Web of Science: 5 cites, Scopus: 5 cites, Google Scholar: cites,
Serum Biomarker gMS-Classifier2 : Predicting Conversion to Clinically Definite Multiple Sclerosis
Arrambide, Georgina (Hospital Universitari Vall d'Hebron)
Espejo, Carmen (Hospital Universitari Vall d'Hebron)
Yarden, Jennifer (Department of Research and Development, Glycominds, Modi'in, Israel)
Fire, Ella (Department of Research and Development, Glycominds, Modi'in, Israel)
Spector, Larissa (Department of Research and Development, Glycominds, Modi'in, Israel)
Dotan, Nir (Department of Research and Development, Glycominds, Modi'in, Israel)
Dukler, Avinoam (Department of Research and Development, Glycominds, Simi Valley, California, United States of America)
Rovira, Alex (Hospital Universitari Vall d'Hebron)
Montalban, Xavier (Hospital Universitari Vall d'Hebron)
Tintoré, Mar (Hospital Universitari Vall d'Hebron)
Universitat Autònoma de Barcelona

Data: 2013
Resum: 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. To determine the value of gMS-Classifier2 as an early and independent predictor of conversion to clinically definite multiple sclerosis (CDMS). 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. 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. 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.
Ajuts: Ministerio de Ciencia e Innovación RD07/0060
Agència de Gestió d'Ajuts Universitaris i de Recerca 2009/SGR/0793
Instituto de Salud Carlos III PI08/0788
Ministerio de Sanidad y Consumo CP07/00146
Drets: Aquest document està subjecte a una llicència d'ús Creative Commons. Es permet la reproducció total o parcial, la distribució, la comunicació pública de l'obra i la creació d'obres derivades, fins i tot amb finalitats comercials, sempre i quan es reconegui l'autoria de l'obra original. Creative Commons
Llengua: Anglès
Document: Article ; recerca ; Versió publicada
Publicat a: PloS one, Vol. 8 (march 2013) , ISSN 1932-6203

DOI: 10.1371/journal.pone.0059953
PMID: 23555846


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