Serum neurofilament light chain (sNfL) can be used as a biomarker for monitoring treatment efficacy and predicting disease course in individuals with multiple sclerosis (MS), according to study findings published in Lancet Neurology.
sNfL is an established marker of acute disease activity, treatment response, and predictor of long-term course of disability in MS. However, sNfL as a biomarker is limited to group-level analyses, and in personalized medicine, its routine use has not been possible, the researchers explained. Furthermore, the protein naturally varies with age and weight, which makes it difficult to establish cut-offs where “normal” values for one patient may be considered as “high” for another patient.
The objective of the current study was to evaluate whether sNfL measures could predict the risk for future disease activity at the group level and in individuals in 2 large and independent cohorts of patients with MS.
A control group of participants in 4 European and US population-based studies was included for derivation of a reference database of sNfL values. To test the reference database, the researchers prospectively collected data from participants in the Swiss MS Cohort (SMSC). Validation of the findings was conducted in data from patients with MS from the Swedish MS registry.
A total of 10,133 serum samples (samples available per control person: median 1 [interquartile range [IQR], 1-2]) from 5390 participants without evidence of CNS disease were available for developing the reference database of sNfL percentiles and Z score values. The age-related increase of sNfL percentiles and Z scores in the control group was nonlinear. The increase was exponential but had an inflection point at about age 50 years and a steeper increase afterward.
The researchers also obtained 7769 serum samples from 1313 patients in the SMSC (median number of samples per person, 6.0; IQR, 3.0-8.0). Clinical and MRI measures of disease worsening or progression were strongly and independently associated with higher sNfL Z scores in the multivariable mixed-effects model with sNfL Z scores as a dependent variable.
Compared with untreated participants, a treatment effectiveness hierarchy was observed for high-efficacy monoclonal antibody therapies vs oral therapies and of oral therapies vs platform compounds. These findings were supported in the validation cohort. The estimated additive effects on sNfL Z score were –0.14 (95% CI, –0.23 to 0.05; P =.0018) for high-efficacy monoclonal antibody treatment vs oral therapy, and –0.23 (–0.36 to 0.10; P <.0001) for oral vs platform therapy.
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