Measuring disability progression in multiple sclerosis to improve monitoring and evidence-based treatment

This thesis investigates how disability progression in multiple sclerosis (MS) can be better measured to improve disease monitoring and treatment decisions. It demonstrates that iPad-based digital tools can reliably track cognitive and physical changes over time, offering a more sensitive way to detect disease progression. This doctoral work also evaluates treatment strategies for older people with MS, showing that while high-efficacy therapies reduce relapses, their impact on long-term disability remains unclear. These findings support digital tools as a reliable method to track disability in MS, and generate new real-world evidence to guide tailored treatment approaches for older people with MS.