• This record comes from PubMed

RECLAIM-A retrospective, multicenter observational study aimed at enabling the development of artificial intelligence-driven prognostic models for disease progression in multiple sclerosis

. 2025 ; 16 () : 1557947. [epub] 20250516

Status PubMed-not-MEDLINE Language English Country Switzerland Media electronic-ecollection

Document type Journal Article

Multiple sclerosis (MS) is characterized by a progressive worsening of disability over time. As many regulatory-cleared disease-modifying treatments aiming to slow down this progression are now available, a clear need has arisen for a personalized and data-driven approach to treatment optimization in order to more efficiently slow down disease progression and eventually, progressive disability worsening. This strongly depends on the availability of biomarkers that can detect and differentiate between the different forms of disease worsening, and on predictive models to estimate the disease trajectory for each patient under certain treatment conditions. To this end, we here describe a multicenter, retrospective, observational study, aimed at setting up a harmonized database to allow the development, training, optimization, and validation of such novel biomarkers and AI-based decision models. Additionally, the data will be used to develop the tools required to better monitor this progression and to generate further insights on disease worsening and progression, patient prognosis, treatment decisions and responses, and patient profiles of patients with MS.

AB Science Clinical Development Paris France

Athinoula A Martinos Center Department of Radiology Massachusetts General Hospital Charlestown MA United States

Bristol Myers Squibb Company Corp Princeton NJ United States

Center of Clinical Neuroscience Department of Neurology University Clinic Carl Gustav Carus TU Dresden Dresden Germany

Department of Computer Science Aalto University Espoo Finland

Department of Neurology and Center of Clinical Neuroscience 1st Faculty of Medicine Charles University and General University Hospital Prague Prague Czechia

Department of Neurology Vita Salute San Raffaele University Milan Italy

Department of Neurology with Experimental Neurology Charité Universitätsmedizin Berlin Corporate Member of Freie Universität Berlin and Humboldt Universität zu Berlin Berlin Germany

Department of Neurorehabilitative Sciences Milan Italy

Department of Neuroscience and Biomedical Engineering Aalto University Espoo Finland

European Charcot Foundation Brussels Belgium

Experimental and Clinical Research Center A Cooperation Between the Max Delbrück Center for Molecular Medicine in the Helmholtz Association and Charité Universitätsmedizin Berlin Berlin Germany

Experimental and Clinical Research Center Charité Universitätsmedizin Berlin Corporate Member of Freie Universität Berlin and Humboldt Universität zu Berlin Berlin Germany

F Hoffmann La Roche Ltd Product Development Medical Affairs Neuroscience Basel Switzerland

icometrix NV Leuven Belgium

Imcyse SA Liège Belgium

Institute of Neuroradiology St Josef Hospital Ruhr University Bochum Bochum Germany

Max Delbrück Center for Molecular Medicine in the Helmholtz Association Berlin Germany

Neuroscience Clinical Research Center Charité Universitätsmedizin Berlin Corporate Member of Freie Universität Berlin and Humboldt Universität zu Berlin Berlin Germany

Nocturne GmbH Berlin Germany

SYNAPSE Research Management Partners Madrid Spain

Univ Lille InsermU1172 LilNCog CHU Lille FHU Precise Lille France

See more in PubMed

Thompson AJ, Banwell B, Barkhof F, Carroll WM, Coetzee T, Comi G, et al. . Diagnosis of multiple sclerosis: 2017 revisions of the McDonald criteria. Lancet Neurol. (2018) 17:162–73. doi: 10.1016/s1474-4422(17)30470-2, PMID: PubMed DOI

Lublin FD, Reingold SC, Cohen JA, Cutter GR, Sorensen PS, Thompson AJ, et al. . Defining the clinical course of multiple sclerosis: the 2013 revisions. Neurology. (2014) 83:278–86. doi: 10.1212/wnl.0000000000000560, PMID: PubMed DOI PMC

Montalban X, Gold R, Thompson AJ, Otero-Romero S, Amato MP, Chandraratna D, et al. . ECTRIMS/EAN guideline on the pharmacological treatment of people with multiple sclerosis. Mult Scler J. (2018) 24:96–120. doi: 10.1177/1352458517751049, PMID: PubMed DOI

