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Traditionally, multiple sclerosis has been categorised by distinct clinical descriptors—relapsing-remitting, secondary progressive, and primary progressive—for patient care, research, and regulatory approval of medications. Accumulating evidence suggests that the clinical course of multiple sclerosis is better considered as a continuum, with contributions from concurrent pathophysiological processes that vary across individuals and over time. The apparent evolution to a progressive course reflects a partial shift from predominantly localised acute injury to widespread inflammation and neurodegeneration, coupled with failure of compensatory mechanisms, such as neuroplasticity and remyelination. Ageing increases neural susceptibility to injury and decreases resilience. These observations encourage a new consideration of the course of multiple sclerosis as a spectrum defined by the relative contributions of overlapping pathological and reparative or compensatory processes. New understanding of key mechanisms underlying progression and measures to quantify progressive pathology will potentially have important and beneficial implications for clinical care, treatment targets, and regulatory decision-making.

Many studies report an overlap of MRI and clinical findings between patients with relapsing-remitting multiple sclerosis (RRMS) and secondary progressive multiple sclerosis (SPMS), which in part is reflective of inclusion of subjects with variable disease duration and short periods of follow-up. To overcome these limitations, we examined the differences between RRMS and SPMS and the relationship between MRI measures and clinical outcomes 30 years after first presentation with clinically isolated syndrome suggestive of multiple sclerosis. Sixty-three patients were studied 30 years after their initial presentation with a clinically isolated syndrome; only 14% received a disease modifying treatment at any time point. Twenty-seven patients developed RRMS, 15 SPMS and 21 experienced no further neurological events; these groups were comparable in terms of age and disease duration. Clinical assessment included the Expanded Disability Status Scale, 9-Hole Peg Test and Timed 25-Foot Walk and the Brief International Cognitive Assessment For Multiple Sclerosis. All subjects underwent a comprehensive MRI protocol at 3 T measuring brain white and grey matter (lesions, volumes and magnetization transfer ratio) and cervical cord involvement. Linear regression models were used to estimate age- and gender-adjusted group differences between clinical phenotypes after 30 years, and stepwise selection to determine associations between a large sets of MRI predictor variables and physical and cognitive outcome measures. At the 30-year follow-up, the greatest differences in MRI measures between SPMS and RRMS were the number of cortical lesions, which were higher in SPMS (the presence of cortical lesions had 100% sensitivity and 88% specificity), and grey matter volume, which was lower in SPMS. Across all subjects, cortical lesions, grey matter volume and cervical cord volume explained 60% of the variance of the Expanded Disability Status Scale; cortical lesions alone explained 43%. Grey matter volume, cortical lesions and gender explained 43% of the variance of Timed 25-Foot Walk. Reduced cortical magnetization transfer ratios emerged as the only significant explanatory variable for the symbol digit modality test and explained 52% of its variance. Cortical involvement, both in terms of lesions and atrophy, appears to be the main correlate of progressive disease and disability in a cohort of individuals with very long follow-up and homogeneous disease duration, indicating that this should be the target of therapeutic interventions., Haider et al. followed a cohort of individuals for 30 years after their initial presentation with symptoms suggestive of multiple sclerosis. Cortical involvement was the main correlate of progressive disease and disability and therefore might provide a promising diagnostic and therapeutic target.

ObjectiveTo identify pathologic correlates of magnetization transfer ratio (MTR) in multiple sclerosis (MS) in an MRI–pathology study.MethodsWe acquired MTR maps at 3T from 16 fixed MS brains and 4 controls, and immunostained 100 tissue blocks for neuronal neurofilaments, myelin (SMI94), tissue macrophages (CD68), microglia (IBA1), B-lymphocytes, T-lymphocytes, cytotoxic T-lymphocytes, astrocytes (glial fibrillary acidic protein), and mitochondrial damage (COX4, VDAC). We defined regions of interest in lesions, normal-appearing white matter (NAWM), and cortical normal-appearing gray matter (NAGM). Associations between MTR and immunostaining intensities were explored using linear mixed-effects models (with cassettes nested within patients) and interaction terms (for differences between regions of interest and between cases and controls); a multivariate linear mixed-effects model identified the best pathologic correlates of MTR.ResultsMTR was the lowest in white matter (WM) lesions (23.4 ± 9.4%) and the highest in NAWM (38.1 ± 8.7%). In MS brains, lower MTR was associated with lower immunostaining intensity for myelin (coefficient 0.31; 95% confidence interval [CI] 0.07–0.55), macrophages (coefficient 0.03; 95% CI 0.01–0.07), and astrocytes (coefficient 0.51; 95% CI 0.02–1.00), and with greater mitochondrial damage (coefficient 0.31; 95% CI 0.07–0.55). Based on interaction terms, MTR was more strongly associated with myelin in WM (coefficient 1.58; 95% CI 1.09–2.08) and gray matter (GM) lesions (coefficient 0.66; 95% CI 0.13–1.20), and with macrophages (coefficient 1.40; 95% CI 0.56–2.25), astrocytes (coefficient 2.66; 95% CI 1.31–4.01), and mitochondrial damage (coefficient −12.59; 95% CI −23.16 to −2.02) in MS brains than controls. In the multivariate model, myelin immunostaining intensity was the best correlate of MTR (coefficient 0.31; 95% CI 0.09–0.52; p = 0.004).ConclusionsMyelin was the strongest correlate of MTR, especially in WM and cortical GM lesions, but additional correlates should be kept in mind when designing and interpreting MTR observational and experimental studies in MS.

