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Relapses (episodic exacerbations of neurological signs or symptoms) are a defining feature of relapsing-remitting multiple sclerosis (MS), the most prevalent MS phenotype. While their diagnostic value relates predominantly to the definition of clinically definite MS, their prognostic value is determined by their relatively high associated risk of incomplete remission resulting in residual disability. The mechanisms governing a relapse incidence are unknown, but numerous modifiers of relapse risk have been described, including demographic and clinical characteristics, many of which represent opportunities for improved disease management. Also relapse phenotypes have been associated with patient and disease characteristics and an individual predisposition to certain phenotypic presentations may imply individual neuroanatomical disease patterns. While immunomodulatory therapies and corticosteroids represent the mainstay of relapse prevention and acute management, respectively, their effect has only been partial and further search for more efficient relapse therapies is warranted. Other areas of research include pathophysiology and determinants of relapse incidence, recurrence and phenotypes, including the characteristics of the relapsing and non-relapsing multiple sclerosis variants and their responsiveness to therapies.

B cell-depleting agents are emerging as important disease-modifying drugs for multiple sclerosis, but their effectiveness in relation to established treatments remains uncertain. To cast light on this issue, several studies have provided head-to-head comparisons of the anti-CD20 antibody rituximab with natalizumab, fingolimod and dimethyl fumarate in patients with multiple sclerosis.

BackgroundThe ASCEND trial did not find benefit of natalizumab during secondary progressive multiple sclerosis compared with placebo; however, its open-label extension suggests this may be obscured by therapeutic lag.We aimed to compare the efficacy of natalizumab and interferon β-1a in slowing disease progression in secondary progressive multiple sclerosis after accounting for therapeutic lag.MethodsWe analysed pooled data from the ASCEND (natalizumab vs placebo) and SPECTRIMS (interferon β-1a vs placebo) trials. Cumulative hazards of 6-month confirmed disability progression during secondary progressive multiple sclerosis were compared using Cox proportional hazards models adjusted for confounding variables. We accounted for therapeutic lag in each patient based on baseline expanded disability status scale, annualised relapse rate and sex. Differences between SPECTRIMS and ASCEND placebo arms were used to adjust the differences between interferon β-1a and natalizumab arms.ResultsBaseline characteristics of 1156 patients were similar between SPECTRIMS and ASCEND cohorts, except for a higher proportion of older patients and lower relapse rates in the ASCEND trial. Natalizumab exhibited a lower cumulative hazard of disability progression compared with interferon β-1a (HR 0.15, 95% CI 0.08 to 0.29, p<0.0001). After adjusting for the difference in cumulative hazards between placebo groups (HR 0.36, 95% CI 0.20 to 0.63, p=0.0004), natalizumab remained associated with a lower hazard of disability progression compared with interferon β-1a (HR 0.42, 95% CI 0.22 to 0.77, p=0.0016).ConclusionAfter accounting for therapeutic lag and differences between ASCEND and SPECTRIMS trials, natalizumab, compared with interferon β-1a, reduces disability progression during secondary progressive multiple sclerosis.

The complexity of multiple sclerosis (MS) treatment means that doctors and decision-makers need the best available evidence to make the best decisions for patient care. Randomized controlled trials (RCTs) are accepted as the gold standard for assessing the efficacy and safety of any new drug, but conclusions of these trials do not always aid in daily decision-making processes. Indeed, RCTs are usually conducted in ideal conditions, so can measure efficacy only in restricted and unrepresentative populations. In the past decade, a growing number of MS databases and registries have started to produce long-term outcome data from large cohorts of patients with MS treated with disease-modifying therapies in real-world settings. Such observational studies are addressing issues that are otherwise difficult or impossible to study. In this Review, we focus on the most recently published observational studies designed to identify predictors of poor outcome and treatment response or failure, and to evaluate the relative and long-term effectiveness of currently used MS treatments. We also outline the statistical approaches that are most commonly used to reduce bias and limitations in these studies, and the challenges associated with the use of 'big MS data' to facilitate the implementation of personalized medicine in MS.

