Predictors of Ability to Work in Multiple Sclerosis

Multiple sclerosis (MS) is a chronic disorder that typically shows accumulation of disability, affecting the ability to work. The disease severity is usually graded by physicians with the expanded disability status scale (EDSS) in the clinic, but patient-reported outcome questionnaires are also available, like the Multiple Sclerosis Impact Scale (MSIS-29) or Fatigue Scale for Motor and Cognitive Functions (FSMC). The aim of this work was to investigate the quantitative link between disease severity and the number of days with MS-related sickness benefits from registry data (the Swedish MS registry and the Swedish Social Insurance Agency's Micro Data for Analyzes of Social Insurance registry). An item response theory model for the disability was built, linking the EDSS, MSIS-29, and FSMC to the same underlying disease construct through five correlated latent variables. A Markov state model for the level of sickness benefits was also developed, in which the disease severities from the disability model were tested as covariates, on top of age. The latent variable for EDSS was the most important predictor of work ability. Patients with low disability (EDSS < 3) hardly had any sickness benefit days, while patients with severe disability (EDSS ≥ 6) were found to spend over 50% of their time with sickness benefits. Physical aspects of the disease were found to be more important than psychological aspects in predicting work ability. This underlines the patient-specific nature of MS, and the need for predictive models such as these to evaluate treatment effects, make risk assessments, and calculate societal and individual costs.