The long-term outcomes of CIS patients in the Barcelona inception cohort: Looking back to recognize aggressive MS

Exploring miRNAs' Based Modeling Approach for Predicting PIRA in Multiple Sclerosis: A Comprehensive Analysis

The current hypothesis on the pathophysiology of multiple sclerosis (MS) suggests the involvement of both inflammatory and neurodegenerative mechanisms. Disease Modifying Therapies (DMTs) effectively decrease relapse rates, thus reducing relapse-associated disability in people with MS. In some patients, disability progression, however, is not solely linked to new lesions and clinical relapses but can manifest independently. Progression Independent of Relapse Activity (PIRA) significantly contributes to long-term disability, stressing the urge to unveil biomarkers to forecast disease progression. Twenty-five adult patients with relapsing-remitting multiple sclerosis (RRMS) were enrolled in a cohort study, according to the latest McDonald criteria, and tested before and after high-efficacy Disease Modifying Therapies (DMTs) (6-24 months). Through Agilent microarrays, we analyzed miRNA profiles from peripheral blood mononuclear cells. Multivariate logistic and linear models with interactions were generated. Robustness was assessed by randomization tests in R. A subset of miRNAs, correlated with PIRA, and the Expanded Disability Status Scale (EDSS), was selected. To refine the patient stratification connected to the disease trajectory, we computed a robust logistic classification model derived from baseline miRNA expression to predict PIRA status (AUC = 0.971). We built an optimal multilinear model by selecting four other miRNA predictors to describe EDSS changes compared to baseline. Multivariate modeling offers a promising avenue to uncover potential biomarkers essential for accurate prediction of disability progression in early MS stages. These models can provide valuable insights into developing personalized and effective treatment strategies.

Early prediction of unfavorable evolution after a first clinical episode suggestive of multiple sclerosis: the EUMUS score

BACKGROUND

Predicting disease progression in patients with the first clinical episode suggestive of multiple sclerosis (MS) is crucial for personalized therapeutic approaches. This study aimed to develop the EUMUS score for accurately estimating the risk of early evidence of disease activity and progression (EDA).

METHODS

Retrospective analysis was conducted on data from 221 patients with a first clinical MS episode collected from four Italian MS centers. Various variables including socio-demographics, clinical features, cerebrospinal fluid analysis, evoked potentials, and brain MRI were considered. A prognostic multivariate regression model was identified to develop the EUMUS score. The optimal cutoff for predicting the transition from no evidence of disease activity (NEDA3) to EDA was determined. The accuracy of the prognostic model and score were tested in a separate UK MS cohort.

RESULTS

After 12 months, 61.54% of patients experienced relapses and/or new MRI lesions. Younger age (OR 0.96, CI 0.93-0.99; p = 0.005), MRI infratentorial lesion(s) at baseline (OR 2.21, CI 1.27-3.87; p = 0.005), positive oligoclonal bands (OR 2.89, CI 1.47-5.69; p = 0.002), and abnormal lower limb somatosensory-evoked potentials (OR 2.77, CI 1.41-5.42; p = 0.003) were significantly associated with increased risk of EDA. The EUMUS score demonstrated good specificity (72%) and correctly classified 80% of patients with EDA in the independent UK cohort.

CONCLUSIONS

The EUMUS score is a simple and useful tool for predicting MS evolution within 12 months of the first clinical episode. It has the potential to guide personalized therapeutic approaches and aid in clinical decision-making.

Matching proposed clinical and MRI criteria of aggressive multiple sclerosis to serum and cerebrospinal fluid markers of neuroaxonal and glial injury

BACKGROUND

Definitions of aggressive MS employ clinical and MR imaging criteria to identify highly active, rapidly progressing disease courses. However, the degree of overlap between clinical and radiological parameters and biochemical markers of CNS injury is not fully understood. Aim of this cross-sectional study was to match clinical and MR imaging hallmarks of aggressive MS to serum/CSF markers of neuroaxonal and astroglial injury (neurofilament light chain (sNfL, cNfL), and glial fibrillary acidic protein (sGFAP, cGFAP)).

METHODS

We recruited 77 patients with relapsing-remitting MS (RRMS) and 22 patients with clinically isolated syndrome. NfL and GFAP levels in serum and CSF were assessed using a single-molecule-array HD-1-analyzer. A general linear model with each biomarker as a dependent variable was computed. Clinical and imaging criteria of aggressive MS, as recently proposed by the ECTRIMS Consensus Group, were modeled as independent variables. Other demographic, clinical or laboratory parameters, were modeled as covariates. Analyses were repeated in a homogenous subgroup, consisting only of newly diagnosed, treatment-naïve RRMS patients presenting with an acute relapse.

RESULTS

After adjusting for covariates and multiplicity of testing, sNfL and cNfL concentrations were strongly associated with the presence of ≥2 gadolinium-enhancing lesions (psNfL = 0.00008; pcNfL = 0.004) as well as the presence of infratentorial lesions on MRI (psNfL = 0.0003; pcNfL < 0.004). No other clinical and imaging criteria of aggressive MS correlated significantly with NfL or GFAP in serum and CSF. In the more homogeneous subgroup, sNfL still was associated with the presence of ≥2 gadolinium-enhancing lesions (psNfL = 0.001), presence of more than 20 T2-lesions (psNfL = 0.049) as well as the presence of infratentorial lesions on MRI (psNfL = 0.034), while cNfL was associated with the presence of ≥2 gadolinium-enhancing lesions (psNfL = 0.011) and presence of more than 20 T2-lesions (psNfL = 0.029).

