1. Prognostic factors for worsening and improvement in multiple sclerosis using a multistate model.
- Author
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Ocampo A, Hatami F, Čuklina J, Graham G, Ganjgahi H, Sun Y, Su W, Mousseau MC, Gardiner S, Pendleton SC, Aarden P, Kieseier BC, Arnold DL, Bermel RA, Häring DA, Nichols TE, and Wiendl H
- Subjects
- Humans, Female, Male, Adult, Middle Aged, Prognosis, Brain pathology, Brain diagnostic imaging, Magnetic Resonance Imaging, Multiple Sclerosis diagnostic imaging, Multiple Sclerosis physiopathology, Multiple Sclerosis pathology, Disease Progression
- Abstract
Background: The long-term disease trajectory of people living with multiple sclerosis (MS) can be improved by initiating efficacious treatment early. More quantitative evidence is needed on factors that affect a patient's risk of disability worsening or possibility of improvement to inform timely treatment decisions., Methods: We developed a multistate model to quantify the influence of demographic, clinical, and imaging factors on disability worsening and disability improvement simultaneously across the disability spectrum as measured by the Expanded Disability Status Scale (EDSS). We used clinical trial data from the Novartis-Oxford MS database including ~130,000 EDSS assessments from ~8000 patients, spanning all MS phenotypes., Results: Higher brain volume was positively associated with disability improvement at all disability levels (hazard ratio (HR) = 1.09-1.19; 95% credible interval (CI) = 1.02-1.27). Higher T2 lesion volume was negatively associated with disability improvement up to EDSS 6 (HR = 0.80-0.89; 95% CI = 0.75-0.94). Older age, time since first symptoms, and the number of relapses in the past year were confirmed as predictors of future disability worsening., Conclusions: Brain damage was identified as the most consistent factor limiting the patient's probability for improvements from the earliest stages and across the whole course of MS. Protecting brain integrity early in MS should have greater weight in clinical decision-making., Competing Interests: Declaration of conflicting interestsThe author(s) declared the following potential conflicts of interest with respect to the research, authorship, and/or publication of this article: F.H. is currently employee of Exact Sciences, which was not involved in the study. D.L.A. has received personal compensation for serving as a Consultant for Alexion, Biogen, Celgene, Eli Lilly, EMD Serono, Frequency Therapeutics, Genentech, Merck, Novartis, Roche, Sanofi, and Shionogi, and holds an equity interest in NeuroRx. T.E.N received consulting fees from Perspectum Ltd. H.W. has received honoraria for acting as a member of scientific advisory boards for Biogen, Evgen, Genzyme, MedDay Pharmaceuticals, Merck Serono, Novartis, Roche Pharma AG, and Sanofi-Aventis, as well as speaker honoraria and travel support from Alexion, Biogen, Cognomed, F. Hoffmann-La Roche Ltd., Gemeinnützige Hertie-Stiftung, Merck Serono, Novartis, Roche Pharma AG, Genzyme, Teva, and WebMD Global. H.W is acting as a paid consultant for AbbVie, Actelion, Biogen, IGES, Johnson & Johnson, Novartis, Roche, Sanofi-Aventis, and the Swiss Multiple Sclerosis Society. His research is funded by the German Ministry for Education and Research (BMBF), Deutsche Forschungsgemeinschaft (DFG), Else Kröner Fresenius Foundation, Fresenius Foundation, the European Union, Hertie Foundation, NRW Ministry of Education and Research, Interdisciplinary Center for Clinical Studies (IZKF) Muenster and RE Children’s Foundation, Biogen, GlaxoSmithKline GmbH, Roche Pharma AG, and Sanofi-Genzyme. R.A.B. has served as a consultant for Astra Zeneca, Biogen, EMD Serono, Genzyme, Genentech, Novartis, and VielaBio. He receives research support from Biogen, Genentech, and Novartis. D.A.H., A.O., J.Č., G.G., W.S., M-C.M., P.A., and B.C.K. are employees of Novartis. H.G., Y.S., S.G., S.C.P., and T.E.N. are current employees of the Big Data Institute (Oxford, UK) which received funding from Novartis to collaborate on AI in Medicine including the work presented here.
- Published
- 2024
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