Auger
- Neuroradiology Section, Department of Radiology (IDI), Vall d'Hebron University Hospital, Barcelona, Spain/Neuroradiology Research Group, Vall d'Hebron Research Institute (VHIR), Barcelona, Spain/Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Sergi Valverde
- TensorMedical, Girona, Spain/Department of Computer Architecture and Technology, University of Girona, Girona, Spain
| | - Angela Vidal-Jordana
- Department of Neurology and Neuroimmunology, Centre d'Esclerosi Múltiple de Catalunya (Cemcat), Vall d'Hebron University Hospital, Barcelona, Spain/Clinical Neuroimmunology Research Group, Vall d'Hebron Research Institute, Barcelona, Spain/Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Arnau Oliver
- Department of Computer Architecture and Technology, University of Girona, Girona, Spain
| | - Andrea de Barros
- Neuroradiology Section, Department of Radiology (IDI), Vall d'Hebron University Hospital, Barcelona, Spain
| | - Yiken Karelys Ng Wong
- Neuroradiology Section, Department of Radiology (IDI), Vall d'Hebron University Hospital, Barcelona, Spain
| | - Mar Tintoré
- Department of Neurology and Neuroimmunology, Centre d'Esclerosi Múltiple de Catalunya (Cemcat), Vall d'Hebron University Hospital, Barcelona, Spain/Clinical Neuroimmunology Research Group, Vall d'Hebron Research Institute, Barcelona, Spain/Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Deborah Pareto
- Neuroradiology Section, Department of Radiology (IDI), Vall d'Hebron University Hospital, Barcelona, Spain/Neuroradiology Research Group, Vall d'Hebron Research Institute (VHIR), Barcelona, Spain
| | - Francesc Xavier Aymerich
- Neuroradiology Section, Department of Radiology (IDI), Vall d'Hebron University Hospital, Barcelona, Spain/Neuroradiology Research Group, Vall d'Hebron Research Institute (VHIR), Barcelona, Spain/Universitat Autònoma de Barcelona, Barcelona, Spain/Automatic Control Department, Universitat Politècnica de Catalunya BarcelonaTech, Barcelona, Spain
| | - Xavier Montalban
- Department of Neurology and Neuroimmunology, Centre d'Esclerosi Múltiple de Catalunya (Cemcat), Vall d'Hebron University Hospital, Barcelona, Spain/Clinical Neuroimmunology Research Group, Vall d'Hebron Research Institute, Barcelona, Spain/Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Xavier Lladó
- Department of Computer Architecture and Technology, University of Girona, Girona, Spain
| | - Juli Alonso
- Neuroradiology Section, Department of Radiology (IDI), Vall d'Hebron University Hospital, Barcelona, Spain/Neuroradiology Research Group, Vall d'Hebron Research Institute (VHIR), Barcelona, Spain/Universitat Autònoma de Barcelona, Barcelona, Spain
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Thompson AJ, Carroll W, Ciccarelli O, Comi G, Cross A, Donnelly A, Feinstein A, Fox RJ, Helme A, Hohlfeld R, Hyde R, Kanellis P, Landsman D, Lubetzki C, Marrie RA, Morahan J, Montalban X, Musch B, Rawlings S, Salvetti M, Sellebjerg F, Sincock C, Smith KE, Strum J, Zaratin P, Coetzee T. Charting a global research strategy for progressive MS-An international progressive MS Alliance proposal. Mult Scler 2021; 28:16-28. [PMID: 34850641 PMCID: PMC8688983 DOI: 10.1177/13524585211059766] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
BACKGROUND Progressive forms of multiple sclerosis (MS) affect more than 1 million individuals globally. Recent approvals of ocrelizumab for primary progressive MS and siponimod for active secondary progressive MS have opened the therapeutic door, though results from early trials of neuroprotective agents have been mixed. The recent introduction of the term 'active' secondary progressive MS into the therapeutic lexicon has introduced potential confusion to disease description and thereby clinical management. OBJECTIVE This paper reviews recent progress, highlights continued knowledge and proposes, on behalf of the International Progressive MS Alliance, a global research strategy for progressive MS. METHODS Literature searches of PubMed between 2015 and May, 2021 were conducted using the search terms "progressive multiple sclerosis", "primary progressive multiple sclerosis", "secondary progressive MS". Proposed strategies were developed through a series of in-person and virtual meetings of the International Progressive MS Alliance Scientific Steering Committee. RESULTS Sustaining and accelerating progress will require greater understanding of underlying mechanisms, identification of potential therapeutic targets, biomarker discovery and validation, and conduct of clinical trials with improved trial design. Encouraging developments in symptomatic and rehabilitative interventions are starting to address ongoing challenges experienced by people with progressive MS. CONCLUSION We need to manage these challenges and realise the opportunities in the context of a global research strategy, which will improve quality of life for people with progressive MS.
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Affiliation(s)
| | | | | | | | - Anne Cross
- Washington University in St. Louis, St. Louis, MO, USA
| | | | | | | | | | - Reinhard Hohlfeld
- Munich Cluster for Systems Neurology, Ludwig Maximilian University of Munich, Munich, Germany
| | | | | | | | | | | | | | - Xavier Montalban
- Hospital Vall d'Hebron, Universitat Autònoma de Barcelona, Barcelona, Spain
| | | | | | - Marco Salvetti
- Department of Neurosciences, Mental Health and Sensory Organs, Centre for Experimental Neurological Therapies (CENTERS), Sapienza University of Rome, Rome, Italy/Istituto Neurologico Mediterraneo (INM) Neuromed, Pozzilli, Italy
| | - Finn Sellebjerg
- Copenhagen University Hospital-Rigshospitalet, Glostrup, Denmark
| | | | | | - Jon Strum
- International Progressive MS Alliance, Los Angeles, CA, USA
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Tutuncu M, Altintas A, Dogan BV, Uygunoglu U, Kale Icen N, Deniz Elmalı A, Coban E, Alpaslan BG, Soysal A. The use of Modified Rio score for determining treatment failure in patients with multiple sclerosis: retrospective descriptive case series study. Acta Neurol Belg 2021; 121:1693-1698. [PMID: 32865702 DOI: 10.1007/s13760-020-01476-2] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2020] [Accepted: 08/17/2020] [Indexed: 11/29/2022]
Abstract
Predicting treatment failure and switching effective treatment immediately in patients with multiple sclerosis (MS) is important. We aimed to evaluate the usefulness of Modified Rio score (MRS) in predicting treatment failure in MS patients. This is a retrospective study, which was conducted in two University Hospital. 129 MS patients treated with İnterferon or glatiramer-acetate from 2 clinical sites, were retrospectively selected. MRS was calculated after the first year of therapy. Treatment failure was defined as the presence of a 1 point increase in EDSS, 2 clinical attacks, 1 clinical attack and progression, 1 clinical attack and new lesion on MRI except associated with an attack, or new lesion in 2 different MRI taken at least 3 months apart. The sensitivity, specificity, positive and negative predictive values of the MRS in predicting treatment failure were determined. 71 (55%) patients with score '0', 41 (31.8%) patients with score '1', 11 (8.5%) patients with score '2', 6 (4.7%) patients with score '3' were detected. 14 patients needed treatment switching during the first three years of the treatment. Sensitivity was 57%, specificity was 92%, positive predictive value was 95%, negative predictive value was 47% and accuracy was 89%. Modified Rio score (MRS) was found to be effective in determining the treatment failure as mentioned before. This study will be useful for clinicians who evaluate the treatment failure like us, and this study revealed that the MRS may also help predict treatment failure.
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Affiliation(s)
- Mesude Tutuncu
- Bakirkoy Prof. Dr. Mazhar Osman Training and Research Hospital for Psychiatry and Neurological Disorders, Zuhuratbaba Mah. Bakirkoy Ruh Sağlığı Ve Sinir Hastalıkları Hastanesi, bitam binasıi 3, Noroloji kliniği Bakirkoy, 34147, Istanbul, Turkey.
| | - Ayse Altintas
- Koc University Medical School, Topkapı, Koç Üniversitesi Hastanesi, Davutpaşa Cd. No:4, 34010 Zeytinburnu/İstanbul, 34200, Istanbul, Turkey
| | - Burcu V Dogan
- Bakirkoy Prof. Dr. Mazhar Osman Training and Research Hospital for Psychiatry and Neurological Disorders, Zuhuratbaba Mah. Bakirkoy Ruh Sağlığı Ve Sinir Hastalıkları Hastanesi, bitam binasıi 3, Noroloji kliniği Bakirkoy, 34147, Istanbul, Turkey
| | - Ugur Uygunoglu
- Cerrahpasa School of Medicine, Cerrahpasa mahallesi, Kocamustafapasa cad. No: 34/E Noroloji Klinigi Fatih, 34200, Istanbul, Turkey
| | - Nilufer Kale Icen
- Bagcilar Research and Tarining Hospital, Merkezmah. Dr. Sadık Ahmet Cad. Bagcılar, 34100, Istanbul, Turkey
| | - Ayse Deniz Elmalı
- Neurology Department, Istanbul Faculty of Medicine, Istanbul University, Istanbul, Turkey
| | - Eda Coban
- Bakirkoy Prof. Dr. Mazhar Osman Training and Research Hospital for Psychiatry and Neurological Disorders, Zuhuratbaba Mah. Bakirkoy Ruh Sağlığı Ve Sinir Hastalıkları Hastanesi, bitam binasıi 3, Noroloji kliniği Bakirkoy, 34147, Istanbul, Turkey
| | - Bengi G Alpaslan
- Cerrahpasa School of Medicine, Cerrahpasa mahallesi, Kocamustafapasa cad. No: 34/E Noroloji Klinigi Fatih, 34200, Istanbul, Turkey
| | - Aysun Soysal
- Bakirkoy Prof. Dr. Mazhar Osman Training and Research Hospital for Psychiatry and Neurological Disorders, Zuhuratbaba Mah. Bakirkoy Ruh Sağlığı Ve Sinir Hastalıkları Hastanesi, bitam binasıi 3, Noroloji kliniği Bakirkoy, 34147, Istanbul, Turkey
- Neurology Department, Bakirkoy Prof. Dr. Mazhar Osman Training and Research Hospital for Psychiatry and Neurological Disorders, Zuhuratbaba mah. Bitam Binası, doktor odası. Bakirkoy, Istanbul, Turkey
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Inshasi JS, Alfahad S, Alsaadi T, Hassan A, Zein T, Mifsud VA, Nouri SI, Shakra M, Shatila AO, Szolics M, Thakre M, Kumar A, Boshra A. Position of Cladribine Tablets in the Management of Relapsing-Remitting Multiple Sclerosis: An Expert Narrative Review From the United Arab Emirates. Neurol Ther 2021; 10:435-454. [PMID: 33891277 PMCID: PMC8062252 DOI: 10.1007/s40120-021-00243-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/05/2021] [Accepted: 03/16/2021] [Indexed: 11/06/2022] Open
Abstract
The use of immune reconstitution therapies (IRT) in patients with relapsing-remitting multiple sclerosis (RRMS) is associated with a prolonged period of freedom from relapses in the absence of continuously applied therapy. Cladribine tablets is a disease-modifying treatment (DMT) indicated for highly active relapsing multiple sclerosis (MS) as defined by clinical or imaging features. Treatment with cladribine tablets is effective and well tolerated in patients with active MS disease and have a low burden of monitoring during and following treatment. In this article, an expert group of specialist neurologists involved in the care of patients with MS in the United Arab Emirates provides their consensus recommendations for the practical use of cladribine tablets according to the presenting phenotype of patients with RRMS. The IRT approach may be especially useful for patients with highly active MS insufficiently responsive to treatment with a first-line DMT, those who are likely to adhere poorly to a continuous therapeutic regimen, treatment-naïve patients with high disease activity at first presentation, or patients planning a family who are prepared to wait until at least 6 months after the end of treatment. Information available to date does not suggest an adverse interaction between cladribine tablets and COVID-19 infection. Data are unavailable at this time regarding the efficacy of COVID-19 vaccination in patients treated with cladribine tablets. Robust immunological responses to COVID-19 infection or to other vaccines have been observed in patients receiving this treatment, and treatment with cladribine tablets per se should not represent a barrier to this vaccination.
