Risk factors for leaving employment due to multiple sclerosis and changes in risk over the past decades: using competing risk survival analysis

Jing Chen, Bruce Taylor, Leigh Blizzard, Steve Simpson-Yap, Andrew J. Palmer, Andrea Kirk-Brown, Pieter Van Dijk, Ingrid van der Mei

Research output: Contribution to journalArticleResearchpeer-review

Abstract

Background: No studies have assessed changes in employment survival in multiple sclerosis (MS) populations over recent decades, including the introduction of disease-modifying therapies (DMTs). Objectives: To evaluate factors associated with leaving employment due to MS; to assess whether the risk of leaving employment has changed over recent decades in Australia, stratified by MS phenotype. Methods: We included 1240 participants who were working before MS diagnosis. Information on employment status, reasons for leaving employment and year of leaving were collected. Data were analysed using competing risk survival analysis. Results: Males, progressive MS, lower education level and older age at diagnosis were associated with a higher sub-distribution hazard of leaving employment. Compared to the period before 2010, the sub-distribution hazard during 2010–2016 for relapsing-remitting multiple sclerosis (RRMS) was reduced by 43% (sub-distribution hazard ratio (sHR) 0.67, 95% confidence interval (CI): 0.50 to 0.90), while no significant reduction was seen for primary-progressive multiple sclerosis (PPMS) (sHR 1.25, 95% CI: 0.72 to 2.16) or secondary-progressive multiple sclerosis (SPMS) (sHR 1.37, 95% CI: 0.84 to 2.25). Conclusion: Males, people with progressive MS and those of lower education level were at higher risk of leaving employment. The differential changed risk of leaving employment between people with different MS phenotype after 2010 coincides with the increased usage of high-efficacy DMTs for RRMS.

Original languageEnglish
Number of pages12
JournalMultiple Sclerosis Journal
DOIs
Publication statusAccepted/In press - 2020

Keywords

  • competing risks
  • disease-modifying therapies
  • employment
  • Multiple sclerosis
  • sex
  • survival analysis

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