Elsevier

EBioMedicine

Volume 56, June 2020, 102807
EBioMedicine

Research paper
Clinical implications of serum neurofilament in newly diagnosed MS patients: A longitudinal multicentre cohort study

https://doi.org/10.1016/j.ebiom.2020.102807Get rights and content
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Abstract

Background

We aim to evaluate serum neurofilament light chain (sNfL), indicating neuroaxonal damage, as a biomarker at diagnosis in a large cohort of early multiple sclerosis (MS) patients.

Methods

In a multicentre prospective longitudinal observational cohort, patients with newly diagnosed relapsing-remitting MS (RRMS) or clinically isolated syndrome (CIS) were recruited between August 2010 and November 2015 in 22 centers. Clinical parameters, MRI, and sNfL levels (measured by single molecule array) were assessed at baseline and up to four-year follow-up.

Findings

Of 814 patients, 54.7% (445) were diagnosed with RRMS and 45.3% (369) with CIS when applying 2010 McDonald criteria (RRMS[2010] and CIS[2010]). After reclassification of CIS[2010] patients with existing CSF analysis, according to 2017 criteria, sNfL levels were lower in CIS[2017] than RRMS[2017] patients (9.1 pg/ml, IQR 6.2–13.7 pg/ml, n = 45; 10.8 pg/ml, IQR 7.4–20.1 pg/ml, n = 213; p = 0.036). sNfL levels correlated with number of T2 and Gd+ lesions at baseline and future clinical relapses. Patients receiving disease-modifying therapy (DMT) during the first four years had higher baseline sNfL levels than DMT-naïve patients (11.8 pg/ml, IQR 7.5-20.7 pg/ml, n = 726; 9.7 pg/ml, IQR 6.4–15.3 pg/ml, n = 88). Therapy escalation decisions within this period were reflected by longitudinal changes in sNfL levels.

Interpretation

Assessment of sNfL increases diagnostic accuracy, is associated with disease course prognosis and may, particularly when measured longitudinally, facilitate therapeutic decisions.

Funding

Supported the German Federal Ministry for Education and Research, the German Research Council, and Hertie-Stiftung.

Keywords

Neurofilament light chain
sNfL
Multiple sclerosis
Prediction
Biomarker

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1

These authors contributed equally.