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Affiliation(s)
- Jihad S Inshasi
- Neurology Department, Rashid Hospital and Dubai Medical College, Dubai Health Authority (DHA), PO Box 4545, Dubai, UAE.
| | - Sarmed Alfahad
- Neurology Department, Neurospinal Hospital, Baghdad Medical College, Dubai, UAE
| | - Taoufik Alsaadi
- Neurology Department, American Center for Psychiatry and Neurology, Dubai, UAE
| | - Ali Hassan
- Neurology Medical Clinic, Tawam Hospital, Abu Dhabi, UAE
| | - Tayseer Zein
- Neurology Department, AlQassami Hospital, Sharjah, UAE
| | | | | | - Mustafa Shakra
- Department of Neurology, Sheikh Khalifa Medical City, Abu Dhabi, UAE
| | | | - Miklos Szolics
- Neurology Medical Clinic, Tawam Hospital, Abu Dhabi, UAE
| | - Mona Thakre
- Neurology Department, Al Zahra Hospital, Dubai, UAE
| | - Ajit Kumar
- Neurology Department, NMC Specialty Hospital, Al Nahda, Dubai, UAE
| | - Amir Boshra
- Merck Serono Middle East FZ Ltd, Dubai, UAE
- Merck KgaA, Darmstadt, Germany
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Di Sabatino E, Gaetani L, Sperandei S, Fiacca A, Guercini G, Parnetti L, Di Filippo M. The no evidence of disease activity (NEDA) concept in MS: impact of spinal cord MRI. J Neurol 2021; 269:3129-3135. [PMID: 34820734 DOI: 10.1007/s00415-021-10901-2] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2021] [Revised: 11/08/2021] [Accepted: 11/09/2021] [Indexed: 10/19/2022]
Abstract
BACKGROUND Measures to define treatment response, such as no evidence of disease activity (NEDA), are routinely used in multiple sclerosis (MS) clinical practice. Although spinal cord involvement is a frequent feature of MS, its magnetic resonance imaging (MRI) monitoring is not routinely performed. OBJECTIVE To assess the impact of spinal cord MRI in the definition of NEDA in a cohort of people with MS (pwMS) with available spinal cord imaging performed as for routine monitoring. METHODS We included 115 pwMS undergoing treatment with first-line disease-modifying therapies (DMTs) and retrospectively analyzed the presence of NEDA in the whole cohort, either considering or not spinal cord imaging. RESULTS When considering only clinical and brain MRI measures, 97 out of 115 pwMS (84.3%) satisfied the criteria for NEDA. In the same cohort, the number of pwMS with NEDA significantly decreased to 88 (76.5%) (p < 0.01) when considering also spinal cord imaging. CONCLUSION These findings suggest that, in routine clinical practice, spinal cord MRI monitoring in pwMS under first-line DMTs leads to a slight but significant change in the proportion of subjects classified as clinically and radiologically stable according to the NEDA definition.
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Affiliation(s)
- Elena Di Sabatino
- Section of Neurology, Department of Medicine and Surgery, University of Perugia, Santa Maria della Misericordia Hospital, Piazzale Menghini 1, 06132, Perugia, Italy
| | - Lorenzo Gaetani
- Section of Neurology, Department of Medicine and Surgery, University of Perugia, Santa Maria della Misericordia Hospital, Piazzale Menghini 1, 06132, Perugia, Italy
| | - Silvia Sperandei
- Section of Neurology, Department of Medicine and Surgery, University of Perugia, Santa Maria della Misericordia Hospital, Piazzale Menghini 1, 06132, Perugia, Italy
| | - Andrea Fiacca
- Section of Neuroradiology, Santa Maria della Misericordia Hospital, Piazzale Menghini 1, 06132, Perugia, Italy
| | - Giorgio Guercini
- Section of Neuroradiology, Santa Maria della Misericordia Hospital, Piazzale Menghini 1, 06132, Perugia, Italy
| | - Lucilla Parnetti
- Section of Neurology, Department of Medicine and Surgery, University of Perugia, Santa Maria della Misericordia Hospital, Piazzale Menghini 1, 06132, Perugia, Italy
| | - Massimiliano Di Filippo
- Section of Neurology, Department of Medicine and Surgery, University of Perugia, Santa Maria della Misericordia Hospital, Piazzale Menghini 1, 06132, Perugia, Italy.
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Combès B, Kerbrat A, Pasquier G, Commowick O, Le Bon B, Galassi F, L'Hostis P, El Graoui N, Chouteau R, Cordonnier E, Edan G, Ferré JC. A Clinically-Compatible Workflow for Computer-Aided Assessment of Brain Disease Activity in Multiple Sclerosis Patients. Front Med (Lausanne) 2021; 8:740248. [PMID: 34805206 PMCID: PMC8595265 DOI: 10.3389/fmed.2021.740248] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2021] [Accepted: 09/30/2021] [Indexed: 11/21/2022] Open
Abstract
Over the last 10 years, the number of approved disease modifying drugs acting on the focal inflammatory process in Multiple Sclerosis (MS) has increased from 3 to 10. This wide choice offers the opportunity of a personalized medicine with the objective of no clinical and radiological activity for each patient. This new paradigm requires the optimization of the detection of new FLAIR lesions on longitudinal MRI. In this paper, we describe a complete workflow—that we developed, implemented, deployed, and evaluated—to facilitate the monitoring of new FLAIR lesions on longitudinal MRI of MS patients. This workflow has been designed to be usable by both hospital and private neurologists and radiologists in France. It consists of three main components: (i) a software component that allows for automated and secured anonymization and transfer of MRI data from the clinical Picture Archive and Communication System (PACS) to a processing server (and vice-versa); (ii) a fully automated segmentation core that enables detection of focal longitudinal changes in patients from T1-weighted, T2-weighted and FLAIR brain MRI scans, and (iii) a dedicated web viewer that provides an intuitive visualization of new lesions to radiologists and neurologists. We first present these different components. Then, we evaluate the workflow on 54 pairs of longitudinal MRI scans that were analyzed by 3 experts (1 neuroradiologist, 1 radiologist, and 1 neurologist) with and without the proposed workflow. We show that our workflow provided a valuable aid to clinicians in detecting new MS lesions both in terms of accuracy (mean number of detected lesions per patient and per expert 1.8 without the workflow vs. 2.3 with the workflow, p = 5.10−4) and of time dedicated by the experts (mean time difference 2′45″, p = 10−4). This increase in the number of detected lesions has implications in the classification of MS patients as stable or active, even for the most experienced neuroradiologist (mean sensitivity was 0.74 without the workflow and 0.90 with the workflow, p-value for no difference = 0.003). It therefore has potential consequences on the therapeutic management of MS patients.
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Affiliation(s)
- Benoit Combès
- Univ Rennes, Inria, CNRS, Inserm IRISA UMR 6074, Empenn ERL U 1228, Rennes, France
| | - Anne Kerbrat
- Univ Rennes, Inria, CNRS, Inserm IRISA UMR 6074, Empenn ERL U 1228, Rennes, France.,Neurology Department, Rennes University Hospital, Rennes, France
| | | | - Olivier Commowick
- Univ Rennes, Inria, CNRS, Inserm IRISA UMR 6074, Empenn ERL U 1228, Rennes, France
| | - Brandon Le Bon
- Univ Rennes, Inria, CNRS, Inserm IRISA UMR 6074, Empenn ERL U 1228, Rennes, France
| | - Francesca Galassi
- Univ Rennes, Inria, CNRS, Inserm IRISA UMR 6074, Empenn ERL U 1228, Rennes, France
| | | | - Nora El Graoui
- Univ Rennes, Inria, CNRS, Inserm IRISA UMR 6074, Empenn ERL U 1228, Rennes, France.,CHU Rennes, Department of Neuroradiology, Rennes, France
| | - Raphael Chouteau
- Neurology Department, Rennes University Hospital, Rennes, France
| | | | - Gilles Edan
- Univ Rennes, Inria, CNRS, Inserm IRISA UMR 6074, Empenn ERL U 1228, Rennes, France.,Neurology Department, Rennes University Hospital, Rennes, France
| | - Jean-Christophe Ferré
- Univ Rennes, Inria, CNRS, Inserm IRISA UMR 6074, Empenn ERL U 1228, Rennes, France.,CHU Rennes, Department of Neuroradiology, Rennes, France
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Lees S, Dicker M, Ku JE, Chaganti V, Mew-Sum M, Wang N, Smith A, Oldmeadow C, Goon WL, Bevan M, Lang D, Hinwood M. Impact of disease-modifying therapies on MRI and neurocognitive outcomes in relapsing-remitting multiple sclerosis: a protocol for a systematic review and network meta-analysis. BMJ Open 2021; 11:e051509. [PMID: 34728450 PMCID: PMC8565566 DOI: 10.1136/bmjopen-2021-051509] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/24/2022] Open
Abstract
INTRODUCTION Disease-modifying therapies (DMTs) are the mainstay of treatment for relapsing-remitting multiple sclerosis (RRMS). There is established evidence that DMTs are effective at reducing relapse rate and disease progression in RRMS, but there has been less consideration to the synthesis of MRI and neurocognitive outcomes, which play an increasingly important role in treatment decisions. The aim of this systematic review and network meta-analysis is to examine the relative efficacy, acceptability and tolerability of DMTs for RRMS, using MRI and neurocognitive outcomes. METHODS AND ANALYSIS We will search electronic databases, including MEDLINE, Embase and the Cochrane Central Register of Controlled Trials, with no date restrictions. We will also search the websites of international regulatory bodies for pharmaceuticals and international trial registries. We will include parallel group randomised controlled trials of DMTs including interferon beta-1a intramuscular, interferon beta-1a subcutaneous, interferon beta-1b, peginterferon beta-1a, glatiramer acetate, natalizumab, ocrelizumab, alemtuzumab, dimethyl fumarate, teriflunomide, fingolimod, cladribine, ozanimod, mitoxantrone and rituximab, either head-to-head or against placebo in adults with RRMS. Primary outcomes include efficacy (MRI outcomes including new T1/hypointense lesions and T2/hyperintense lesions) and acceptability (all-cause dropouts). Secondary outcomes include gadolinium-enhancing lesions, cerebral atrophy and tolerability (dropouts due to adverse events). Neurocognitive measures across three domains including processing speed, working memory and verbal learning will be included as exploratory outcomes. Data will be analysed using a random-effects pairwise meta-analysis and a Bayesian hierarchical random effects network meta-analysis to evaluate the efficacy, acceptability and tolerability of the included DMTs. Subgroup and sensitivity analyses will be conducted to assess the robustness of the findings. The review will be reported using the Preferred Reporting Items for Systematic Reviews incorporating Network Meta-Analyses statement. ETHICS AND DISSEMINATION This protocol does not require ethics approval. Results will be disseminated in a peer-reviewed academic journal. PROSPERO REGISTRATION NUMBER CRD42021239630.
