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Cerebrospinal fluid neurofilament light chains predicts early disease-activity in Multiple Sclerosis.
Multiple Sclerosis and related Disorders 2023 November 8
BACKGROUND: Among biomarkers of axonal damage, neurofilament light chains (NFL) seem to play a major role, representing a promising and interesting tool in Multiple Sclerosis (MS). Our aim was to explore the predictive role of cerebrospinal fluid (CSF) NFL in patients with a recent diagnosis of MS, naïve to any MS therapy.
METHODS: We retrospectively collected data of patients diagnosed with MS, referred to the Neurology Clinic of the University-Hospital G. Rodolico of Catania between January 1st 2005 and December 31st 2015. All patients underwent CSF collection at the time of MS diagnosis and were followed-up for at least three years afterwards. NFL levels were measured in CSF samples with Simoa NFLight advantage kit at the CRESM (University Hospital San Luigi Gonzaga, Orbassano, Torino). NFL levels were expressed as LogNFL. Symbol Digit Modalities test (SDMT) was performed at baseline, at 1-year and at 3-year follow-up. Multivariate logistic regression analysis was performed to investigate LogNFL as a potential risk factor of different clinical outcomes.
RESULTS: 244 MS patients (230 relapsing-remitting, RRMS; 94.3 %), with a mean age at diagnosis of 37.0 ± 11.1 years, were recruited. LogNFL did not correlate neither with EDSS score at diagnosis and at subsequent follow-up up to 12 years, nor with SDMT performed at diagnosis, at 1 year and at 3 years. LogNFL were an independent factor for the occurrence of at least one relapse during the first two years after MS diagnosis (OR = 2.75; 95 % CI 1.19-6.31; p = 0.02) and for the occurrence of gadolinium-enhanced (Gd+) lesions during the first 2 years from diagnosis at brain and spine MRI scans (OR = 3.45, 95 % CI 1.81-6.57; p < 0.001).
CONCLUSION: The detection of CSF NFL at the time of MS diagnosis can be a useful support to predict the two-year risk of clinical and radiological relapses, thus affecting therapeutic choices in the very early phases of the disease.
METHODS: We retrospectively collected data of patients diagnosed with MS, referred to the Neurology Clinic of the University-Hospital G. Rodolico of Catania between January 1st 2005 and December 31st 2015. All patients underwent CSF collection at the time of MS diagnosis and were followed-up for at least three years afterwards. NFL levels were measured in CSF samples with Simoa NFLight advantage kit at the CRESM (University Hospital San Luigi Gonzaga, Orbassano, Torino). NFL levels were expressed as LogNFL. Symbol Digit Modalities test (SDMT) was performed at baseline, at 1-year and at 3-year follow-up. Multivariate logistic regression analysis was performed to investigate LogNFL as a potential risk factor of different clinical outcomes.
RESULTS: 244 MS patients (230 relapsing-remitting, RRMS; 94.3 %), with a mean age at diagnosis of 37.0 ± 11.1 years, were recruited. LogNFL did not correlate neither with EDSS score at diagnosis and at subsequent follow-up up to 12 years, nor with SDMT performed at diagnosis, at 1 year and at 3 years. LogNFL were an independent factor for the occurrence of at least one relapse during the first two years after MS diagnosis (OR = 2.75; 95 % CI 1.19-6.31; p = 0.02) and for the occurrence of gadolinium-enhanced (Gd+) lesions during the first 2 years from diagnosis at brain and spine MRI scans (OR = 3.45, 95 % CI 1.81-6.57; p < 0.001).
CONCLUSION: The detection of CSF NFL at the time of MS diagnosis can be a useful support to predict the two-year risk of clinical and radiological relapses, thus affecting therapeutic choices in the very early phases of the disease.
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