4.5 Review

Neurofilament light chain as a biological marker for multiple sclerosis: a meta-analysis study

Journal

NEUROPSYCHIATRIC DISEASE AND TREATMENT
Volume 14, Issue -, Pages 2241-2254

Publisher

DOVE MEDICAL PRESS LTD
DOI: 10.2147/NDT.S173280

Keywords

multiple sclerosis; neurofilament light chain; meta-analysis

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Purpose: There is a need for biomarkers in multiple sclerosis (MS) to make an early diagnosis and monitor its progression. This study was designed to evaluate the value of neurofilament light (NFL) chain levels as cerebrospinal fluid (CSF) or blood biomarker in patients with MS by using a quantitative meta-analysis. Methods: The PubMed, Embase, and Web of Science databases were systematically searched for relevant studies. Articles in English that evaluated the utility of NFL in CSF and blood in the diagnosis of MS were included. Data were extracted by two independent researchers. Mean (+/- SD) NFL concentration for MS patients and control subjects were extracted. Review Manager version 5.3 software with a continuous-variable random-effects model was used to summarize the diagnostic indexes from eligible studies. The Newcastle-Ottawa Scale was used for assessing the quality and risk of bias of included studies. In addition, subgroup analysis and meta-regression were performed to assess potential heterogeneity sources. Results: The meta-analysis included 13 articles containing results from 15 studies. A total of 10 studies measured NFL levels in CSF and five studies measured NFL levels in blood. Data were available on 795 participants in CSF and 1,856 participants in blood. Moreover, CSF NFL in MS patients was higher than that in healthy control groups (pooled standard mean difference [Std.MD]=0.88, 95% CI [0.50, 1.26], P<0.00001) and serum NFL in MS patients was higher than that in control subjects (pooled Std.MD=0.47, 95% CI [0.24, 0.71], P<0.0001). Conclusion: NFL chain has significantly increased in MS patients, which substantially strengthens the clinical evidence of the NFL in MS. The NFL may be used as a prognostic biomarker to monitor disease progression, disease activity, and treatment efficacy in the future.

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