Teriflunomide in pediatric patients with relapsing multiple sclerosis: Open-label extension of TERIKIDS.

BACKGROUND: The double-blind TERIKIDS study demonstrated the efficacy and safety of teriflunomide. OBJECTIVE: To evaluate the efficacy, safety, and tolerability of continuous teriflunomide treatment in the TERIKIDS open-label extension. METHODS: In the double-blind period, children with relapsing MS were randomized to placebo or teriflunomide (14 mg adult-equivalent dose) for ⩽ 96 weeks. Participants received teriflunomide for ⩽ 192 weeks post-randomization in the open-label extension. RESULTS: The mean age at screening was 14.6 years. For teriflunomide/teriflunomide versus placebo/teriflunomide, estimated clinical relapse risk was reduced by 38% (hazard ratio (HR) 0.62; 95% confidence interval (CI) 0.39-0.98; p = 0.11) and numbers of gadolinium-enhancing T1 and new/enlarging T2 lesions were reduced by 43% (relative risk (RR) 0.570; 95% CI 0.33-0.98; p = 0.043) and 49% (RR 0.511; 95% CI 0.34-0.76; p = 0.001), respectively, in the combined double-blind and open-label periods. There was a trend toward reduced risk of 24-week sustained disability progression for teriflunomide/teriflunomide versus placebo/teriflunomide (HR 0.47; 95% CI 0.23-0.96). During the open-label extension, incidences of safety-related discontinuations were 4.0% (teriflunomide/teriflunomide) and 13.5% (placebo/teriflunomide), including two children who developed pancreatitis in the teriflunomide/teriflunomide group. CONCLUSION: Teriflunomide reduced the long-term risk of focal inflammatory activity, with generally manageable tolerability and no new safety signals. Further evidence would strengthen clinical efficacy findings.ClinicalTrials.gov: NCT02201108.

Efficacy and safety results after >3.5 years of treatment with the Bruton's tyrosine kinase inhibitor evobrutinib in relapsing multiple sclerosis: Long-term follow-up of a Phase II randomised clinical trial with a cerebrospinal fluid sub-study.

BACKGROUND: Evobrutinib - an oral, central nervous system (CNS)-penetrant, and highly selective Bruton's tyrosine kinase inhibitor - has shown efficacy in a 48-week, double-blind, Phase II trial in patients with relapsing MS. OBJECTIVE: Report results of the Phase II open-label extension (OLE; up to week 192 from randomisation) and a cerebrospinal fluid (CSF) sub-study. METHODS: In the 48-week double-blind period (DBP), patients received evobrutinib 25 mg once-daily, 75 mg once-daily, 75 mg twice-daily or placebo (switched to evobrutinib 25 mg once-daily after week 24). Patients could then enter the OLE, receiving evobrutinib 75 mg once-daily (mean (± standard deviation (SD)) duration = 50.6 weeks (±6.0)) before switching to 75 mg twice-daily. RESULTS: Of 164 evobrutinib-treated patients who entered the OLE, 128 (78.0%) completed ⩾192 weeks of treatment. Patients receiving DBP evobrutinib 75 mg twice-daily: annualised relapse rate at week 48 (0.11 (95% confidence interval (CI) = 0.04-0.25)) was maintained with the OLE twice-daily dose up to week 192 (0.11 (0.05-0.22)); Expanded Disability Status Scale score remained stable; serum neurofilament light chain fell to levels like a non-MS population (Z-scores); T1 gadolinium-enhancing lesion numbers remained low. No new safety signals were identified. In the OLE, evobrutinib was detected in the CSF of all sub-study patients. CONCLUSION: Long-term evobrutinib treatment was well tolerated and associated with a sustained low level of disease activity. Evobrutinib was present in CSF at concentrations similar to plasma.

Epstein-Barr Virus Strongly Associates With Pediatric Multiple Sclerosis, But Not Myelin Oligodendrocyte Glycoprotein-Antibody-Associated Disease.

Reported rates of Epstein-Barr virus (EBV) seropositivity in children meeting multiple sclerosis (MS) diagnostic criteria are considerably lower than those reported in adult-onset MS, putting in question a requisite role for EBV in MS development. As prior work preceded recognition of myelin oligodendrocyte glycoprotein-associated disease (MOGAD), we assessed viral serologies in 251 children with incident demyelination and prospectively ascertained diagnoses. When MOGAD was serologically accounted for, the prevalence of EBV infection among MS children exceeded 90%, whereas remote EBV infection was not associated with MOGAD risk. Together, these findings substantiate EBV's role across the MS spectrum, and support distinct pathobiological mechanisms in MS versus MOGAD. ANN NEUROL 2024;95:700-705.

