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Background and objectivesAn unmet need exists for validated quantitative tools to measure multiple sclerosis (MS) disease activity and progression. We developed a custom immunoassay-based MS disease activity (MSDA) Test incorporating 18 protein concentrations into an algorithm to calculate four Disease Pathway scores (Immunomodulation, Neuroinflammation, Myelin Biology, and Neuroaxonal Integrity) and an overall Disease Activity score. The objective was to clinically validate the MSDA Test based on associations between scores and clinical/radiographic assessments.MethodsSerum samples (N=614) from patients with MS at multiple sites were split into Train (n=426; algorithm development) and Test (n=188; evaluation) subsets. Subsets were stratified by demographics, sample counts per site, and gadolinium-positive (Gd+) lesion counts; age and sex were used to demographically adjust protein concentrations. MSDA Test results were evaluated for potential association with Gd+ lesion presence/absence, new and enlarging (N/E) T2 lesion presence, and active versus stable disease status (composite endpoint combining radiographic and clinical evidence of disease activity).ResultsA multi-protein model was developed (trained and cross-validated) using the Train subset. When applied to the Test subset, the model classified the Gd+ lesion presence/absence, N/E T2 lesion presence, and active versus stable disease status assessments with an area under the receiver operating characteristic (AUROC) of 0.781, 0.750, and 0.768, respectively. In each case, the multi-protein model had significantly (bootstrapped, one-sidedpDiscussionThe MSDA Test was clinically validated; the multi-protein model had greater performance compared with the top-performing single-protein model. The MSDA Test may serve as a quantitative and objective tool to enhance care for MS.

Objective Serum neurofilament light (sNfL) is a promising new biomarker in multiple sclerosis (MS). We explored the relationship between sNfL and health outcomes and resource use in MS patients. Methods MS patients with serum samples and health‐outcome measurements collected longitudinally between 2011 and 2016 were analyzed. sNfL values were evaluated across age and gender. Data were analyzed using correlation with log‐transformed sNfL values. Results A total of 304 MS patients with a mean age of 32.9 years, average EDSS of 1.6 (SD = 1.5) and baseline sNfL of 8.8 (range 1.23–78.3) pg/mL were studied. Baseline sNFL values increased with age and were higher in females. Baseline sNfL correlated with baseline Multiple Sclerosis Quality of Life physical composite (mean = 49.4 (9.1), P = 0.035) and baseline EDSS (P = 0.002). Other PRO measures at baseline did not show a significant relationship with baseline sNfL. Average of baseline and follow‐up sNfL correlated with MSQoL physical‐role limitations (mean = 48.9 (10.8), P = 0.043) and social‐functioning (mean = 52.3 (7), P = 0.034) at 24‐month follow‐up. We found a trend for numerically higher sNfL levels in nonpersistent patients compared to those who were persistent to treatment (11.13 vs. 8.53 pg/mL, P = 0.093) measured as average of baseline and 24‐month values. Baseline NfL was associated with number of intravenous steroid infusions (mean = 0.2; SD = 3.0, P = 0.013), whereas the average of baseline and 12 months NfL values related to inpatient stays at 12 months (mean = 0.2; SD = 3.0 P = 0.053). Conclusion Serum NfL is a patient‐centric biomarker that correlated with MS patient health‐outcomes and healthcare utilization measures in a real‐world cohort.