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A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data
Published on: December 9, 2015
The relevance of fatigue to relapse rate in multiple sclerosis: Applying patient preference data to the OPTIMUM trial
Robert J Fox1, Tommi Tervonen2, Andrea Phillips-Beyer3
1Mellen Center for Multiple Sclerosis, Neurological Institute, Cleveland Clinic, Cleveland, OH, USA.
Background:
In the OPTIMUM trial in patients with relapsing MS, treatment differences in annualized relapse rate (ARR, 0.088) and change in fatigue at week 108 (3.57 points, measured using the Fatigue Symptoms and Impacts Questionnaire-Relapsing Multiple Sclerosis, symptom domain (FSIQ-RMS-S)) favored ponesimod over teriflunomide. However, the importance of the fatigue outcome to patients was unclear.
Objective:
To assess the importance of the OPTIMUM FSIQ-RMS-S results using data from an MS discrete choice experiment (DCE).
Methods:
The DCE included components to correlate levels of physical and cognitive fatigue with FSIQ-RMS-S scores. Changes in relapses/year and time to MS progression equivalent to the treatment difference in fatigue in OPTIMUM were determined for similar fatigue levels as mean baseline fatigue in OPTIMUM.
Results:
DCE participants would accept 0.06 more relapses/year or a 0.15-0.17 year decrease in time to MS progression for a 3.57-point difference in physical fatigue on the FSIQ-RMS-S. To improve cognitive fatigue by 3.57-points on the FSIQ-RMS-S, DCE participants would accept 0.09-0.10 more relapses/year or a 0.24-0.28 year decrease in time to MS progression.
Conclusion:
MS patients would accept 0.06 more relapses/year to change their fatigue by a similar magnitude as the between-treatment difference observed in the OPTIMUM trial.
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