Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2024 Mar 29:17:17562864241239101.
doi: 10.1177/17562864241239101. eCollection 2024.

Serum neurofilament light chain correlations in patients with a first clinical demyelinating event in the REFLEX study: a post hoc analysis

Affiliations

Serum neurofilament light chain correlations in patients with a first clinical demyelinating event in the REFLEX study: a post hoc analysis

Jens Kuhle et al. Ther Adv Neurol Disord. .

Abstract

Background: In REFLEX, subcutaneous interferon beta-1a (sc IFN β-1a) delayed the onset of multiple sclerosis (MS) in patients with a first clinical demyelinating event (FCDE).

Objectives: This post hoc analysis aimed to determine whether baseline serum neurofilament light (sNfL) chain can predict conversion to MS and whether correlations exist between baseline sNfL and magnetic resonance imaging (MRI) metrics.

Methods: sNfL was measured for 494 patients who received sc IFN β-1a 44 μg once weekly (qw; n = 168), three times weekly (tiw; n = 161), or placebo (n = 165) over 24 months. Median baseline sNfL (26.1 pg/mL) was used to define high/low sNfL subgroups. Hazard ratios (HRs) and 95% confidence intervals (CIs) were calculated using Cox's proportional hazard model to determine factors influencing the risk of conversion to MS. Kaplan-Meier estimates calculated median time-to-conversion to MS (McDonald 2005 criteria) or clinically definite MS (CDMS; Poser criteria). Correlations between sNfL and MRI findings were assessed using Spearman's rank correlation coefficient (r).

Results: Multivariable models indicated that high baseline sNfL was associated with the likelihood of converting to MS and inversely to time-to-conversion (HR = 1.3, 95% CI: 1.03-1.64; p = 0.024). Significant additional factors affecting conversion to McDonald MS were on-study treatment (sc IFN β-1a/placebo; qw: HR = 0.59, 95% CI: 0.46-0.76; tiw: HR = 0.45, 95% CI: 0.34-0.59), classification of FCDE (monofocal/multifocal; HR = 0.69, 95% CI: 0.55-0.85), and most baseline imaging findings (T2 and T1 gadolinium-enhancing [Gd+] lesions; HR = 1.02, 95% CI: 1.01-1.03 and HR = 1.07, 95% CI: 1.03-1.11); all p ⩽ 0.001. Conversion to CDMS showed similar results. At month 24, sNfL was strongly correlated with a mean number of combined unique active (r = 0.71), new T2 (r = 0.72), and new T1 Gd+ (r = 0.60) lesions; weak correlations were observed between sNfL and clinical outcomes for all treatment groups.

Conclusion: Higher baseline sNfL was associated with an increased risk of MS conversion, a risk that was mitigated by treatment with sc IFN β-1a tiw.

Trial registration: ClinicalTrials.gov identifier: NCT00404352. Date registered: 28 November 2006.

Keywords: interferon beta-1a; multiple sclerosis; serum neurofilament light chain.

PubMed Disclaimer

Figures

Figure 1.
Figure 1.
Kaplan–Meier cumulative incidence curves for time to conversion to MS (McDonald 2005 criteria) or clinically definite MS (Poser criteria) by treatment group, for each baseline sNfL subgroup. (a) Time to conversion to MS (McDonald 2005 criteria). (i) Low baseline sNfL (⩽ median baseline value). (ii) High baseline sNfL (> median baseline value). (b) Time to conversion to clinically definite MS (Poser criteria). (i) Low baseline sNfL (⩽ median baseline value). (ii) High baseline sNfL (> median baseline value). CI, confidence interval; IFN, interferon; MS, multiple sclerosis; qw, once weekly; sc, subcutaneous; sc IFN β-1a, subcutaneous interferon beta-1a; sNfL, serum neurofilament light chain; tiw, three times weekly.

References

    1. Oreja-Guevara C. Overview of magnetic resonance imaging for management of relapsing-remitting multiple sclerosis in everyday practice. Eur J Neurol 2015; 22(Suppl. 2): 22–27. - PubMed
    1. Orme M, Kerrigan J, Tyas D, et al.. The effect of disease, functional status, and relapses on the utility of people with multiple sclerosis in the UK. Value Health 2007; 10: 54–60. - PubMed
    1. Jongen PJ. Health-related quality of life in patients with multiple sclerosis: impact of disease-modifying drugs. CNS Drugs 2017; 31: 585–602. - PMC - PubMed
    1. Wattjes MP, Rovira À, Miller D, et al.. Evidence-based guidelines: MAGNIMS consensus guidelines on the use of MRI in multiple sclerosis – establishing disease prognosis and monitoring patients. Nat Rev Neurol 2015; 11: 597–606. - PubMed
    1. Plavina T, Singh CM, Sangurdekar D, et al.. Association of serum neurofilament light levels with long-term brain atrophy in patients with a first multiple sclerosis episode. JAMA Netw Open 2020; 3: e2016278. - PMC - PubMed

Associated data

LinkOut - more resources