Multiple sclerosis is a heterogeneous disease with an unpredictable course. We applied machine learning to generate individualised risk scores of disability worsening and stratify patients into subgroups with different prognosis.Clinical data and MRI scans from published randomised clinical trials in patients with relapsing-remitting and progressive MS were divided into training (n=5,483) and external validation data sets (n=2,668). We processed brain MRI scans to obtain 18 measures for lobar grey matter, deep grey matter and lesion volumes, and T1-/T2-weighted ratio of the normal-appearing white matter regions. We developed a machine learning model, called subpopulation risk stratification (SunRiSe), that combines multi-parametric clinical and MRI data to estimate individualised risk scores and stratify patients into subgroups on the basis of this risk; in particular, we entered MRI measures, the Expanded Disability Status Scale, age and gender to generate risk scores of disability worsening (i.e., the time to confirmed disability worsening). Based on SunRiSe risk scores, high-, medium-, and low-risk subpopulations were defined at study entry. We assessed whether selecting patients at high risk of disability worsening reduces sample size compared to when all risk groups were sampled together.In both the training and external validation data sets, SunRiSe-stratified patients in three groups associated with different levels of risk of disability worsening. In the external validation data set, patients at high risk were mainly progressive MS and had more disability events compared to those at medium-risk (hazard ratio [HR]=1.34, pThe inclusion of patients predicted to be at high risk, reduced (i) duration of an event-driven trial by an average of 4.5 months (±2.1 months); (ii) the number of participants in a randomised trial by approximately 200, with 80% statistical power to detect a 30% treatment effect.Machine learning provides a personalised risk score that can identify patients who have the greatest risk of disability worsening and therefore should be treated with the most effective medications and monitored more closely. Risk stratification allows the enrichment of clinical trials with patients more likely to worsen, and thereby reduces trial duration and sample size.

Previous cohort studies on paediatric multiple sclerosis (MS) have reported very low frequencies for a primary progressive MS (PPMS) course ranging from 0% to 7%. We identified six patients presenting prior to the age of 18 years and fulfilling the 2017 McDonald Criteria for PPMS. Presentation with progressive neurological symptoms and signs in young people should prompt evaluation for genetic causes such as leukodystrophies, hereditary spastic paraparesis and mitochondrial diseases given the rarity of primary progressive course in paediatric MS. In the absence of an alternative diagnosis, with new therapeutic options becoming available for PPMS, this diagnosis should then be considered.

ObjectivesTraumatic and non-traumatic spinal cord injury produce neurodegeneration across the entire neuraxis. However, the spatiotemporal dynamics of spinal cord grey and white matter neurodegeneration above and below the injury is understudied.MethodsWe acquired longitudinal data from 13 traumatic and 3 non-traumatic spinal cord injury patients (8–8 cervical and thoracic cord injuries) within 1.5 years after injury and 10 healthy controls over the same period. The protocol encompassed structural and diffusion-weighted MRI rostral (C2/C3) and caudal (lumbar enlargement) to the injury level to track tissue-specific neurodegeneration. Regression models assessed group differences in the temporal evolution of tissue-specific changes and associations with clinical outcomes.ResultsAt 2 months post-injury, white matter area was decreased by 8.5% and grey matter by 15.9% in the lumbar enlargement, while at C2/C3 only white matter was decreased (−9.7%). Patients had decreased cervical fractional anisotropy (FA: −11.3%) and increased radial diffusivity (+20.5%) in the dorsal column, while FA was lower in the lateral (−10.3%) and ventral columns (−9.7%) of the lumbar enlargement. White matter decreased by 0.34% and 0.35% per month at C2/C3 and lumbar enlargement, respectively, and grey matter decreased at C2/C3 by 0.70% per month.ConclusionsThis study describes the spatiotemporal dynamics of tissue-specific spinal cord neurodegeneration above and below a spinal cord injury. While above the injury, grey matter atrophy lagged initially behind white matter neurodegeneration, in the lumbar enlargement these processes progressed in parallel. Tracking trajectories of tissue-specific neurodegeneration provides valuable assessment tools for monitoring recovery and treatment effects.

