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Montréal, Canada

Bar-Or A.,Montreal Neurological Institute | Gold R.,Ruhr University Bochum | Kappos L.,University of Basel | Arnold D.L.,Montreal Neurological Institute | And 6 more authors.
Journal of Neurology | Year: 2013

In the double-blind, placebo-controlled, Phase 3 DEFINE study in patients with relapsing-remitting multiple sclerosis, oral BG-12 (dimethyl fumarate) significantly reduced the proportion of patients relapsed (primary endpoint), the annualized relapse rate (ARR), and confirmed disability progression (secondary endpoints) at two years compared with placebo. We investigated the efficacy of BG-12 240 mg twice daily (BID) and three times daily (TID) in patient subgroups stratified according to baseline demographic and disease characteristics including gender, age, relapse history, McDonald criteria, treatment history, expanded disability status scale score, T2 lesion volume, and gadolinium-enhancing lesions. The clinical efficacy of BG-12 was generally consistent across patient subgroups and reflected positive findings in the overall DEFINE study population. Treatment with BG-12 BID and TID reduced the proportion of patients relapsed and the ARR at two years compared with placebo in all patient subgroups. Reductions in the risk of relapse with BG-12 BID vs. placebo ranged from 68 % [hazard ratio 0.32 (95 % confidence interval (CI) 0.16-0.62)] to 26 % [0.74 (0.51-1.09)] and from 66 % [0.34 (0.23-0.50)] to 25 % [0.75 (0.42-1.36)] with BG-12 TID vs. placebo. BG-12 also reduced the risk of disability progression at two years compared with placebo in most subgroups of patients treated with the BID dosing regimen and in all subgroups treated with the TID regimen. These analyses indicate that treatment with BG-12 is consistently effective across a wide spectrum of patients with relapsing-remitting multiple sclerosis with varied demographic and disease characteristics. © 2013 Springer-Verlag Berlin Heidelberg. Source

Gold R.,Ruhr University Bochum | Kappos L.,University of Basel | Arnold D.L.,NeuroRx Research | Arnold D.L.,Montreal Neurological Institute | And 8 more authors.
New England Journal of Medicine | Year: 2012

Background: BG-12 (dimethyl fumarate) was shown to have antiinflammatory and cytoprotective properties in preclinical experiments and to result in significant reductions in disease activity on magnetic resonance imaging (MRI) in a phase 2, placebo-controlled study involving patients with relapsing-remitting multiple sclerosis. Methods: We conducted a randomized, double-blind, placebo-controlled phase 3 study involving patients with relapsing-remitting multiple sclerosis. Patients were randomly assigned to receive oral BG-12 at a dose of 240 mg twice daily, BG-12 at a dose of 240 mg three times daily, or placebo. The primary end point was the proportion of patients who had a relapse by 2 years. Other end points included the annualized relapse rate, the time to confirmed progression of disability, and findings on MRI. Results The estimated proportion of patients who had a relapse was significantly lower in the two BG-12 groups than in the placebo group (27% with BG-12 twice daily and 26% with BG-12 thrice daily vs. 46% with placebo, P<0.001 for both comparisons). The annualized relapse rate at 2 years was 0.17 in the twice-daily BG-12 group and 0.19 in the thrice-daily BG-12 group, as compared with 0.36 in the placebo group, representing relative reductions of 53% and 48% with the two BG-12 regimens, respectively (P<0.001 for the comparison of each BG-12 regimen with placebo). The estimated proportion of patients with confirmed progression of disability was 16% in the twicedaily BG-12 group, 18% in the thrice-daily BG-12 group, and 27% in the placebo group, with significant relative risk reductions of 38% with BG-12 twice daily (P = 0.005) and 34% with BG-12 thrice daily (P = 0.01). BG-12 also significantly reduced the number of gadolinium-enhancing lesions and of new or enlarging T 2-weighted hyperintense lesions (P<0.001 for the comparison of each BG-12 regimen with placebo). Adverse events associated with BG-12 included flushing and gastrointestinal events, such as diarrhea, nausea, and upper abdominal pain, as well as decreased lymphocyte counts and elevated liver aminotransferase levels. Conclusions: In patients with relapsing-remitting multiple sclerosis, both BG-12 regimens, as compared with placebo, significantly reduced the proportion of patients who had a relapse, the annualized relapse rate, the rate of disability progression, and the number of lesions on MRI. Copyright © 2012 Massachusetts Medical Society. Source

Karimaghaloo Z.,McGill University | Arnold D.L.,NeuroRx Research | Arbel T.,McGill University
Medical Image Analysis | Year: 2016