Effect of Evobrutinib on Slowly Expanding Lesion Volume in Relapsing Multiple Sclerosis: A Post Hoc Analysis of a Phase 2 Trial.

BACKGROUND AND OBJECTIVES: Chronic active lesions (CALs) are demyelinated multiple sclerosis (MS) lesions with ongoing microglia/macrophage activity, resulting in irreversible neuronal damage and axonal loss. Evobrutinib is a highly selective, covalent, CNS-penetrant, Bruton tyrosine kinase inhibitor. This post hoc analysis evaluated the effect of evobrutinib on slowly expanding lesion (SEL) volume, an MRI marker of CALs, assessed baseline-week 48 in a phase 2, double-blind, randomized trial (NCT02975349) in relapsing MS (RMS). METHODS: In the 48-week, double-blind trial, adult patients received evobrutinib (25 mg once daily [QD], 75 mg QD, or 75 mg twice daily [BID]), placebo (switched to evobrutinib 25 mg QD after week 24), or open-label dimethyl fumarate (DMF) 240 mg BID. SELs were defined as slowly and consistently radially expanding areas of preexisting T2 lesions of ≥10 contiguous voxels (∼30 mm3) over time. SELs were identified by MRI and assessed by the Jacobian determinant of the nonlinear deformation from baseline to week 48. SEL volume analysis, stratified by baseline T2 lesion volume tertiles, was based on week 48/end-of-treatment status (completers/non-completers). Treatment effect was analyzed using the stratified Hodges-Lehmann estimate of shift in distribution and stratified Wilcoxon rank-sum test. Comparisons of evobrutinib and DMF vs placebo/evobrutinib 25 mg QD were made. Subgroup analyses used pooled treatment groups (evobrutinib high dose [75 mg QD/BID] vs low dose [placebo/evobrutinib 25 mg QD]). RESULTS: The SEL analysis set included 223 patients (mean [SD] age: 42.4 [10.7] years; 69.3% female; 87.4% relapsing/remitting MS). Mean (SD) SEL volume was 2,099 (2,981.0) mm3 with evobrutinib 75 mg BID vs 2,681 (3,624.2) mm3 with placebo/evobrutinib 25 mg QD. Median number of SELs/patient ranged from 7 to 11 across treatments. SEL volume decreased with increasing evobrutinib dose vs placebo/evobrutinib 25 mg QD, and no difference with DMF vs placebo/evobrutinib 25 mg QD was noted. SEL volume significantly decreased with evobrutinib 75 mg BID vs placebo/evobrutinib 25 mg QD (-474.5 mm3 [-1,098.0 to -3.0], p = 0.047) and vs DMF (-711.6 [-1,290.0 to -149.0], p = 0.011). SEL volume was significantly reduced for evobrutinib high vs low dose within baseline Expanded Disability Status Scale ≥3.5 and longer disease duration (≥8.5 years) subgroups. DISCUSSION: Evobrutinib reduced SEL volume in a dose-dependent manner in RMS, with a significant reduction with evobrutinib 75 mg BID. This is evident that evobrutinib affects brain lesions associated with chronic inflammation and tissue loss. TRIAL REGISTRATION INFORMATION: ClinicalTrials.gov number: NCT02975349. Submitted to ClinicalTrials.gov on November 29, 2016. First patient enrolled: March 7, 2017. CLASSIFICATION OF EVIDENCE: This study provides Class II evidence that evobrutinib reduces the volume of SELs assessed on MRI comparing baseline with week 48, in patients with RMS.

Brain volume increase after discontinuing natalizumab therapy: Evidence for reversible pseudoatrophy.

BACKGROUND: The phenomenon of pseudoatropy after initiation of anti-inflammatory therapy is believed to be reversible, but a rebound in brain volume following cessation of highly-effective therapy has not been reported. OBJECTIVES: To evaluate brain volume change in a treatment interruption study (RESTORE) in which relapsing-remitting multiple sclerosis (RRMS) patients were randomized to switch from natalizumab to placebo, from natalizumab to once-monthly intravenous methylprednisolone (IVMP), or to remain on natalizumab. METHODS: T2 lesion volume (T2LV), baseline normalized brain volumes, and follow-up percent brain volume changes (PBVC) were calculated. Approximate T2 relaxation-time (pT2) was calculated within the brain mask and the T2 lesions to estimate changes in water content. Linear mixed effects models were used to detect differences in T2LV, pT2 in whole brain, pT2 in T2-weighted lesions, and PBVC among the placebo, natalizumab, and IVMP groups. We also estimated contributions of T2LV and pT2 (in whole brain and T2 lesions) to PBVC. RESULTS: T2LV increased in the placebo group (by 0.66 ml/year, p<0.0001) and IVMP (+1.98 ml/year, p = 0.05) groups relative to the natalizumab group. The rates of PBVC were significantly different: -0.239%/year with continued natalizumab and +0.126 %/year after switch to placebo (p = 0.03), while the IVMP group showed brain volume loss (-0.74 %/ year, p = 0.08). pT2 was not statistically different between the groups (p ≥ 0.29) and did not have significant effects on PBVC (p ≥ 0.25). CONCLUSION: The increase in the brain volume in patients witching from natalizumab to placebo is consistent with reversal of so-called pseudoatrophy after starting natalizumab.