The original version of this Article contained an error in Fig. 2, in which the plot shown in panel c was inadvertently duplicated in panel d. The correct version of Fig. 2 is: (Figure presented.) which replaces the previous incorrect version: (Figure presented.).

Pathophysiological changes in the spinal cord white and grey matter resulting from injury can be observed with MRI techniques. These techniques provide sensitive markers of macrostructural and microstructural tissue integrity, which correlate with histological findings. Spinal cord MRI findings in traumatic spinal cord injury (tSCI) and nontraumatic spinal cord injury - the most common form of which is degenerative cervical myelopathy (DCM) - have provided important insights into the pathophysiological processes taking place not just at the focal injury site but also rostral and caudal to the spinal injury. Although tSCI and DCM have different aetiologies, they show similar degrees of spinal cord pathology remote from the injury site, suggesting the involvement of similar secondary degenerative mechanisms. Advanced quantitative MRI protocols that are sensitive to spinal cord pathology have the potential to improve diagnosis and, more importantly, predict outcomes in patients with tSCI or nontraumatic spinal cord injury. This Review describes the insights into tSCI and DCM that have been revealed by neuroimaging and outlines current activities and future directions for the field.

Objective: To compare the performance of the 2017 McDonald criteria with that of the 2010 criteria for the diagnosis of multiple sclerosis (MS) in children in the clinical setting. Methods: In this retrospective, multi-centre study, we identified children who presented with symptoms suggestive of a clinically isolated syndrome (CIS) and were followed up for at least 2 years or until their second attack. Results: Of 156 children with CIS followed up for a median of 4.17 years, 94 (60.3%) were diagnosed with MS. In all, 83 (88.3%) of these fulfilled the 2010 dissemination in space (DIS) criteria at onset. Three additional children fulfilled the 2017 DIS criteria because of the inclusion of symptomatic lesions. Of the 59 children with MS who underwent post-gadolinium magnetic resonance imaging (MRI), 44 (74.6%) fulfilled the 2010 dissemination in time (DIT) criteria at baseline. When the presence of oligoclonal bands (OCBs) was used to substitute DIT, an additional 35 children (79/94, 84.0%) were diagnosed with MS according to the 2017 criteria. The 2017 criteria had higher accuracy (87.2% vs 66.7%), higher sensitivity (84.0% vs 46.8%), but reduced specificity (91.9% vs 96.8%) when compared to the 2010 criteria. Conclusion: The improved performance of the 2017 criteria when compared to the 2010 criteria was predominantly due to the inclusion of intrathecal OCBs.

Significance Traditional analysis of clinical trials precludes a mechanistic understanding of drug actions. This is further compounded by the use of outcome measures in clinical trials not directly related to the mechanism of action of the medication under study. Here, we applied structural equation models to the double-blind randomized controlled trial of simvastatin in secondary progressive multiple sclerosis to investigate causal associations that underlie treatment effects. Our results suggest that beneficial effects of simvastatin on reducing the rate of brain atrophy and slowing the deterioration of disability are independent of serum cholesterol reduction. Our work demonstrates that structural models can elucidate the statistical pathways underlying treatment effects in clinical trials of poorly understood neurodegenerative disorders, such as progressive multiple sclerosis., Understanding the mode of action of drugs is a challenge with conventional methods in clinical trials. Here, we aimed to explore whether simvastatin effects on brain atrophy and disability in secondary progressive multiple sclerosis (SPMS) are mediated by reducing cholesterol or are independent of cholesterol. We applied structural equation models to the MS-STAT trial in which 140 patients with SPMS were randomized to receive placebo or simvastatin. At baseline, after 1 and 2 years, patients underwent brain magnetic resonance imaging; their cognitive and physical disability were assessed on the block design test and Expanded Disability Status Scale (EDSS), and serum total cholesterol levels were measured. We calculated the percentage brain volume change (brain atrophy). We compared two models to select the most likely one: a cholesterol-dependent model with a cholesterol-independent model. The cholesterol-independent model was the most likely option. When we deconstructed the total treatment effect into indirect effects, which were mediated by brain atrophy, and direct effects, simvastatin had a direct effect (independent of serum cholesterol) on both the EDSS, which explained 69% of the overall treatment effect on EDSS, and brain atrophy, which, in turn, was responsible for 31% of the total treatment effect on EDSS [β = −0.037; 95% credible interval (CI) = −0.075, −0.010]. This suggests that simvastatin’s beneficial effects in MS are independent of its effect on lowering peripheral cholesterol levels, implicating a role for upstream intermediate metabolites of the cholesterol synthesis pathway. Importantly, it demonstrates that computational models can elucidate the causal architecture underlying treatment effects in clinical trials of progressive MS.

