New Algorithms Improving PML Risk Stratification in MS Patients Treated With Natalizumab

Area of Science:

• Neuroimmunology
• Infectious Disease Epidemiology
• Pharmacovigilance

Background:

• Multiple sclerosis (MS) patients treated with natalizumab are at risk of progressive multifocal leucoencephalopathy (PML), a serious opportunistic infection.
• Identifying predictive factors for PML is crucial for patient safety and personalized treatment strategies.

Purpose of the Study:

• To assess the role of age and disease activity in predicting the risk of progressive multifocal leucoencephalopathy (PML) in multiple sclerosis patients treated with natalizumab.
• To develop a risk stratification model for PML onset in natalizumab-treated patients.

Main Methods:

• A cohort study involving 1,307 multiple sclerosis patients from 36 European University Hospitals treated with natalizumab.
• Collection of epidemiological, clinical, and laboratory data, including anti-John Cunningham virus (JCV) antibody indices and lipid-specific IgM oligoclonal bands.
• Uni- and multivariate logistic regression analyses to identify factors associated with PML onset.

Main Results:

• Thirty-five patients developed PML. Anti-JCV antibody indices and relapse rate were the best predictors of PML in the overall cohort (AUC = 0.85).
• In patients with lipid-specific IgM oligoclonal bands assessed, age at natalizumab initiation, anti-JCV antibody indices, and lipid-specific IgM oligoclonal band status predicted PML risk (AUC = 0.92).
• Absence of lipid-specific IgM oligoclonal bands was a strong individual predictor (OR = 40.94).

Conclusions:

• Disease activity, anti-JCV antibody levels, age, and lipid-specific IgM oligoclonal bands are valuable predictors for tailoring natalizumab therapy in multiple sclerosis patients.
• These factors enable personalized risk stratification for progressive multifocal leucoencephalopathy, aiding in informed treatment decisions.