CONCLUSIONS

Among proposed risk factors for an aggressive disease course, MRI findings but not clinical characteristics correlated with sNfL and cNfL as a marker of neuroaxonal injury and should be given appropriate weight considering MS prognosis and therapy. No significant correlation was detected for GFAP alone.

CD138 as a Specific CSF Biomarker of Multiple Sclerosis

BACKGROUND AND OBJECTIVES

The aim of this study was to identify novel biomarkers for multiple sclerosis (MS) diagnosis and prognosis, addressing the critical need for specific and prognostically valuable markers in the field.

METHODS

We conducted an extensive proteomic investigation, combining analysis of (1) CSF proteome from symptomatic controls, fast and slow converters after clinically isolated syndromes, and patients with relapsing-remitting MS (n = 10 per group) using label-free quantitative proteomics and (2) oligodendrocyte secretome changes under proinflammatory or proapoptotic conditions using stable isotope labeling by amino acids in cell culture. Proteins exhibiting differential abundance in both proteomic analyses were combined with other putative MS biomarkers, yielding a comprehensive list of 87 proteins that underwent quantification through parallel reaction monitoring (PRM) in a novel cohort, comprising symptomatic controls, inflammatory neurologic disease controls, and patients with MS at various disease stages (n = 10 per group). The 11 proteins that passed this qualification step were subjected to a new PRM assay within an expanded cohort comprising 158 patients with either MS at different disease stages or other inflammatory or noninflammatory neurologic disease controls.

RESULTS

This study unveiled a promising biomarker signature for MS, including previously established candidates, such as chitinase 3-like protein 1, chitinase 3-like protein 2, chitotriosidase, immunoglobulin kappa chain region C, neutrophil gelatinase-associated lipocalin, and CD27. In addition, we identified novel markers, namely cat eye syndrome critical region protein 1 (adenosine deaminase 2, a therapeutic target in multiple sclerosis) and syndecan-1, a proteoglycan, also known as plasma cell surface marker CD138 and acting as chitinase 3-like protein 1 receptor implicated in inflammation and cancer signaling. CD138 exhibited good diagnostic accuracy in distinguishing MS from inflammatory neurologic disorders (area under the curve [AUC] = 0.85, CI 0.75-0.95). CD138 immunostaining was also observed in the brains of patients with MS and cultured oligodendrocyte precursor cells but was absent in astrocytes.

DISCUSSION

These findings identify CD138 as a specific CSF biomarker for MS and suggest the selective activation of the chitinase 3-like protein 1/CD138 pathway within the oligodendrocyte lineage in MS. They offer promising prospects for improving MS diagnosis and prognosis by providing much-needed specificity and clinical utility.

CLASSIFICATION OF EVIDENCE

This study provides Class II evidence that CD138 distinguishes multiple sclerosis from other inflammatory neurologic disorders with an AUC of 0.85 (95% CI 0.75-0.95).

Routine CSF parameters as predictors of disease course in multiple sclerosis: an MSBase cohort study

BACKGROUND

It remains unclear whether routine cerebrospinal fluid (CSF) parameters can serve as predictors of multiple sclerosis (MS) disease course.

METHODS

This large-scale cohort study included persons with MS with CSF data documented in the MSBase registry. CSF parameters to predict time to reach confirmed Expanded Disability Status Scale (EDSS) scores 4, 6 and 7 and annualised relapse rate in the first 2 years after diagnosis (ARR2) were assessed using (cox) regression analysis.

RESULTS

In total, 11 245 participants were included of which 93.7% (n=10 533) were persons with relapsing-remitting MS (RRMS). In RRMS, the presence of CSF oligoclonal bands (OCBs) was associated with shorter time to disability milestones EDSS 4 (adjusted HR=1.272 (95% CI, 1.089 to 1.485), p=0.002), EDSS 6 (HR=1.314 (95% CI, 1.062 to 1.626), p=0.012) and EDSS 7 (HR=1.686 (95% CI, 1.111 to 2.558), p=0.014). On the other hand, the presence of CSF pleocytosis (≥5 cells/µL) increased time to moderate disability (EDSS 4) in RRMS (HR=0.774 (95% CI, 0.632 to 0.948), p=0.013). None of the CSF variables were associated with time to disability milestones in persons with primary progressive MS (PPMS). The presence of CSF pleocytosis increased ARR2 in RRMS (adjusted R2=0.036, p=0.015).

CONCLUSIONS

In RRMS, the presence of CSF OCBs predicts shorter time to disability milestones, whereas CSF pleocytosis could be protective. This could however not be found in PPMS. CSF pleocytosis is associated with short-term inflammatory disease activity in RRMS. CSF analysis provides prognostic information which could aid in clinical and therapeutic decision-making.

Baseline serum neurofilament light chain levels differentiate aggressive from benign forms of relapsing-remitting multiple sclerosis: a 20-year follow-up cohort

BACKGROUND AND OBJECTIVES

Serum biomarkers are emerging as useful prognostic tools for multiple sclerosis (MS); however, long-term studies are lacking. We aimed to evaluate the long-term prognostic value of the serum levels of neurofilament light chain (NfL), total tau, glial fibrillary acidic protein (GFAP), and chitinase 3-like-1 (CHI3L1) measured close to the time of MS onset.

METHODS

In this retrospective, exploratory, observational, case and controls study, patients with relapsing-remitting MS (RRMS) with available baseline serum samples and prospectively follow-up in our MS unit for a long time were selected based on their clinical evolution to form two groups: (1) a benign RRMS (bRRMS) group, defined as patients with an Expanded Disability Status Scale (EDSS) score of ≤ 3 at ≥ 10 years of follow-up; (2) an aggressive RRMS (aRRMS) group, defined as patients with an EDSS score of ≥ 6 at ≤ 15 years of follow-up. An age-matched healthy control (HC) group was selected. NfL, total tau, and GFAP serum levels were quantified using a single-molecule array (SIMOA), and CHI3L1 was quantified using ELISA.