A cross-sectional study of MRI features and the gut microbiome in pediatric-onset multiple sclerosis.

OBJECTIVE: To identify gut microbiome features associated with MRI lesion burden in persons with pediatric-onset multiple sclerosis (symptom onset <18 years). METHODS: A cross-sectional study involving the Canadian Paediatric Demyelinating Disease Network study participants. Gut microbiome features (alpha diversity, phylum- and genus-level taxa) were derived using 16S rRNA sequencing from stool samples. T1- and T2-weighted lesion volumes were measured on brain MRI obtained within 6 months of stool sample procurement. Associations between the gut microbiota and MRI metrics (cube-root-transformed) were assessed using standard and Lasso regression models. RESULTS: Thirty-four participants were included; mean ages at symptom onset and MRI were 15.1 and 19.0 years, respectively, and 79% were female. The T1- and T2-weighted lesion volumes were not significantly associated with alpha diversity (age and sex-adjusted p > 0.08). At the phylum level, high Tenericutes (relative abundance) was associated with higher T1 and T2 volumes (ß coefficient = 0.25, 0.37) and high Firmicutes, Patescibacteria or Actinobacteria with lower lesion volumes (ß coefficient = -0.30 to -0.07). At the genus level, high Ruminiclostridium, whereas low Coprococcus 3 and low Erysipelatoclostridium were associated with higher lesion volumes. INTERPRETATION: Our study characterized the gut microbiota features associated with MRI lesion burden in pediatric-onset MS, shedding light onto possible pathophysiological mechanisms.

Deep learning, data ramping, and uncertainty estimation for detecting artifacts in large, imbalanced databases of MRI images.

Magnetic resonance imaging (MRI) is increasingly being used to delineate morphological changes underlying neurological disorders. Successfully detecting these changes depends on the MRI data quality. Unfortunately, image artifacts frequently compromise the MRI utility, making it critical to screen the data. Currently, quality assessment requires visual inspection, a time-consuming process that suffers from inter-rater variability. Automated methods to detect MRI artifacts could improve the efficiency of the process. Such automated methods have achieved high accuracy using small datasets, with balanced proportions of MRI data with and without artifacts. With the current trend towards big data in neuroimaging, there is a need for automated methods that achieve accurate detection in large and imbalanced datasets. Deep learning (DL) is the ideal MRI artifact detection algorithm for large neuroimaging databases. However, the inference generated by DL does not commonly include a measure of uncertainty. Here, we present the first stochastic DL algorithm to generate automated, high-performing MRI artifact detection implemented on a large and imbalanced neuroimaging database. We implemented Monte Carlo dropout in a 3D AlexNet to generate probabilities and epistemic uncertainties. We then developed a method to handle class imbalance, namely data-ramping to transfer the learning by extending the dataset size and the proportion of the artifact-free data instances. We used a 34,800 scans (98% clean) dataset. At baseline, we obtained 89.3% testing accuracy (F1 = 0.230). Following the transfer learning (with data-ramping), we obtained 94.9% testing accuracy (F1 = 0.357) outperforming focal cross-entropy (92.9% testing accuracy, F1 = 0.304) incorporated for comparison at handling class imbalance. By implementing epistemic uncertainties, we improved the testing accuracy to 99.5% (F1 = 0.834), outperforming the results obtained in previous comparable studies. In addition, we estimated aleatoric uncertainties by incorporating random flips to the MRI volumes, and demonstrated that aleatoric uncertainty can be implemented as part of the pipeline. The methods we introduce enhance the efficiency of managing large databases and the exclusion of artifact images from big data analyses.

Diroximel fumarate in patients with relapsing-remitting multiple sclerosis: Final safety and efficacy results from the phase 3 EVOLVE-MS-1 study.