Detection and segmentation of large structures in an image or within a region of interest have received great attention in the medical image processing domains. However, the problem of small pathology detection and segmentation still remains an unresolved challenge due to the small size of these pathologies, their low contrast and variable position, shape and texture. In many contexts, early detection of these pathologies is critical in diagnosis and assessing the outcome of treatment. In this paper, we propose a probabilistic Adaptive Multi-level Conditional Random Fields (AMCRF) with the incorporation of higher order cliques for detecting and segmenting such pathologies. In the first level of our graphical model, a voxel-based CRF is used to identify candidate lesions. In the second level, in order to further remove falsely detected regions, a new CRF is developed that incorporates higher order textural features, which are invariant to rotation and local intensity distortions. At this level, higher order textures are considered together with the voxel-wise cliques to refine boundaries and is therefore adaptive. The proposed algorithm is tested in the context of detecting enhancing Multiple Sclerosis (MS) lesions in brain MRI, where the problem is further complicated as many of the enhancing voxels are associated with normal structures (i.e. blood vessels) or noise in the MRI. The algorithm is trained and tested on large multi-center clinical trials from Relapsing-Remitting MS patients. The effect of several different parameter learning and inference techniques is further investigated. When tested on 120 cases, the proposed method reaches a lesion detection rate of 90%, with very few false positive lesion counts on average, ranging from 0.17 for very small (3-5 voxels) to 0 for very large (50+ voxels) regions. The proposed model is further tested on a very large clinical trial containing 2770 scans where a high sensitivity of 91% with an average false positive count of 0.5 is achieved. Incorporation of contextual information at different scales is also explored. Finally, superior performance is shown upon comparing with Support Vector Machine (SVM), Random Forest and variant of an MRF. © 2015 Elsevier B.V. Source

Elliott C.,McGill University | Arnold D.L.,NeuroRx Research | Collins D.L.,Montreal Neurological Institute | Arbel T.,McGill University
IEEE Transactions on Medical Imaging | Year: 2013

Detection of new Multiple Sclerosis (MS) lesions on magnetic resonance imaging (MRI) is important as a marker of disease activity and as a potential surrogate for relapses. We propose an approach where sequential scans are jointly segmented, to provide a temporally consistent tissue segmentation while remaining sensitive to newly appearing lesions. The method uses a two-stage classification process: 1) a Bayesian classifier provides a probabilistic brain tissue classification at each voxel of reference and follow-up scans, and 2) a random-forest based lesion-level classification provides a final identification of new lesions. Generative models are learned based on 364 scans from 95 subjects from a multi-center clinical trial. The method is evaluated on sequential brain MRI of 160 subjects from a separate multi-center clinical trial, and is compared to 1) semi-automatically generated ground truth segmentations and 2) fully manual identification of new lesions generated independently by nine expert raters on a subset of 60 subjects. For new lesions greater than 0.15 cc in size, the classifier has near perfect performance (99% sensitivity, 2% false detection rate), as compared to ground truth. The proposed method was also shown to exceed the performance of any one of the nine expert manual identifications. © 1982-2012 IEEE. Source

Kappos L.,University of Basel | Gold R.,Ruhr University Bochum | Arnold D.L.,NeuroRx Research | Bar-Or A.,Montreal Neurological Institute | And 8 more authors.
Multiple Sclerosis | Year: 2014

Background: Oral BG-12 (dimethyl fumarate), approved for the treatment of the relapsing forms of MS, has demonstrated clinical efficacy with an acceptable safety profile in the Phase III "Determination of the Efficacy and Safety of Oral Fumarate in Relapsing-Remitting Multiple Sclerosis (RRMS)" (DEFINE) and "Comparator and an Oral Fumarate in RRMS" (CONFIRM) studies. Objectives: To evaluate the health-related quality of life (HRQoL) impairment that is associated with RRMS and to assess the effects of BG-12 on HRQoL in the DEFINE study. Methods: Patients with RRMS were randomized to BG-12 240 mg twice (BID) or three times (TID) daily, or placebo, for 2 years. HRQoL was assessed by the Short Form-36 (SF-36), global assessment of well-being visual analog scale and the EuroQol-5D. Results: In the 1237 patients from DEFINE, HRQoL impairment was greatest in patients who had higher disability scores and in those who had experienced relapse. Change in SF-36 physical component summary scores during 2 years' treatment significantly favored BG-12 over placebo (both doses: p < 0.001). We saw similar benefits in other measures of functioning and general well-being as early as Week 24. These benefits were maintained during the study. Conclusions: Our results add to evidence for a negative impact of RRMS on HRQoL and they demonstrate the benefits of BG-12 on HRQoL measures, which coupled with significant clinical efficacy, further support its use as a new treatment for RRMS. © 2013 The Author(s). Source

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