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Serum Biomarker gMS-Classifier2: Predicting Conversion to Clinically Definite Multiple Sclerosis

BACKGROUND: Anti-glycan antibodies can be found in autoimmune diseases. IgM against glycan P63 was identified in clinically isolated syndromes (CIS) and included in gMS-Classifier2, an algorithm designed with the aim of identifying patients at risk of a second demyelinating attack. OBJECTIVE: To det...

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Autores principales: Arrambide, Georgina, Espejo, Carmen, Yarden, Jennifer, Fire, Ella, Spector, Larissa, Dotan, Nir, Dukler, Avinoam, Rovira, Alex, Montalban, Xavier, Tintore, Mar
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3610690/
https://www.ncbi.nlm.nih.gov/pubmed/23555846
http://dx.doi.org/10.1371/journal.pone.0059953
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author Arrambide, Georgina
Espejo, Carmen
Yarden, Jennifer
Fire, Ella
Spector, Larissa
Dotan, Nir
Dukler, Avinoam
Rovira, Alex
Montalban, Xavier
Tintore, Mar
author_facet Arrambide, Georgina
Espejo, Carmen
Yarden, Jennifer
Fire, Ella
Spector, Larissa
Dotan, Nir
Dukler, Avinoam
Rovira, Alex
Montalban, Xavier
Tintore, Mar
author_sort Arrambide, Georgina
collection PubMed
description BACKGROUND: Anti-glycan antibodies can be found in autoimmune diseases. IgM against glycan P63 was identified in clinically isolated syndromes (CIS) and included in gMS-Classifier2, an algorithm designed with the aim of identifying patients at risk of a second demyelinating attack. OBJECTIVE: To determine the value of gMS-Classifier2 as an early and independent predictor of conversion to clinically definite multiple sclerosis (CDMS). METHODS: Data were prospectively acquired from a CIS cohort. gMS-Classifier2 was determined in patients first seen between 1995 and 2007 with ≥ two 200 µL serum aliquots (N = 249). The primary endpoint was time to conversion to CDMS at two years, the factor tested was gMS-Classifier2 status (positive/negative) or units; other exploratory time points were 5 years and total time of follow-up. RESULTS: Seventy-five patients (30.1%) were gMS-Classifier2 positive. Conversion to CDMS occurred in 31/75 (41.3%) of positive and 45/174 (25.9%) of negative patients (p = 0.017) at two years. Median time to CDMS was 37.8 months (95% CI 10.4–65.3) for positive and 83.9 months (95% CI 57.5–110.5) for negative patients. gMS-Classifier2 status predicted conversion to CDMS within two years of follow-up (HR = 1.8, 95% CI 1.1–2.8; p = 0.014). gMS-Classifier2 units were also independent predictors when tested with either Barkhof criteria and OCB (HR = 1.2, CI 1.0–1.5, p = 0.020) or with T2 lesions and OCB (HR = 1.3, CI 1.1–1.5, p = 0.008). Similar results were obtained at 5 years of follow-up. Discrimination measures showed a significant change in the area under the curve (ΔAUC) when adding gMS-Classifier2 to a model with either Barkhof criteria (ΔAUC 0.0415, p = 0.012) or number of T2 lesions (ΔAUC 0.0467, p = 0.009), but not when OCB were added to these models. CONCLUSIONS: gMS-Classifier2 is an independent predictor of early conversion to CDMS and could be of clinical relevance, particularly in cases in which OCB are not available.
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spelling pubmed-36106902013-04-03 Serum Biomarker gMS-Classifier2: Predicting Conversion to Clinically Definite Multiple Sclerosis Arrambide, Georgina Espejo, Carmen Yarden, Jennifer Fire, Ella Spector, Larissa Dotan, Nir Dukler, Avinoam Rovira, Alex Montalban, Xavier Tintore, Mar PLoS One Research Article BACKGROUND: Anti-glycan antibodies can be found in autoimmune diseases. IgM against glycan P63 was identified in clinically isolated syndromes (CIS) and included in gMS-Classifier2, an algorithm designed with the aim of identifying patients at risk of a second demyelinating attack. OBJECTIVE: To determine the value of gMS-Classifier2 as an early and independent predictor of conversion to clinically definite multiple sclerosis (CDMS). METHODS: Data were prospectively acquired from a CIS cohort. gMS-Classifier2 was determined in patients first seen between 1995 and 2007 with ≥ two 200 µL serum aliquots (N = 249). The primary endpoint was time to conversion to CDMS at two years, the factor tested was gMS-Classifier2 status (positive/negative) or units; other exploratory time points were 5 years and total time of follow-up. RESULTS: Seventy-five patients (30.1%) were gMS-Classifier2 positive. Conversion to CDMS occurred in 31/75 (41.3%) of positive and 45/174 (25.9%) of negative patients (p = 0.017) at two years. Median time to CDMS was 37.8 months (95% CI 10.4–65.3) for positive and 83.9 months (95% CI 57.5–110.5) for negative patients. gMS-Classifier2 status predicted conversion to CDMS within two years of follow-up (HR = 1.8, 95% CI 1.1–2.8; p = 0.014). gMS-Classifier2 units were also independent predictors when tested with either Barkhof criteria and OCB (HR = 1.2, CI 1.0–1.5, p = 0.020) or with T2 lesions and OCB (HR = 1.3, CI 1.1–1.5, p = 0.008). Similar results were obtained at 5 years of follow-up. Discrimination measures showed a significant change in the area under the curve (ΔAUC) when adding gMS-Classifier2 to a model with either Barkhof criteria (ΔAUC 0.0415, p = 0.012) or number of T2 lesions (ΔAUC 0.0467, p = 0.009), but not when OCB were added to these models. CONCLUSIONS: gMS-Classifier2 is an independent predictor of early conversion to CDMS and could be of clinical relevance, particularly in cases in which OCB are not available. Public Library of Science 2013-03-28 /pmc/articles/PMC3610690/ /pubmed/23555846 http://dx.doi.org/10.1371/journal.pone.0059953 Text en © 2013 Arrambide et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Arrambide, Georgina
Espejo, Carmen
Yarden, Jennifer
Fire, Ella
Spector, Larissa
Dotan, Nir
Dukler, Avinoam
Rovira, Alex
Montalban, Xavier
Tintore, Mar
Serum Biomarker gMS-Classifier2: Predicting Conversion to Clinically Definite Multiple Sclerosis
title Serum Biomarker gMS-Classifier2: Predicting Conversion to Clinically Definite Multiple Sclerosis
title_full Serum Biomarker gMS-Classifier2: Predicting Conversion to Clinically Definite Multiple Sclerosis
title_fullStr Serum Biomarker gMS-Classifier2: Predicting Conversion to Clinically Definite Multiple Sclerosis
title_full_unstemmed Serum Biomarker gMS-Classifier2: Predicting Conversion to Clinically Definite Multiple Sclerosis
title_short Serum Biomarker gMS-Classifier2: Predicting Conversion to Clinically Definite Multiple Sclerosis
title_sort serum biomarker gms-classifier2: predicting conversion to clinically definite multiple sclerosis
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3610690/
https://www.ncbi.nlm.nih.gov/pubmed/23555846
http://dx.doi.org/10.1371/journal.pone.0059953
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