Nicholas Schwab1, Tilman Schneider-Hohendorf2, Béatrice Pignolet3, Michela Spadaro4, Dennis Görlich5, Ingrid Meinl6, Susanne Windhagen7, Björn Tackenberg8, Johanna Breuer2, Ester Cantó9, Tania Kümpfel6, Reinhard Hohlfeld6, Volker Siffrin10, Felix Luessi10, Anita Posevitz-Fejfár2, Xavier Montalban9, Sven G Meuth2, Frauke Zipp10, Ralf Gold11, Renaud A Du Pasquier12, Christoph Kleinschnitz13, Annett Jacobi14, Manuel Comabella9, Antonio Bertolotto4, David Brassat15, Heinz Wiendl2. 1. Department of Neurology, University of Münster, Germany nicholas.schwab@ukmuenster.de heinz.wiendl@ukmuenster.de. 2. Department of Neurology, University of Münster, Germany. 3. Pole des Neurosciences Centre Hospitalier Universitaire Toulouse, CPTP INSERM UMR 1043 et Université de Toulouse, UPS, France. 4. Clinical Neurobiology Unit, Regional Referring Multiple Sclerosis Centre (CRESM), Neuroscience Institute Cavalieri Ottolenghi (NICO), University Hospital San Luigi Gonzaga, Orbassano, Italy. 5. Institute of Biostatistics and Clinical Research, University of Münster, Germany. 6. Institute for Clinical Neuroimmunology, Ludwig-Maximilians-University Munich and Munich Cluster Systems Neurology (SyNergy), Germany. 7. Department of Neurology, Clinics Osnabrück, Germany. 8. Department of Neurology, Philipps University and University Clinics Gießen and Marburg, Germany. 9. Servei de Neurologia-Neuroimmunologia, Centre d'Esclerosi Múltiple de Catalunya (Cemcat), Institut de Recerca Vall d'Hebron (VHIR), Hospital Universitari Vall d'Hebron, Universitat Autònoma de Barcelona, Spain. 10. Department of Neurology, University of Mainz, Germany. 11. Department of Neurology, Ruhr University Bochum, Germany. 12. Divisions of Immunology and Allergy and of Neurology, Centre Hospitalier Universitaire Vaudois, Switzerland. 13. Department of Neurology, University of Würzburg, Germany. 14. Division of Rheumatology and Clinical Immunology, University of Münster, Germany/Division of Rheumatology and Clinical Immunology, Brandenburg Medical School, Neuruppin, Germany. 15. Pole des Neurosciences Centre Hospitalier Universitaire Toulouse, CPTP INSERM UMR 1043 et Université de Toulouse, UPS, France/David Brassat also represents the BioNAT study group.
Abstract
BACKGROUND: Natalizumab 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. OBJECTIVE: This study aimed at verifying and integrating both parameters into one algorithm for risk stratification. METHODS: Multicentric, 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). RESULTS: CD62L 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. CONCLUSIONS: Both 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.
BACKGROUND:Natalizumab 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. OBJECTIVE: This study aimed at verifying and integrating both parameters into one algorithm for risk stratification. METHODS: Multicentric, international cohorts of natalizumab-treated MSpatients were assessed for JCV index (1921 control patients and nine pre-PML patients) and CD62L (1410 control patients and 17 pre-PML patients). RESULTS:CD62L 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. CONCLUSIONS: Both 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.
Authors: Martyn K White; Ilker K Sariyer; Jennifer Gordon; Serena Delbue; Valeria Pietropaolo; Joseph R Berger; Kamel Khalili Journal: Rev Med Virol Date: 2015-12-14 Impact factor: 6.989
Authors: L Klotz; A Berthele; W Brück; A Chan; P Flachenecker; R Gold; A Haghikia; K Hellwig; B Hemmer; R Hohlfeld; T Korn; T Kümpfel; M Lang; V Limmroth; R A Linker; U Meier; S G Meuth; F Paul; A Salmen; M Stangel; B Tackenberg; H Tumani; C Warnke; M S Weber; T Ziemssen; F Zipp; H Wiendl Journal: Nervenarzt Date: 2016-06 Impact factor: 1.214