Motor skill learning relies on neural plasticity in the motor and limbic systems. However, the spatial and temporal dependencies of these changes, and their microstructural underpinnings, remain unclear. Eighteen healthy males received training in a computer- controlled motion game 4 times a week, for 4 weeks. Performance improvements were observed in all trained participants. Serial myelin-sensitive multiparametric mapping at 3T during this period of intensive motor skill acquisition revealed temporally and spatially distributed, performance-related myelin-sensitive microstructural changes in the grey and white matter across the corticospinal system and hippocampus. Interestingly, analysis of the trajectory of these transient changes revealed a time-shifted choreography across white and grey matter of the corticospinal system as well as with changes in the hippocampus. Crucially, in the cranial corticospinal tracts, myelin-sensitive changes during training in the posterior part of the limb of the internal capsule were of greater magnitude in lower-limb trainees compared to upper limb trainees. Motor skill learning is depended on coherent waves of plasticity within a corticospinal-hippocampal loop.

Multiple sclerosis (MS) can be divided into four phenotypes based on clinical evolution. The pathophysiological boundaries of these phenotypes are unclear, limiting treatment stratification. Machine learning can identify groups with similar features using multidimensional data. Here, to classify MS subtypes based on pathological features, we apply unsupervised machine learning to brain MRI scans acquired in previously published studies. We use a training dataset from 6322 MS patients to define MRI-based subtypes and an independent cohort of 3068 patients for validation. Based on the earliest abnormalities, we define MS subtypes as cortex-led, normal-appearing white matter-led, and lesion-led. People with the lesion-led subtype have the highest risk of confirmed disability progression (CDP) and the highest relapse rate. People with the lesion-led MS subtype show positive treatment response in selected clinical trials. Our findings suggest that MRI-based subtypes predict MS disability progression and response to treatment and may be used to define groups of patients in interventional trials., Multiple sclerosis is a heterogeneous progressive disease. Here, the authors use an unsupervised machine learning algorithm to determine multiple sclerosis subtypes, progression, and response to potential therapeutic treatments based on neuroimaging data.

ObjectiveSporadic Creutzfeldt-Jakob disease (sCJD) causes rapidly-progressive dementia and complex abnormalities of motor systems with striking phenotypic heterogeneity, but no tools are available for the clinician to determine disease severity from bedside cognitive and neurological assessments. We used a robust statistical methodology and routinely-collected examination data to develop and validate short clinical rating scales quantifying longitudinal motor and cognitive dysfunction in sCJD.MethodsWe undertook a retrospective analysis of clinical examination data from the prospective National Prion Monitoring Cohort study, October 2008 – December 2016. Rasch analysis was used to iteratively construct interval scales measuring composite cognitive and motor dysfunction from pooled bedside neurological and cognitive examination tests.A longitudinal clinical examination dataset was constructed from a total of 528 patients with sCJD, comprising 1030 Motor Scale and 757 Cognitive Scale scores, over 130 patient-years of study, and used to demonstrate scale utility.ResultsThe Rasch-derived Motor Scale consists of 8 items, including examination items reliant on pyramidal, extrapyramidal and cerebellar systems. The Cognitive Scale comprises 6 items, and includes measures of executive function, language, visual perception and memory. Both scales are unidimensional, perform consistently regardless of age or gender and have excellent inter-rater reliability. Each scale can be completed in a few minutes at the bedside, as part of a normal neurocognitive examination. Several uses of the scales, in measuring longitudinal change, prognosis, and phenotypic heterogeneity are illustrated.InterpretationThese two novel scales measuring motor and cognitive dysfunction in sCJD should prove useful to objectively measure phenotypic and clinical change in future clinical trials and for patient stratification. This statistical approach can help to overcome obstacles to assessing clinical change in rapidly-progressive, multisystem conditions with limited longitudinal follow-up.

