BACKGROUND: Disease progression and treatment efficacy vary among individuals with multiple sclerosis. Reliable predictors of individual disease outcomes are lacking. OBJECTIVE: To examine the accuracy of the early prediction of 12-year disability outcomes using clinical and magnetic resonance imaging (MRI) parameters. METHODS: A total of 177 patients from the original Avonex-Steroids-Azathioprine study were included. Participants underwent 3-month clinical follow-ups. Cox models were used to model the associations between clinical and MRI markers at baseline or after 12 months with sustained disability progression (SDP) over the 12-year observation period. RESULTS: At baseline, T2 lesion number, T1 and T2 lesion volumes, corpus callosum (CC), and thalamic fraction were the best predictors of SDP (hazard ratio (HR) = 1.7-4.6; p ⩽ 0.001-0.012). At 12 months, Expanded Disability Status Scale (EDSS) and its change, number of new or enlarging T2 lesions, and CC volume % change were the best predictors of SDP over the follow-up (HR = 1.7-3.5; p ⩽ 0.001-0.017). A composite score was generated from a subset of the best predictors of SDP. Scores of ⩾4 had greater specificity (90%-100%) and were associated with greater cumulative risk of SDP (HR = 3.2-21.6; p < 0.001) compared to the individual predictors. CONCLUSION: The combination of established MRI and clinical indices with MRI volumetric predictors improves the prediction of SDP over long-term follow-up and may provide valuable information for therapeutic decisions.

Buffalo Neuroimaging Analysis Center Department of Neurology School of Medicine and Biomedical Sciences University at Buffalo State University of New York Buffalo NY USA

Buffalo Neuroimaging Analysis Center Department of Neurology School of Medicine and Biomedical Sciences University at Buffalo State University of New York Buffalo NY USA MR Imaging Clinical Translational Research Center School of Medicine and Biomedical Sciences University at Buffalo State University of New York Buffalo NY USA

Department of Medicine University of Melbourne Melbourne VIC Australia Department of Neurology Royal Melbourne Hospital Melbourne VIC Australia

Department of Neurology and Center of Clinical Neuroscience 1st Faculty of Medicine and General University Hospital Charles University Prague Czech Republic

Department of Radiology 1st Faculty of Medicine and General University Hospital Charles University Prague Czech Republic

Department of Statistics and Probability University of Economics Prague Czech Republic

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