Background: Using the local divergence exponent (LDE), it has been concluded that walking stability is impaired in people with multiple sclerosis (pwMS). However, the use of several calculation approaches hinders comparisons across studies. We aimed to determine whether using different parameters for state space reconstruction to calculate LDE affects the classification of pwMS. Methods: A total of 55 pwMS and 23 controls walked up and down a 20 m corridor for 5 min. The LDE was calculated using three different combinations of n-dimensions (dE) and time delays (τ): (a) trial-specific, (b) median across subjects, and (c) fixed dE = 5 and τ = 10. The LDE was calculated using vertical (VT), mediolateral (ML), and anteroposterior (AP) accelerations, the norm (N), and 3D data from sensors placed on the sternum and lumbar. Classification accuracy across results obtained with different parameter combinations was compared using a Quadratic Discriminant Analysis (QDA). Results: The best classification accuracy, 84%, was achieved when using the LDE obtained with norm acceleration data from the sternum sensor with a fixed dE = 5 and τ = 10 and considering speed as a covariate. Lumbar LDEs were less accurate than sternum LDEs. Conclusions: LDEs calculated with a fixed dE = 5 and τ = 10 for the norm acceleration from a sternum-placed sensor can best classify pwMS. Using fixed parameters for the state space reconstruction, and consequently LDE calculation, can simplify the implementation of the LDE as a mobility biomarker in MS and provides evidence for future consensus for its calculation.

To compare clinical and MRI parameters between patients with clinically isolated syndrome and those converting to clinically definite multiple sclerosis within 2 years, to identify volumetric MRI predictors of this conversion and to assess effect of early relapses. The SET study comprised 220 patients with clinically isolated syndrome treated with interferon beta (mean age, 29 years; Expanded Disability Status Scale, 1.5). Three patients with missing data were excluded from the analysis. Physical disability, time to clinically definite multiple sclerosis and volumetric MRI data were recorded for 2 years. Patients reaching clinically definite multiple sclerosis showed impaired recovery of neurological function, faster decrease in corpus callosum cross-sectional area, higher T2 lesion volume and more contrast-enhancing lesions. Six-month decrease in corpus callosum cross-sectional area (≥ 1%) and baseline T2 lesion volume (≥ 5 cm(3)) predicted clinically definite multiple sclerosis within 2 years (hazard ratios 2.5 and 1.8, respectively). Of 22 patients fulfilling both predictive criteria, 83% reached clinically definite multiple sclerosis (hazard ratio 6.5). More relapses were associated with poorer recovery of neurological function and accelerated brain atrophy. Neurological impairment is more permanent, brain atrophy is accelerated and focal inflammatory activity is greater in patients converting to clinically definite multiple sclerosis. Six-month corpus callosum atrophy and baseline T2 lesion volume jointly help predict individual risk of clinically definite multiple sclerosis. Early relapses contribute to permanent damage of the central nervous system.

Alemtuzumab, an anti-CD52 antibody, is proven to be more efficacious than interferon beta-1a in the treatment of relapsing-remitting multiple sclerosis, but its efficacy relative to more potent immunotherapies is unknown. We compared the effectiveness of alemtuzumab with natalizumab, fingolimod, and interferon beta in patients with relapsing-remitting multiple sclerosis treated for up to 5 years. In this international cohort study, we used data from propensity-matched patients with relapsing-remitting multiple sclerosis from the MSBase and six other cohorts. Longitudinal clinical data were obtained from 71 MSBase centres in 21 countries and from six non-MSBase centres in the UK and Germany between Nov 1, 2015, and June 30, 2016. Key inclusion criteria were a diagnosis of definite relapsing-remitting multiple sclerosis, exposure to one of the study therapies (alemtuzumab, interferon beta, fingolimod, or natalizumab), age 65 years or younger, Expanded Disability Status Scale (EDSS) score 6·5 or lower, and no more than 10 years since the first multiple sclerosis symptom. The primary endpoint was annualised relapse rate. The secondary endpoints were cumulative hazards of relapses, disability accumulation, and disability improvement events. We compared relapse rates with negative binomial models, and estimated cumulative hazards with conditional proportional hazards models. Patients were treated between Aug 1, 1994, and June 30, 2016. The cohorts consisted of 189 patients given alemtuzumab, 2155 patients given interferon beta, 828 patients given fingolimod, and 1160 patients given natalizumab. Alemtuzumab was associated with a lower annualised relapse rate than interferon beta (0·19 [95% CI 0·14–0·23] vs 0·53 [0·46–0·61], p<0·0001) and fingolimod (0·15 [0·10–0·20] vs 0·34 [0·26–0·41], p<0·0001), and was associated with a similar annualised relapse rate as natalizumab (0·20 [0·14–0·26] vs 0·19 [0·15–0·23], p=0·78). For the disability outcomes, alemtuzumab was associated with similar probabilities of disability accumulation as interferon beta (hazard ratio [HR] 0·66 [95% CI 0·36–1·22], p=0·37), fingolimod (1·27 [0·60–2·70], p=0·67), and natalizumab (0·81 [0·47–1·39], p=0·60). Alemtuzumab was associated with similar probabilities of disability improvement as interferon beta (0·98 [0·65–1·49], p=0·93) and fingolimod (0·50 [0·25–1·01], p=0·18), and a lower probability of disability improvement than natalizumab (0·35 [0·20–0·59], p=0·0006). Alemtuzumab and natalizumab seem to have similar effects on annualised relapse rates in relapsing-remitting multiple sclerosis. Alemtuzumab seems superior to fingolimod and interferon beta in mitigating relapse activity. Natalizumab seems superior to alemtuzumab in enabling recovery from disability. Both natalizumab and alemtuzumab seem highly effective and viable immunotherapies for multiple sclerosis. Treatment decisions between alemtuzumab and natalizumab should be primarily governed by their safety profiles. National Health and Medical Research Council, and the University of Melbourne.

