Background and Aims:

The main aim of the study is to evaluate the efficacy and safety profile of Ocrelizumab (OCR), Rituximab (RTX), and Cladribine (CLA), employed as Natalizumab (NTZ) exit-strategies in Relapsing-Remitting Multiple Sclerosis (RRMS) patients at high-risk for progressive multifocal leukoencephalopathy (PML).

Methods:

This is a multicentre, retrospective, real-world study on consecutive RRMS patients from eleven tertiary Italian MS centres, who switched from NTZ to OCR, RTX and CLA from January 1^st, 2019 to December 31^st, 2019. The primary study outcomes were the annualized relapse rate (ARR) and Magnetic Resonance Imaging (MRI) outcome. Treatment effects were estimated by the inverse probability treatment weighting (IPTW), based on propensity score (PS) approach. Additional endpoint included confirmed disability progression (CDP) as measured by Expanded Disability Status Scale and adverse events (AEs).

Results:

Patients satisfying predefined inclusion and exclusion criteria were 120; 64 switched to OCR, 36 to RTX and 20 to CLA. Patients from the three groups did not shown differences for baseline characteristics, also after post-hoc analysis. The IPTW PS-adjusted models revealed that patients on OCR had a lower risk for ARR than patients on CLA (ExpB _OCR 0.485, CI 95% 0.264-0.893, p=.020). This result was confirmed also for 12-months MRI activity (ExpB _OCR 0.248 CI 95% 0.065-0.948, p=.042). No differences were found in other pairwise comparisons (OCR vs RTX and RTX vs CLA) for the investigated outcomes. AEs were similar among the three groups.

Conclusions:

Anti-CD20 drugs revealed to be effective and safe options as NTZ exit strategies. All investigated DMTs showed a good safety profile

Background and Aims:

Resting state (RS) functional connectivity (FC) and graph theoretical analysis shed light into functional reorganization in multiple sclerosis (MS). Advanced network-based methods exploiting machine learning on RS FC may support MS patients’ classification. Here, we developed advanced methods of RS FC analysis to classify MS patients according to disease phenotype.

Methods:

RS fMRI scans were obtained from 46 healthy controls (HC) and 113 MS patients (62 relapsing-remitting [RR] and 51 progressive [P]MS). Dominant sets clustering was used to group covariance-based RS FC matrices into clusters of subjects sharing some similarities in their network configuration. Support vector machines (SVMs) were used to classify disease phenotypes exploiting a representation of networks based on their geodesic distance from cluster means. Finally, a sensitivity analysis on the trained classifier identified features relevant for classification.

Results:

The described machine learning tool was able to classify RRMS patients from HC (accuracy=72.5%), PMS patients from HC (accuracy=85.2%) and PMS from RRMS patients (accuracy=76%). The sensitivity analysis on trained SVMs found that increased connectivity within the basal ganglia sub-network and decreased RS FC within the temporal sub-network contributed to an accurate classification of both RRMS and PMS patients from HC. Moreover, decreased RS FC within the occipital and parietal sub-networks contributed to differentiate PMS patients from HC.

Conclusions:

A combination of different machine learning principles allowed to detect specific RS FC configurations of our study subjects, which allowed to classify MS patients with different clinical phenotypes from HC with a good accuracy.

Funding. Partially supported from Fondazione Italiana Sclerosi Multipla (FISM2018/R/5)

Background and Aims:

Disability accrual in multiple sclerosis (MS) may occur as relapse-associated worsening (RAW) or progression independent of relapse activity (PIRA). We investigated the contribution of RAW and PIRA to confirmed disability accumulation (CDA) in patients with clinically isolated syndrome (CIS) and early relapsing-remitting (RR) MS.

Methods:

Relapsing-onset MS patients assessed within one year from onset and with follow-up >/= 5 years (n=5,340) were extracted from the Italian MS Registry. CDA was defined by an increase in Expanded Disability Status Scale (EDSS) score confirmed at 6 months, and classified per temporal association with relapses. Predictors of PIRA and RAW were assessed using multivariable Cox regression models.