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Affiliation(s)
- Samuel Lees
- School of Medicine and Public Health, The University of Newcastle, Callaghan, New South Wales, Australia
| | - Mathew Dicker
- School of Medicine and Public Health, The University of Newcastle, Callaghan, New South Wales, Australia
| | - Jie En Ku
- School of Medicine and Public Health, The University of Newcastle, Callaghan, New South Wales, Australia
| | - Varun Chaganti
- School of Medicine and Public Health, The University of Newcastle, Callaghan, New South Wales, Australia
| | - Matthew Mew-Sum
- School of Medicine and Public Health, The University of Newcastle, Callaghan, New South Wales, Australia
| | - Nick Wang
- School of Medicine and Public Health, The University of Newcastle, Callaghan, New South Wales, Australia
| | - Angela Smith
- HNEHealth Libraries, Hunter New England Local Health District, New Lambton, New South Wales, Australia
| | | | - Wooi Lynn Goon
- School of Medicine and Public Health, The University of Newcastle, Callaghan, New South Wales, Australia
| | - Marc Bevan
- School of Medicine and Public Health, The University of Newcastle, Callaghan, New South Wales, Australia
| | - Danielle Lang
- School of Medicine and Public Health, The University of Newcastle, Callaghan, New South Wales, Australia
- Hunter Medical Research Institute, New Lambton Heights, New South Wales, Australia
| | - Madeleine Hinwood
- School of Medicine and Public Health, The University of Newcastle, Callaghan, New South Wales, Australia
- Hunter Medical Research Institute, New Lambton Heights, New South Wales, Australia
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Prosperini L, Ruggieri S, Haggiag S, Tortorella C, Pozzilli C, Gasperini C. Prognostic Accuracy of NEDA-3 in Long-term Outcomes of Multiple Sclerosis. NEUROLOGY(R) NEUROIMMUNOLOGY & NEUROINFLAMMATION 2021; 8:8/6/e1059. [PMID: 34373345 PMCID: PMC8353667 DOI: 10.1212/nxi.0000000000001059] [Citation(s) in RCA: 25] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/24/2021] [Accepted: 07/06/2021] [Indexed: 01/02/2023]
Abstract
Background and Objectives To estimate the proportions of patients with relapsing-remitting multiple sclerosis who despite achieving the no evidence of disease activity-3 (NEDA-3) status in the first 2 treatment years experienced relapse-associated worsening (RAW) or progression independent from relapse activity (PIRA) in the following years. Methods We selected patients with NEDA-3—defined as no relapse, no disability worsening, and no MRI activity—in the first 2 years of either glatiramer acetate or interferon beta as initial treatment. We estimated the long-term probability of subsequent RAW and PIRA (considered as 2 contrasting outcomes) by cumulative incidence functions. Competing risk regressions were used to identify the baseline (i.e., at treatment start) predictors of RAW and PIRA. Results Of 687 patients, 224 (32.6%) had NEDA-3 in the first 2 treatment years. After a median follow-up time of 12 years from treatment start, 58 patients (26%) experienced disability accrual: 31 (14%) had RAW and 27 (12%) had PIRA. RAW was predicted by the presence of >9 T2 lesions (subdistribution hazard ratio [SHR] = 3.92, p = 0.012) and contrast-enhancing lesions (SHR = 2.38, p = 0.047) on baseline MRI scan and either temporary or permanent discontinuation of the initial treatment (SHR = 1.11, p = 0.015). PIRA was predicted by advancing age (SHR = 1.05, p = 0.036 for each year increase) and presence of ≥1 spinal cord lesion on baseline MRI scan (SHR = 4.08, p = 0.016). Discussion The adoption of NEDA-3 criteria led to prognostic misclassification in 1 of 4 patients. Different risk factors were associated with RAW and PIRA, suggesting alternative mechanisms for disability accrual. Classification of Evidence This study provides Class II evidence that in patients with RRMS who attained NEDA-3 status, subsequent RAW was associated with baseline MRI activity and discontinuation of treatment and PIRA was associated with age and the presence of baseline spinal cord lesions.
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Affiliation(s)
- Luca Prosperini
- From the Department of Neurosciences (L.P., S.H., C.T., C.G.), S. Camillo-Forlanini Hospital; Department of Human Neurosciences (S.R., C.P.), Sapienza University; and Neuroimmunology Unit (S.R.), Santa Lucia Foundation, Rome, Italy.
| | - Serena Ruggieri
- From the Department of Neurosciences (L.P., S.H., C.T., C.G.), S. Camillo-Forlanini Hospital; Department of Human Neurosciences (S.R., C.P.), Sapienza University; and Neuroimmunology Unit (S.R.), Santa Lucia Foundation, Rome, Italy
| | - Shalom Haggiag
- From the Department of Neurosciences (L.P., S.H., C.T., C.G.), S. Camillo-Forlanini Hospital; Department of Human Neurosciences (S.R., C.P.), Sapienza University; and Neuroimmunology Unit (S.R.), Santa Lucia Foundation, Rome, Italy
| | - Carla Tortorella
- From the Department of Neurosciences (L.P., S.H., C.T., C.G.), S. Camillo-Forlanini Hospital; Department of Human Neurosciences (S.R., C.P.), Sapienza University; and Neuroimmunology Unit (S.R.), Santa Lucia Foundation, Rome, Italy
| | - Carlo Pozzilli
- From the Department of Neurosciences (L.P., S.H., C.T., C.G.), S. Camillo-Forlanini Hospital; Department of Human Neurosciences (S.R., C.P.), Sapienza University; and Neuroimmunology Unit (S.R.), Santa Lucia Foundation, Rome, Italy
| | - Claudio Gasperini
- From the Department of Neurosciences (L.P., S.H., C.T., C.G.), S. Camillo-Forlanini Hospital; Department of Human Neurosciences (S.R., C.P.), Sapienza University; and Neuroimmunology Unit (S.R.), Santa Lucia Foundation, Rome, Italy
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Laboratory biomarkers of Multiple Sclerosis (MS). Clin Biochem 2021; 99:1-8. [PMID: 34673037 DOI: 10.1016/j.clinbiochem.2021.10.004] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2021] [Revised: 10/11/2021] [Accepted: 10/12/2021] [Indexed: 11/22/2022]
Abstract
Multiple Sclerosis (MS) is a neurological disease that affects the central nervous system (CNS). The diagnosis of the disease is quite challenging due to its variation among patients. As a result, the need to enhance diagnostic procedures, evaluate objective prognostic markers and promote effective monitoring of patients' responses to treatment has prompted the identification of many biomarkers. To present up-to-date knowledge on potential biomarkers for MS used to assess disease activity, progression, and therapeutic responses. The search for articles was conducted in various databases, namely, PubMed, Cochrane Library, and CINAHL, using an identical search strategy and terms that included "Multiple Sclerosis," "MS," "biomarkers," "potential," "magnetic resonance spectroscopy," "progress," "marker," "predict," "disability," "indicator," and "mass spectrometry." Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines were followed when scrutinizing the articles for inclusion in the study. The search process identified 75 articles that were used in this systematic review. MS biomarkers consisted of laboratory biomarkers, imaging biomarkers, and genetic and immunogenetic biomarkers. The efficacy, which leads to their potential classification, relies on numerous factors, such as sensitivity, specificity, clinical rationale, predictability, practicality, biological rationale, reproducibility, and correlations with prognosis and disability. Oligoclonal bands (OCBs) and magnetic resonance imaging (MRI) features are the most established biomarkers so far, although kappa free light chains (kFLCs), the measles-rubella-zoster (MRZ) reaction, and neurofilament light chains (NfLs) might show potential in the near future after more studies are conducted.
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Cloosterman S, Wijnands I, Huygens S, Wester V, Lam KH, Strijbis E, den Teuling B, Versteegh M. The Potential Impact of Digital Biomarkers in Multiple Sclerosis in The Netherlands: An Early Health Technology Assessment of MS Sherpa. Brain Sci 2021; 11:1305. [PMID: 34679370 PMCID: PMC8534078 DOI: 10.3390/brainsci11101305] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2021] [Revised: 09/22/2021] [Accepted: 09/26/2021] [Indexed: 11/16/2022] Open
Abstract
(1) Background: Monitoring of Multiple Sclerosis (MS) with eHealth interventions or digital biomarkers provides added value to the current care path. Evidence in the literature is currently scarce. MS sherpa is an eHealth intervention with digital biomarkers, aimed at monitoring symptom progression and disease activity. To show the added value of digital biomarker-based eHealth interventions to the MS care path, an early Health Technology Assessment (eHTA) was performed, with MS sherpa as an example, to assess the potential impact on treatment switches. (2) Methods: The eHTA was performed according to the Dutch guidelines for health economic evaluations. A decision analytic MS model was used to estimate the costs and benefits of MS standard care with and without use of MS sherpa, expressed in incremental cost-effectiveness ratios (ICERs) from both societal and health care perspectives. The efficacy of MS sherpa on early detection of active disease and the initiation of a treatment switch were modeled for a range of assumed efficacy (5%, 10%, 15%, 20%). (3) Results: From a societal perspective, for the efficacy of 15% or 20%, MS sherpa became dominant, which means cost-saving compared to the standard of care. MS sherpa is cost-effective in the 5% and 10% scenarios (ICERs EUR 14,535 and EUR 4069, respectively). From the health care perspective, all scenarios were cost-effective. Sensitivity analysis showed that increasing the efficacy of MS sherpa in detecting active disease early leading to treatment switches be the most impactful factor in the MS model. (4) Conclusions: The results indicate the potential of eHealth interventions to be cost-effective or even cost-saving in the MS care path. As such, digital biomarker-based eHealth interventions, like MS sherpa, are promising cost-effective solutions in optimizing MS disease management for people with MS, by detecting active disease early and helping neurologists in decisions on treatment switch.
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Affiliation(s)
- Sonja Cloosterman
- Orikami Digital Health Products, Ridderstraat 29, 6511 TM Nijmegen, The Netherlands; (I.W.); (B.d.T.)
| | - Inez Wijnands
- Orikami Digital Health Products, Ridderstraat 29, 6511 TM Nijmegen, The Netherlands; (I.W.); (B.d.T.)
| | - Simone Huygens
- Institute for Medical Technology Assessment (iMTA), Erasmus University of Rotterdam, Burgemeester Oudlaan 50, 3062 PA Rotterdam, The Netherlands; (S.H.); (V.W.); (M.V.)
| | - Valérie Wester
- Institute for Medical Technology Assessment (iMTA), Erasmus University of Rotterdam, Burgemeester Oudlaan 50, 3062 PA Rotterdam, The Netherlands; (S.H.); (V.W.); (M.V.)