RESULTS

Thirty-one patients with bRRMS, 19 with aRRMS, and 10 HC were included. The median follow-up time from sample collection was 17.74 years (interquartile range, 14.60-20.37). Bivariate and multivariate analyses revealed significantly higher NfL and GFAP levels in the aRRMS group than in the bRRMS group. A receiver operating characteristic curve analysis identified serum NfL level as the most efficient marker for distinguishing aRRMS from bRRMS.

DISCUSSION

This proof-of-concept study comparing benign and aggressive RRMS groups reinforces the potential role of baseline NfL serum levels as a promising long-term disability prognostic marker. In contrast, serum GFAP, total tau, and CHI3L1 levels demonstrated a lower or no ability to differentiate between the long-term outcomes of RRMS.

Consensus statement of the Spanish Society of Neurology on the treatment of multiple sclerosis and holistic patient management in 2023

The last consensus statement of the Spanish Society of Neurology's Demyelinating Diseases Study Group on the treatment of multiple sclerosis (MS) was issued in 2016. Although many of the positions taken remain valid, there have been significant changes in the management and treatment of MS, both due to the approval of new drugs with different action mechanisms and due to the evolution of previously fixed concepts. This has enabled new approaches to specific situations such as pregnancy and vaccination, and the inclusion of new variables in clinical decision-making, such as the early use of high-efficacy disease-modifying therapies (DMT), consideration of the patient's perspective, and the use of such novel technologies as remote monitoring. In the light of these changes, this updated consensus statement, developed according to the Delphi method, seeks to reflect the new paradigm in the management of patients with MS, based on the available scientific evidence and the clinical expertise of the participants. The most significant recommendations are that immunomodulatory DMT be started in patients with radiologically isolated syndrome with persistent radiological activity, that patient perspectives be considered, and that the term "lines of therapy" no longer be used in the classification of DMTs (> 90% consensus). Following diagnosis of MS, the first DMT should be selected according to the presence/absence of factors of poor prognosis (whether epidemiological, clinical, radiological, or biomarkers) for the occurrence of new relapses or progression of disability; high-efficacy DMTs may be considered from disease onset.

Predictive factors and treatment challenges in malignant progression of relapsing-remitting multiple sclerosis

Objective

Our objective was to uncover the predictive factors that can help anticipate the malignant progression of individuals with Relapsing-Remitting Multiple Sclerosis (RRMS). Additionally, we sought to analyze and compare the response to treatment between patients with benign and malignant forms of RRMS.

Methods

This cohort study included RRMS patients categorized as benign (≥10 years since disease onset, Expanded Disability Status Scale (EDSS) ≤ 1) or malignant (≤5 years since disease onset, EDSS ≥6). Patients' data, including demographics, medical history, treatment, and MRI (Magnetic Resonance Imaging) scans, were collected and statistically analyzed.

Results

Among the 254 patients diagnosed with RRMS, 174 were found to have benign RRMS, while the remaining 80 were diagnosed with malignant RRMS. Notably, patients with malignant RRMS exhibited a significantly higher mean age of onset (32.00 ± 7.96 vs. 25.70 ± 17.19; P < 0.001) and a greater prevalence of males (40% vs. 18.4%; P = 0.014). Additionally, within the initial five years of diagnosis, patients with malignant RRMS experienced a higher number of relapses (median: 4 vs. 2; P < 0.001) and hospitalizations (median: 2 vs. 1; P = 0.006) compared to those with benign RRMS. Clinical presentations of malignant RRMS were predominantly characterized by multifocal attacks, whereas unifocal attacks were more prevalent in patients with benign RRMS. MRI scans revealed that malignant RRMS patients displayed a higher burden of plaques in the infratentorial and cord regions, as well as a greater number of black hole lesions. Conversely, benign RRMS patients exhibited a higher number of Gadolinium-enhanced lesions. Utilizing Disease-Modifying Therapies (DMTs) with an escalating approach has shown effectiveness in managing benign RRMS. However, it has proven insufficient in addressing malignant RRMS, resulting in frequent transitions to higher-line DMTs. As a result, it places a considerable burden on patients with malignant RRMS, consuming valuable time and resources, and ultimately yielding subpar outcomes.

Conclusion

Our study identifies prognostic factors for malignant progression in RRMS, including older age of onset, male gender, increased relapses and hospitalizations, multifocal attacks, higher plaque load, and black hole lesions. The current escalation strategy for DMTs is insufficient for managing malignant RRMS, requiring alternative approaches for improved outcomes. In other words, MS is a spectrum rather than a single disease, and some patients progress to a malignant phenotype of MS that is not effectively treated by the current approach.

Prognostic relevance of MRI in early relapsing multiple sclerosis: ready to guide treatment decision making?

Magnetic resonance imaging (MRI) of the brain and spinal cord plays a crucial role in the diagnosis and monitoring of multiple sclerosis (MS). There is conclusive evidence that brain and spinal cord MRI findings in early disease stages also provide relevant insight into individual prognosis. This includes prediction of disease activity and disease progression, the accumulation of long-term disability and the conversion to secondary progressive MS. The extent to which these MRI findings should influence treatment decisions remains a subject of ongoing discussion. The aim of this review is to present and discuss the current knowledge and scientific evidence regarding the utility of MRI at early MS disease stages for prognostic classification of individual patients. In addition, we discuss the current evidence regarding the use of MRI in order to predict treatment response. Finally, we propose a potential approach as to how MRI data may be categorized and integrated into early clinical decision making.

