The Multiple Sclerosis Severity Score: fluctuations and prognostic ability in a longitudinal cohort of patients with MS

Author:

Gross RH1ORCID,Sillau SH1,Miller AE2,Farrell C2,Krieger SC2

Affiliation:

1. Department of Neurology, University of Colorado School of Medicine, Aurora, CO, USA

2. Corinne Goldsmith Dickinson Center for Multiple Sclerosis, Icahn School of Medicine at Mount Sinai, New York, NY, USA

Abstract

Background The Multiple Sclerosis Severity Score (MSSS), combining the Expanded Disability Status Scale (EDSS) and disease duration, attempts to stratify multiple sclerosis (MS) patients based on their rate of progression. Its prognostic ability in the individual patient remains unproven. Objectives To assess the stability of MSSS within individual persons with MS in a longitudinal cohort, to evaluate whether certain factors influence MSSS variability, and to explore the ability of MSSS to predict future ambulatory function. Methods A single-center retrospective review was performed of patients following a single provider for at least 8 years. Mixed model regression modeled MSSS over time. A Kaplan–Meier survival plot was fitted, using change of baseline MSSS by at least one decile as the event. Cox modeling assessed the influence of baseline clinical and demographic factors on the hazard of changing MSSS by at least one decile. Linear models evaluated the impact of baseline EDSS, baseline MSSS, and other factors on the Timed 25-Foot Walk (T25FW). Results Out of 122 patients, 68 (55.7%) deviated from baseline MSSS by at least one decile. Final T25FW had slightly weaker correlation to baseline MSSS than to baseline EDSS, which was moderately strongly correlated with future log T25FW. Conclusion Individual MSSS scores often vary over time. Clinicians should exercise caution when using MSSS to prognosticate.

Publisher

SAGE Publications

Subject

Cellular and Molecular Neuroscience,Neurology (clinical)

Cited by 5 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. A novel imaging marker of cortical “cellularity” in multiple sclerosis patients;Scientific Reports;2024-04-29

2. The role of machine learning in developing non-magnetic resonance imaging based biomarkers for multiple sclerosis: a systematic review;BMC Medical Informatics and Decision Making;2022-09-15

3. L’intelligence hybride pour prédire l’évolution des maladies chroniques;IHM '22: Proceedings of the 33rd Conference on l'Interaction Humain-Machine: Adjunct;2022-04-05

4. Regarding the letter from Roxburgh, et al.;Multiple Sclerosis Journal - Experimental, Translational and Clinical;2020-04

5. Regarding the publication The Multiple Sclerosis Severity Score: Fluctuations and prognostic ability in a longitudinal cohort of patients with MS authored by RH Gross et al;Multiple Sclerosis Journal - Experimental, Translational and Clinical;2020-04

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