• Mult. Scler. · Jul 2016

    Multicenter Study

    PML risk stratification using anti-JCV antibody index and L-selectin.

    • Nicholas Schwab, Tilman Schneider-Hohendorf, Béatrice Pignolet, Michela Spadaro, Dennis Görlich, Ingrid Meinl, Susanne Windhagen, Björn Tackenberg, Johanna Breuer, Ester Cantó, Tania Kümpfel, Reinhard Hohlfeld, Volker Siffrin, Felix Luessi, Anita Posevitz-Fejfár, Xavier Montalban, Sven G Meuth, Frauke Zipp, Ralf Gold, Renaud A Du Pasquier, Christoph Kleinschnitz, Annett Jacobi, Manuel Comabella, Antonio Bertolotto, David Brassat, and Heinz Wiendl.
    • Department of Neurology, University of Münster, Germany nicholas.schwab@ukmuenster.de heinz.wiendl@ukmuenster.de.
    • Mult. Scler. 2016 Jul 1; 22 (8): 1048-60.

    BackgroundNatalizumab treatment is associated with progressive multifocal leukoencephalopathy (PML) development. Treatment duration, prior immunosuppressant use, and JCV serostatus are currently used for risk stratification, but PML incidence stays high. Anti-JCV antibody index and L-selectin (CD62L) have been proposed as additional risk stratification parameters.ObjectiveThis study aimed at verifying and integrating both parameters into one algorithm for risk stratification.MethodsMulticentric, international cohorts of natalizumab-treated MS patients were assessed for JCV index (1921 control patients and nine pre-PML patients) and CD62L (1410 control patients and 17 pre-PML patients).ResultsCD62L values correlate with JCV serostatus, as well as JCV index values. Low CD62L in natalizumab-treated patients was confirmed and validated as a biomarker for PML risk with the risk factor "CD62L low" increasing a patient's relative risk 55-fold (p < 0.0001). Validation efforts established 86% sensitivity/91% specificity for CD62L and 100% sensitivity/59% specificity for JCV index as predictors of PML. Using both parameters identified 1.9% of natalizumab-treated patients in the reference center as the risk group.ConclusionsBoth JCV index and CD62L have merit for risk stratification and share a potential biological relationship with implications for general PML etiology. A risk algorithm incorporating both biomarkers could strongly reduce PML incidence.© The Author(s), 2015.

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