The clinical courses of multiple sclerosis were defined in 1996 and refined in 2013 to provide a time-based assessment of the current status of the individual. These definitions have been successfully used by clinicians, clinical trialists, and regulatory authorities. Recent regulatory decisions produced variations and discrepancies in the use of the clinical course descriptions. We provide here a clarification of the concepts underlying these descriptions and restate the principles used in their development. Importantly, we highlight the critical importance of time framing the disease course modifiers activity and progression and clarify the difference between the terms worsening and progressing.

Structural network-based approaches can assess white matter connections revealing topological alterations in multiple sclerosis (MS). However, principal network (PN) organisation and its clinical relevance in MS has not been explored yet. Here, structural networks were reconstructed from diffusion data in 58 relapsing-remitting MS (RRMS), 28 primary progressive MS (PPMS), 36 secondary progressive (SPMS) and 51 healthy controls (HCs). Network hubs’ strengths were compared with HCs. Then, PN analysis was performed in each clinical subtype. Regression analysis was applied to investigate the associations between nodal strength derived from the first and second PNs (PN1 and PN2) in MS, with clinical disability. Compared with HCs, MS patients had preserved hub number, but some hubs exhibited reduced strength. PN1 comprised 10 hubs in HCs, RRMS and PPMS but did not include the right thalamus in SPMS. PN2 comprised 10 hub regions with intra-hemispheric connections in HCs. In MS, this subnetwork did not include the right putamen whilst in SPMS the right thalamus was also not included. Decreased nodal strength of the right thalamus and putamen from the PNs correlated strongly with higher clinical disability. These PN analyses suggest distinct patterns of disruptions in MS subtypes which are clinically relevant

Multiple sclerosis (MS) is subdivided into four phenotypes on the basis of medical history and clinical symptoms. These phenotypes are defined retrospectively and lack clear pathobiological underpinning. Since Magnetic Resonance Imaging (MRI) better reflects disease pathology than clinical symptoms, we aimed to explore MRI-driven subtypes of MS based on pathological changes visible on MRI using unsupervised machine learning. In separate train and external validation sets we looked at a total of 21,170 patient-years of data from 15 randomised controlled trials and three observational cohorts to explore MRI-driven subtypes and test whether these subtypes had differential clinical outcomes. We processed MRI data to obtain measures of brain volumes, lesion volumes, and normal appearing white matter T1/T2. We identified three MRI-driven subtypes who were similar in how they accumulated MRI abnormality. Based on the earliest abnormalities suggested by our model they were called: cortex-led, normal appearing white matter-led, and lesion-led subtypes. In the external validation datasets, the lesion-led subtype showed a faster disability progression and higher disease activity than the cortex-led subtype. In all datasets, MRI-driven subtypes were associated with disability progression (βSubtype=0.04, p=0.02; βStage=-0.06, p

The 2010 McDonald criteria for the diagnosis of multiple sclerosis are widely used in research and clinical practice. Scientific advances in the past 7 years suggest that they might no longer provide the most up-to-date guidance for clinicians and researchers. The International Panel on Diagnosis of Multiple Sclerosis reviewed the 2010 McDonald criteria and recommended revisions. The 2017 McDonald criteria continue to apply primarily to patients experiencing a typical clinically isolated syndrome, define what is needed to fulfil dissemination in time and space of lesions in the CNS, and stress the need for no better explanation for the presentation. The following changes were made: in patients with a typical clinically isolated syndrome and clinical or MRI demonstration of dissemination in space, the presence of CSF-specific oligoclonal bands allows a diagnosis of multiple sclerosis; symptomatic lesions can be used to demonstrate dissemination in space or time in patients with supratentorial, infratentorial, or spinal cord syndrome; and cortical lesions can be used to demonstrate dissemination in space. Research to further refine the criteria should focus on optic nerve involvement, validation in diverse populations, and incorporation of advanced imaging, neurophysiological, and body fluid markers.