BACKGROUND: Diroximel fumarate (DRF) is approved for adults with relapsing-remitting multiple sclerosis (RRMS) in Europe and for relapsing forms of MS in the United States. DRF and dimethyl fumarate (DMF) yield bioequivalent exposure of the active metabolite monomethyl fumarate. Prior studies indicated fewer gastrointestinal (GI)-related adverse events (AEs) with DRF compared with DMF. OBJECTIVE: To report final outcomes from EVOLVE-MS-1. METHODS: EVOLVE-MS-1 was an open-label, 96-week, phase 3 study assessing DRF safety, tolerability, and efficacy in patients with RRMS. The primary endpoint was safety and tolerability; efficacy endpoints were exploratory. RESULTS: Overall, 75.7% (800/1057) of patients completed the study; median exposure was 1.8 (range: 0.0-2.0) years. AEs occurred in 938 (88.7%) patients, mostly of mild (28.9%) or moderate (50.3%) severity. DRF was discontinued due to AEs in 85 (8.0%) patients, with < 2% discontinuing due to GI or flushing/flushing-related AEs. At Week 96, mean number of gadolinium-enhancing lesions was significantly reduced from baseline (72.7%; p < 0.0001); adjusted annualized relapse rate was 0.13 (95% confidence interval: 0.11-0.15). CONCLUSION: DRF was generally well tolerated over 2 years, with few discontinuations due to AEs; radiological measures indicated decreased disease activity from baseline. These outcomes support DRF as a treatment option in patients with RRMS.

Assessing the utility of magnetic resonance imaging-based "SuStaIn" disease subtyping for precision medicine in relapsing-remitting and secondary progressive multiple sclerosis.

BACKGROUND: Patient stratification and individualized treatment decisions based on multiple sclerosis (MS) clinical phenotypes are arbitrary. Subtype and Staging Inference (SuStaIn), a published machine learning algorithm, was developed to identify data-driven disease subtypes with distinct temporal progression patterns using brain magnetic resonance imaging; its clinical utility has not been assessed. The objective of this study was to explore the prognostic capability of SuStaIn subtyping and whether it is a useful personalized predictor of treatment effects of natalizumab and dimethyl fumarate. METHODS: Subtypes were available from the trained SuStaIn model for 3 phase 3 clinical trials in relapsing-remitting and secondary progressive MS. Regression models were used to determine whether baseline SuStaIn subtypes could predict on-study clinical and radiological disease activity and progression. Differences in treatment responses relative to placebo between subtypes were determined using interaction terms between treatment and subtype. RESULTS: Natalizumab and dimethyl fumarate reduced inflammatory disease activity in all SuStaIn subtypes (all p < 0.001). SuStaIn MS subtyping alone did not discriminate responder heterogeneity based on new lesion formation and disease progression (p > 0.05 across subtypes). CONCLUSION: SuStaIn subtypes correlated with disease severity and functional impairment at baseline but were not predictive of disability progression and could not discriminate treatment response heterogeneity.

Networks of microstructural damage predict disability in multiple sclerosis.

BACKGROUND: Network-based measures are emerging MRI markers in multiple sclerosis (MS). We aimed to identify networks of white (WM) and grey matter (GM) damage that predict disability progression and cognitive worsening using data-driven methods. METHODS: We analysed data from 1836 participants with different MS phenotypes (843 in a discovery cohort and 842 in a replication cohort). We calculated standardised T1-weighted/T2-weighted (sT1w/T2w) ratio maps in brain GM and WM, and applied spatial independent component analysis to identify networks of covarying microstructural damage. Clinical outcomes were Expanded Disability Status Scale worsening confirmed at 24 weeks (24-week confirmed disability progression (CDP)) and time to cognitive worsening assessed by the Symbol Digit Modalities Test (SDMT). We used Cox proportional hazard models to calculate predictive value of network measures. RESULTS: We identified 8 WM and 7 GM sT1w/T2w networks (of regional covariation in sT1w/T2w measures) in both cohorts. Network loading represents the degree of covariation in regional T1/T2 ratio within a given network. The loading factor in the anterior corona radiata and temporo-parieto-frontal components were associated with higher risks of developing CDP both in the discovery (HR=0.85, p<0.05 and HR=0.83, p<0.05, respectively) and replication cohorts (HR=0.84, p<0.05 and HR=0.80, p<0.005, respectively). The decreasing or increasing loading factor in the arcuate fasciculus, corpus callosum, deep GM, cortico-cerebellar patterns and lesion load were associated with a higher risk of developing SDMT worsening both in the discovery (HR=0.82, p<0.01; HR=0.87, p<0.05; HR=0.75, p<0.001; HR=0.86, p<0.05 and HR=1.27, p<0.0001) and replication cohorts (HR=0.82, p<0.005; HR=0.73, p<0.0001; HR=0.80, p<0.005; HR=0.85, p<0.01 and HR=1.26, p<0.0001). CONCLUSIONS: GM and WM networks of microstructural changes predict disability and cognitive worsening in MS. Our approach may be used to identify patients at greater risk of disability worsening and stratify cohorts in treatment trials.