Multiple sclerosis

Multiple sclerosis remains one of the most common causes of neurological disability in the young adult population (aged 18-40 years). Novel pathophysiological findings underline the importance of the interaction between genetics and environment. Improvements in diagnostic criteria, harmonised guidelines for MRI, and globalised treatment recommendations have led to more accurate diagnosis and an earlier start of effective immunomodulatory treatment than previously. Understanding and capturing the long prodromal multiple sclerosis period would further improve diagnostic abilities and thus treatment initiation, eventually improving long-term disease outcomes. The large portfolio of currently available medications paved the way for personalised therapeutic strategies that will balance safety and effectiveness. Incorporation of cognitive interventions, lifestyle recommendations, and management of non-neurological comorbidities could further improve quality of life and outcomes. Future challenges include the development of medications that successfully target the neurodegenerative aspect of the disease and creation of sensitive imaging and fluid biomarkers that can effectively predict and monitor disease changes.

Predictors of long-term disability in multiple sclerosis patients using routine magnetic resonance imaging data: A 15-year retrospective study

INTRODUCTION

Early identification of patients at high risk of progression could help with a personalised treatment strategy. Magnetic resonance imaging (MRI) measures have been proposed to predict long-term disability in multiple sclerosis (MS), but a reliable predictor that can be easily implemented clinically is still needed.

AIM

Assess MRI measures during the first 5 years of the MS disease course for the ability to predict progression at 10+ years.

METHODS

Eighty-two MS patients (53 females), with ≥10 years of clinical follow-up and having two MRI scans, were included. Clinical data were obtained at baseline, follow-up and at ≥10 years. White matter lesion (WML) counts and volumes, and four linear brain sizes were measured on T2/FLAIR 'Fluid-Attenuated-Inversion-Recovery' and T1-weighted images.

RESULTS

Baseline and follow-up inter-caudate diameter (ICD) and third ventricular width (TVW) measures correlated positively with Expanded Disability Status Scale, ≥10 or more of WMLs showed a high sensitivity in predicting progression, at ≥10 years. A steeper rate of lesion volume increase was observed in subjects converting to secondary progressive MS. The sensitivity and specificity of both ICD and TVW, to predict disability at ≥10 years were 60% and 64%, respectively.

CONCLUSION

Despite advances in brain imaging and computerised volumetric analysis, ICD and TVW remain relevant as they are simple, fast and have the potential in predicting long-term disability. However, in this study, despite the statistical significance of these measures, the clinical utility is still not reliable.

Socioeconomic, health-care access and clinical determinants of disease severity in Multiple Sclerosis in Chile

BACKGROUND

MS severity may be affected by genetic, patient-related, disease-related and environmental factors. Socioeconomic status, including income and healthcare access, amongst others, may also have a role in affecting diagnostic delay or therapy prescription. In Chile, two main healthcare systems exist, public-healthcare and private-healthcare, nonetheless universal care laws (e.g., access to High Efficacy Therapy-HET), including both systems, have been recently enacted for people with MS.

OBJECTIVE

To assess the role of Socioeconomic Conditions (SEC), clinical variables and public health policies on the impact of disease severity of MS patients in Chile.

METHODS

Multicentric, observational, cross-sectional study including patients from two reference centres (1 national reference centre from the private-health system and 1 regional reference centre from the public-health system). SEC and clinical variables included healthcare insurance (private or public), subclassification of health insurance according to monthly income, sex, age at onset, diagnostic delay, disease duration, diagnosis before HET law (as a proxy of HET delay), and current HET treatment. Progression Index (PI), EDSS ≥6.0 and Progressive MS diagnosis were used as outcome measures. Multivariable binary logistic regression was performed.

RESULTS

We included 604 patients (460 private-health, 144 public-health), 67% women, 100% white/mestizo, 88% RRMS, mean age 42±12 years, mean age at onset 32±11 years, mean disease duration 10±6 years, median diagnostic delay 0 (0-34) years, 86% currently receiving any DMT, 55% currently receiving HET, median EDSS at last visit of 2.0 (0-10), and median PI 0.17 (0-4.5). Lower monthly income was associated with higher EDSS and higher PI. In the multivariable analysis, public-healthcare (OR 10.2), being diagnosed before HET-law (OR 4.89), longer diagnostic delay (OR 1.26), and older age at onset (OR 1.05) were associated with a higher risk of PI>0.2, while current HET (OR 0.39) was a protective factor. Diagnosis before HET-law (OR 7.59), public-healthcare (OR 6.49), male sex (OR 2.56), longer disease duration (OR 1.2) and older age at onset (OR 1.1) were associated with a higher risk of Progressive MS. Public-healthcare (OR 5.54), longer disease duration (OR 1.14) and older age at onset (OR 1.08) were associated with a higher risk of EDSS ≥6.0 while current treatment with HET had a trend as being a protective factor (OR 0.44, p = 0.05).

CONCLUSION

MS severity is impacted by non-modifiable factors such as sex and age at onset. Interventions focused on shortening diagnostic delay and encouraging early access to high-efficacy therapies, as well as initiatives that may reduce the disparities inherent to lower socioeconomic status, may improve outcomes in people with MS.

