Multiple sclerosis subgroups: Data-driven clusters based on patient-reported outcomes and a large clinical sample
The present study highlights an opportunity to advance precision medicine approaches in MS. Combining PROs with data-driven methodology allows for a cost-effective and personalized characterization of symptom presentations. that can inform clinical practice and future research designs.
Authors
- Daniel Ontaneda (ORCID: https://orcid.org/0000-0002-2838-9148)
- Alyse Finch
- Alessandro S. De Nadai (ORCID: https://orcid.org/0000-0002-7280-576X)
- Deborah Miller (ORCID: https://orcid.org/0000-0002-8026-1854)
- Ryan J. Zamora
- Farren B. S. Briggs (ORCID: https://orcid.org/0000-0003-0903-1359)
- Douglas Gunzler (ORCID: https://orcid.org/0000-0003-3786-8578)
Institutions
- Cleveland Clinic (US)
- Harvard University (US)
- University of Miami (US)
- McLean Hospital (US)
- Cleveland Clinic Lerner College of Medicine (US)
- Case Western Reserve University (US)
Publication Details
- Journal
- Multiple Sclerosis Journal
- Published
- 2024-10-17
- DOI
- https://doi.org/10.1177/13524585241282763
- Citations
- 3
- Primary Topic
- Multiple Sclerosis Research Studies
- Type
- article
- Field-Weighted Citation Impact
- 1.27
Funders
- National Institutes of Health
- National Institute of Mental Health
- National Institute on Drug Abuse
- National Institute of Nursing Research