Ocrelizumab-treated patients with relapsing multiple sclerosis show volume loss rates similar to healthy aging.

BACKGROUND: Multiple sclerosis (MS) is a chronic autoimmune disease of the central nervous system characterized by two major and interconnected hallmarks: inflammation and progressive neurodegeneration. OBJECTIVE: The aim of this work was to compare neurodegenerative processes, in the form of global and regional brain volume loss rates, in healthy controls (HCs) and in patients with relapsing MS (RMS) treated with ocrelizumab, which suppresses acute inflammation. METHODS: Whole brain, white matter, cortical gray matter, thalamic, and cerebellar volume loss rates were assessed in 44 HCs that were part of a substudy in the OPERA II randomized controlled trial (NCT01412333) and 59 patients with RMS enrolled in the same substudy as well as age- and sex-matched patients in OPERA I (NCT01247324) and II. Volume loss rates were computed using random coefficients models over a period of 2 years. RESULTS: Ocrelizumab-treated patients showed global and regional brain volume loss rates that were approaching that of HCs. CONCLUSION: These findings are consistent with an important role of inflammation on overall tissue loss and the role of ocrelizumab in reducing this phenomenon.

Deviation From Normative Whole Brain and Deep Gray Matter Growth in Children With MOGAD, MS, and Monophasic Seronegative Demyelination.

BACKGROUND AND OBJECTIVES: Pediatric-acquired demyelination of the CNS associated with antibodies directed against myelin oligodendrocyte glycoprotein (MOG; MOG antibody-associated disease [MOGAD]) occurs as a monophasic or relapsing disease and with variable but often extensive T2 lesions in the brain. The impact of MOGAD on brain growth during maturation is unknown. We quantified the effect of pediatric MOGAD on brain growth trajectories and compared this with the growth trajectories of age-matched and sex-matched healthy children and children with multiple sclerosis (MS, a chronic relapsing disease known to lead to failure of normal brain growth and to loss of brain volume) and monophasic seronegative demyelination. METHODS: We included children enrolled at incident attack in the prospective longitudinal Canadian Pediatric Demyelinating Disease Study who were recruited at the 3 largest enrollment sites, underwent research brain MRI scans, and were tested for serum MOG-IgG. Children seropositive for MOG-IgG were diagnosed with MOGAD. MS was diagnosed per the 2017 McDonald criteria. Monophasic seronegative demyelination was confirmed in children with no clinical or MRI evidence of recurrent demyelination and negative results for MOG-IgG and aquaporin-4-IgG. Whole and regional brain volumes were computed through symmetric nonlinear registration to templates. We computed age-normalized and sex-normalized z scores for brain volume using a normative dataset of 813 brain MRI scans obtained from typically developing children and used mixed-effect models to assess potential deviation from brain growth trajectories. RESULTS: We assessed brain volumes of 46 children with MOGAD, 26 with MS, and 51 with monophasic seronegative demyelinating syndrome. Children with MOGAD exhibited delayed (p < 0.001) age-expected and sex-expected growth of thalamus, caudate, and globus pallidus, normalized for the whole brain volume. Divergence from expected growth was particularly pronounced in the first year postonset and was detected even in children with monophasic MOGAD. Thalamic volume abnormalities were less pronounced in children with MOGAD compared with those in children with MS. DISCUSSION: The onset of MOGAD during childhood adversely affects the expected trajectory of growth of deep gray matter structures, with accelerated changes in the months after an acute attack. Further studies are required to better determine the relative impact of monophasic vs relapsing MOGAD and whether relapsing MOGAD with attacks isolated to the optic nerves or spinal cord affects brain volume over time.

Lesion-level correspondence and longitudinal properties of paramagnetic rim and slowly expanding lesions in multiple sclerosis.

