Serum biomarker gMS-Classifier2: predicting conversion to clinically definite multiple sclerosis.

<h4>Background</h4>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...

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Autores principales:	Georgina Arrambide, Carmen Espejo, Jennifer Yarden, Ella Fire, Larissa Spector, Nir Dotan, Avinoam Dukler, Alex Rovira, Xavier Montalban, Mar Tintore
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2013
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/642ff7eaad4f4f0ca1d633309f68b14c
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spelling	oai:doaj.org-article:642ff7eaad4f4f0ca1d633309f68b14c2021-11-18T07:51:33ZSerum biomarker gMS-Classifier2: predicting conversion to clinically definite multiple sclerosis.1932-620310.1371/journal.pone.0059953https://doaj.org/article/642ff7eaad4f4f0ca1d633309f68b14c2013-01-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/pmid/23555846/pdf/?tool=EBIhttps://doaj.org/toc/1932-6203<h4>Background</h4>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.<h4>Objective</h4>To determine the value of gMS-Classifier2 as an early and independent predictor of conversion to clinically definite multiple sclerosis (CDMS).<h4>Methods</h4>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.<h4>Results</h4>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.<h4>Conclusions</h4>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.Georgina ArrambideCarmen EspejoJennifer YardenElla FireLarissa SpectorNir DotanAvinoam DuklerAlex RoviraXavier MontalbanMar TintorePublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 8, Iss 3, p e59953 (2013)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Georgina Arrambide Carmen Espejo Jennifer Yarden Ella Fire Larissa Spector Nir Dotan Avinoam Dukler Alex Rovira Xavier Montalban Mar Tintore Serum biomarker gMS-Classifier2: predicting conversion to clinically definite multiple sclerosis.
description	<h4>Background</h4>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.<h4>Objective</h4>To determine the value of gMS-Classifier2 as an early and independent predictor of conversion to clinically definite multiple sclerosis (CDMS).<h4>Methods</h4>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.<h4>Results</h4>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.<h4>Conclusions</h4>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.
format	article
author	Georgina Arrambide Carmen Espejo Jennifer Yarden Ella Fire Larissa Spector Nir Dotan Avinoam Dukler Alex Rovira Xavier Montalban Mar Tintore
author_facet	Georgina Arrambide Carmen Espejo Jennifer Yarden Ella Fire Larissa Spector Nir Dotan Avinoam Dukler Alex Rovira Xavier Montalban Mar Tintore
author_sort	Georgina Arrambide
title	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_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_sort	serum biomarker gms-classifier2: predicting conversion to clinically definite multiple sclerosis.
publisher	Public Library of Science (PLoS)
publishDate	2013
url	https://doaj.org/article/642ff7eaad4f4f0ca1d633309f68b14c
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Serum biomarker gMS-Classifier2: predicting conversion to clinically definite multiple sclerosis.

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