NfL predicts relapse-free progression in a longitudinal multiple sclerosis cohort study.


Journal

EBioMedicine
ISSN: 2352-3964
Titre abrégé: EBioMedicine
Pays: Netherlands
ID NLM: 101647039

Informations de publication

Date de publication:
Oct 2021
Historique:
received: 06 02 2021
revised: 02 09 2021
accepted: 06 09 2021
pubmed: 28 9 2021
medline: 8 2 2022
entrez: 27 9 2021
Statut: ppublish

Résumé

Easily accessible biomarkers enabling the identification of those patients with multiple sclerosis (MS) who will accumulate irreversible disability in the long term are essential to guide early therapeutic decisions. We here examine the utility of serum neurofilament light chain (sNfL) for forecasting relapse-free disability progression and conversion to secondary progressive MS (SPMS) in the prospective Neurofilamentandlongtermoutcome inMS (NaloMS) cohort. The predictive ability of sNfL at Baseline and sNfL follow-up (FU)/ Baseline (BL) ratio with regard to disability progression was assessed within a development cohort (NaloMS, n=196 patients with relapsing-remitting MS (RRMS) or clinically isolated syndrome) and validated with an external independent cohort (Düsseldorf, Essen, n=204). Both relapse-free EDSS-progression (RFP: inflammatory-independent EDSS-increase 12 months prior to FU) and SPMS-transition (minimum EDSS-score of 3.0) were investigated. During the study period, 17% (n=34) of NaloMS patients suffered from RFP and 14% (n=27) converted to SPMS at FU (validation cohort RFP n=42, SPMS-conversion n=24). sNfL at BL was increased in patients with RFP (10.8 pg/ml (interquartile range (IQR) 7.7-15.0) vs. 7.2 pg/ml (4.5-12.5), p<0.017). In a multivariable logistic regression model, increased sNfL levels at BL (Odds Ratio (OR) 1.02, 95% confidence interval (CI) 1.01-1.04, p=0.012) remained an independent risk factor for RFP and predicted individual RFP risk with an accuracy of 82% (NaloMS) and 83% (validation cohort) as revealed by support vector machine. In addition, the sNfL FU/BL ratio was increased in SPMS-converters (1.16 (0.89-1.70) vs. 0.96 (0.75-1.23), p=0.011). This was confirmed by a multivariable logistic regression model, as sNfL FU/BL ratio remained in the model (OR 1.476, 95%CI 1.078-2,019, p=0.015) and individual sNfL FU/BL ratios showed a predictive accuracy of 72% in NaloMS (63% in the validation cohort) as revealed by machine learning. sNfL levels at baseline predict relapse-free disability progression in a prospective longitudinal cohort study 6 years later. While prediction was confirmed in an independent cohort, sNfL further discriminates patients with SPMS at follow-up and supports early identification of patients at risk for later SPMS conversion. This work was supported by the German Research Council (CRC-TR-128), Else Kröner Fresenius Foundation and Hertie-Stiftung.

Sections du résumé

BACKGROUND BACKGROUND
Easily accessible biomarkers enabling the identification of those patients with multiple sclerosis (MS) who will accumulate irreversible disability in the long term are essential to guide early therapeutic decisions. We here examine the utility of serum neurofilament light chain (sNfL) for forecasting relapse-free disability progression and conversion to secondary progressive MS (SPMS) in the prospective Neurofilamentandlongtermoutcome inMS (NaloMS) cohort.
METHODS METHODS
The predictive ability of sNfL at Baseline and sNfL follow-up (FU)/ Baseline (BL) ratio with regard to disability progression was assessed within a development cohort (NaloMS, n=196 patients with relapsing-remitting MS (RRMS) or clinically isolated syndrome) and validated with an external independent cohort (Düsseldorf, Essen, n=204). Both relapse-free EDSS-progression (RFP: inflammatory-independent EDSS-increase 12 months prior to FU) and SPMS-transition (minimum EDSS-score of 3.0) were investigated.
FINDINGS RESULTS
During the study period, 17% (n=34) of NaloMS patients suffered from RFP and 14% (n=27) converted to SPMS at FU (validation cohort RFP n=42, SPMS-conversion n=24). sNfL at BL was increased in patients with RFP (10.8 pg/ml (interquartile range (IQR) 7.7-15.0) vs. 7.2 pg/ml (4.5-12.5), p<0.017). In a multivariable logistic regression model, increased sNfL levels at BL (Odds Ratio (OR) 1.02, 95% confidence interval (CI) 1.01-1.04, p=0.012) remained an independent risk factor for RFP and predicted individual RFP risk with an accuracy of 82% (NaloMS) and 83% (validation cohort) as revealed by support vector machine. In addition, the sNfL FU/BL ratio was increased in SPMS-converters (1.16 (0.89-1.70) vs. 0.96 (0.75-1.23), p=0.011). This was confirmed by a multivariable logistic regression model, as sNfL FU/BL ratio remained in the model (OR 1.476, 95%CI 1.078-2,019, p=0.015) and individual sNfL FU/BL ratios showed a predictive accuracy of 72% in NaloMS (63% in the validation cohort) as revealed by machine learning.
INTERPRETATION CONCLUSIONS
sNfL levels at baseline predict relapse-free disability progression in a prospective longitudinal cohort study 6 years later. While prediction was confirmed in an independent cohort, sNfL further discriminates patients with SPMS at follow-up and supports early identification of patients at risk for later SPMS conversion.
FUNDING BACKGROUND
This work was supported by the German Research Council (CRC-TR-128), Else Kröner Fresenius Foundation and Hertie-Stiftung.

