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Updated: May 20, 2025

A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data
Published on: December 9, 2015
Prodromal phase of multiple sclerosis: evidence from sickness absence patterns before disease onset - a matched
Ali Manouchehrinia1, Feng Zhu2, Jan Hillert1
1Clinical Neuroscience, Karolinska Institute, Stockholm, Sweden.
Background:
We aimed to investigate the prodromal phase of multiple sclerosis (MS) by investigating annual sickness absence rates before MS onset.
Methods:
A retrospective cohort study was conducted using Sweden's linked clinical and health administrative data. We identified MS cases via a validated algorithm using International Classification of Diseases (ICD) diagnostic codes for MS ('administrative cohort') or registration in the Swedish MS registry ('clinical cohort'). MS onset was defined as the first MS/demyelinating disease ICD code (administrative cohort) or, for the clinical cohort, MS symptom onset date, if earlier. Cases were matched with up to five controls from the general population with no MS/demyelinating disease history. Yearly sickness absence rates up to 18 years pre-MS onset were compared using negative binomial regression with generalised estimating equations.
Results:
The administrative/clinical cohorts comprised 8618/6361 MS cases and 43 072/31 776 controls. Sickness absence rate ratios were significantly elevated from 6 years before MS onset in the administrative cohort and 2 years before in the clinical cohort. The adjusted rate ratios peaked in the year pre-MS onset, reaching 2.59 (95% CI 2.40 to 2.79) in the administrative cohort and 1.19 (95% CI 1.06 to 1.34) in the clinical cohort. We also observed age-related and sex-related differences primarily in the year before MS onset, with males and older individuals exhibiting higher rate ratios.
Conclusions:
We observed a significant increase in sickness absence spells in individuals on the path to developing MS. Investigating sick leave patterns may provide a unique and broad perspective on the health trajectories of chronic conditions like MS.
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