Timely initiation of effective therapy is crucial for preventing disability in multiple sclerosis; however, treatment response varies greatly among patients. Comprehensive predictive models of individual treatment response are lacking. Our aims were: (i) to develop predictive algorithms for individual treatment response using demographic, clinical and paraclinical predictors in patients with multiple sclerosis; and (ii) to evaluate accuracy, and internal and external validity of these algorithms. This study evaluated 27 demographic, clinical and paraclinical predictors of individual response to seven disease-modifying therapies in MSBase, a large global cohort study. Treatment response was analysed separately for disability progression, disability regression, relapse frequency, conversion to secondary progressive disease, change in the cumulative disease burden, and the probability of treatment discontinuation. Multivariable survival and generalized linear models were used, together with the principal component analysis to reduce model dimensionality and prevent overparameterization. Accuracy of the individual prediction was tested and its internal validity was evaluated in a separate, non-overlapping cohort. External validity was evaluated in a geographically distinct cohort, the Swedish Multiple Sclerosis Registry. In the training cohort (n = 8513), the most prominent modifiers of treatment response comprised age, disease duration, disease course, previous relapse activity, disability, predominant relapse phenotype and previous therapy. Importantly, the magnitude and direction of the associations varied among therapies and disease outcomes. Higher probability of disability progression during treatment with injectable therapies was predominantly associated with a greater disability at treatment start and the previous therapy. For fingolimod, natalizumab or mitoxantrone, it was mainly associated with lower pretreatment relapse activity. The probability of disability regression was predominantly associated with pre-baseline disability, therapy and relapse activity. Relapse incidence was associated with pretreatment relapse activity, age and relapsing disease course, with the strength of these associations varying among therapies. Accuracy and internal validity (n = 1196) of the resulting predictive models was high (>80%) for relapse incidence during the first year and for disability outcomes, moderate for relapse incidence in Years 2–4 and for the change in the cumulative disease burden, and low for conversion to secondary progressive disease and treatment discontinuation. External validation showed similar results, demonstrating high external validity for disability and relapse outcomes, moderate external validity for cumulative disease burden and low external validity for conversion to secondary progressive disease and treatment discontinuation. We conclude that demographic, clinical and paraclinical information helps predict individual response to disease-modifying therapies at the time of their commencement.

Disease progression and treatment efficacy vary among individuals with multiple sclerosis. Reliable predictors of individual disease outcomes are lacking. To examine the accuracy of the early prediction of 12-year disability outcomes using clinical and magnetic resonance imaging (MRI) parameters. 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. 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. 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.

Tomas Uher, Kelly Fellows, Dana Horakova, Robert Zivadinov, Manuela Vaneckova, Lukas Sobisek, Michaela Tyblova, Zdenek Seidl, Jan Krasensky, Niels Bergsland, Bianca Weinstock-Guttman, Eva Havrdova, Murali Ramanathan

BACKGROUND AND PURPOSE: Potential differences between primary progressive and relapsing remitting multiple sclerosis are the subject of ongoing controversial discussions. The aim of this work was to determine whether and how primary-progressive and relapsing-remitting multiple sclerosis subtypes differ regarding conventional MR imaging parameters, cerebral iron deposits, and their association with clinical status. MATERIALS AND METHODS: We analyzed 24 patients with primary-progressive MS, 80 with relapsing-remitting MS, and 20 healthy controls with 1.5T MR imaging for assessment of the conventional quantitative parameters: T2 lesion load, T1 lesion load, brain parenchymal fraction, and corpus callosum volume. Quantitative susceptibility mapping was performed to estimate iron concentration in the deep gray matter. RESULTS: Decreased susceptibility within the thalamus in relapsing-remitting MS compared with primary-progressive MS was the only significant MR imaging difference between these MS subtypes. In the relapsing-remitting MS subgroup, the Expanded Disability Status Scale score was positively associated with conventional parameters reflecting white matter lesions and brain atrophy and with iron in the putamen and caudate nucleus. A positive association with putaminal iron and the Expanded Disability Status Scale score was found in primary-progressive MS. CONCLUSIONS: Susceptibility in the thalamus might provide additional support for the differentiation between primary-progressive and relapsing-remitting MS. That the Expanded Disability Status Scale score was associated with conventional MR imaging parameters and iron concentrations in several deep gray matter regions in relapsing-remitting MS, while only a weak association with putaminal iron was observed in primary-progressive MS suggests different driving forces of disability in these MS subtypes.

No evidence of disease activity (NEDA) has been proposed as a new treatment goal in multiple sclerosis (MS). NEDA-3 status is defined as the absence of magnetic resonance imaging (MRI; new/enlarging/enhancing lesions and increased whole brain volume loss in NEDA-4) and clinical disease activity. To investigate the persistence of NEDA status over long-term follow-up in MS patients treated with weekly intramuscular interferon beta-1a. We included 192 patients after the first demyelinating event suggestive of MS, that is, clinically isolated syndrome (CIS) and 162 relapsing-remitting MS (RRMS) patients. NEDA-3 status was observed in 40.1% of CIS and 20.4% of RRMS patients after 1 year. After 4 years, 10.1% of CIS patients had NEDA-3 status. After 10 years, none of the RRMS patients had NEDA-3 status. Only 4.6% of CIS and 1.0% of RRMS patients maintained NEDA-4 status after 4 years. Loss of NEDA-3 status after the first year was associated with a higher risk of disability progression (hazard ratio (HR) = 2.3–4.0; p = 0.005–0.03) over 6 years. Despite intramuscular interferon beta-1a treatment, loss of NEDA status occurred in the vast majority of individuals. Loss of NEDA status during the first year was associated with disability progression over long-term follow-up; however, specificity for individual patient was low.