The professor of medicine at the University of Manitoba provided insight on a recently published paper which challenges the way multiple sclerosis is categorized and treated. [WATCH TIME: 5 minutes]
WATCH TIME: 5 minutes
"We felt it was time to reevaluate where we were with that issue, particularly given the sort of evolution of new treatments and the hope that in the future we would move into others that address repair and remyelination."
As the knowledge and advancement of agents to treat multiple sclerosis (MS) has improved, halting and reversing disease progression remain major unmet needs. Recently, the International Advisory Committee on Clinical Trials in Multiple Sclerosis published a paper addressing those needs, concluding that its essential to move from clinically based to biologically based definitions of the disease. Additionally, the paper called for extended efforts to develop and validate tools that can reliably assess and track relevant disease biology in clinical settings.
The paper focused on clarifying the 1996 and 2013 clinical course descriptors, commonly referred to as the Lublin-Reingold classification, with the goal of determining an approach to developing a new framework for describing the disease. Overall, the thought is that disease evolution to a progressive course reflects a partial shift from predominantly localized acute injury to widespread inflammation and neurodegeneration, coupled with the failure of compensatory mechanisms such as neuroplasticity and remyelination.
Ruth Ann Marrie, MD, PhD, FRCPC, an author on the paper, doesn’t believe the ideas presented are a matter of "right or wrong," but rather that the previous ways to describe the disease don’t fully showcase the underlying biology of these individuals. In an interview with NeurologyLive®, Marrie, a professor of medicine at the University of Manitoba, provided perspective on the need for this paper in a rapidly-growing therapeutic setting. Additionally, she detailed the body of evidence for this new view, and why traditional categorization of MS comes with faults when trying to optimize treatment selection.