Chimeric antigen receptor T-cell (CAR-T) therapy has become an established treatment for several haematological malignancies in relapse and is being evaluated for new indications. An important clinical challenge associated with the use of CAR-T therapy, however, is the common development of neurotoxicity. Different neurotoxicity syndromes have been reported. The best-known form of CAR-T neurotoxicity is immune effector cell-associated neurotoxicity syndrome, which can be associated with various findings on magnetic resonance imaging (MRI), including cerebral oedema and leptomeningeal enhancement. Other manifestations of neurotoxicity include movement disorders, myelopathy, cranial nerve palsies and ischaemic strokes. MRI plays a key role in the diagnosis and management of patients with suspected neurotoxicity. It can be used to support the diagnosis, exclude differential diagnoses and forms part of the grading of neurotoxicity. Other roles for MRI after CAR-T therapy include assessment of potential longer-term effects of therapy and neurotoxicity, and the evaluation of patients with emerging indications for CAR-T therapy. We recommend performing a baseline MRI brain prior to CAR-T therapy where feasible, as this greatly aids in the interpretation of neuroimaging findings. Here, we discuss the established and potential roles of neuroimaging in the context of neurotoxicity secondary to CAR-T therapy. Neuroimaging in CAR-T neurotoxicity Chimeric antigen receptor T-cell therapy is a promising treatment for some cancers and autoimmune disorders, but side effects affecting the brain and spinal cord are a common challenge. Imaging, in particular Magnetic Resonance Imaging (MRI), plays a key role in the care of these patients. This review discusses the established and potential roles of imaging in this context, including assisting with the diagnosis, assessing severity, excluding alternate possibilities and evaluating for possible longer-term effects of treatment.

PurposeA circulating biomarker has potential to provide more accurate information for glioma progression post treatment, however no such biomarker is currently available. We aimed to discover a microRNA serum biomarker for longitudinal monitoring of glioma patients.MethodsA prospectively collected cohort of 91 glioma patients and 17 healthy controls underwent pre and post-operative serum miRNA profiling using Nanostring®. Differentially expressed miRNAs were discovered using a machine learning random forest analysis. Candidate miRNAs were then assessed by droplet digital PCR in 11 patients with multiple follow up samples and compared to tumor volume based on magnetic resonance imaging.ResultsA 9-gene miRNA signature was identified that could distinguish between glioma and healthy controls with 99.8% accuracy. Two miRNAs miR-223 and miR-320e, best demonstrated dynamic changes that correlated closely with tumor volume in LGG and GBM respectively. Importantly, miRNA levels did not increase in two cases of pseudo-progression, indicating the potential utility of this test in guiding treatment decisions.ConclusionsWe identified a highly accurate 9-miRNA signature associated with glioma serum. Additionally, we observed dynamic changes in specific miRNAs correlating with tumor volume over long-term follow up. These results support a large prospective validation study of serum miRNA biomarkers in glioma.

Postural impairment in people with multiple sclerosis (pwMS) is an early indicator of disease progression. Common measures of disease assessment are not sensitive to early-stage MS. Sample entropy (SE) may better identify early impairments. We compared the sensitivity and specificity of SE with linear measurements, differentiating pwMS (EDSS 0–4) from healthy controls (HC). 58 pwMS (EDSS ≤ 4) and 23 HC performed quiet standing tasks, combining a hard or foam surface with eyes open or eyes closed as a condition. Sway was recorded at the sternum and lumbar spine. Linear measures, mediolateral acceleration range with eyes open, mediolateral jerk with eyes closed, and SE in the anteroposterior and mediolateral directions were calculated. A multivariate ANOVA and AUC-ROC were used to determine between-groups differences and discriminative ability, respectively. Mild MS (EDSS ≤ 2.0) discriminability was secondarily assessed. Significantly lower SE was observed under most conditions in pwMS compared to HC, except for lumbar and sternum SE when on a hard surface with eyes closed and in the anteroposterior direction, which also offered the strongest discriminability (AUC = 0.747), even for mild MS. Overall, between-groups differences were task-dependent, and SE (anteroposterior, hard surface, eyes closed) was the best pwMS classifier. SE may prove a useful tool to detect subtle MS progression and intervention effectiveness.