Proteomics and relationship with axonal pathology in multiple sclerosis: 5-year diffusion tensor imaging study

Blood-based biomarkers can be economic and easily accessible tools for monitoring and predicting disease activity in multiple sclerosis. The objective of this study was to determine the predictive value of a multivariate proteomic assay for concurrent and future microstructural/axonal brain pathology in a longitudinal study of a heterogeneous group of people with multiple sclerosis. A proteomic analysis was obtained on serum samples from 202 people with multiple sclerosis (148 relapsing-remitting and 54 progressive) at baseline and 5-year follow-up. The concentration of 21 proteins related to multiple pathways of multiple sclerosis pathophysiology was derived using Proximity Extension Assay on the Olink platform. Patients were imaged on the same 3T MRI scanner at both timepoints. Тhe rate of whole brain, white matter and grey matter atrophy over the 5-year follow-up was determined using the multi-timepoint Structural Image Evaluation, using Normalisation, of Atrophy algorithms. Lesion burden measures were also assessed. The severity of microstructural axonal brain pathology was quantified using diffusion tensor imaging. Fractional anisotropy and mean diffusivity of normal-appearing brain tissue, normal-appearing white matter, grey matter, T2 and T1 lesions were calculated. Age, sex and body mass index-adjusted step-wise regression models were used. Glial fibrillary acidic protein was the most common and highest-ranked proteomic biomarker associated with greater concurrent microstructural central nervous system alterations (P < 0.001). The rate of whole brain atrophy was associated with baseline levels of glial fibrillary acidic protein, protogenin precursor, neurofilament light chain and myelin oligodendrocyte (P < 0.009), whereas grey matter atrophy was associated with higher baseline neurofilament light chain, higher osteopontin and lower protogenin precursor levels (P < 0.016). Higher baseline glial fibrillary acidic protein level was a significant predictor of future severity of the microstructural CNS alterations as measured by normal-appearing brain tissue fractional anisotropy and mean diffusivity (standardized β = -0.397/0.327, P < 0.001), normal-appearing white matter fractional anisotropy (standardized β = -0.466, P < 0.0012), grey matter mean diffusivity (standardized β = 0.346, P < 0.011) and T2 lesion mean diffusivity (standardized β = 0.416, P < 0.001) at the 5-year follow-up. Serum levels of myelin-oligodendrocyte glycoprotein, neurofilament light chain, contactin-2 and osteopontin proteins were additionally and independently associated with worse concomitant and future axonal pathology. Higher glial fibrillary acidic protein levels were associated with future disability progression (Exp(B) = 8.65, P = 0.004). Multiple proteomic biomarkers are independently associated with greater severity of axonal brain pathology as measured by diffusion tensor imaging in multiple sclerosis. Baseline serum glial fibrillary acidic protein levels can predict future disability progression.

Performance of McDonald 2017 multiple sclerosis diagnostic criteria and evaluation of genetic ancestry in patients with a first demyelinating event in Argentina

BACKGROUND

Information on performance of multiple sclerosis (MS) diagnostic criteria is scarce for populations from Latin America, Asia, or the Caribbean.

OBJECTIVE

To assess performance of revised 2017 McDonald criteria as well as evaluate genetic ancestry in a group of MS patients from Argentina experiencing a debut demyelinating event.

METHODS

Demographic and clinical characteristics, cerebrospinal fluid (CSF), and magnetic resonance imaging (MRI) findings and new T2 lesions were recorded at baseline and during relapses. Diagnostic accuracy in predicting conversion to clinically defined MS (CDMS) based on initial imaging applying revised 2017 criteria was evaluated and genetic ancestry-informative markers analyzed.

RESULTS

Of 201 patients experiencing their first demyelinating event (median follow-up 60 months), CDMS was confirmed in 67. We found 2017 diagnostic criteria were more sensitive (84% vs 67%) and less specific (14% vs 33%) than 2010 criteria, especially in a group of patients revised separately, presenting positive oligoclonal bands (88% vs 8%). Genetic testing performed in 128 cases showed 72% of patients were of European ancestry and 27% presented genetic admixture.

CONCLUSION

2017 McDonald criteria showed higher sensitivity and lower specificity compared with 2010 criteria, shortening both time-to-diagnosis and time-to-treatment implementation.

External validation of a clinical prediction model in multiple sclerosis

BACKGROUND

Timely initiation of disease modifying therapy is crucial for managing multiple sclerosis (MS).

OBJECTIVE

We aimed to validate a previously published predictive model of individual treatment response using a non-overlapping cohort from the Middle East.

METHODS

We interrogated the MSBase registry for patients who were not included in the initial model development. These patients had relapsing MS or clinically isolated syndrome, a recorded date of disease onset, disability and dates of disease modifying therapy, with sufficient follow-up pre- and post-baseline. Baseline was the visit at which a new disease modifying therapy was initiated, and which served as the start of the predicted period. The original models were used to translate clinical information into three principal components and to predict probability of relapses, disability worsening or improvement, conversion to secondary progressive MS and treatment discontinuation as well as changes in the area under disability-time curve (ΔAUC). Prediction accuracy was assessed using the criteria published previously.

RESULTS

The models performed well for predicting the risk of disability worsening and improvement (accuracy: 81%-96%) and performed moderately well for predicting the risk of relapses (accuracy: 73%-91%). The predictions for ΔAUC and risk of treatment discontinuation were suboptimal (accuracy < 44%). Accuracy for predicting the risk of conversion to secondary progressive MS ranged from 50% to 98%.

CONCLUSION

The previously published models are generalisable to patients with a broad range of baseline characteristics in different geographic regions.

Association of Early Progression Independent of Relapse Activity With Long-term Disability After a First Demyelinating Event in Multiple Sclerosis

Importance

Progression independent of relapse activity (PIRA) is the main event responsible for irreversible disability accumulation in relapsing multiple sclerosis (MS).

Objective

To investigate clinical and neuroimaging predictors of PIRA at the time of the first demyelinating attack and factors associated with long-term clinical outcomes of people who present with PIRA.

