Related Experiment Video
Updated: Feb 28, 2026

A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data
Published on: December 9, 2015
Heterogeneity of sickness absence and disability pension trajectories among individuals with MS
Charlotte Björkenstam, Kristina Alexanderson, Michael Wiberg1
1Division of Insurance Medicine, Department of Clinical Neuroscience, Karolinska Institutet, Sweden.
Background:
The variability of progression of multiple sclerosis (MS) suggests that MS is a heterogeneous entity.
Objective:
The objective of this article is to determine whether sickness absence (SA) and disability pension (DP) could be used to identify groups of patients with different progression courses.
Methods:
We analyzed mean-annual net months of SA/DP, five years prior to MS diagnosis, until the year of diagnosis, and five years after for 3543 individuals diagnosed 2003-2006, by modeling trajectory subgroups.
Results:
Five different groups were identified, revealing substantial heterogeneity among MS patients. Before diagnosis, 74% had a flat trajectory, while the remaining had a sharply increasing degree of SA/DP. After diagnosis, 95% had a flat or marginally increasing trajectory, although at various SA/disability pension (DP) levels, whereas a small group of 5% had decreasing SA/DP. A majority had few or no SA/DP months throughout the 11-year study period. Higher age and a lower educational level were associated with an unfavorable trajectory (p values <0.01).
Conclusions:
There's a considerable heterogeneity of MS progression in terms of SA/DP. Compared with other measures of disability, sickness-absence and disability pension offer a continuous variable that can be assigned to every individual for each time period without missing data. To what extent the SA/DP measure reflects classical MS outcome-measures as well as how correlated it is with co-morbidities and working-conditions needs to be investigated further.
Insights
Sickness absence and disability pension reveal significant heterogeneity in multiple sclerosis (MS) progression. These measures identify distinct patient groups, aiding in understanding disease variability.
Area of Science:
- Neurology
- Public Health
- Social Medicine
Background:
- Multiple sclerosis (MS) is characterized by variable progression, indicating underlying heterogeneity.
- Identifying distinct patient trajectories is crucial for personalized management and research.
Purpose of the Study:
- To investigate the utility of sickness absence (SA) and disability pension (DP) in identifying subgroups of MS patients with different disease progression courses.
- To analyze SA/DP patterns before, during, and after MS diagnosis.
Main Methods:
- Analysis of mean-annual net months of SA/DP for 3543 individuals diagnosed with MS between 2003-2006.
- Longitudinal data collection covering 5 years pre-diagnosis to 5 years post-diagnosis (11-year study period).
- Modeling trajectory subgroups to categorize patient progression patterns.
Main Results:
- Five distinct patient trajectory subgroups were identified, highlighting significant MS heterogeneity.
- Pre-diagnosis, 74% showed a flat SA/DP trajectory; post-diagnosis, 95% had stable or marginally increasing trajectories.
- Higher age and lower educational level were associated with unfavorable SA/DP trajectories (p<0.01).
Conclusions:
- Sickness absence and disability pension effectively demonstrate considerable heterogeneity in MS progression.
- SA/DP offer a continuous, universally applicable measure for individuals over time, unlike other disability metrics.
- Further research is needed to correlate SA/DP with established MS outcomes, comorbidities, and working conditions.
Related Concept Videos
Classification of Illness
An illness is a response to a disease in which the person's level of functioning is changed compared with a previous level. The general classification of illness includes acute and chronic.
Acute illness is severe...
Factors Affecting Illness
For instance, risk factors are connected to illness,...

