» Articles » PMID: 35875463

Predicting Long-term Disability in Multiple Sclerosis: A Narrative Review of Current Evidence and Future Directions

Overview
Journal Int J MS Care
Date 2022 Jul 25
PMID 35875463
Authors
Affiliations
Soon will be listed here.
Abstract

The ability to reliably monitor disease progression in patients with multiple sclerosis (MS) is integral to patient care. The Expanded Disability Status Scale (EDSS) is a commonly used tool to assess the disability status of patients with MS; however, it has limited sensitivity in detecting subtle changes in disability levels and, as a result, does not consistently provide clinicians with accurate insight into disease progression. At the 2019 European Committee for Treatment and Research in Multiple Sclerosis meeting in Stockholm, Sweden, a panel of neurologists met to discuss the limitations of the EDSS as a short-term predictor of MS progression. Before this panel discussion, a targeted literature review was conducted to evaluate published evidence on prognostic measures such as fatigue, physical assessments, and measures that are more taxing for patients, all of which may be useful to clinicians at different stages of the course of MS. This article summarizes currently available evidence in support of these measures. In addition, this article highlights the current state of expert clinical consensus regarding the current approaches used to predict and monitor disease progression and offers insight for future studies to assist clinicians in accurately monitoring disease progression in patients with MS.

Citing Articles

Investigating T-cell-derived extracellular vesicles as biomarkers of disease activity, axonal injury, and disability in multiple sclerosis.

Zagrodnik J, Blandford S, Fudge N, Arsenault S, Anthony S, McGrath L Clin Exp Immunol. 2025; 219(1).

PMID: 39798086 PMC: 11791523. DOI: 10.1093/cei/uxaf003.


Neuroimaging to monitor worsening of multiple sclerosis: advances supported by the grant for multiple sclerosis innovation.

Oh J, Airas L, Harrison D, Jarvinen E, Livingston T, Lanker S Front Neurol. 2023; 14:1319869.

PMID: 38107636 PMC: 10722910. DOI: 10.3389/fneur.2023.1319869.


Progression risk stratification with six-minute walk gait speed trajectory in multiple sclerosis.

Goldman M, Chen S, Motl R, Pearsall R, Oh U, Brenton J Front Neurol. 2023; 14:1259413.

PMID: 37859654 PMC: 10582752. DOI: 10.3389/fneur.2023.1259413.


The impact of relapse definition and measures of durability on MS clinical trial outcomes.

Satyanarayan S, Cutter G, Krieger S, Cofield S, Wolinsky J, Lublin F Mult Scler. 2023; 29(4-5):568-575.

PMID: 37119208 PMC: 10471316. DOI: 10.1177/13524585231157211.


Towards Multimodal Machine Learning Prediction of Individual Cognitive Evolution in Multiple Sclerosis.

Denissen S, Chen O, De Mey J, De Vos M, Van Schependom J, Sima D J Pers Med. 2021; 11(12).

PMID: 34945821 PMC: 8707909. DOI: 10.3390/jpm11121349.

References
1.
Balcer L, Raynowska J, Nolan R, Galetta S, Kapoor R, Benedict R . Validity of low-contrast letter acuity as a visual performance outcome measure for multiple sclerosis. Mult Scler. 2017; 23(5):734-747. PMC: 5407511. DOI: 10.1177/1352458517690822. View

2.
Chitnis T, Gonzalez C, Healy B, Saxena S, Rosso M, Barro C . Neurofilament light chain serum levels correlate with 10-year MRI outcomes in multiple sclerosis. Ann Clin Transl Neurol. 2018; 5(12):1478-1491. PMC: 6292183. DOI: 10.1002/acn3.638. View

3.
Uher T, Vaneckova M, Krasensky J, Sobisek L, Tyblova M, Volna J . Pathological cut-offs of global and regional brain volume loss in multiple sclerosis. Mult Scler. 2017; 25(4):541-553. DOI: 10.1177/1352458517742739. View

4.
Vaughn C, Kavak K, Dwyer M, Bushra A, Nadeem M, Cookfair D . Fatigue at enrollment predicts EDSS worsening in the New York State Multiple Sclerosis Consortium. Mult Scler. 2018; 26(1):99-108. DOI: 10.1177/1352458518816619. View

5.
Ebers G, Heigenhauser L, Daumer M, Lederer C, Noseworthy J . Disability as an outcome in MS clinical trials. Neurology. 2008; 71(9):624-31. DOI: 10.1212/01.wnl.0000313034.46883.16. View