Results:

PIRA occurred in 1472 (27.6%) and RAW in 240 (17.6%) patients. Predictors of PIRA were older age (HR=1.02;95%CI 1.02-1.03,p<0.001), RR course (HR=1.46;95%CI 1.30-1.64,p<0.001), longer disease duration (HR=1.49;95%CI 1.22-1.82,p<0.001), lower EDSS (HR=0.89;95%CI 0.85-0.93,p<0.001), lower number of relapses before the event (HR=0.93;95%CI 0.91-0.95,p<0.001). RAW was associated with younger age (HR=0.99;95%CI 0.98-0.99,p<0.001), RR course (HR=1.56; 95%CI 1.35-1.80,p<0.001), lower EDSS (HR=0.92;95%CI 0.87-0.97,p=0.002), higher number of relapses before the event (HR=1.07;95%CI 1.05-1.09,p<0.001). Longer exposure to disease modifying drugs (DMD) reduced the risk of both PIRA and RAW (p<0.001).

Conclusions:

in this early relapsing-onset MS cohort, PIRA was an important contributor to CDA. Our findings indicate that insidious progression appears even in the earliest phases of the disease, suggesting that inflammation and neurodegeneration can represent a single disease continuum. The analysis on progression independent of relapse and radiological activity is ongoing.

Background and Aims:

Cognitive impairment (CI) is a common clinical feature of multiple sclerosis (MS), but its pathophysiology is only partially known. Cerebrospinal fluid (CSF) biomarkers, by reflecting the ongoing pathology, may help in better understanding the determinants of CI in MS. Kappa free light chain index (k-index) is a sensitive biomarker of intrathecal B cells activation. Herein, we investigated the association between k-index and cognitive performance in MS patients.

Methods:

We selected for the study relapsing MS patients who, at the time of the diagnostic work-up, underwent CSF analysis and a complete neuropsychological assessment with the Rao’s Brief Repeatable Battery of Neuropsychological Tests (BRBN). k-index was assessed by nephelometry in a Siemens™ BN II automated analyser using N latex FLC kappa assay for CSF and serum samples (Siemens Healthcare Diagnostics).

Results:

Thirty-nine patients (F:M 2.9, mean age 39.3±13.1 years) were included in the study. k-index was not significantly different between patients with and without global CI and spatial memory, information processing speed and verbal fluency impairment. On the contrary, k-index was higher in patients with verbal memory impairment (median 99.6, range 58.5-195.2 vs. median 37.2, range 2.3-396.9, p<0.05). k-index was negatively associated with Selective Reminding Test (SRT) scores and explained up to 32% of their variance (SRT-LTS: r =-0.6, p<0.001; R²=0.32, F(1.37)=17.2, p<0.001; SRT-CLTR: r=-0.5, p<0.01; R²=0.22, F(1.4)=10.5, p<0.01; SRT-DR: r=-0.4, p<0.05; R²=0.16, F(1.4)=6.7, p<0.05) (Figure).

Conclusions:

k-index is higher in MS patients with impaired verbal memory. Intrathecal B cells activation may be associated with memory dysfunction in MS through mechanisms that deserve further investigations.

Background and Aims:

Cerebrospinal fluid (CSF) immunoglobulin free light chains (FLCs) have been proposed as a quantitative and automatable alternative to oligoclonal bands (OCBs) with a potential role as predictor of Multiple Sclerosis (MS) severity. The aim of the study is to evaluate the utility of FLC determination in the initial assessment of patients with suspected MS as a diagnostic and prognostic biomarker.

Methods:

We included 59 consecutive patients diagnosed as Clinical Isolated Syndrome (CIS) or MS and 31 consecutive patients with not-inflammatory disease who underwent to CSF and blood sampling. We performed OCBs and FLCs on matched CSF/serum samples and calculated κ-index (κFLCs-ratio/albumin-ratio). We collected radiological and clinical data at baseline and clinical data over time (median follow-up: 7 years) for CIS and MS patients.

Results:

Κ-index showed higher sensitivity and specificity for MS diagnosis versus to the gold standard, OCBs (AUC 0,99 versus AUC 0,92) and distinguished patients with higher lesion load on baseline brain and spinal cord MRI (p <0,05). Κ-index directly correlated with Multiple Sclerosis Severity Score (MSSS) at the end of follow-up (rho=0,33; p=0,041) in our population with a low medium disability (median MSSS 1,41 range 0,21-8,53). Patients with κ-index >70° percentile showed a four times greater risk of relapse over time (HR=0,24; p=0,003) and a three times greater risk of disease modifying treatment (DMT) introduction (HR=0,39; p=0,023).

Conclusions:

Our study suggests that κ-index determined during diagnostic work-up of MS could predict disease severity over time, leading to more individualized and early treatment.