Design, Setting, and Participants

This cohort study, conducted from January 1, 1994, to July 31, 2021, included patients with a first demyelinating attack from multiple sclerosis; patients were recruited from 1 study center in Spain. Patients were excluded if they refused to participate, had alternative diagnoses, did not meet protocol requirements, had inconsistent demographic information, or had less than 3 clinical assessments.

Exposures

Exposures included (1) clinical and neuroimaging features at the first demyelinating attack and (2) presenting PIRA, ie, confirmed disability accumulation (CDA) in a free-relapse period at any time after symptom onset, within (vs after) the first 5 years of the disease (ie, early/late PIRA), and in the presence (vs absence) of new T2 lesions in the previous 2 years (ie, active/nonactive PIRA).

Main Outcomes and Measures

Expanded Disability Status Scale (EDSS) yearly increase rates since the first attack and adjusted hazard ratios (HRs) for predictors of time to PIRA and time to EDSS 6.0.

Results

Of the 1128 patients (mean [SD] age, 32.1 [8.3] years; 781 female individuals [69.2%]) included in the study, 277 (25%) developed 1 or more PIRA events at a median (IQR) follow-up time of 7.2 (4.6-12.4) years (for first PIRA). Of all patients with PIRA, 86 of 277 (31%) developed early PIRA, and 73 of 144 (51%) developed active PIRA. Patients with PIRA were slightly older, had more brain lesions, and were more likely to have oligoclonal bands than those without PIRA. Older age at the first attack was the only predictor of PIRA (HR, 1.43; 95% CI, 1.23-1.65; P < .001 for each older decade). Patients with PIRA had steeper EDSS yearly increase rates (0.18; 95% CI, 0.16-0.20 vs 0.04; 95% CI, 0.02-0.05; P < .001) and an 8-fold greater risk of reaching EDSS 6.0 (HR, 7.93; 95% CI, 2.25-27.96; P = .001) than those without PIRA. Early PIRA had steeper EDSS yearly increase rates than late PIRA (0.31; 95% CI, 0.26-0.35 vs 0.13; 95% CI, 0.10-0.16; P < .001) and a 26-fold greater risk of reaching EDSS 6.0 from the first attack (HR, 26.21; 95% CI, 2.26-303.95; P = .009).

Conclusions and Relevance

Results of this cohort study suggest that for patients with multiple sclerosis, presenting with PIRA after a first demyelinating event was not uncommon and suggests an unfavorable long-term prognosis, especially if it occurs early in the disease course.

Retrospective cohort study to devise a treatment decision score predicting adverse 24-month radiological activity in early multiple sclerosis

Background

Multiple sclerosis (MS) is a chronic neuroinflammatory disease affecting about 2.8 million people worldwide. Disease course after the most common diagnoses of relapsing-remitting multiple sclerosis (RRMS) and clinically isolated syndrome (CIS) is highly variable and cannot be reliably predicted. This impairs early personalized treatment decisions.

Objectives

The main objective of this study was to algorithmically support clinical decision-making regarding the options of early platform medication or no immediate treatment of patients with early RRMS and CIS.

Design

Retrospective monocentric cohort study within the Data Integration for Future Medicine (DIFUTURE) Consortium.

Methods

Multiple data sources of routine clinical, imaging and laboratory data derived from a large and deeply characterized cohort of patients with MS were integrated to conduct a retrospective study to create and internally validate a treatment decision score [Multiple Sclerosis Treatment Decision Score (MS-TDS)] through model-based random forests (RFs). The MS-TDS predicts the probability of no new or enlarging lesions in cerebral magnetic resonance images (cMRIs) between 6 and 24 months after the first cMRI.

Results

Data from 65 predictors collected for 475 patients between 2008 and 2017 were included. No medication and platform medication were administered to 277 (58.3%) and 198 (41.7%) patients. The MS-TDS predicted individual outcomes with a cross-validated area under the receiver operating characteristics curve (AUROC) of 0.624. The respective RF prediction model provides patient-specific MS-TDS and probabilities of treatment success. The latter may increase by 5-20% for half of the patients if the treatment considered superior by the MS-TDS is used.

Conclusion

Routine clinical data from multiple sources can be successfully integrated to build prediction models to support treatment decision-making. In this study, the resulting MS-TDS estimates individualized treatment success probabilities that can identify patients who benefit from early platform medication. External validation of the MS-TDS is required, and a prospective study is currently being conducted. In addition, the clinical relevance of the MS-TDS needs to be established.

Oligoclonal M bands and cervical spinal cord lesions predict early secondary progressive multiple sclerosis

Objective

To determine baseline cerebrospinal fluid and magnetic resonance imaging (MRI) variables at the onset of a clinically isolated syndrome (CIS) suggestive of multiple sclerosis (MS) that predict evolution to secondary progressive MS (SPMS).

Methods

276 CIS patients with a minimum follow-up of 10 years were studied. Baseline presence of oligoclonal IgG and IgM bands (OCGB and OCMB respectively); number of brain T2 lesions (B-T2L), brain gadolinium enhancement lesions (brain-GEL), cervical spinal cord T2 lesions (cSC-T2L); and fulfillment of 2017 McDonald criteria among other variables were collected.

Results

14 patients ended up with a non-MS condition. 138/276 CIS patients fulfilled 2017 McDonald criteria. Mean age was 32.4 years, 185 female. 227 received treatment, 95 as CIS. After a mean follow-up of 12 years, 36 patients developed SPMS. Conversion to SPMS was associated with OCGB (p = 0.02), OCMB (p = 0.0001); ≥ 9 B-T2L (p = 0.03), brain-GEL (p = 0.03), and cSC-T2L (p = 0.03). However, after adjusting for sex, age, BT2L, brain-GEL, SC-T2, and OCMB status, only OCMB (HR 4.4, 1.9–10.6) and cSC-T2L (HR 2.2, 1.0–6.2) suggested an independent association with risk of conversion to SPMS. Patients with both risk factors had a HR of 6.12 (2.8–12.9).

