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Updated: Jul 14, 2026
The Multiple Sclerosis Performance Test (MSPT): An iPad-Based Disability Assessment Tool
Published on: June 30, 2014
Predicting short-term disability in multiple sclerosis
S A Gauthier1, M Mandel, C R G Guttmann
1Partners Multiple Sclerosis Center, Brigham and Women's Hospital, Brookline, MA 02445, USA.
Objective:
To develop covariate specific short-term disability curves to demonstrate the probability of progressing by Expanded Disability Status Scale (EDSS) at semiannual visits.
Methods:
Semiannual EDSS scores were prospectively collected in 218 relapsing-remitting (RR) and clinically isolated syndrome (CIS) patients as part of the Comprehensive Longitudinal Investigation of Multiple Sclerosis at the Brigham and Women's Hospital (CLIMB) study. Baseline brain parenchymal fraction (BPF) and T2 lesion volume were available on 205 patients. A partial proportional odds model determined the influence of covariates on the change in EDSS score at subsequent visits. A discrete second order Markov transitional model was fit and generated a probability matrix for each subject; the 6-month probabilities of EDSS change were graphically represented.
Results:
The univariate analysis demonstrated the lowest baseline BPF quartile (OR 1.99; p = 0.0203) and the highest T2 lesion volume quartile (OR 2.19; p = 0.0130) were associated with progression in EDSS. Covariate specific disability curves demonstrated the effect of BPF and T2 lesion volume on short-term progression. In subjects with a 6-month EDSS of 2, the probability of a sustained progression of an EDSS of 3 within 3 years was 0.277 for a subject with low BPF and a high T2 lesion volume vs 0.055 for a subject with high BPF and a low T2 lesion volume.
Conclusions:
Markov transitional models allow for the comparison of covariate specific short-term disability changes among groups of patients with multiple sclerosis.
