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. 2024 Mar;30(3):419-431.
doi: 10.1177/13524585231225929. Epub 2024 Jan 19.

Recent trends in disease-modifying therapy use and associated sickness absence and disability pension among people with multiple sclerosis in Sweden

Fitsum Sebsibe Teni  1 , Alejandra Machado  1 , Katharina Fink  2 , Hanna Gyllensten  3 , Jan Hillert  2 , Emilie Friberg  1
Affiliations

Recent trends in disease-modifying therapy use and associated sickness absence and disability pension among people with multiple sclerosis in Sweden

Fitsum Sebsibe Teni et al. Mult Scler. 2024 Mar.

Abstract

Background: Disease-modifying therapies (DMTs) have led to improved health and work productivity among people with multiple sclerosis (PwMS).

Objectives: To describe trajectories of recent DMT use and their association with sickness absence and/or disability pension (SADP) among PwMS in Sweden.

Methods: A longitudinal register-based study was conducted among 1395 PwMS with treatment start in 2014/2015. While DMT use over 5 years was assessed using sequence analysis resulting in four clusters, a 7-year (Y-2 toY4) trend of SADP was analyzed using zero-inflated negative binomial regression.

Results: Four clusters of DMT use trajectories were identified: long-term non-high-efficacy (483, 34.6%), long-term high-efficacy (572, 41%), escalation (221, 15.8%), and discontinuation (119, 8.5%). Progressive MS and higher expanded disability status scale scores were associated with the escalation, long-term high-efficacy, or discontinuation clusters. PwMS in the long-term high-efficacy and escalation clusters had higher likelihood of being on SADP. However, PwMS initiating high-efficacy DMTs demonstrated steeper decline in SADP than others.

Conclusion: Using sequence analysis, this study showed recent DMT use trajectories among PwMS where initiation of high-efficacy DMTs has become more common. The trend of SADP was stable and lower in those using non-high-efficacy DMTs and larger improvements were shown in those initiating high-efficacy DMTs.

Keywords: Disease-modifying drugs; cluster analysis; high-efficacy DMTs; sick leave.

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Conflict of interest statement

Declaration of Conflicting InterestsThe author(s) declared the following potential conflicts of interest with respect to the research, authorship, and/or publication of this article: F.S.T. is funded partly by unrestricted research grant from Biogen and Celgene/Bristol-Myers Squibb. A.M. is funded partly by unrestricted research grant from Biogen. K.F. received honoraria for serving on advisory boards for Biogen, Merck, and Roche and speaker’s fees from Merck. H.G. has previously been funded partly by unrestricted research grant from Biogen. At the time of conducting this study, H.G. was employed by IQVIA; a contract research organization that performs commissioned pharmacoepidemiological studies and therefore was collaborating with several pharmaceutical companies. J.H. received honoraria for serving on advisory boards for Biogen, Bristol-Myers-Squibb, Janssen, Merck KGaA, Novartis, Sandoz, and Sanofi-Genzyme and speaker’s fees from Biogen, Janssen, Novartis, Merck, Teva, Sandoz, and Sanofi-Genzyme. He has served as P.I. for projects sponsored by, or received unrestricted research support from, Biogen, Bristol-Myers-Squibb, Janssen, Merck KGaA, Novartis, Roche, and Sanofi-Genzyme. His MS research is funded by the Swedish Research Council and the Swedish Brain foundation. E.F. has previously been funded partly by an unrestricted research grant from Biogen, has received unrestricted research grants from Celgene/Bristol-Myers Squibb, and speaker’s fees from Merck.

Figures

Figure 1.
Figure 1.
Sequence index plot of the four disease-modifying therapy (DMT) use clusters showing the states people with multiple sclerosis were in during the follow-up.
Figure 2.
Figure 2.
Mean sickness absence and/or disability pension days per year among the people with multiple sclerosis across disease-modifying therapy use clusters. SADP: sickness absence and/or disability pension, CI: confidence interval.
Figure 3.
Figure 3.
Binary logistic regression component of the zero-inflated negative binomial regression analysis on the odds of occurrence of SADP days. DMT: disease-modifying therapy, EDSS: Expanded Disability Status Scale, SADP: Sickness Absence and/or Disability Pension. *All: adjusted for the variables sex, age, type of MS, comorbidity, EDSS score, DMT switch, EQ-5D index, and MS treatment start year; reference group: long-term non-high-efficacy DMTs cluster. The models in the figure present results of the binary logistic regression component of the zero-inflated negative binomial regression, where the odds of occurrence of SADP days were compared across DMT use clusters in each year of the total 7 years of follow-up.
Figure 4.
Figure 4.
Negative binomial model component of the zero-inflated negative binomial regression analysis on the number of SADP days. DMT: disease-modifying therapy, EDSS: Expanded Disability Status Scale, SADP: Sickness Absence and/or Disability Pension. *All: adjusted for the variables sex, age, type of MS, comorbidity, EDSS score, DMT switch, EQ-5D index, and MS treatment start year; reference group: long-term non-high-efficacy DMTs cluster. The models in the figure show results of negative binomial regression component of the zero-inflated negative binomial regression, where the number of SADP days was compared across DMT use clusters in each year of the total 7 years of follow-up.
See this image and copyright information in PMC

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