Temporal profile of serum neurofilament light in multiple sclerosis: Implications for patient monitoring

Peter A. Calabresi, Douglas L. Arnold, Dipen Sangurdekar, Carol M. Singh, Arman Altincatal, Carl de Moor, Bob Engle, Jaya Goyal, Aaron Deykin, Suzanne Szak, Bernd C. Kieseier, Richard A. Rudick, Tatiana Plavina

Research output: Contribution to journalArticlepeer-review


Objective: To understand how longitudinal serum neurofilament light chain (sNfL) patterns can inform its use as a prognostic biomarker in multiple sclerosis (MS) and evaluate whether sNfL reflects MS disease activity and disease-modifying therapy usage. Methods: This was a post hoc analysis of longitudinal data and samples from the ADVANCE trial (NCT00906399) of patients with relapsing–remitting MS (RRMS). sNfL was measured every 3 months for 2 years, then every 6 months for 4 years. Regression models explored how sNfL data predicted 4-year values of brain volume, expanded disability status scale score, and T2 lesions. sNfL levels were assessed in those receiving placebo, peginterferon beta-1a, and those with disease activity. Results: Baseline sNfL was a predictor of 4-year brain atrophy and development of new T2 lesions. Clinical (p = 0.02) and magnetic resonance imaging (MRI) (p < 0.01) outcomes improved in those receiving peginterferon beta-1a whose sNfL decreased to <16 pg/mL after 12 months versus those whose sNfL remained ⩾16 pg/mL. Mean sNfL levels decreased in peginterferon beta-1a-treated patients and increased in placebo-treated patients (–9.5% vs. 6.8%; p < 0.01). sNfL was higher and more variable in patients with evidence of active MS. Conclusion: These data support sNfL as a prognostic and disease-monitoring biomarker for RRMS.

Original languageEnglish (US)
Pages (from-to)1497-1505
Number of pages9
JournalMultiple Sclerosis Journal
Issue number10
StatePublished - Sep 2021


  • Biomarker
  • brain atrophy
  • magnetic resonance imaging
  • multiple sclerosis
  • prognosis
  • serum neurofilament light chain

ASJC Scopus subject areas

  • Neurology
  • Clinical Neurology


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