Multiple sclerosis continues to be a challenging and disabling condition but there is now greater understanding of the underlying genetic and environmental factors that drive the condition, including low vitamin D levels, cigarette smoking, and obesity. Early and accurate diagnosis is crucial and is supported by diagnostic criteria, incorporating imaging and spinal fluid abnormalities for those presenting with a clinically isolated syndrome. Importantly, there is an extensive therapeutic armamentarium, both oral and by infusion, for those with the relapsing remitting form of the disease. Careful consideration is required when choosing the correct treatment, balancing the side-effect profile with efficacy and escalating as clinically appropriate. This move towards more personalised medicine is supported by a clinical guideline published in 2018. Finally, a comprehensive management programme is strongly recommended for all patients with multiple sclerosis, enhancing health-related quality of life through advocating wellness, addressing aggravating factors, and managing comorbidities. The greatest remaining challenge for multiple sclerosis is the development of treatments incorporating neuroprotection and remyelination to treat and ultimately prevent the disabling, progressive forms of the condition.

The new material developments in the field of thermoelectrics over the past two decades have resulted in new materials with unique transport properties as well as new synthetic approaches. Enhanced thermoelectric properties of these new materials through thermal conductivity reduction and electrical properties enhancement strategies such as nano-structuring and band engineering have also been reported. Nevertheless, the material system upon which all new thermoelectric material developments are compared with continues to be alloys of Bi2Te3. Approaches for thermoelectric property enhancements for Bi2Te3 alloys have also been undertaken, however, oriented polycrystalline materials continue to be of primary interest for thermoelectric device development. To this end we investigate n and p-type Bi2Te3 alloys provided by II-VI Inc. in order to elucidate the texturing in these materials and their transport properties with texturing. These materials are highly textured, as required in order to maximize the thermoelectric properties, with an 80% enhancement of the thermoelectric properties obtained with texturing.

Summary Exercise can be a beneficial rehabilitation strategy for people with multiple sclerosis to manage symptoms, restore function, optimise quality of life, promote wellness, and boost participation in activities of daily living. However, this population typically engages in low levels of health-promoting physical activity compared with adults from the general population, a fact which has not changed in the past 25 years despite growing evidence of the benefits of exercise. To overcome this challenge, the main limitations to promoting exercise through the patient–clinician interaction must be addressed. These limitations are the inadequate quality and scope of existing evidence, incomplete understanding of the mechanisms underlying the beneficial effects of exercise in people with multiple sclerosis, and the absence of a conceptual framework and toolkit for translating the evidence into practice. Future research to address those limitations will be essential to inform decisions about the inclusion of exercise in the clinical care of people with multiple sclerosis.

Introduction: In order to estimate the value of interventions in multiple sclerosis (MS) – where lifetime costs and outcomes cannot be observed – outcome data have to be combined with costs. This requires that cost data be regularly updated. Objectives and methods: This study is part of a cross-sectional retrospective study in 16 countries collecting data on resource consumption and work capacity, health-related quality of life (HRQoL) and prevalent symptoms for patients with MS. Descriptive analyses are presented by level of disability, from the societal perspective, in EUR (2015). Results: A total of 779 patients (mean age = 57 years) participated; 72% were below retirement age and of these, 36% were employed. Employment was related to disease severity, and MS affected productivity at work for 84% of patients. Overall, 96% and 72% of the patients experienced fatigue and cognition as a problem. Mean utility and annual costs were 0.735 and 11,400GBP at Expanded Disability Status Scale (EDSS) = 0–3, 0.534 and 22,700GBP at EDSS = 4–6.5, and 0.135 and 36,500GBP at EDSS = 7–9. The mean cost of a relapse was estimated at 790GBP. Conclusion: This study illustrates the burden of MS on UK patients and provides current data on MS that are important for development of health policies.

Multiple sclerosis is a major cause of neurological disability, which accrues predominantly during progressive forms of the disease. Although development of multifocal inflammatory lesions is the underlying pathological process in relapsing-remitting multiple sclerosis, the gradual accumulation of disability that characterises progressive multiple sclerosis seems to result more from diffuse immune mechanisms and neurodegeneration. As a result, the 14 anti-inflammatory drugs that have regulatory approval for treatment of relapsing-remitting multiple sclerosis have little or no efficacy in progressive multiple sclerosis without inflammatory lesion activity. Effective therapies for progressive multiple sclerosis that prevent worsening, reverse damage, and restore function are a major unmet need. In this Series paper we summarise the current status of therapy for progressive multiple sclerosis and outline prospects for the future.