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Updated: Jun 11, 2025

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A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data
Published on: December 9, 2015
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Prognostic factors for worsening and improvement in multiple sclerosis using a multistate model
Alex Ocampo1, Farhad Hatami2, Jelena Čuklina1
1Novartis Pharma AG, Basel, Switzerland.
Summary
Early intervention in multiple sclerosis (MS) is key. Higher brain volume aids improvement, while T2 lesions and older age predict worsening, highlighting the need to protect brain health.
Area of Science:
- Neurology
- Neuroimmunology
- Clinical Research
Background:
- Early treatment initiation is crucial for improving the long-term disease trajectory in multiple sclerosis (MS).
- Quantitative evidence on factors influencing disability worsening and improvement is needed for timely treatment decisions.
Purpose of the Study:
- To develop a multistate model quantifying demographic, clinical, and imaging factors' influence on disability worsening and improvement in MS.
- To analyze these factors across the full disability spectrum measured by the Expanded Disability Status Scale (EDSS).
Main Methods:
- Utilized clinical trial data from the Novartis-Oxford MS database (~8000 patients, ~130,000 EDSS assessments).
- Employed a multistate model to simultaneously assess predictors of disability worsening and improvement.
- Included all MS phenotypes in the analysis.
Main Results:
- Increased brain volume positively correlated with disability improvement (HR 1.09-1.19).
- Higher T2 lesion volume negatively impacted improvement up to EDSS 6 (HR 0.80-0.89).
- Older age, longer time since symptom onset, and recent relapses predicted disability worsening.
Conclusions:
- Brain damage is a primary factor limiting improvement potential throughout the course of MS.
- Preserving brain integrity early in MS is critical for clinical decision-making and patient outcomes.
Keywords:
Multistate modelbrain reservedisability improvementdisability worseningrecoveryrisk factorsMore Related Videos
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