Predictors of Ability to Work in Multiple Sclerosis.

Area of Science:

• Neurology
• Health Economics
• Biostatistics

Background:

• Multiple sclerosis (MS) is a chronic neurological disease causing progressive disability and affecting work capacity.
• Disease severity is assessed using clinical scales like the Expanded Disability Status Scale (EDSS) and patient-reported outcomes (MSIS-29, FSMC).
• Understanding the link between MS severity and work ability is crucial for economic and healthcare planning.

Purpose of the Study:

• To quantitatively assess the relationship between multiple sclerosis disease severity and the number of sickness benefit days claimed.
• To develop and validate predictive models for work ability in MS patients using registry data.

Main Methods:

• An item response theory model was developed to integrate EDSS, MSIS-29, and FSMC scores into a unified disease severity construct.
• A Markov state model was employed to analyze sickness benefit claims, incorporating disease severity and age as covariates.
• Swedish MS registry and social insurance data were utilized for model development and validation.

Main Results:

• The Expanded Disability Status Scale (EDSS) latent variable was the primary predictor of work ability.
• Patients with low EDSS (<3) had minimal sickness benefit usage, while those with severe EDSS (≥6) used benefits for over 50% of their time.
• Physical aspects of MS disability were more influential on work ability than psychological aspects.

Conclusions:

• Physical disability, particularly as measured by EDSS, is a key determinant of work ability in multiple sclerosis.
• Predictive models integrating clinical and patient-reported data are essential for assessing treatment efficacy, risk, and costs associated with MS.
• The findings underscore the patient-specific nature of MS and its economic impact.