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      Effect of dronabinol on progression in progressive multiple sclerosis (CUPID): a randomised, placebo-controlled trial

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          Summary

          Background

          Laboratory evidence has shown that cannabinoids might have a neuroprotective action. We investigated whether oral dronabinol (Δ 9-tetrahydrocannabinol) might slow the course of progressive multiple sclerosis.

          Methods

          In this multicentre, parallel, randomised, double-blind, placebo-controlled study, we recruited patients aged 18–65 years with primary or secondary progressive multiple sclerosis from 27 UK neurology or rehabilitation departments. Patients were randomly assigned (2:1) to receive dronabinol or placebo for 36 months; randomisation was by stochastic minimisation, using a computer-generated randomisation sequence, balanced according to expanded disability status scale (EDSS) score, centre, and disease type. Maximum dose was 28 mg per day, titrated against bodyweight and adverse effects. Primary outcomes were EDSS score progression (masked assessor, time to progression of ≥1 point from a baseline score of 4·0–5·0 or ≥0·5 points from a baseline score of ≥5·5, confirmed after 6 months) and change from baseline in the physical impact subscale of the 29-item multiple sclerosis impact scale (MSIS-29-PHYS). All patients who received at least one dose of study drug were included in the intention-to-treat analyses. This trial is registered as an International Standard Randomised Controlled Trial (ISRCTN 62942668).

          Findings

          Of the 498 patients randomly assigned to a treatment group, 329 received at least one dose of dronabinol and 164 received at least one dose of placebo (five did not receive the allocated intervention). 145 patients in the dronabinol group had EDSS score progression (0·24 first progression events per patient-year; crude rate) compared with 73 in the placebo group (0·23 first progression events per patient-year; crude rate); HR for prespecified primary analysis was 0·92 (95% CI 0·68–1·23; p=0·57). Mean yearly change in MSIS-29-PHYS score was 0·62 points (SD 3·29) in the dronabinol group versus 1·03 points (3·74) in the placebo group. Primary analysis with a multilevel model gave an estimated between-group difference (dronabinol–placebo) of −0·9 points (95% CI −2·0 to 0·2). We noted no serious safety concerns (114 [35%] patients in the dronabinol group had at least one serious adverse event, compared with 46 [28%] in the placebo group).

          Interpretation

          Our results show that dronabinol has no overall effect on the progression of multiple sclerosis in the progressive phase. The findings have implications for the design of future studies of progressive multiple sclerosis, because lower than expected progression rates might have affected our ability to detect clinical change.

          Funding

          UK Medical Research Council, National Institute for Health Research Efficacy and Mechanism Evaluation programme, Multiple Sclerosis Society, and Multiple Sclerosis Trust.

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          Most cited references24

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          R: a language and environment for statistic computing

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            Recommended diagnostic criteria for multiple sclerosis: guidelines from the International Panel on the diagnosis of multiple sclerosis.

            The International Panel on MS Diagnosis presents revised diagnostic criteria for multiple sclerosis (MS). The focus remains on the objective demonstration of dissemination of lesions in both time and space. Magnetic resonance imaging is integrated with dinical and other paraclinical diagnostic methods. The revised criteria facilitate the diagnosis of MS in patients with a variety of presentations, including "monosymptomatic" disease suggestive of MS, disease with a typical relapsing-remitting course, and disease with insidious progression, without clear attacks and remissions. Previously used terms such as "clinically definite" and "probable MS" are no longer recommended. The outcome of a diagnostic evaluation is either MS, "possible MS" (for those at risk for MS, but for whom diagnostic evaluation is equivocal), or "not MS."
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              Accurate, robust, and automated longitudinal and cross-sectional brain change analysis.

              Quantitative measurement of brain size, shape, and temporal change (for example, in order to estimate atrophy) is increasingly important in biomedical image analysis applications. New methods of structural analysis attempt to improve robustness, accuracy, and extent of automation. A fully automated method of longitudinal (temporal change) analysis, SIENA, was presented previously. In this paper, improvements to this method are described, and also an extension of SIENA to a new method for cross-sectional (single time point) analysis. The methods are fully automated, robust, and accurate: 0.15% brain volume change error (longitudinal): 0.5-1% brain volume accuracy for single-time point (cross-sectional). A particular advantage is the relative insensitivity to differences in scanning parameters. The methods provide easy manual review of their output by the automatic production of summary images which show the results of the brain extraction, registration, tissue segmentation, and final atrophy estimation.
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                Author and article information

                Contributors
                Journal
                Lancet Neurol
                Lancet Neurol
                Lancet Neurology
                Lancet Pub. Group
                1474-4422
                1474-4465
                1 September 2013
                September 2013
                : 12
                : 9
                : 857-865
                Affiliations
                [1]Peninsula Clinical Trials Unit, Plymouth University Peninsula Schools of Medicine and Dentistry, Plymouth, UK
                [2]Medical Research Council Clinical Trials Unit, London, UK
                [3]Institute of Neurology, University College London, London, UK
                Author notes
                [* ]Correspondence to: Prof John Zajicek, Room N13, ITTC Building 1, Tamar Science Park, Plymouth PL6 8BX, UK john.zajicek@ 123456nhs.net
                Article
                LANEUR70159
                10.1016/S1474-4422(13)70159-5
                3744749
                23856559
                ee21aed8-f065-450a-a9a0-ce06fa5bd440
                © 2013 Elsevier Ltd. All rights reserved.

                This document may be redistributed and reused, subject to certain conditions.

                History
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                Neurology
                Neurology

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