- Erasmus School for Health Policy & Management, Erasmus University of Rotterdam, Burgemeester Oudlaan 50, 3062 PA Rotterdam, The Netherlands
| | - Ka-Hoo Lam
- Department of Neurology, MS Center Amsterdam, Amsterdam University Medical Centers, Location VUmc, De Boelelaan, 1117 HV Amsterdam, The Netherlands; (K.-H.L.); (E.S.)
| | - Eva Strijbis
- Department of Neurology, MS Center Amsterdam, Amsterdam University Medical Centers, Location VUmc, De Boelelaan, 1117 HV Amsterdam, The Netherlands; (K.-H.L.); (E.S.)
| | - Bram den Teuling
- Orikami Digital Health Products, Ridderstraat 29, 6511 TM Nijmegen, The Netherlands; (I.W.); (B.d.T.)
| | - Matthijs Versteegh
- Institute for Medical Technology Assessment (iMTA), Erasmus University of Rotterdam, Burgemeester Oudlaan 50, 3062 PA Rotterdam, The Netherlands; (S.H.); (V.W.); (M.V.)
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Decreased Cerebrospinal Fluid Antioxidative Capacity Is Related to Disease Severity and Progression in Early Multiple Sclerosis. Biomolecules 2021; 11:biom11091264. [PMID: 34572477 PMCID: PMC8472420 DOI: 10.3390/biom11091264] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2021] [Revised: 08/20/2021] [Accepted: 08/23/2021] [Indexed: 12/12/2022] Open
Abstract
Background: Oxidative stress-induced neuronal damage in multiple sclerosis (MS) results from an imbalance between toxic free radicals and counteracting antioxidants, i.e., antioxidative capacity (AOC). The relation of AOC to outcome measures in MS still remains inconclusive. We aimed to compare AOC in cerebrospinal fluid (CSF) and serum between early MS and controls and assess its correlation with clinical/radiological measures. Methods: We determined AOC (ability of CSF and serum of patients to inhibit 2,2′-azobis(2-amidinopropane) dihydrochloride-induced oxidation of dihydrorhodamine) in clinically isolated syndrome (CIS)/early relapsing-remitting MS (RRMS) (n = 55/11) and non-inflammatory neurological controls (n = 67). MS patients underwent clinical follow-up (median, 4.5; IQR, 5.2 years) and brain MRI at 3 T (baseline/follow-up n = 47/34; median time interval, 3.5; IQR, 2.1 years) to determine subclinical disease activity. Results: CSF AOC was differently regulated among CIS, RRMS and controls (p = 0.031) and lower in RRMS vs. CIS (p = 0.020). Lower CSF AOC correlated with physical disability (r = −0.365, p = 0.004) and risk for future relapses (exp(β) = 0.929, p = 0.033). No correlations with MRI metrics were found. Conclusion: Decreased CSF AOC was associated with increased disability and clinical disease activity in MS. While our finding cannot prove causation, they should prompt further investigations into the role of AOC in the evolution of MS.
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Wiendl H, Gold R, Berger T, Derfuss T, Linker R, Mäurer M, Aktas O, Baum K, Berghoff M, Bittner S, Chan A, Czaplinski A, Deisenhammer F, Di Pauli F, Du Pasquier R, Enzinger C, Fertl E, Gass A, Gehring K, Gobbi C, Goebels N, Guger M, Haghikia A, Hartung HP, Heidenreich F, Hoffmann O, Kallmann B, Kleinschnitz C, Klotz L, Leussink VI, Leutmezer F, Limmroth V, Lünemann JD, Lutterotti A, Meuth SG, Meyding-Lamadé U, Platten M, Rieckmann P, Schmidt S, Tumani H, Weber F, Weber MS, Zettl UK, Ziemssen T, Zipp F. Multiple Sclerosis Therapy Consensus Group (MSTCG): position statement on disease-modifying therapies for multiple sclerosis (white paper). Ther Adv Neurol Disord 2021; 14:17562864211039648. [PMID: 34422112 PMCID: PMC8377320 DOI: 10.1177/17562864211039648] [Citation(s) in RCA: 88] [Impact Index Per Article: 29.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2021] [Accepted: 07/28/2021] [Indexed: 12/20/2022] Open
Abstract
Multiple sclerosis is a complex, autoimmune-mediated disease of the central nervous system characterized by inflammatory demyelination and axonal/neuronal damage. The approval of various disease-modifying therapies and our increased understanding of disease mechanisms and evolution in recent years have significantly changed the prognosis and course of the disease. This update of the Multiple Sclerosis Therapy Consensus Group treatment recommendation focuses on the most important recommendations for disease-modifying therapies of multiple sclerosis in 2021. Our recommendations are based on current scientific evidence and apply to those medications approved in wide parts of Europe, particularly German-speaking countries (Germany, Austria, and Switzerland).
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Affiliation(s)
- Heinz Wiendl
- Klinik für Neurologie mit Institut für Translationale Neurologie, Universitätsklinikum Münster, Albert-Schweitzer-Campus 1, Gebäude A1, 48149 Münster
| | - Ralf Gold
- Neurologie, St. Josef-Hospital, Klinikum der Ruhr-Universität Bochum, Gudrunstraße 56, 44791 Bochum, Germany
| | - Thomas Berger
- Universitätsklinik für Neurologie, Medizinische Universität Wien, Wien, Austria
| | - Tobias Derfuss
- Neurologische Klinik und Poliklinik, Universitätsspital Basel, Basel, Switzerland
| | - Ralf Linker
- Klinik und Poliklinik für Neurologie, Universitätsklinikum Regensburg, Regensburg, Germany
| | - Mathias Mäurer
- Neurologie und Neurologische Frührehabilitation, Klinikum Würzburg Mitte gGmbH, Standort Juliusspital, Würzburg, Germany
| | - Orhan Aktas
- Neurologische Klinik, Heinrich-Heine-Universität Düsseldorf, Düsseldorf, Germany
| | - Karl Baum
- Neurologie, Klinik Hennigsdorf, Hennigsdorf, Germany
| | | | - Stefan Bittner
- Klinik für Neurologie, Universitätsmedizin der Johannes Gutenberg-Universität Mainz, Mainz, Germany
| | - Andrew Chan
- Neurologie, Inselspital, Universitätsspital Bern, Bern, Switzerland
| | | | | | | | | | - Christian Enzinger
- Universitätsklinik für Neurologie, Medizinische Universität Graz, Graz, Austria
| | - Elisabeth Fertl
- Wiener Gesundheitsverbund, Neurologische Abteilung, Wien, Austria
| | - Achim Gass
- Neurologische Klinik, Universitätsmedizin Mannheim/Medizinische Fakultät Mannheim, Universität Heidelberg, Mannheim, Germany
| | - Klaus Gehring
- Berufsverband Deutscher Nervenärzte (BVDN), Neurozentrum am Klosterforst, Itzehoe, Germany
| | | | - Norbert Goebels
- Klinik für Neurologie, Universitätsklinikum Düsseldorf, Düsseldorf, Germany
| | - Michael Guger
- Klinik für Neurologie 2, Kepler Universitätsklinikum, Linz, Austria
| | | | - Hans-Peter Hartung
- Klinik für Neurologie, Medizinische Fakultät, Heinrich-Heine-Universität Düsseldorf, Düsseldorf, Germany; Klinik für Neurologie, Medizinische Universität Wien, Wien, Austria
| | - Fedor Heidenreich
- Diakovere Krankenhaus, Henriettenstift, Klinik für Neurologie und klinische Neurophysiologie, Hannover, Germany
| | - Olaf Hoffmann
- Klinik für Neurologie, Alexianer St. Josefs-Krankenhaus Potsdam, Potsdam, Germany; NeuroCure, Charité-Universitätsmedizin Berlin, Berlin, Germany; Medizinische Hochschule Brandenburg Theodor Fontane, Neuruppin, Germany
| | - Boris Kallmann
- Kallmann Neurologie, Multiple Sklerose Zentrum Bamberg, Bamberg, Germany
| | | | - Luisa Klotz
- Klinik für Neurologie mit Institut für Translationale Neurologie, Universitätsklinikum Münster, Münster, Germany
| | | | - Fritz Leutmezer
- Neurologie, Universitäts-Klinik für Neurologie Wien, Wien, Austria
| | - Volker Limmroth
- Klinik für Neurologie, Krankenhaus Köln-Merheim, Köln, Germany
| | - Jan D Lünemann
- Klinik für Neurologie mit Institut für Translationale Neurologie, Universitätsklinikum Münster, Münster, Germany
| | | | - Sven G Meuth
- Neurologische Klinik, Heinrich-Heine-Universität Düsseldorf, Düsseldorf, Germany
| | | | - Michael Platten
- Neurologische Klinik, Universitätsmedizin Mannheim/Medizinische Fakultät Mannheim, Universität Heidelberg, Mannheim, Germany
| | - Peter Rieckmann
- Medical Park, Fachklinik für Neurologie, Zentrum für Klinische Neuroplastizität, Bischofswiesen, Germany
| | - Stephan Schmidt
- Neurologie, Gesundheitszentrum St. Johannes Hospital, Bonn, Germany
| | - Hayrettin Tumani
- Fachklinik für Neurologie Dietenbronn, Akademisches Krankenhaus der Universität Ulm, Ulm, Germany
| | - Frank Weber
- Neurologie, Sana Kliniken, Cham, Switzerland
| | - Martin S Weber
- Institut für Neuropathologie, Neurologische Klinik, Universitätsmedizin Göttingen, Göttingen, Germany
| | - Uwe K Zettl
- Klinik und Poliklinik für Neurologie, Zentrum für Nervenheilkunde, Universitätsmedizin Rostock, Rostock, Germany
| | - Tjalf Ziemssen
- Klinik und Poliklinik für Neurologie, Universitätsklinikum Carl Gustav Carus an der Technischen Universität Dresden, Dresden, Germany
| | - Frauke Zipp
- Klinik und Poliklinik für Neurologie, Universitätsmedizin der Johannes Gutenberg-Universität Mainz, Langenbeckstraße 1, 55131 Mainz, Germany
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Wiendl H, Gold R, Berger T, Derfuss T, Linker R, Mäurer M, Stangel M, Aktas O, Baum K, Berghoff M, Bittner S, Chan A, Czaplinski A, Deisenhammer F, Di Pauli F, Du Pasquier R, Enzinger C, Fertl E, Gass A, Gehring K, Gobbi C, Goebels N, Guger M, Haghikia A, Hartung HP, Heidenreich F, Hoffmann O, Hunter ZR, Kallmann B, Kleinschnitz C, Klotz L, Leussink V, Leutmezer F, Limmroth V, Lünemann JD, Lutterotti A, Meuth SG, Meyding-Lamadé U, Platten M, Rieckmann P, Schmidt S, Tumani H, Weber MS, Weber F, Zettl UK, Ziemssen T, Zipp F. [Multiple sclerosis treatment consensus group (MSTCG): position paper on disease-modifying treatment of multiple sclerosis 2021 (white paper)]. DER NERVENARZT 2021; 92:773-801. [PMID: 34297142 PMCID: PMC8300076 DOI: 10.1007/s00115-021-01157-2] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Accepted: 05/07/2021] [Indexed: 12/16/2022]
Abstract
Die Multiple Sklerose ist eine komplexe, autoimmun vermittelte Erkrankung des zentralen Nervensystems, charakterisiert durch inflammatorische Demyelinisierung sowie axonalen/neuronalen Schaden. Die Zulassung verschiedener verlaufsmodifizierender Therapien und unser verbessertes Verständnis der Krankheitsmechanismen und -entwicklung in den letzten Jahren haben die Prognose und den Verlauf der Erkrankung deutlich verändert. Diese Aktualisierung der Behandlungsempfehlung der Multiple Sklerose Therapie Konsensus Gruppe konzentriert sich auf die wichtigsten Empfehlungen für verlaufsmodifizierende Therapien der Multiplen Sklerose im Jahr 2021. Unsere Empfehlungen basieren auf aktuellen wissenschaftlichen Erkenntnissen und gelten für diejenigen Medikamente, die in weiten Teilen Europas, insbesondere in den deutschsprachigen Ländern (Deutschland, Österreich, Schweiz), zugelassen sind.