BACKGROUND: Paramagnetic rim lesions (PRLs) and slowly expanding lesions (SELs) have been posited as markers of chronic active lesions (CALs). OBJECTIVE: To assess the lesion-level concordance of PRLs and SELs in MS and to characterize changes in brain tissue integrity in CALs over time. METHODS: MRIs were analyzed from a substudy of AFFINITY [NCT03222973], a phase 2 trial of opicinumab in relapsing MS. Assessments included (1) identification of SELs based on longitudinal MRIs over 72 weeks, and identification of PRLs on susceptibility-weighted imaging (SWI) filtered phase images at week 72; (2) evaluation of subject-level correlation of SEL and PRL counts, volumes, and degree of lesion-level overlap between SELs and PRLs; and (3) characterization of tissue integrity over time in overlapping and non-overlapping SELs and PRLs. RESULTS: In 41 subjects, 119 chronic PRLs and 267 SELs were detected. Of 119 (39.5%) chronic PRLs, 47 co-localized with a SEL; 46/267 (17.2%) SELs co-localized with a PRL. PRLs co-localized with SELs showed expansion and worsening microstructural damage over time. SELs with and without co-localization with PRLs showed ongoing tissue damage. CONCLUSIONS: Chronic MS lesions identified as both PRL and SEL were associated with the most severe accumulation of tissue damage. TRIAL REGISTRATION: AFFINITY [NCT03222973].

Exploratory clinical efficacy and patient-reported outcomes from NOVA: A randomized controlled study of intravenous natalizumab 6-week dosing versus continued 4-week dosing for relapsing-remitting multiple sclerosis.

BACKGROUND: Natalizumab (TYSABRI®) 300 mg administered intravenously every-4-weeks (Q4W) is approved for treatment of relapsing-remitting multiple sclerosis but is associated with increased risk of progressive multifocal leukoencephalopathy (PML). Extended natalizumab dosing intervals of approximately every-6-weeks (Q6W) are associated with a lower risk of PML. Primary and secondary clinical outcomes from the NOVA randomized clinical trial (NCT03689972) suggest that effective disease control is maintained in patients who were stable during treatment with natalizumab Q4W for ≥12 months and who then switched to Q6W dosing. We compared additional exploratory clinical and patient-reported outcomes (PROs) from NOVA to assess the efficacy of Q6W dosing. METHODS: Prespecified exploratory clinical efficacy endpoints in NOVA included change from baseline in Expanded Disability Status Scale (EDSS) score, Timed 25-Foot Walk (T25FW), dominant- and nondominant-hand 9-Hole Peg Test (9HPT), and Symbol Digit Modalities Test (SDMT). Exploratory patient-reported outcome (PRO) efficacy endpoints included change from baseline in the Treatment Satisfaction Questionnaire for Medication (TSQM), Neuro-QoL fatigue questionnaire, Multiple Sclerosis Impact Scale (MSIS-29), EuroQol 5 Dimensions (EQ-5D-5 L) index score, Clinical Global Impression (CGI)-Improvement (patient- and clinician-assessed) and CGI-Severity (clinician-assessed) rating scales. Estimated proportions of patients with confirmed EDSS improvement were based on Kaplan-Meier methods. Estimates of mean treatment differences for Q6W versus Q4W in other outcomes were assessed by least squares mean (LSM) and analyzed using a linear mixed model of repeated measures or ordinal logistic regression (CGI-scale). RESULTS: Exploratory clinical and patient-reported outcomes were assessed in patients who received ≥1 dose of randomly assigned study treatment and had ≥1 postbaseline efficacy assessment (Q6W group, n = 247, and Q4W group, n = 242). Estimated proportions of patients with EDSS improvement at week 72 were similar for Q6W and Q4W groups (11.7% [19/163] vs 10.8% [17/158]; HR 1.02 [95% confidence interval [CI], 0.53-1.98]; P = 0.9501). At week 72, there were no significant differences between Q6W and Q4W groups in LSM change from baseline for T25FW (0.00, P = 0.975), 9HPT (dominant [0.22, P = 0.533] or nondominant [0.09, P = 0.862] hand), or SDMT (-1.03, P = 0.194). Similarly, there were no significant differences between Q6W and Q4W groups in LSM change from baseline for any PRO (TSQM, -1.00, P = 0.410; Neuro-QoL fatigue, 0.52, P = 0.292; MSIS-29 Psychological, 0.67, P = 0.572; MSIS-29 Physical, 0.74, P = 0.429; EQ-5D-5 L, 0.00, P = 0.978). For the EQ-5D-5 L, a higher proportion of Q6W patients than Q4W patients demonstrated worsening (≥0.5 standard deviation increase in the EQ-5D-5 L index score; P = 0.0475). From baseline to week 72 for Q6W versus Q4W, odds ratio (ORs) of LSM change in CGI scores did not show meaningful differences between groups (CGI-Improvement [patient]: OR [95% CI] 1.2 [0.80-1.73]; CGI-Improvement [physician]: 0.8 [0.47-1.36]; CGI-Severity [physician]: 1.0 [0.71-1.54]). CONCLUSIONS: No significant differences were observed in change from baseline to week 72 between natalizumab Q6W and Q4W groups for all exploratory clinical or PRO-related endpoints assessed. For the EQ-5D-5 L, a higher proportion of Q6W than Q4W patients demonstrated worsening.

