Background: Inter-individual courses of multiple sclerosis (MS) are extremely variable. The objective of this study was to investigate whether κ-free light chain (κ-FLC) index and serum neurofilament light (sNfL) have an additive predictive value for MS disease activity.
Methods: Patients with early MS who had cerebrospinal fluid (CSF) and serum sampling at disease onset were followed for four years. At baseline, age, sex, disease duration, number of T2-hyperintense (T2L), and contrast-enhancing T1 lesions (CEL) on MRI were determined. During follow-up, the occurrence of a second clinical attack and start of disease-modifying treatment (DMT) were registered. κ-FLC was measured by nephelometry, and κ-FLC index calculated as [CSF κ-FLC/serum κ-FLC]/albumin quotient. sNfL was determined by single-molecule array, and age- and body-mass-index adjusted Z scores were calculated.
Findings: A total of 86 patients at a mean age of 33 ± 10 years and with a female predominance of 67% were included; 36 (42%) patients experienced a second clinical attack during follow-up. Cox regression analysis adjusted for age, sex, T2L, CEL, disease and follow-up duration, and DMT use during follow-up revealed that both κ-FLC index as well as sNfL Z score independently predict time to second clinical attack. The chance for freedom of relapse within 12 months was 2% in patients with high levels of κ-FLC index (>100) and high sNfL Z score (>3), 30% in patients with high κ-FLC index (>100) and lower sNfL Z score (≤3), 70% in patients with lower κ-FLC index (≤100) but high sNfL Z score (>3), and 90% in patients with lower levels of κ-FLC index (≤100) and sNfL Z score (≤3).
Interpretation: κ-FLC index and sNfL Z score have an additive predictive value for early MS disease activity that is independent of known predictors.
Funding: This study was funded by a grant of the charitable foundation of the Austrian Multiple Sclerosis Society.
Keywords: Cerebrospinal fluid; Disease activity; Kappa free light chain; Multiple sclerosis; Neurofilament light; Prediction.
Copyright © 2023 The Author(s). Published by Elsevier B.V. All rights reserved.