Better Defining Multiple Sclerosis Categorization: Daniel Ontaneda, MD, PhD

Disease Spotlight | <b>Disease Spotlight: Multiple Sclerosis</b>

The associate professor of Neurology at the Cleveland Clinic Lerner College of Medicine of Case Western Reserve University discussed the potential of a data-driven approach to classifying patients with MS.

“What we did was all cross-sectional. We just kind of identified them based on what they look like right now… You would think that category 1 and category 2 will accrue disability slower or in a different way than category 3 and 4. So what is going to be important for us going forward is taking these patients across the 4 categories and looking to see what happens to their patient-determined disease steps—an EDSS equivalent—over time.”

At the 2021 American Academy of Neurology (AAN) Annual Meeting, April 17-22, Daniel Ontaneda, MD, PhD, associate professor of neurology, Cleveland Clinic Lerner College of Medicine, Case Western Reserve University, and staff member, Mellen Center for Multiple Sclerosis, Cleveland Clinic Neurological Institute, presented data from an assessment that he and colleagues conducted attempting to take a more data-driven approach to patient categorization in multiple sclerosis (MS).

These individuals are usually classified by their standard disease state—relapsing-remitting MS, secondary progressive MS, and primary progressive MS—which are mostly based on how a given patient accrues disability. For Ontaneda and others in MS, these categories do not always provide a complete picture of the patient, and he posits that perhaps a novel, data-driven method of categorization may be useful in clinical care and prognostication.

In this interview with NeurologyLive, he spoke to the potential future work that he and his colleagues are hoping to explore with regard to these 4 new categories that they have developed. Some patients, he noted, have shifted categories unexpectedly, so he stressed identifying if this category evolution might be clinically relevant in predicting patients’ progression. Additionally, he shared how new categorization through data-driven approaches may help with the strive for precision medicine in MS.

For more coverage of AAN 2021, click here.

REFERENCE
Ontaneda D, Qu J, McGinley MP, et al. A Data Driven Approach to Define Disease Course Categories in Multiple Sclerosis. Presented at American Academy of Neurology Annual Meeting; April 17-22. Abstract 1115.