Plasma neurofilament light chain in children with relapsing MS receiving teriflunomide or placebo: A post hoc analysis of the randomized TERIKIDS trial.

BACKGROUND: The phase 3 TERIKIDS study demonstrated efficacy and manageable safety for teriflunomide versus placebo in children with relapsing multiple sclerosis (RMS). OBJECTIVE: Evaluate plasma neurofilament light chain (pNfL) concentrations in TERIKIDS. METHODS: Patients received placebo or teriflunomide (14 mg adult equivalent) for up to 96 weeks in the double-blind (DB) period. In the open-label extension (OLE), all patients received teriflunomide until up to 192 weeks after randomization. pNfL was measured using single-molecule array assay (Simoa® NF-light™). RESULTS: Baseline mean age was 14.5 years; 69.4% were female. Baseline geometric least square mean pNfL levels were similar for teriflunomide (n = 78) and placebo (n = 33) patients (19.83 vs 18.30 pg/mL). Over the combined DB and OLE periods, pNfL values were lower for teriflunomide versus placebo (analysis of variance p < 0.01; Week 192: 10.61 vs 17.32 pg/mL). Observed between-group pNfL differences were attenuated upon adjustment for gadolinium (Gd)-enhancing or new/enlarged T2 lesion counts at DB Week 24. Higher baseline pNfL levels were associated with shorter time since first MS symptom onset, higher baseline Gd-enhancing lesion counts and T2 lesion volume, and increased hazard of high magnetic resonance imaging activity or clinical relapse during the DB period. CONCLUSION: Teriflunomide treatment was associated with significantly reduced pNfL levels in children with RMS. CLINICALTRIALS.GOV IDENTIFIER: NCT02201108.

Magnetization transfer saturation reveals subclinical optic nerve injury in pediatric-onset multiple sclerosis.

BACKGROUND: The presence of subclinical optic nerve (ON) injury in youth living with pediatric-onset MS has not been fully elucidated. Magnetization transfer saturation (MTsat) is an advanced magnetic resonance imaging (MRI) parameter sensitive to myelin density and microstructural integrity, which can be applied to the study of the ON. OBJECTIVE: The objective of this study was to investigate the presence of subclinical ON abnormalities in pediatric-onset MS by means of magnetization transfer saturation and evaluate their association with other structural and functional parameters of visual pathway integrity. METHODS: Eleven youth living with pediatric-onset MS (ylPOMS) and no previous history of optic neuritis and 18 controls underwent standardized brain MRI, optical coherence tomography (OCT), Magnetoencephalography (MEG)-Visual Evoked Potentials (VEPs), and visual battery. Data were analyzed with mixed effect models. RESULTS: While ON volume, OCT parameters, occipital MEG-VEPs outcomes, and visual function did not differ significantly between ylPOMS and controls, ylPOMS had lower MTsat in the supratentorial normal appearing white matter (-0.26 nU, p = 0.0023), and in both in the ON (-0.62 nU, p < 0.001) and in the normal appearing white matter of the optic radiation (-0.56 nU, p = 0.00071), with these being positively correlated (+0.57 nU, p = 0.00037). CONCLUSIONS: Subclinical microstructural injury affects the ON of ylPOMS. This may appear as MTsat changes before being detectable by other currently available testing.

Present and future of the diagnostic work-up of multiple sclerosis: the imaging perspective.

In recent years, the use of magnetic resonance imaging (MRI) for the diagnostic work-up of multiple sclerosis (MS) has evolved considerably. The 2017 McDonald criteria show high sensitivity and accuracy in predicting a second clinical attack in patients with a typical clinically isolated syndrome and allow an earlier diagnosis of MS. They have been validated, are evidence-based, simplify the clinical use of MRI criteria and improve MS patients' management. However, to limit the risk of misdiagnosis, they should be applied by expert clinicians only after the careful exclusion of alternative diagnoses. Recently, new MRI markers have been proposed to improve diagnostic specificity for MS and reduce the risk of misdiagnosis. The central vein sign and chronic active lesions (i.e., paramagnetic rim lesions) may increase the specificity of MS diagnostic criteria, but further effort is necessary to validate and standardize their assessment before implementing them in the clinical setting. The feasibility of subpial demyelination assessment and the clinical relevance of leptomeningeal enhancement evaluation in the diagnostic work-up of MS appear more limited. Artificial intelligence tools may capture MRI attributes that are beyond the human perception, and, in the future, artificial intelligence may complement human assessment to further ameliorate the diagnostic work-up and patients' classification. However, guidelines that ensure reliability, interpretability, and validity of findings obtained from artificial intelligence approaches are still needed to implement them in the clinical scenario. This review provides a summary of the most recent updates regarding the application of MRI for the diagnosis of MS.