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Affiliation(s)
- Heinz Wiendl
- Klinik für Neurologie mit Institut für Translationale Neurologie, Universitätsklinikum Münster, Westfälische Wilhelms-Universität Münster, Albert-Schweitzer-Campus 1, Gebäude A1, 48149, Münster, Deutschland. .,Steuerungsgruppe der MSTKG, Münster, Deutschland. .,Multiple Sklerose Therapie Konsensus Gruppe (MSTKG), Münster, Deutschland.
| | - Ralf Gold
- Steuerungsgruppe der MSTKG, Münster, Deutschland. .,Multiple Sklerose Therapie Konsensus Gruppe (MSTKG), Münster, Deutschland. .,Neurologie, St. Josef-Hospital, Klinikum der Ruhr-Universität Bochum, Gudrunstraße 56, 44791, Bochum, Deutschland.
| | - Thomas Berger
- Steuerungsgruppe der MSTKG, Münster, Deutschland.,Multiple Sklerose Therapie Konsensus Gruppe (MSTKG), Münster, Deutschland.,Universitätsklinik für Neurologie, Medizinische Universität Wien, Wien, Österreich
| | - Tobias Derfuss
- Steuerungsgruppe der MSTKG, Münster, Deutschland.,Multiple Sklerose Therapie Konsensus Gruppe (MSTKG), Münster, Deutschland.,Neurologische Klinik und Poliklinik, Universitätsspital Basel, Basel, Schweiz
| | - Ralf Linker
- Steuerungsgruppe der MSTKG, Münster, Deutschland.,Multiple Sklerose Therapie Konsensus Gruppe (MSTKG), Münster, Deutschland.,Klinik und Poliklinik für Neurologie, Universitätsklinikum Regensburg, Regensburg, Deutschland
| | - Mathias Mäurer
- Steuerungsgruppe der MSTKG, Münster, Deutschland.,Multiple Sklerose Therapie Konsensus Gruppe (MSTKG), Münster, Deutschland.,Neurologie und Neurologische Frührehabilitation, Klinikum Würzburg Mitte gGmbH, Standort Juliusspital, Würzburg, Deutschland
| | - Martin Stangel
- Steuerungsgruppe der MSTKG, Münster, Deutschland.,Multiple Sklerose Therapie Konsensus Gruppe (MSTKG), Münster, Deutschland.,Klinische Neuroimmunologie und Neurochemie, Klinik für Neurologie, Medizinische Hochschule Hannover, Hannover, Deutschland
| | - Orhan Aktas
- Multiple Sklerose Therapie Konsensus Gruppe (MSTKG), Münster, Deutschland
| | - Karl Baum
- Multiple Sklerose Therapie Konsensus Gruppe (MSTKG), Münster, Deutschland
| | - Martin Berghoff
- Multiple Sklerose Therapie Konsensus Gruppe (MSTKG), Münster, Deutschland
| | - Stefan Bittner
- Multiple Sklerose Therapie Konsensus Gruppe (MSTKG), Münster, Deutschland
| | - Andrew Chan
- Multiple Sklerose Therapie Konsensus Gruppe (MSTKG), Münster, Deutschland
| | - Adam Czaplinski
- Multiple Sklerose Therapie Konsensus Gruppe (MSTKG), Münster, Deutschland
| | | | - Franziska Di Pauli
- Multiple Sklerose Therapie Konsensus Gruppe (MSTKG), Münster, Deutschland
| | - Renaud Du Pasquier
- Multiple Sklerose Therapie Konsensus Gruppe (MSTKG), Münster, Deutschland
| | - Christian Enzinger
- Multiple Sklerose Therapie Konsensus Gruppe (MSTKG), Münster, Deutschland
| | - Elisabeth Fertl
- Multiple Sklerose Therapie Konsensus Gruppe (MSTKG), Münster, Deutschland
| | - Achim Gass
- Multiple Sklerose Therapie Konsensus Gruppe (MSTKG), Münster, Deutschland
| | - Klaus Gehring
- Multiple Sklerose Therapie Konsensus Gruppe (MSTKG), Münster, Deutschland
| | - Claudio Gobbi
- Multiple Sklerose Therapie Konsensus Gruppe (MSTKG), Münster, Deutschland
| | - Norbert Goebels
- Multiple Sklerose Therapie Konsensus Gruppe (MSTKG), Münster, Deutschland
| | - Michael Guger
- Multiple Sklerose Therapie Konsensus Gruppe (MSTKG), Münster, Deutschland
| | - Aiden Haghikia
- Multiple Sklerose Therapie Konsensus Gruppe (MSTKG), Münster, Deutschland
| | - Hans-Peter Hartung
- Multiple Sklerose Therapie Konsensus Gruppe (MSTKG), Münster, Deutschland
| | - Fedor Heidenreich
- Multiple Sklerose Therapie Konsensus Gruppe (MSTKG), Münster, Deutschland
| | - Olaf Hoffmann
- Multiple Sklerose Therapie Konsensus Gruppe (MSTKG), Münster, Deutschland
| | - Zoë R Hunter
- Klinik für Neurologie mit Institut für Translationale Neurologie, Universitätsklinikum Münster, Münster, Deutschland
| | - Boris Kallmann
- Multiple Sklerose Therapie Konsensus Gruppe (MSTKG), Münster, Deutschland
| | | | - Luisa Klotz
- Multiple Sklerose Therapie Konsensus Gruppe (MSTKG), Münster, Deutschland
| | - Verena Leussink
- Multiple Sklerose Therapie Konsensus Gruppe (MSTKG), Münster, Deutschland
| | - Fritz Leutmezer
- Multiple Sklerose Therapie Konsensus Gruppe (MSTKG), Münster, Deutschland
| | - Volker Limmroth
- Multiple Sklerose Therapie Konsensus Gruppe (MSTKG), Münster, Deutschland
| | - Jan D Lünemann
- Multiple Sklerose Therapie Konsensus Gruppe (MSTKG), Münster, Deutschland
| | - Andreas Lutterotti
- Multiple Sklerose Therapie Konsensus Gruppe (MSTKG), Münster, Deutschland
| | - Sven G Meuth
- Multiple Sklerose Therapie Konsensus Gruppe (MSTKG), Münster, Deutschland
| | - Uta Meyding-Lamadé
- Multiple Sklerose Therapie Konsensus Gruppe (MSTKG), Münster, Deutschland
| | - Michael Platten
- Multiple Sklerose Therapie Konsensus Gruppe (MSTKG), Münster, Deutschland
| | - Peter Rieckmann
- Multiple Sklerose Therapie Konsensus Gruppe (MSTKG), Münster, Deutschland
| | - Stephan Schmidt
- Multiple Sklerose Therapie Konsensus Gruppe (MSTKG), Münster, Deutschland
| | - Hayrettin Tumani
- Multiple Sklerose Therapie Konsensus Gruppe (MSTKG), Münster, Deutschland
| | - Martin S Weber
- Multiple Sklerose Therapie Konsensus Gruppe (MSTKG), Münster, Deutschland
| | - Frank Weber
- Multiple Sklerose Therapie Konsensus Gruppe (MSTKG), Münster, Deutschland
| | - Uwe K Zettl
- Multiple Sklerose Therapie Konsensus Gruppe (MSTKG), Münster, Deutschland
| | - Tjalf Ziemssen
- Multiple Sklerose Therapie Konsensus Gruppe (MSTKG), Münster, Deutschland
| | - Frauke Zipp
- Steuerungsgruppe der MSTKG, Münster, Deutschland.,Multiple Sklerose Therapie Konsensus Gruppe (MSTKG), Münster, Deutschland.,Klinik und Poliklinik für Neurologie, Universitätsmedizin der Johannes Gutenberg-Universität Mainz, Langenbeckstraße 1, 55131, Mainz, Deutschland
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Monreal E, Sainz de la Maza S, Costa-Frossard L, Walo-Delgado P, Zamora J, Fernández-Velasco JI, Villarrubia N, Espiño M, Lourido D, Lapuente P, Toboso I, Álvarez-Cermeño JC, Masjuan J, Villar LM. Predicting Aggressive Multiple Sclerosis With Intrathecal IgM Synthesis Among Patients With a Clinically Isolated Syndrome. NEUROLOGY-NEUROIMMUNOLOGY & NEUROINFLAMMATION 2021; 8:8/5/e1047. [PMID: 34301819 PMCID: PMC8299514 DOI: 10.1212/nxi.0000000000001047] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/25/2021] [Accepted: 06/14/2021] [Indexed: 01/14/2023]
Abstract
Objective To determine the best method to measure intrathecal immunoglobulin (Ig) M synthesis (ITMS), a biomarker of worse prognosis in multiple sclerosis (MS). We compared the ability for predicting a poor evolution of 4 methods assessing ITMS (IgM oligoclonal bands [OCMBs], lipid-specific OCMBs [LS-OCMBs], Reibergram, and IgM index) in patients with a clinically isolated syndrome (CIS). Methods Prospective study with consecutive patients performed at a referral MS center. We used unadjusted and multivariate Cox regressions for predicting a second relapse, Expanded Disability Status Scale (EDSS) scores of 4 and 6, and development of secondary progressive MS (SPMS). Results A total of 193 patients were included, with a median (interquartile range) age of 31 (25–38) years and a median follow-up of 12.9 years. Among all methods, only OCMB, LS-OCMB, and Reibergram significantly identified patients at risk of some of the pre-established outcomes, being LS-OCMB the technique with the strongest associations. Adjusted hazard ratio (aHR) of LS-OCMB for predicting a second relapse was 2.50 (95% CI 1.72–3.64, p < 0.001). The risk of reaching EDSS scores of 4 and 6 and SPMS was significantly higher among patients with LS-OCMB (aHR 2.96, 95% CI 1.54–5.71, p = 0.001; aHR 4.96, 95% CI 2.22–11.07, p < 0.001; and aHR 2.31, 95% CI 1.08–4.93, p = 0.03, respectively). Conclusions ITMS predicts an aggressive MS at disease onset, especially when detected as LS-OCMB. Classification of Evidence This study provides Class II evidence that lipid-specific IgM oligoclonal bands can predict progression from CIS to MS and a worse disease course over a follow-up of at least 2 years.