Background and Aims:

No universal guidelines exist on Disease-Modifying Therapies (DMTs) use in people with Secondary Progressive Multiple Sclerosis (SPMS). The aim is to investigate in a large cohort of patients with a diagnosis of SPMS after at least two years of non-relapsing MS, the ability of DMTs in delaying disability accrual, expressed as the time to 24‐week confirmed Expanded Disability Status Scale (EDSS) ≥7.0.

Methods:

A retrospective study on longitudinally collected data. All patients with a conversion to SPMS within December 31^st, 2015 were enrolled. Patients were consequently divided in two groups according to the shared decision to stop DMTs (group A) or to switch to licensed DMTs for SPMS (group B) after the confirmed SPMS diagnosis.

Results:

311 patients were enrolled. Among them, 178 were in group A and 133 were in group B. Patients in the two groups were similar for baseline characteristics. The IPTW PS adjusted Cox model for the event time to 24 weeks confirmed EDSS 7.0 did not show differences between the two groups (ExpB 0.96, CI.739-1.271, p=.819). No significant differences in the disease activity recurrence were observed.

Conclusions:

In a real-world setting the maintenance of DMTs in patients with SPMS did not increase the risk to reach wheelchair in our cohort.

Background and Aims:

Neuropathic pain (NP) is frequently underestimated in Multiple Sclerosis (MS). The aim of this work is to evaluate for the first time the relationship between NP and spinothalamic tract (STT) microstructural integrity in Relapsing Remitting MS (RR-MS) patients through tractography reconstruction from Diffusion Tensor Imaging.

Methods:

A cohort of 35 RR-MS patients, and 15 healthy controls was enrolled and acquired on 3T scanner, including T1, T2, FLAIR and DTI. All participants underwent a complete clinical comprising pain evaluation (DN4) and cognitive assessment. Five ROIs (Fig1.A) were manually traced on controls DTI to obtain STT probabilistic masks, and to create STT template (Fig1.B). Diffusion metrics (FA, MD, AD, RD) of all participants were extracted from template and their laterality index (LI). ANCOVA corrected for age and gender was used for comparing the STT diffusion LI between controls and patients, while partial correlation was employed for assessing the relationships between alterations in LI and clinical/cognitive scores (p <0.05).

Results:

Results of the ANCOVA were reported in Fig2.A. The LI of FA was significant higher in RR-MS patients than controls (Fig2.B). Moreover, there was a positive correlation between the LI of MD and AD and FSS and between LI of MD, AD and RD with DN4 (Fig.2.C).

Conclusions:

We demonstrated that RR-MS patients had higher asymmetry than controls and more interestingly this abnormal STT laterality had a significant association with higher levels of fatigue and NP. In conclusion, we provided a first evidence of neuroanatomic correlate of the NP in RR-MS with STT microstructural alterations.

Background and Aims:

The ongoing global SARS-CoV-2 pandemic has raised concerns that multiple sclerosis (MS) may increase the risk for death in this patient population. Therefore, we sought to assess the COVID-19-related fatality rate of patients with MS as compared to the general population.

Methods:

We searched PubMed/Medline for articles reporting the cause-specific (COVID-19) number of death in patients with MS to calculate the crude death rate (CDR) attributable to COVID-19 on individual-patient data. We estimated indirectly-adjusted age-standardised infection-fatality ratio (IFR) to compare the cause-specific risk of death in patients and in the general population. Inverse-variance weighted meta-regressions with random-effect models were fitted to explore potential effect modifiers for the CDR on aggregate data from articles with adequate sample size (n=/>30).

Results:

Out of 367 screened articles, 60 fulfilled criteria for meta-analysis, with a total of 5474 patients included (27% males, median age 45 years). Of them, 168 died, yielding a CDR of 3.1% (95% CIs 2.3-3.9). The age-standardised IFR was 1.24 (95% CIs 1.05-1.41) using age-specific fatality rates provided by the World Health Organization (WHO) from Europe and America. We found an increased death risk in studies including higher proportion of patients either with comorbidity (p=0.013) or treated with anti-CD20 agents (p=0.021). Studies involving greater proportions of suspected rather than confirmed COVID-19 cases reported fewer deaths (p=0.001).

Conclusions:

People with MS have a 24% higher lethality risk from COVID-19 than the general population. Appropriate attention should be paid to patients with comorbidities and for those treated with anti-CD20 agents.