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Changes in employment status over time in multiple sclerosis following a first episode of central nervous system demyelination, a Markov multistate model study

Abstract

Background and purpose: Understanding predictors of changes in employment status among people living with multiple sclerosis (MS) can assist health care providers to develop appropriate work retention/rehabilitation programs. We aimed to model longitudinal transitions of employment status in MS and estimate the probabilities of retaining employment status or losing or gaining employment over time in individuals with a first clinical diagnosis of central nervous system demyelination (FCD). Methods: This prospective cohort study comprised adults (aged 18–59 years) diagnosed with FCD (n = 237) who were followed for more than 11 years. At each review, participants were assigned to one of three states: unemployed, part-time, or full-time employed. A Markov multistate model was used to examine the rate of state-to-state transitions. Results: At the time of FCD, participants with full-time employment had an 89% chance of being in the same state over a 1-year period, but this decreased to 42% over the 10-year follow-up period. For unemployed participants, there was a 92% likelihood of remaining unemployed after 1 year, but this probability decreased to 53% over 10 years. Females, those who progressed to clinically definite MS, those with a higher relapse count, and those with a greater level of disability were at increased risk of transitioning to a deteriorated employment state. In addition, those who experienced clinically significant fatigue over the follow-up period were less likely to gain employment after being unemployed. Conclusions: In our FCD cohort, we found a considerable rate of employment transition during the early years post-diagnosis. Over more than a decade of follow-up post-FCD, we found that females and individuals with a greater disability and a higher relapse count are at higher risk of losing employment.

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European Journal of Neurology

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