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Affiliation(s)
- Enric Monreal
- From the Department of Neurology (E.M., S.S.d.l.M., L.C.-F., J.C.Á.-C., J.M.), and Department of Immunology (P.W.-D., J.I.F.-V., N.V., M.E., P.L., I.T., L.M.V.), Hospital Universitario Ramón y Cajal, REEM, IRYCIS; Clinical Biostatistics Unit (J.Z.), Hospital Universitario Ramón y Cajal, IRYCIS, CIBERESP, Madrid, Spain; Institute of Metabolism and System Research (J.Z.), University of Birmingham, United Kingdom; and Department of Radiology (D.L.), Hospital Universitario Ramón y Cajal, IRYCIS, Madrid, Spain.
| | - Susana Sainz de la Maza
- From the Department of Neurology (E.M., S.S.d.l.M., L.C.-F., J.C.Á.-C., J.M.), and Department of Immunology (P.W.-D., J.I.F.-V., N.V., M.E., P.L., I.T., L.M.V.), Hospital Universitario Ramón y Cajal, REEM, IRYCIS; Clinical Biostatistics Unit (J.Z.), Hospital Universitario Ramón y Cajal, IRYCIS, CIBERESP, Madrid, Spain; Institute of Metabolism and System Research (J.Z.), University of Birmingham, United Kingdom; and Department of Radiology (D.L.), Hospital Universitario Ramón y Cajal, IRYCIS, Madrid, Spain
| | - Lucienne Costa-Frossard
- From the Department of Neurology (E.M., S.S.d.l.M., L.C.-F., J.C.Á.-C., J.M.), and Department of Immunology (P.W.-D., J.I.F.-V., N.V., M.E., P.L., I.T., L.M.V.), Hospital Universitario Ramón y Cajal, REEM, IRYCIS; Clinical Biostatistics Unit (J.Z.), Hospital Universitario Ramón y Cajal, IRYCIS, CIBERESP, Madrid, Spain; Institute of Metabolism and System Research (J.Z.), University of Birmingham, United Kingdom; and Department of Radiology (D.L.), Hospital Universitario Ramón y Cajal, IRYCIS, Madrid, Spain
| | - Paulette Walo-Delgado
- From the Department of Neurology (E.M., S.S.d.l.M., L.C.-F., J.C.Á.-C., J.M.), and Department of Immunology (P.W.-D., J.I.F.-V., N.V., M.E., P.L., I.T., L.M.V.), Hospital Universitario Ramón y Cajal, REEM, IRYCIS; Clinical Biostatistics Unit (J.Z.), Hospital Universitario Ramón y Cajal, IRYCIS, CIBERESP, Madrid, Spain; Institute of Metabolism and System Research (J.Z.), University of Birmingham, United Kingdom; and Department of Radiology (D.L.), Hospital Universitario Ramón y Cajal, IRYCIS, Madrid, Spain
| | - Javier Zamora
- From the Department of Neurology (E.M., S.S.d.l.M., L.C.-F., J.C.Á.-C., J.M.), and Department of Immunology (P.W.-D., J.I.F.-V., N.V., M.E., P.L., I.T., L.M.V.), Hospital Universitario Ramón y Cajal, REEM, IRYCIS; Clinical Biostatistics Unit (J.Z.), Hospital Universitario Ramón y Cajal, IRYCIS, CIBERESP, Madrid, Spain; Institute of Metabolism and System Research (J.Z.), University of Birmingham, United Kingdom; and Department of Radiology (D.L.), Hospital Universitario Ramón y Cajal, IRYCIS, Madrid, Spain
| | - José Ignacio Fernández-Velasco
- From the Department of Neurology (E.M., S.S.d.l.M., L.C.-F., J.C.Á.-C., J.M.), and Department of Immunology (P.W.-D., J.I.F.-V., N.V., M.E., P.L., I.T., L.M.V.), Hospital Universitario Ramón y Cajal, REEM, IRYCIS; Clinical Biostatistics Unit (J.Z.), Hospital Universitario Ramón y Cajal, IRYCIS, CIBERESP, Madrid, Spain; Institute of Metabolism and System Research (J.Z.), University of Birmingham, United Kingdom; and Department of Radiology (D.L.), Hospital Universitario Ramón y Cajal, IRYCIS, Madrid, Spain
| | - Noelia Villarrubia
- From the Department of Neurology (E.M., S.S.d.l.M., L.C.-F., J.C.Á.-C., J.M.), and Department of Immunology (P.W.-D., J.I.F.-V., N.V., M.E., P.L., I.T., L.M.V.), Hospital Universitario Ramón y Cajal, REEM, IRYCIS; Clinical Biostatistics Unit (J.Z.), Hospital Universitario Ramón y Cajal, IRYCIS, CIBERESP, Madrid, Spain; Institute of Metabolism and System Research (J.Z.), University of Birmingham, United Kingdom; and Department of Radiology (D.L.), Hospital Universitario Ramón y Cajal, IRYCIS, Madrid, Spain
| | - Mercedes Espiño
- From the Department of Neurology (E.M., S.S.d.l.M., L.C.-F., J.C.Á.-C., J.M.), and Department of Immunology (P.W.-D., J.I.F.-V., N.V., M.E., P.L., I.T., L.M.V.), Hospital Universitario Ramón y Cajal, REEM, IRYCIS; Clinical Biostatistics Unit (J.Z.), Hospital Universitario Ramón y Cajal, IRYCIS, CIBERESP, Madrid, Spain; Institute of Metabolism and System Research (J.Z.), University of Birmingham, United Kingdom; and Department of Radiology (D.L.), Hospital Universitario Ramón y Cajal, IRYCIS, Madrid, Spain
| | - Daniel Lourido
- From the Department of Neurology (E.M., S.S.d.l.M., L.C.-F., J.C.Á.-C., J.M.), and Department of Immunology (P.W.-D., J.I.F.-V., N.V., M.E., P.L., I.T., L.M.V.), Hospital Universitario Ramón y Cajal, REEM, IRYCIS; Clinical Biostatistics Unit (J.Z.), Hospital Universitario Ramón y Cajal, IRYCIS, CIBERESP, Madrid, Spain; Institute of Metabolism and System Research (J.Z.), University of Birmingham, United Kingdom; and Department of Radiology (D.L.), Hospital Universitario Ramón y Cajal, IRYCIS, Madrid, Spain
| | - Paloma Lapuente
- From the Department of Neurology (E.M., S.S.d.l.M., L.C.-F., J.C.Á.-C., J.M.), and Department of Immunology (P.W.-D., J.I.F.-V., N.V., M.E., P.L., I.T., L.M.V.), Hospital Universitario Ramón y Cajal, REEM, IRYCIS; Clinical Biostatistics Unit (J.Z.), Hospital Universitario Ramón y Cajal, IRYCIS, CIBERESP, Madrid, Spain; Institute of Metabolism and System Research (J.Z.), University of Birmingham, United Kingdom; and Department of Radiology (D.L.), Hospital Universitario Ramón y Cajal, IRYCIS, Madrid, Spain
| | - Inmaculada Toboso
- From the Department of Neurology (E.M., S.S.d.l.M., L.C.-F., J.C.Á.-C., J.M.), and Department of Immunology (P.W.-D., J.I.F.-V., N.V., M.E., P.L., I.T., L.M.V.), Hospital Universitario Ramón y Cajal, REEM, IRYCIS; Clinical Biostatistics Unit (J.Z.), Hospital Universitario Ramón y Cajal, IRYCIS, CIBERESP, Madrid, Spain; Institute of Metabolism and System Research (J.Z.), University of Birmingham, United Kingdom; and Department of Radiology (D.L.), Hospital Universitario Ramón y Cajal, IRYCIS, Madrid, Spain
| | - José Carlos Álvarez-Cermeño
- From the Department of Neurology (E.M., S.S.d.l.M., L.C.-F., J.C.Á.-C., J.M.), and Department of Immunology (P.W.-D., J.I.F.-V., N.V., M.E., P.L., I.T., L.M.V.), Hospital Universitario Ramón y Cajal, REEM, IRYCIS; Clinical Biostatistics Unit (J.Z.), Hospital Universitario Ramón y Cajal, IRYCIS, CIBERESP, Madrid, Spain; Institute of Metabolism and System Research (J.Z.), University of Birmingham, United Kingdom; and Department of Radiology (D.L.), Hospital Universitario Ramón y Cajal, IRYCIS, Madrid, Spain
| | - Jaime Masjuan
- From the Department of Neurology (E.M., S.S.d.l.M., L.C.-F., J.C.Á.-C., J.M.), and Department of Immunology (P.W.-D., J.I.F.-V., N.V., M.E., P.L., I.T., L.M.V.), Hospital Universitario Ramón y Cajal, REEM, IRYCIS; Clinical Biostatistics Unit (J.Z.), Hospital Universitario Ramón y Cajal, IRYCIS, CIBERESP, Madrid, Spain; Institute of Metabolism and System Research (J.Z.), University of Birmingham, United Kingdom; and Department of Radiology (D.L.), Hospital Universitario Ramón y Cajal, IRYCIS, Madrid, Spain
| | - Luisa María Villar
- From the Department of Neurology (E.M., S.S.d.l.M., L.C.-F., J.C.Á.-C., J.M.), and Department of Immunology (P.W.-D., J.I.F.-V., N.V., M.E., P.L., I.T., L.M.V.), Hospital Universitario Ramón y Cajal, REEM, IRYCIS; Clinical Biostatistics Unit (J.Z.), Hospital Universitario Ramón y Cajal, IRYCIS, CIBERESP, Madrid, Spain; Institute of Metabolism and System Research (J.Z.), University of Birmingham, United Kingdom; and Department of Radiology (D.L.), Hospital Universitario Ramón y Cajal, IRYCIS, Madrid, Spain
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Tortora M, Tranfa M, D’Elia AC, Pontillo G, Petracca M, Bozzao A, Caranci F, Cervo A, Cosottini M, Falini A, Longo M, Manara R, Muto M, Porcu M, Roccatagliata L, Todeschini A, Saba L, Brunetti A, Cocozza S, Elefante A. Walk Your Talk: Real-World Adherence to Guidelines on the Use of MRI in Multiple Sclerosis. Diagnostics (Basel) 2021; 11:diagnostics11081310. [PMID: 34441245 PMCID: PMC8394408 DOI: 10.3390/diagnostics11081310] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2021] [Revised: 07/15/2021] [Accepted: 07/19/2021] [Indexed: 11/23/2022] Open
Abstract
(1) Although guidelines about the use of MRI sequences for Multiple Sclerosis (MS) diagnosis and follow-up are available, variability in acquisition protocols is not uncommon in everyday clinical practice. The aim of this study was to evaluate the real-world application of MS imaging guidelines in different settings to clarify the level of adherence to these guidelines. (2) Via an on-line anonymous survey, neuroradiologists (NR) were asked about MRI protocols and parameters routinely acquired when MS patients are evaluated in their center, both at diagnosis and follow-up. Furthermore, data about report content and personal opinions about emerging neuroimaging markers were also retrieved. (3) A total of 46 participants were included, mostly working in a hospital or university hospital (80.4%) and with more than 10 years of experience (47.9%). We found a relatively good adherence to the suggested MRI protocols regarding the use of T2-weighted sequences, although almost 10% of the participants routinely acquired 2D sequences with a slice thickness superior to 3 mm. On the other hand, a wider degree of heterogeneity was found regarding gadolinium administration, almost routinely performed at follow-up examination (87.0% of cases) in contrast with the current guidelines, as well as a low use of a standardized reporting system (17.4% of cases). (4) Although the MS community is getting closer to a standardization of MRI protocols, there is still a relatively wide heterogeneity among NR, with particular reference to contrast administration, which must be overcome to guarantee an adequate quality of patients’ care in MS.
