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

Author

Listed:
  • Georgina Arrambide
  • Carmen Espejo
  • Jennifer Yarden
  • Ella Fire
  • Larissa Spector
  • Nir Dotan
  • Avinoam Dukler
  • Alex Rovira
  • Xavier Montalban
  • Mar Tintore

Abstract

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.

Suggested Citation

  • Georgina Arrambide & Carmen Espejo & Jennifer Yarden & Ella Fire & Larissa Spector & Nir Dotan & Avinoam Dukler & Alex Rovira & Xavier Montalban & Mar Tintore, 2013. "Serum Biomarker gMS-Classifier2: Predicting Conversion to Clinically Definite Multiple Sclerosis," PLOS ONE, Public Library of Science, vol. 8(3), pages 1-8, March.
    • Handle: RePEc:plo:pone00:0059953
    DOI: 10.1371/journal.pone.0059953
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