Single-timepoint low-dimensional characterization and classification of acute versus chronic multiple sclerosis lesions using machine learning.

Multiple sclerosis (MS) is a chronic inflammatory and neurodegenerative disease characterized by the appearance of focal lesions across the central nervous system. The discrimination of acute from chronic MS lesions may yield novel biomarkers of inflammatory disease activity which may support patient management in the clinical setting and provide endpoints in clinical trials. On a single timepoint and in the absence of a prior reference scan, existing methods for acute lesion detection rely on the segmentation of hyperintense foci on post-gadolinium T1-weighted magnetic resonance imaging (MRI), which may underestimate recent acute lesion activity. In this paper, we aim to improve the sensitivity of acute MS lesion detection in the single-timepoint setting, by developing a novel machine learning approach for the automatic detection of acute MS lesions, using single-timepoint conventional non-contrast T1- and T2-weighted brain MRI. The MRI input data are supplemented via the use of a convolutional neural network generating "lesion-free" reconstructions from original "lesion-present" scans using image inpainting. A multi-objective statistical ranking module evaluates the relevance of textural radiomic features from the core and periphery of lesion sites, compared within "lesion-free" versus "lesion-present" image pairs. Then, an ensemble classifier is optimized through a recursive loop seeking consensus both in the feature space (via a greedy feature-pruning approach) and in the classifier space (via model selection repeated after each pruning operation). This leads to the identification of a compact textural signature characterizing lesion phenotype. On the patch-level task of acute versus chronic MS lesion classification, our method achieves a balanced accuracy in the range of 74.3-74.6% on fully external validation cohorts.

Estimating individual treatment effect on disability progression in multiple sclerosis using deep learning.

Disability progression in multiple sclerosis remains resistant to treatment. The absence of a suitable biomarker to allow for phase 2 clinical trials presents a high barrier for drug development. We propose to enable short proof-of-concept trials by increasing statistical power using a deep-learning predictive enrichment strategy. Specifically, a multi-headed multilayer perceptron is used to estimate the conditional average treatment effect (CATE) using baseline clinical and imaging features, and patients predicted to be most responsive are preferentially randomized into a trial. Leveraging data from six randomized clinical trials (n = 3,830), we first pre-trained the model on the subset of relapsing-remitting MS patients (n = 2,520), then fine-tuned it on a subset of primary progressive MS (PPMS) patients (n = 695). In a separate held-out test set of PPMS patients randomized to anti-CD20 antibodies or placebo (n = 297), the average treatment effect was larger for the 50% (HR, 0.492; 95% CI, 0.266-0.912; p = 0.0218) and 30% (HR, 0.361; 95% CI, 0.165-0.79; p = 0.008) predicted to be most responsive, compared to 0.743 (95% CI, 0.482-1.15; p = 0.179) for the entire group. The same model could also identify responders to laquinimod in another held-out test set of PPMS patients (n = 318). Finally, we show that using this model for predictive enrichment results in important increases in power.

Permanent tissue damage in multiple sclerosis lesions is associated with reduced pre-lesion myelin and axon volume fractions.

BACKGROUND: The use of advanced magnetic resonance imaging (MRI) techniques in MS research has led to new insights in lesion evolution and disease outcomes. It has not yet been determined if, or how, pre-lesional abnormalities in normal-appearing white matter (NAWM) relate to the long-term evolution of new lesions. OBJECTIVE: To investigate the relationship between abnormalities in MRI measures of axonal and myelin volume fractions (AVF and MVF) in NAWM preceding development of black-hole (BH) and non-BH lesions in people with MS. METHODS: We obtained magnetization transfer and diffusion MRI at 6-month intervals in patients with MS to estimate MVF and AVF during lesion evolution. Lesions were classified as either BH or non-BH on the final imaging visit using T1 maps. RESULTS: Longitudinal data from 97 new T2 lesions from 9 participants were analyzed; 25 lesions in 8 participants were classified as BH 6-12 months after initial appearance. Pre-lesion MVF, AVF, and MVF/AVF were significantly lower, and T1 was significantly higher, in the lesions that later became BHs (p < 0.001) compared to those that did not. No significant pre-lesion abnormalities were found in non-BH lesions (p > 0.05). CONCLUSION: The present work demonstrated that pre-lesion abnormalities are associated with worse long-term lesion-level outcome.