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Affiliation(s)
- Mario Tortora
- Department of Advanced Biomedical Sciences, University of Naples “Federico II”, 80131 Naples, Italy; (M.T.); (M.T.); (A.C.D.); (G.P.); (A.B.); (A.E.)
| | - Mario Tranfa
- Department of Advanced Biomedical Sciences, University of Naples “Federico II”, 80131 Naples, Italy; (M.T.); (M.T.); (A.C.D.); (G.P.); (A.B.); (A.E.)
| | - Anna Chiara D’Elia
- Department of Advanced Biomedical Sciences, University of Naples “Federico II”, 80131 Naples, Italy; (M.T.); (M.T.); (A.C.D.); (G.P.); (A.B.); (A.E.)
| | - Giuseppe Pontillo
- Department of Advanced Biomedical Sciences, University of Naples “Federico II”, 80131 Naples, Italy; (M.T.); (M.T.); (A.C.D.); (G.P.); (A.B.); (A.E.)
| | - Maria Petracca
- Department of Neurosciences and Reproductive and Odontostomatological Sciences, University “Federico II”, 80131 Naples, Italy;
- Department of Human Neurosciences, Sapienza University of Rome, 00189 Rome, Italy
| | - Alessandro Bozzao
- Neuroradiology Unit, NESMOS Department, Sapienza University of Rome, 00189 Rome, Italy;
| | - Ferdinando Caranci
- Department of Medicine of Precision, University of Campania “Luigi Vanvitelli”, 80138 Naples, Italy;
| | - Amedeo Cervo
- Department of Neuroradiology, ASST Grande Ospedale Metropolitano Niguarda, 20121 Milan, Italy;
| | - Mirco Cosottini
- Department of Translational Research and New Technologies in Medicine and Surgery, University of Pisa, 56126 Pisa, Italy;
| | - Andrea Falini
- Neuroradiology Department, IRCCS San Raffaele Hospital and University, 20132 Milan, Italy;
| | - Marcello Longo
- Neuroradiology Unit, Department of Biomedical Sciences and Morphological and Functional Images, University of Messina, 98124 Messina, Italy;
| | - Renzo Manara
- Department of Neurosciences, University of Padua, 35121 Padua, Italy;
| | - Mario Muto
- Diagnostic and Interventional Neuroradiology, Cardarelli Hospital, 80131 Naples, Italy;
| | - Michele Porcu
- Department of Radiology, Azienda Ospedaliero Universitaria (A.O.U.) di Cagliari, 09124 Cagliari, Italy; (M.P.); (L.S.)
| | - Luca Roccatagliata
- Department of Health Sciences, University of Genova, 16132 Genova, Italy;
- Neuroradiology Unit, IRCCS Ospedale Policlinico San Martino, 16132 Genova, Italy
| | - Alessandra Todeschini
- Neuroradiology Unit, Department of Neuroscience, Nuovo Ospedale Civile S. Agostino Estense, 41126 Modena, Italy;
| | - Luca Saba
- Department of Radiology, Azienda Ospedaliero Universitaria (A.O.U.) di Cagliari, 09124 Cagliari, Italy; (M.P.); (L.S.)
| | - Arturo Brunetti
- Department of Advanced Biomedical Sciences, University of Naples “Federico II”, 80131 Naples, Italy; (M.T.); (M.T.); (A.C.D.); (G.P.); (A.B.); (A.E.)
| | - Sirio Cocozza
- Department of Advanced Biomedical Sciences, University of Naples “Federico II”, 80131 Naples, Italy; (M.T.); (M.T.); (A.C.D.); (G.P.); (A.B.); (A.E.)
- Correspondence:
| | - Andrea Elefante
- Department of Advanced Biomedical Sciences, University of Naples “Federico II”, 80131 Naples, Italy; (M.T.); (M.T.); (A.C.D.); (G.P.); (A.B.); (A.E.)
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47
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A Pilot Study of 24-h Motor Activity Patterns in Multiple Sclerosis: Pre-Planned Follow-Up at 2 Years. Clocks Sleep 2021; 3:366-376. [PMID: 34203507 PMCID: PMC8293228 DOI: 10.3390/clockssleep3030023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2021] [Revised: 06/16/2021] [Accepted: 06/16/2021] [Indexed: 11/23/2022] Open
Abstract
Early multiple sclerosis (MS) predictive markers of disease activity/prognosis have been proposed but are not universally accepted. Aim of this pilot prospective study is to verify whether a peculiar hyperactivity, observed at baseline (T0) in early relapsing-remitting (RR) MS patients, could represent a further prognostic marker. Here we report results collected at T0 and at a 24-month follow-up (T1). Eighteen RRMS patients (11 females, median Expanded Disability Status Scale-EDSS score 1.25, range EDSS score 0–2) were monitored at T0 (mean age 32.33 ± 7.51) and T1 (median EDSS score 1.5, range EDSS score 0–2.5). Patients were grouped into two groups: responders (R, 14 patients) and non-responders (NR, 4 patients) to treatment at T1. Each patient wore an actigraph for one week to record the 24-h motor activity pattern. At T0, NR presented significantly lower motor activity than R between around 9:00 and 13:00. At T1, NR were characterized by significantly lower motor activity than R between around 12:00 and 17:00. Overall, these data suggest that through the 24-h motor activity pattern, we can fairly segregate at T0 patients who will show a therapeutic failure, possibly related to a more active disease, at T1. These patients are characterized by a reduced morning level of motor activation. Further studies on larger populations are needed to confirm these preliminary findings.
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48
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Wattjes MP, Ciccarelli O, Reich DS, Banwell B, de Stefano N, Enzinger C, Fazekas F, Filippi M, Frederiksen J, Gasperini C, Hacohen Y, Kappos L, Li DKB, Mankad K, Montalban X, Newsome SD, Oh J, Palace J, Rocca MA, Sastre-Garriga J, Tintoré M, Traboulsee A, Vrenken H, Yousry T, Barkhof F, Rovira À. 2021 MAGNIMS-CMSC-NAIMS consensus recommendations on the use of MRI in patients with multiple sclerosis. Lancet Neurol 2021; 20:653-670. [PMID: 34139157 DOI: 10.1016/s1474-4422(21)00095-8] [Citation(s) in RCA: 294] [Impact Index Per Article: 98.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2020] [Revised: 02/15/2021] [Accepted: 03/12/2021] [Indexed: 12/11/2022]
Abstract
The 2015 Magnetic Resonance Imaging in Multiple Sclerosis and 2016 Consortium of Multiple Sclerosis Centres guidelines on the use of MRI in diagnosis and monitoring of multiple sclerosis made an important step towards appropriate use of MRI in routine clinical practice. Since their promulgation, there have been substantial relevant advances in knowledge, including the 2017 revisions of the McDonald diagnostic criteria, renewed safety concerns regarding intravenous gadolinium-based contrast agents, and the value of spinal cord MRI for diagnostic, prognostic, and monitoring purposes. These developments suggest a changing role of MRI for the management of patients with multiple sclerosis. This 2021 revision of the previous guidelines on MRI use for patients with multiple sclerosis merges recommendations from the Magnetic Resonance Imaging in Multiple Sclerosis study group, Consortium of Multiple Sclerosis Centres, and North American Imaging in Multiple Sclerosis Cooperative, and translates research findings into clinical practice to improve the use of MRI for diagnosis, prognosis, and monitoring of individuals with multiple sclerosis. We recommend changes in MRI acquisition protocols, such as emphasising the value of three dimensional-fluid-attenuated inversion recovery as the core brain pulse sequence to improve diagnostic accuracy and ability to identify new lesions to monitor treatment effectiveness, and we provide recommendations for the judicious use of gadolinium-based contrast agents for specific clinical purposes. Additionally, we extend the recommendations to the use of MRI in patients with multiple sclerosis in childhood, during pregnancy, and in the post-partum period. Finally, we discuss promising MRI approaches that might deserve introduction into clinical practice in the near future.
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Affiliation(s)
- Mike P Wattjes
- Department of Diagnostic and Interventional Neuroradiology, Hannover Medical School, Hannover, Germany; Department of Radiology and Nuclear Medicine, Amsterdam UMC, Amsterdam, Netherlands
| | - Olga Ciccarelli
- Faculty of Brain Sciences, University College London Queen Square Institute of Neurology, University College London, London, UK; National Institute for Health Research University College London Hospitals Biomedical Research Centre, London, UK
| | - Daniel S Reich
- Translational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
| | - Brenda Banwell
- Division of Neurology, Children's Hospital of Philadelphia, Philadelphia, PA, USA; Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Nicola de Stefano
- Department of Medicine, Surgery and Neuroscience, University of Siena, Siena, Italy
| | - Christian Enzinger
- Department of Neurology, Medical University of Graz, Graz, Austria; Division of Neuroradiology, Vascular and Interventional Radiology, Department of Radiology, Medical University of Graz, Graz, Austria
| | - Franz Fazekas
- Department of Neurology, Medical University of Graz, Graz, Austria
| | - Massimo Filippi
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy; Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy; Neurophysiology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy; Vita-Salute San Raffaele University, Milan, Italy
| | - Jette Frederiksen
- Department of Neurology, Rigshospitalet Glostrup, University Hospital of Copenhagen, Glostrup, Denmark
| | - Claudio Gasperini
- Department of Neurology, San Camillo-Forlanini Hospital, Roma, Italy
| | - Yael Hacohen
- Faculty of Brain Sciences, University College London Queen Square Institute of Neurology, University College London, London, UK; Department of Paediatric Neurology, Great Ormond Street Hospital for Children, London, UK
| | - Ludwig Kappos
- Department of Neurology and Research Center for Clinical Neuroimmunology and Neuroscience, University Hospital of Basel and University of Basel, Basel, Switzerland
| | - David K B Li
- Department of Radiology, University of British Columbia, Vancouver, BC, Canada
| | - Kshitij Mankad
- Department of Neuroradiology, Great Ormond Street Hospital for Children, London, UK
| | - Xavier Montalban
- Multiple Sclerosis Centre of Catalonia, Department of Neurology-Neuroimmunology, Hospital Universitari Vall d'Hebron, Universitat Autònoma de Barcelona, Barcelona, Spain; Division of Neurology, St Michael's Hospital, University of Toronto, Toronto, ON, Canada
| | - Scott D Newsome
- Department of Neurology, Johns Hopkins School of Medicine, Baltimore, MD, USA
| | - Jiwon Oh
- Division of Neurology, St Michael's Hospital, University of Toronto, Toronto, ON, Canada
| | | | - Maria A Rocca
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy; Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy; Vita-Salute San Raffaele University, Milan, Italy
| | - Jaume Sastre-Garriga
- Multiple Sclerosis Centre of Catalonia, Department of Neurology-Neuroimmunology, Hospital Universitari Vall d'Hebron, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Mar Tintoré
- Multiple Sclerosis Centre of Catalonia, Department of Neurology-Neuroimmunology, Hospital Universitari Vall d'Hebron, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Anthony Traboulsee
- Division of Neurology, University of British Columbia, Vancouver, BC, Canada
| | - Hugo Vrenken
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, Amsterdam, Netherlands
| | - Tarek Yousry
- Lysholm Department of Neuroradiology, UCLH National Hospital for Neurology and Neurosurgery, London, UK; Neuroradiological Academic Unit, University College London Queen Square Institute of Neurology, University College London, London, UK
| | - Frederik Barkhof
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, Amsterdam, Netherlands; Faculty of Brain Sciences, University College London Queen Square Institute of Neurology, University College London, London, UK; National Institute for Health Research University College London Hospitals Biomedical Research Centre, London, UK
| | - Àlex Rovira
- Section of Neuroradiology, Department of Radiology, Hospital Universitari Vall d'Hebron, Universitat Autònoma de Barcelona, Barcelona, Spain.
