Serum neurofilament light chain in multiple sclerosis: from biological signal to clinically informed decision-making.

Serum neurofilament light chain (sNfL) is an analytically robust blood-based biomarker of recent neuroaxonal injury in multiple sclerosis (MS), supported by validated ultrasensitive immunoassays suitable for routine measurement. These assays now enable reliable measurement in routine care, and evidence links higher levels and rising trajectories to inflammatory activity, treatment response, and-at a population level-future tissue loss and disability risk. Clinical implementation is constrained by overinterpretation of single measurements: sNfL is not MS-specific, is strongly age-dependent, is influenced by systemic and neurological confounders, and reflects injury over weeks to months rather than cumulative neurodegeneration. This review proposes a clinically oriented framework in which sNfL serves as decision support alongside MRI and clinical assessment, not as a stand-alone trigger for therapy changes. We prioritize longitudinal interpretation anchored to an individual baseline or nadir, the use of age-adjusted reference frameworks (percentiles or Z-scores where available), standardization of key pre-analytical and analytical conditions, and structured approaches to discordance between biomarkers, imaging, and symptoms. We discuss the complementary role of serum glial fibrillary acidic protein (sGFAP) as a marker of chronic astroglial pathology and progression-dominant biology, and how combined biomarker patterns may refine interpretation when disability worsens despite limited inflammatory activity. Across the MS continuum-from prodromal states and radiologically isolated syndrome to relapsing and progressive phenotypes-we summarize practical use cases, limitations, and safety-critical "red flags" where marked sNfL surges warrant urgent reassessment. Finally, we highlight consensus-based implementation principles and research priorities, including pragmatic trials to test whether biomarker-informed strategies improve patient-relevant outcomes.