Discussion

OCMB and SC-T2 lesions are potential independent predictors of conversion to SPMS.

Expert-Agreed Practical Recommendations on the Use of Cladribine

Cladribine is a disease-modifying selective immune reconstitution oral therapy for adult patients with highly active relapsing multiple sclerosis (RMS). It was approved in the USA in 2019 and in Europe in 2017, thus there are still gaps in existing guidelines for using cladribine tablets in clinical practice. Nine experts with extensive experience in managing patients with multiple sclerosis in Spain identified some of the unanswered questions related to the real-life use of cladribine tablets. They reviewed the available clinical trial data and real-world evidence, including their own experiences of using cladribine, over the course of three virtual meetings held between November 2020 and January 2021. This article gathers their practical recommendations to aid treatment decision-making and optimise the use of cladribine tablets in patients with RMS. The consensus recommendations cover the following areas: candidate patient profiles, switching strategies (to and from cladribine), managing response to cladribine and safety considerations.

Increased intrathecal neurofilament light and immunoglobulin M predict severe disability in relapsing-remitting multiple sclerosis

Background

Emerging evidence supports that determination of intrathecal immunoglobulin M (IgM) synthesis (ITMS) and neurofilament light (NfL) concentration in cerebrospinal fluid (CSF) may be clinically useful as disease severity biomarkers in relapsing-remitting multiple sclerosis (RRMS).

Methods

Monocentric observational longitudinal cohort study in which prospectively collected data were retrospectively retrieved. Included were patients with RRMS (n=457) who had a diagnostic investigation including analysis of ITMS and CSF neurofilament light (cNfL). ITMS was calculated with the linear index formula, the intrathecal fraction of IgM according to Reiber (IgM_IF), and by qualitative determination of oligoclonal IgM bands (OCMB). Univariable and multivariable models were performed to predict Evidence of Disease Activity-3 (EDA-3) status within 24 months from onset, and the risk of Expanded Disability Status Score (EDSS) ≥3 and ≥6.

Results

All investigated methods to calculate ITMS significantly predicted evidence of disease activity (EDA-3) within 24 months. IgM_IF>0% showed the strongest association with EDA-3 status (adjusted hazard ratio [aHR] 3.7, 95%CI 2.7-5, p<0.001). Combining IgM-index>0.1 or OCMB with increased cNfL were strong predictors of EDSS≥3 (for cNfL⁺/IgM-index⁺: aHR 4.6, 95%CI 2.6-8.2, p<0.001) and EDSS≥6 (aHR 8.2, 95%CI 2.3-30, p<0.001).

Conclusions

In a real-world setting, ITMS was a useful biomarker in early RRMS to predict disabling MS and its prognostic value was even stronger in combination with cNfL. Our data suggest that determination of ITMS and cNfL should be included in the diagnostic work-up of RRMS for prognostic purposes and in decisions of disease-modifying therapy.

Long-term prognosis communication preferences in early-stage relapsing-remitting multiple sclerosis

BACKGROUND

Multiple sclerosis is one of the most common causes of neurological disability in young adults with major consequences for their future lives. Improving communication strategies on prognosis may help patients deal with the disease and adjust their long-term life goals. However, there is limited information on patients' preferences of long-term prognosis (LTP) communication and associated factors.

OBJECTIVE

The aim of this study was to describe patients' preferences and assess the factors associated with LTP communication preferences in early-stage relapsing-remitting multiple sclerosis (RRMS) patients.

METHODS

A multicenter, non-interventional study was conducted. Adult patients with a diagnosis of RRMS, a disease duration from first attack ≤ 3 years, and an Expanded Disability Status Scale (EDSS) score of 0-5.5 were included. The Prognosis in MS questionnaire was used to assess how much patients want to know about their LTP. Different patient-reported measures were administered to gather information on symptom severity, pain, fatigue, mood/anxiety, quality of life, stigma, illness perception, feeling of hopelessness, self-efficacy, information avoidance and coping strategies. Cognition was assessed using the Symbol Digit Modalities Test (SDMT). A multivariate logistic regression analysis was performed to assess the association between LTP information preference and demographic and clinical characteristics, as well as patients' perspectives.

RESULTS

A total of 189 patients were included (mean age: 36.1  ±  9.4 years, 71.4% female, mean disease duration: 1.2  ±  0.8 years). Median EDSS score was 1.0 (IQR = 0.0-2.0). A proportion of 68.5% (n  =  126) of patients had never discussed LTP with their neurologists, whereas 69.2% (n = 126) reported interest in knowing it (73.5% at diagnosis). Bivariate analyses suggested that patients were significantly more likely to have higher LTP information preferences if they were male and had a lower SDMT score. Male gender and a lower SDMT score were predictors of LTP information preferences.

CONCLUSIONS

Patients with early-stage RRMS want to discuss their LTP shortly after diagnosis. Understanding the factors involved may be useful to design individualized communication strategies.

Interrogating large multiple sclerosis registries and databases: what information can be gained?

PURPOSE OF REVIEW

Although substantial progress has been made in understanding the natural history of multiple sclerosis (MS) and the development of new therapies, many questions concerning disease behavior and therapeutics remain to be answered. Data generated from real-world observational studies, based on large MS registries and databases and analyzed with advanced statistical methods, are offering the scientific community answers to some of these questions that are otherwise difficult or impossible to address. This review focuses on observational studies published in the last 2 years designed to compare the effectiveness of escalation vs. induction treatment strategies, to assess the effectiveness of treatment in pediatric-onset and late-onset MS, and to identify the clinical phenotype of secondary progressive (SP)MS.

