| Title: |
Clinical validation of a multi-protein, serum-based assay for disease activity assessments in multiple sclerosis |
| Authors: |
Chitnis, Tanuja; Foley, John; Ionete, Carolina; El Ayoubi, Nabil K; Saxena, Shrishti; Gaitan-Walsh, Patricia; Lokhande, Hrishikesh; Paul, Anu; Saleh, Fermisk; Weiner, Howard; Qureshi, Ferhan; Becich, Michael J; da Costa, Fatima Rubio; Gehman, Victor M; Zhang, Fujun; Keshavan, Anisha; Jalaleddini, Kian; Ghoreyshi, Ati; Khoury, Samia J |
| Contributors: |
Neurology |
| Source: |
Clinical immunology (Orlando, Fla.) ; 253 ; 109688 ; United States |
| Publication Year: |
2025 |
| Collection: |
University of Massachusetts, Medical School: eScholarship@UMMS |
| Subject Terms: |
Clinical validation; Gadolinium-positive lesion; MS disease activity; Multiple sclerosis |
| Description: |
An 18-protein multiple sclerosis (MS) disease activity (DA) test was validated based on associations between algorithm scores and clinical/radiographic assessments (N = 614 serum samples; Train [n = 426; algorithm development] and Test [n = 188; evaluation] subsets). The multi-protein model was trained based on presence/absence of gadolinium-positive (Gd+) lesions and was also strongly associated with new/enlarging T2 lesions, and active versus stable disease (composite of radiographic and clinical evidence of DA) with improved performance (p < 0.05) compared to the neurofilament light single protein model. The odds of having ≥1 Gd+ lesions with a moderate/high DA score were 4.49 times that of a low DA score, and the odds of having ≥2 Gd+ lesions with a high DA score were 20.99 times that of a low/moderate DA score. The MSDA Test was clinically validated with improved performance compared to the top-performing single-protein model and can serve as a quantitative tool to enhance the care of MS patients. ; No embargo |
| Document Type: |
article in journal/newspaper |
| File Description: |
application/pdf |
| Language: |
English |
| Relation: |
Clinical Immunology; https://doi.org/10.1016/j.clim.2023.109688; https://hdl.handle.net/20.500.14038/54276 |
| DOI: |
10.1016/j.clim.2023.109688 |
| Availability: |
https://doi.org/10.1016/j.clim.2023.109688; https://hdl.handle.net/20.500.14038/54276 |
| Rights: |
© 2023 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by- nc-nd/4.0/). ; Attribution-NonCommercial-NoDerivatives 4.0 International ; http://creativecommons.org/licenses/by-nc-nd/4.0/ |
| Accession Number: |
edsbas.74E139C4 |
| Database: |
BASE |