Serum neurofilament light chain levels predict long-term disability progression in patients with progressive multiple sclerosis

J Neurol Neurosurg Psychiatry. 2022 Apr 29:jnnp-2022-329020. doi: 10.1136/jnnp-2022-329020. Online ahead of print.

Abstract

ObjectiveThere is a lack of sensitive and specific biomarkers for use in progressive multiple sclerosis (MS). The study aimed to assess the potential of serum neurofilament light chain (sNfL) levels as biomarker of disability progression in patients with progressive MS.

Methods: We performed a prospective observational cohort study in 51 patients with progressive MS who participated in a 2-year phase II single-centre, randomised, double-blind, placebo-controlled trial of interferon-beta. Mean (SD) follow-up duration was 13.9 (6.2) years. Levels of sNfL were measured using a single molecule array immunoassay at baseline, 1, 2 and 6 years. Univariable and multivariable analyses were carried out to evaluate associations between sNfL levels and disability progression at short term (2 years), medium term (6 years) and long term (at the time of the last follow-up).

Results: A sNfL cut-off value of 10.2 pg/mL at baseline discriminated between long-term progressors and non-progressors with a 75% sensitivity and 67% specificity (adjusted OR 7.8; 95% CI 1.8 to 46.4; p=0.01). Similar performance to discriminate between long-term progressors and non-progressors was observed using age/body mass index-adjusted sNfL Z-scores derived from a normative database of healthy controls. A cut-off increase of 5.1 pg/mL in sNfL levels between baseline and 6 years also discriminated between long-term progressors and non-progressors with a 71% sensitivity and 86% specificity (adjusted OR 49.4; 95% CI 4.4 to 2×103; p=0.008).

Conclusions: sNfL can be considered a prognostic biomarker of future long-term disability progression in patients with progressive MS. These data expand the little knowledge existing on the role of sNfL as long-term prognostic biomarker in patients with progressive MS.

Keywords: MULTIPLE SCLEROSIS.