Identifiants

pubmed: 34571362
pii: S2352-3964(21)00383-2
doi: 10.1016/j.ebiom.2021.103590
pmc: PMC8479646
pii:
doi:

Substances chimiques

Biomarkers 0
Neurofilament Proteins 0
neurofilament protein L 0

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

103590

Informations de copyright

Copyright © 2021 The Author(s). Published by Elsevier B.V. All rights reserved.

Déclaration de conflit d'intérêts

Declaration of Competing Interest Timo Uphaus has received honoraria from Merck Serono. Tobias Ruck has received travel grants and financial research support from Genzyme and Novartis and received honoraria for lecturing from Roche, Merck, Genzyme, Biogen, and Teva. Sven G. Meuth has received honoraria for lecturing and travel expenses for attending meetings from Almirall, Amicus Therapeutics Germany, Bayer Health Care, Biogen, Celgene, Diamed, Genzyme, MedDay Pharmaceuticals, Merck Serono, Novartis, Novo Nordisk, ONO Pharma, Roche, Sanofi-Aventis, Chugai Pharma, QuintilesIMS, and Teva. His research is funded by the German Ministry for Education and Research (BMBF), Deutsche Forschungsgemeinschaft (DFG), Else Kröner Fresenius Foundation, German Academic Exchange Service, Hertie Foundation, Interdisciplinary Center for Clinical Studies (IZKF) Muenster, German Foundation Neurology and by Almirall, Amicus Therapeutics Germany, Biogen, Diamed, Fresenius Medical Care, Genzyme, Merck Serono, Novartis, ONO Pharma, Roche, and Teva. Frauke Zipp has recently received research grants and/or consultation funds from DFG, BMBF, PMSA, Genzyme, Janssen, Merck Serono, Roche, Novartis, Celgene, and Sanofi-Aventis. Stefan Bittner has received honoraria and compensation for travel from Biogen Idec, Merck Serono, Novartis, Sanofi-Genzyme and Roche. The other authors declare no competing interests.

Auteurs

Timo Uphaus (T)

Department of Neurology, Focus Program Translational Neuroscience (FTN) and Immunotherapy (FZI), Rhine Main Neuroscience Network (rmn(2)), University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany.

Falk Steffen (F)

Department of Neurology, Focus Program Translational Neuroscience (FTN) and Immunotherapy (FZI), Rhine Main Neuroscience Network (rmn(2)), University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany.

Muthuraman Muthuraman (M)

Biomedical Statistics and Multimodal Signal Processing Unit, Focus Program Translational Neuroscience (FTN) Neuroimaging Center, Department of Neurology, Rhine Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany.

Nina Ripfel (N)

Department of Neurology, Focus Program Translational Neuroscience (FTN) and Immunotherapy (FZI), Rhine Main Neuroscience Network (rmn(2)), University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany.

Vinzenz Fleischer (V)

Department of Neurology, Focus Program Translational Neuroscience (FTN) and Immunotherapy (FZI), Rhine Main Neuroscience Network (rmn(2)), University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany.

Sergiu Groppa (S)

Department of Neurology, Focus Program Translational Neuroscience (FTN) and Immunotherapy (FZI), Rhine Main Neuroscience Network (rmn(2)), University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany.

Tobias Ruck (T)

Department of Neurology, Heinrich-Heine-University, Düsseldorf, Germany.

Sven G Meuth (SG)

Department of Neurology, Heinrich-Heine-University, Düsseldorf, Germany.

Refik Pul (R)

Department of Neurology and Center for Translational and Behavioral Neuroscience (C-TBNS), University Duisburg-Essen, Essen, Germany.

Christoph Kleinschnitz (C)

Department of Neurology and Center for Translational and Behavioral Neuroscience (C-TBNS), University Duisburg-Essen, Essen, Germany.

Erik Ellwardt (E)

Department of Neurology, Focus Program Translational Neuroscience (FTN) and Immunotherapy (FZI), Rhine Main Neuroscience Network (rmn(2)), University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany.

Julia Loos (J)

Department of Neurology, Focus Program Translational Neuroscience (FTN) and Immunotherapy (FZI), Rhine Main Neuroscience Network (rmn(2)), University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany.

Sinah Engel (S)

Department of Neurology, Focus Program Translational Neuroscience (FTN) and Immunotherapy (FZI), Rhine Main Neuroscience Network (rmn(2)), University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany.

Frauke Zipp (F)

Department of Neurology, Focus Program Translational Neuroscience (FTN) and Immunotherapy (FZI), Rhine Main Neuroscience Network (rmn(2)), University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany.

Stefan Bittner (S)

Department of Neurology, Focus Program Translational Neuroscience (FTN) and Immunotherapy (FZI), Rhine Main Neuroscience Network (rmn(2)), University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany. Electronic address: bittner@uni-mainz.de.

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