Spelman T, Magyari M, Piehl F, Svenningsson A, Rasmussen PV, Kant M, et al. . Treatment escalation vs immediate initiation of highly effective treatment for patients with relapsing-remitting multiple sclerosis. JAMA Neurol. (2021) 78:1197–204. doi: 10.1001/jamaneurol.2021.2738, PMID: PubMed DOI PMC

Montalban X, Hauser SL, Kappos L, Arnold DL, Bar-Or A, Comi G, et al. . Ocrelizumab versus placebo in primary progressive multiple sclerosis. N Engl J Med. (2017) 376:209–20. doi: 10.1056/nejmoa1606468, PMID: PubMed DOI

Tur C, Carbonell-Mirabent P, Cobo-Calvo A, Otero-Romero S, Arrambide G, Midaglia L, et al. . Association of Early Progression Independent of relapse activity with long-term disability after a first demyelinating event in multiple sclerosis. JAMA Neurol. (2023) 80:151–60. doi: 10.1001/jamaneurol.2022.4655, PMID: PubMed DOI PMC

Lublin FD, Häring DA, Ganjgahi H, Ocampo A, Hatami F, Čuklina J, et al. . How patients with multiple sclerosis acquire disability. Brain. (2022) 145:3147–61. doi: 10.1093/brain/awac016, PMID: PubMed DOI PMC

Cagol A, Schaedelin S, Barakovic M, Benkert P, Todea RA, Rahmanzadeh R, et al. . Association of Brain Atrophy with Disease Progression Independent of relapse activity in patients with relapsing multiple sclerosis. JAMA Neurol. (2022) 79:682–92. doi: 10.1001/jamaneurol.2022.1025, PMID: PubMed DOI PMC

Giovannoni G, Popescu V, Wuerfel J, Hellwig K, Iacobeus E, Jensen MB, et al. . Smouldering multiple sclerosis: the ‘real MS. Ther Adv Neurol Disord. (2022) 15:175628642110667. doi: 10.1177/17562864211066751, PMID: PubMed DOI PMC

Praet J, Anderhalten L, Comi G, Horakova D, Ziemssen T, Vermersch P, et al. . A future of AI-driven personalized care for people with multiple sclerosis. Front Immunol. (2024) 15:1446748. doi: 10.3389/fimmu.2024.1446748, PMID: PubMed DOI PMC

Voigt I, Inojosa H, Wenk J, Akgün K, Ziemssen T. Building a monitoring matrix for the management of multiple sclerosis. Autoimmun Rev. (2021) 22:103358. doi: 10.1016/j.autrev.2023.103358, PMID: PubMed DOI

Wattjes MP, Ciccarelli O, Reich DS, Banwell B, de Stefano N, Enzinger C, et al. . 2021 MAGNIMS–CMSC–NAIMS consensus recommendations on the use of MRI in patients with multiple sclerosis. Lancet Neurol. (2021) 20:653–70. doi: 10.1016/S1474-4422(21)00095-8 PubMed DOI

Rakić M, Vercruyssen S, Van Eyndhoven S, de la Rosa E, Jain S, Van Huffel S, et al. . Icobrain ms 5.1: combining unsupervised and supervised approaches for improving the detection of multiple sclerosis lesions. NeuroImage Clin. (2021) 31:102707. doi: 10.1016/j.nicl.2021.102707, PMID: PubMed DOI PMC

Smeets D, Ribbens A, Sima DM, Cambron M, Horakova D, Jain S, et al. . Reliable measurements of brain atrophy in individual patients with multiple sclerosis. Brain Behav. (2016) 6:e00518. doi: 10.1002/brb3.518, PMID: PubMed DOI PMC

Parciak T, Geys L, Helme A, van der Mei I, Hillert J, Schmidt H, et al. . Introducing a core dataset for real-world data in multiple sclerosis registries and cohorts: recommendations from a global task force. Mult Scler. (2023) 30:396–418. doi: 10.1177/13524585231216004, PMID: PubMed DOI PMC

Sima DM, Esposito G, Van Hecke W, Ribbens A, Nagels G, Smeets D. Health economic impact of software-assisted brain MRI on therapeutic decision-making and outcomes of relapsing-remitting multiple sclerosis patients—a microsimulation study. Brain Sci. (2021) 11:1570. doi: 10.3390/brainsci11121570, PMID: PubMed DOI PMC

Find record

Citation metrics

Loading data ...

Archiving options

Loading data ...