Objective: To develop and evaluate multimodal survival models in MSA integrating clinical features with plasma NfL.

Background: Progression in Multiple System Atrophy (MSA) is highly heterogeneous. Robust prognostic markers are needed to support clinical care planning and enable patient selection and stratification in therapeutic trials. Neurofilament Light Chain (NfL) is a promising biomarker that may provide prognostic information in MSA.

Method: Patients with clinically possible, probable, or neuropathologically confirmed MSA were enrolled in the longitudinal natural history study. Survival analyses were performed using two reference timepoints: disease onset and baseline visit. Longitudinal clinical assessments were paired with plasma NfL measurements in a subset of participants using a six-month collection window. Plasma NfL concentrations were quantified using the Single Molecule Array assay. Survival was examined using Kaplan–Meier analysis and Cox proportional hazards models. Multivariable models were compared using Harrell’s concordance index (C-index) and the Akaike information criterion (AIC).

Results: A total of 318 patients with MSA from a prospective longitudinal cohort were included. Older age at onset (HR 1.04, 95% CI 1.03–1.06, p<0.001), early falls (HR 1.82, 95% CI 1.06–3.15, p=0.03), early walking-aid use (HR 1.90, 95% CI 1.14–3.15, p=0.01), and early dysautonomia (HR 2.08, 95% CI 1.20–3.62, p=0.009) were associated with shorter survival from disease onset. Higher plasma NfL within three years of onset (HR 1.03, 95% CI 1.00–1.06, p=0.05) was also associated with reduced survival. From baseline, higher UMSARS scores (HR 1.02, 95% CI 1.01–1.04, p=0.003) and higher plasma NfL levels (HR 1.02, 95% CI 1.01–1.03, p<0.001) predicted poorer survival. Multimodal models integrating clinical predictors with plasma NfL improved discriminatory performance.

Conclusion: Clinical features and plasma NfL provide complementary prognostic information in MSA. Integrating clinical and biomarker data improves survival prediction and may enable biomarker-informed risk stratification and trial enrichment, supporting both prognostic assessment in routine care and more efficient design of future therapeutic trials.

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MDS Abstracts - https://www.mdsabstracts.org/abstract/biomarker-informed-survival-modelling-using-plasma-neurofilament-light-and-clinical-predictors-in-a-prospective-multiple-system-atrophy-cohort/