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49
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Rocca MA, Valsasina P, Meani A, Pagani E, Cordani C, Cervellin C, Filippi M. Network Damage Predicts Clinical Worsening in Multiple Sclerosis: A 6.4-Year Study. NEUROLOGY-NEUROIMMUNOLOGY & NEUROINFLAMMATION 2021; 8:8/4/e1006. [PMID: 34021055 PMCID: PMC8143700 DOI: 10.1212/nxi.0000000000001006] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/26/2020] [Accepted: 03/05/2021] [Indexed: 01/06/2023]
Abstract
OBJECTIVE In multiple sclerosis (MS), clinical impairment is likely due to both structural damage and abnormal brain function. We assessed the added value of integrating structural and functional network MRI measures to predict 6.4-year MS clinical disability deterioration. METHODS Baseline 3D T1-weighted and resting-state functional MRI scans were obtained from 233 patients with MS and 77 healthy controls. Patients underwent a neurologic evaluation at baseline and at 6.4-year median follow-up (interquartile range = 5.06-7.51 years). At follow-up, patients were classified as clinically stable/worsened according to disability changes. In relapsing-remitting (RR) MS, secondary progressive (SP) MS conversion was evaluated. Global brain volumetry was obtained. Furthermore, independent component analysis identified the main functional connectivity (FC) and gray matter (GM) network patterns. RESULTS At follow-up, 105/233 (45%) patients were clinically worsened; 26/157 (16%) patients with RRMS evolved to SPMS. The treatment-adjusted random forest model identified normalized GM and brain volumes, decreased FC between default-mode networks, increased FC of the left precentral gyrus in the sensorimotor network (SMN), and GM atrophy in the fronto-parietal network (false discovery rate [FDR]-corrected p = range 0.01-0.09) as predictors of clinical worsening (out-of-bag [OOB] accuracy = 0.74). An expected contribution of baseline disability was also present (FDR-p = 0.01). Baseline disability, normalized GM volume, and GM atrophy in the SMN (FDR-p = range 0.01-0.09) were independently associated with SPMS conversion (OOB accuracy = 0.84). At receiver operating characteristic analysis, including network MRI variables improved disability worsening (p = 0.05) and SPMS conversion (p = 0.02) prediction. CONCLUSIONS Integration of MRI network measures helped determining the relative contributions of global/local GM damage and functional reorganization to clinical deterioration in MS.
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Affiliation(s)
- Maria A Rocca
- From the Neuroimaging Research Unit (M.A.R.), Division of Neuroscience; and Neurology Unit, IRCCS San Raffaele Scientific Institute; Vita-Salute San Raffaele University (M.A.R., M.F.); Neuroimaging Research Unit (P.V., A.M., E.P., Claudio Cordani, Chiara Cervellin), Division of Neuroscience, IRCCS San Raffaele Scientific Institute; and Neuroimaging Research Unit (M.F.), Division of Neuroscience, Neurology Unit, Neurorehabilitation Unit, and Neurophysiology Service, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Paola Valsasina
- From the Neuroimaging Research Unit (M.A.R.), Division of Neuroscience; and Neurology Unit, IRCCS San Raffaele Scientific Institute; Vita-Salute San Raffaele University (M.A.R., M.F.); Neuroimaging Research Unit (P.V., A.M., E.P., Claudio Cordani, Chiara Cervellin), Division of Neuroscience, IRCCS San Raffaele Scientific Institute; and Neuroimaging Research Unit (M.F.), Division of Neuroscience, Neurology Unit, Neurorehabilitation Unit, and Neurophysiology Service, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Alessandro Meani
- From the Neuroimaging Research Unit (M.A.R.), Division of Neuroscience; and Neurology Unit, IRCCS San Raffaele Scientific Institute; Vita-Salute San Raffaele University (M.A.R., M.F.); Neuroimaging Research Unit (P.V., A.M., E.P., Claudio Cordani, Chiara Cervellin), Division of Neuroscience, IRCCS San Raffaele Scientific Institute; and Neuroimaging Research Unit (M.F.), Division of Neuroscience, Neurology Unit, Neurorehabilitation Unit, and Neurophysiology Service, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Elisabetta Pagani
- From the Neuroimaging Research Unit (M.A.R.), Division of Neuroscience; and Neurology Unit, IRCCS San Raffaele Scientific Institute; Vita-Salute San Raffaele University (M.A.R., M.F.); Neuroimaging Research Unit (P.V., A.M., E.P., Claudio Cordani, Chiara Cervellin), Division of Neuroscience, IRCCS San Raffaele Scientific Institute; and Neuroimaging Research Unit (M.F.), Division of Neuroscience, Neurology Unit, Neurorehabilitation Unit, and Neurophysiology Service, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Claudio Cordani
- From the Neuroimaging Research Unit (M.A.R.), Division of Neuroscience; and Neurology Unit, IRCCS San Raffaele Scientific Institute; Vita-Salute San Raffaele University (M.A.R., M.F.); Neuroimaging Research Unit (P.V., A.M., E.P., Claudio Cordani, Chiara Cervellin), Division of Neuroscience, IRCCS San Raffaele Scientific Institute; and Neuroimaging Research Unit (M.F.), Division of Neuroscience, Neurology Unit, Neurorehabilitation Unit, and Neurophysiology Service, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Chiara Cervellin
- From the Neuroimaging Research Unit (M.A.R.), Division of Neuroscience; and Neurology Unit, IRCCS San Raffaele Scientific Institute; Vita-Salute San Raffaele University (M.A.R., M.F.); Neuroimaging Research Unit (P.V., A.M., E.P., Claudio Cordani, Chiara Cervellin), Division of Neuroscience, IRCCS San Raffaele Scientific Institute; and Neuroimaging Research Unit (M.F.), Division of Neuroscience, Neurology Unit, Neurorehabilitation Unit, and Neurophysiology Service, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Massimo Filippi
- From the Neuroimaging Research Unit (M.A.R.), Division of Neuroscience; and Neurology Unit, IRCCS San Raffaele Scientific Institute; Vita-Salute San Raffaele University (M.A.R., M.F.); Neuroimaging Research Unit (P.V., A.M., E.P., Claudio Cordani, Chiara Cervellin), Division of Neuroscience, IRCCS San Raffaele Scientific Institute; and Neuroimaging Research Unit (M.F.), Division of Neuroscience, Neurology Unit, Neurorehabilitation Unit, and Neurophysiology Service, IRCCS San Raffaele Scientific Institute, Milan, Italy.
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50
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Tommasin S, Cocozza S, Taloni A, Giannì C, Petsas N, Pontillo G, Petracca M, Ruggieri S, De Giglio L, Pozzilli C, Brunetti A, Pantano P. Machine learning classifier to identify clinical and radiological features relevant to disability progression in multiple sclerosis. J Neurol 2021; 268:4834-4845. [PMID: 33970338 PMCID: PMC8563671 DOI: 10.1007/s00415-021-10605-7] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2020] [Revised: 05/05/2021] [Accepted: 05/05/2021] [Indexed: 01/22/2023]
Abstract
Objectives To evaluate the accuracy of a data-driven approach, such as machine learning classification, in predicting disability progression in MS. Methods We analyzed structural brain images of 163 subjects diagnosed with MS acquired at two different sites. Participants were followed up for 2–6 years, with disability progression defined according to the expanded disability status scale (EDSS) increment at follow-up. T2-weighted lesion load (T2LL), thalamic and cerebellar gray matter (GM) volumes, fractional anisotropy of the normal appearing white matter were calculated at baseline and included in supervised machine learning classifiers. Age, sex, phenotype, EDSS at baseline, therapy and time to follow-up period were also included. Classes were labeled as stable or progressed disability. Participants were randomly chosen from both sites to build a sample including 50% patients showing disability progression and 50% patients being stable. One-thousand machine learning classifiers were applied to the resulting sample, and after testing for overfitting, classifier confusion matrix, relative metrics and feature importance were evaluated. Results At follow-up, 36% of participants showed disability progression. The classifier with the highest resulting metrics had accuracy of 0.79, area under the true positive versus false positive rates curve of 0.81, sensitivity of 0.90 and specificity of 0.71. T2LL, thalamic volume, disability at baseline and administered therapy were identified as important features in predicting disability progression. Classifiers built on radiological features had higher accuracy than those built on clinical features. Conclusions Disability progression in MS may be predicted via machine learning classifiers, mostly evaluating neuroradiological features. Supplementary Information The online version contains supplementary material available at 10.1007/s00415-021-10605-7.
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Affiliation(s)
- Silvia Tommasin
- Department of Human Neurosciences, Sapienza University of Rome, Viale dell'Università, 30, 00185, Rome, Italy.
| | - Sirio Cocozza
- Dipartimento di Scienze Biomediche Avanzate, Università degli Studi di Napoli Federico II, Naples, Italy
| | - Alessandro Taloni
- Institute for Complex Systems, Italian National Research Council, Rome, Italy
| | - Costanza Giannì
- Department of Human Neurosciences, Sapienza University of Rome, Viale dell'Università, 30, 00185, Rome, Italy
| | | | - Giuseppe Pontillo
- Dipartimento di Scienze Biomediche Avanzate, Università degli Studi di Napoli Federico II, Naples, Italy.,Dipartimento di Ingegneria Elettrica e delle Tecnologie dell'Informazione, Università degli Studi di Napoli Federico II, Naples, Italy
| | - Maria Petracca
- Department of Human Neurosciences, Sapienza University of Rome, Viale dell'Università, 30, 00185, Rome, Italy.,Dipartimento di Neuroscienze, Scienze Riproduttive e Odontostomatologiche, Università degli Studi di Napoli Federico II, Naples, Italy
| | - Serena Ruggieri
- Department of Human Neurosciences, Sapienza University of Rome, Viale dell'Università, 30, 00185, Rome, Italy.,Neuroimmunology Unit, IRCSS Fondazione Santa Lucia, Rome, Italy
| | - Laura De Giglio
- Department of Human Neurosciences, Sapienza University of Rome, Viale dell'Università, 30, 00185, Rome, Italy.,Neurology Unit, Medicine Department, San Filippo Neri Hospital, Rome, Italy
| | - Carlo Pozzilli
- Department of Human Neurosciences, Sapienza University of Rome, Viale dell'Università, 30, 00185, Rome, Italy
| | - Arturo Brunetti
- Dipartimento di Scienze Biomediche Avanzate, Università degli Studi di Napoli Federico II, Naples, Italy
| | - Patrizia Pantano
- Department of Human Neurosciences, Sapienza University of Rome, Viale dell'Università, 30, 00185, Rome, Italy.,Department of Radiology, IRCCS NEUROMED, Pozzilli, Italy
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