Combining clinical and magnetic resonance imaging markers enhances prediction of 12-year employment status in multiple sclerosis patients.

BACKGROUND: Multiple sclerosis (MS) is frequently diagnosed in the most productive years of adulthood and is often associated with worsening employment status. However, reliable predictors of employment status change are lacking. OBJECTIVE: To identify early clinical and brain magnetic resonance imaging (MRI) markers of employment status worsening in MS patients at 12-year follow-up. METHODS: A total of 145 patients with early relapsing-remitting MS from the original Avonex-Steroids-Azathioprine (ASA) study were included in this prospective, longitudinal, observational cohort study. Cox models were conducted to identify MRI and clinical predictors (at baseline and during the first 12 months) of worsening employment status (patients either (1) working full-time or part-time with no limitations due to MS and retaining this status during the course of the study, or (2) patients working full-time or part-time with no limitations due to MS and switching to being unemployed or working part-time due to MS). RESULTS: In univariate analysis, brain parenchymal fraction, T1 and T2 lesion volume were the best MRI predictors of worsening employment status over the 12-year follow-up period. MS duration at baseline (hazard ratio (HR) = 1.10, 95% confidence interval (CI) 1.03-1.18; p = 0.040) was the only significant clinical predictor. Having one extra milliliter of T1 lesion volume was associated with a 53% greater risk of worsening employment status (HR = 1.53, 95% CI 1.16-2.02; p = 0.018). A brain parenchymal fraction decrease of 1% increased the risk of worsening employment status by 22% (HR = 0.78, 95% CI 0.65-0.95; p = 0.034). CONCLUSION: Brain atrophy and lesion load were significant predictors of worsening employment status in MS patients. Using a combination of clinical and MRI markers may improve the early prediction of an employment status change over long-term follow-up.

Characteristics of motor speech phenotypes in multiple sclerosis.

BACKGROUND: Motor speech disorders in multiple sclerosis (MS) are poorly understood and their quantitative, objective acoustic characterization remains limited. Additionally, little data regarding relationships between the severity of speech disorders and neurological involvement in MS, as well as the contribution of pyramidal and cerebellar functional systems on speech phenotypes, is available. METHODS: Speech data were acquired from 141 MS patients with Expanded Disability Status Scale (EDSS) ranging from 1 to 6.5 and 70 matched healthy controls. Objective acoustic speech assessment including subtests on phonation, oral diadochokinesis, articulation and prosody was performed. RESULTS: The prevalence of dysarthria in our MS cohort was 56% while the severity was generally mild and primarily consisted of a combination of spastic and ataxic components. Prosodic-articulatory disorder presenting with monopitch, articulatory decay, excess loudness variations and slow rate was the most salient. Speech disorders reflected subclinical motor impairment with 78% accuracy in discriminating between a subgroup of asymptomatic MS (EDSS < 2.0) and control speakers. Speech disorder severity was related to the severity of neurological involvement. Decreased articulation rate was moderately correlated to EDSS as well as all subtests of the multiple sclerosis functional composite. The strongest correlation was observed between irregular oral diadochokinesis and the 9-Hole Peg Test (r = - 0.65, p < 0.001). Irregular oral diadochokinesis and excess loudness variations significantly separated pure pyramidal and mixed pyramidal-cerebellar MS subgroups. CONCLUSIONS: Automated speech analyses may provide valuable biomarkers of disease progression in MS as dysarthria represents common and early manifestation that reflects disease disability and underlying pyramidal-cerebellar pathophysiology.