RECENT FINDINGS

The main findings originating from real-world studies suggest that MS patients who will qualify for high-efficacy disease-modifying therapies (DMTs) should be offered these as early as possible to prevent irreversible accumulation of neurological disability. Especially pediatric patients derive substantial benefits from early treatment. In patients with late-onset MS, sustained exposure to DMTs may result in more favorable outcomes. Data-driven definitions are more accurate in defining transition to SPMS than diagnosis based solely on neurologists' judgment.

SUMMARY

Patients, physicians, industry, and policy-makers have all benefited from real-world evidence based on registry data, in answering questions of diagnostics, choice of treatment, and timing of treatment decisions.

Predictive MRI Biomarkers in MS—A Critical Review

Background and Objectives: In this critical review, we explore the potential use of MRI measurements as prognostic biomarkers in multiple sclerosis (MS) patients, for both conventional measurements and more novel techniques such as magnetization transfer, diffusion tensor, and proton spectroscopy MRI. Materials and Methods: All authors individually and comprehensively reviewed each of the aspects listed below in PubMed, Medline, and Google Scholar. Results: There are numerous MRI metrics that have been proven by clinical studies to hold important prognostic value for MS patients, most of which can be readily obtained from standard 1.5T MRI scans. Conclusions: While some of these parameters have passed the test of time and seem to be associated with a reliable predictive power, some are still better interpreted with caution. We hope this will serve as a reminder of how vast a resource we have on our hands in this versatile tool—it is up to us to make use of it.

Ofatumumab subcutaneous injection for the treatment of relapsing forms of multiple sclerosis

INTRODUCTION

In recent years, different studies have highlighted the importance of B cells in the pathophysiology of multiple sclerosis (MS): they secrete cytokines to modulate the inflammatory environment, present antigens for the activation of T lymphocytes, and they secrete antibodies contributing to the destruction of the myelin sheath. Combined, these findings have lead to new possible means for treating MS.

AREAS COVERED

In this review, we provide an up-to-date overview of the characteristics of ofatumumab (aka Kesimpta), and the differences between this drug and the other anti-CD20 monoclonal antibodies used to treat MS.

EXPERT OPINION

The evolution of disease-modifying treatment algorithms in MS underlines the importance of starting treatment as soon as the diagnosis is defined, and with adequate "treatment intensity". Monoclonal antibodies and other aggressive treatments are now considered as an option at the clinical presentation of the disease, based to the prognostic profile emerging through clinical and paraclinical investigations. The recent adoption of new diagnostic criteria allows for the early diagnosis of MS. This, together with the availability of disease-modifying therapies (DMTs), such as ofatumumab, with a good efficacy/safety profile and which are easy to administer, could contribute to significant improvements in the long-term prognosis of MS.

Magnetic Resonance Imaging as a Prognostic Disability Marker in Clinically Isolated Syndrome and Multiple Sclerosis: A Systematic Review and Meta-Analysis

To date, there are no definite imaging predictors for long-term disability in multiple sclerosis (MS). Magnetic resonance imaging (MRI) is the key prognostic tool for MS, primarily at the early stage of the disease. Recent findings showed that white matter lesion (WML) counts and volumes could predict long-term disability for MS. However, the prognostic value of MRI in the early stage of the disease and its link to long-term physical disability have not been assessed systematically and quantitatively. A meta-analysis was conducted using studies from four databases to assess whether MS lesion counts and volumes at baseline MRI scans could predict long-term disability, assessed by the expanded disability status scale (EDSS). Fifteen studies were eligible for the qualitative analysis and three studies for meta-analysis. T2 brain lesion counts and volumes after the disease onset were associated with disability progression after 10 years. Four or more lesions at baseline showed a highly significant association with EDSS 3 and EDSS 6, with a pooled OR of 4.10 and 4.3, respectively. The risk increased when more than 10 lesions were present. This review and meta-analysis confirmed that lesion counts and volumes could be associated with disability and might offer additional valid guidance in treatment decision making. Future work is essential to determine whether these prognostic markers have high predictive potential.

Apparent changes in the epidemiology and severity of multiple sclerosis

Multiple sclerosis (MS) is an immunological disease that causes acute inflammatory lesions and chronic inflammation in the CNS, leading to tissue damage and disability. As awareness of MS has increased and options for therapy have come into use, a large amount of epidemiological data have been collected, enabling studies of changes in incidence and disease course over time. Overall, these data seem to indicate that the incidence of MS has increased, but the course of the disease has become milder, particularly in the 25 years since the first disease-modifying therapies (DMTs) became available. A clear understanding of these trends and the reasons for them is important for understanding the factors that influence the development and progression of MS, and for clinical management with respect to prevention and treatment decisions. In this Review, we consider the evidence for changes in the epidemiology of MS, focusing on trends in the incidence of the disease over time and trends in the disease severity. In addition, we discuss the factors influencing these trends, including refinement of diagnostic criteria and improvements in health-care systems that have increased diagnosis in people with mild disease, and the introduction and improvement of DMT.

Effect of Changes in MS Diagnostic Criteria Over 25 Years on Time to Treatment and Prognosis in Patients With Clinically Isolated Syndrome

BACKGROUND AND OBJECTIVES

To explore whether time to diagnosis, time to treatment initiation, and age to reach disability milestones have changed in patients with clinically isolated syndrome (CIS) according to different multiple sclerosis (MS) diagnostic criteria periods.

METHODS

This retrospective study was based on data collected prospectively from the Barcelona-CIS cohort between 1994 and 2020. Patients were classified into 5 periods according to different MS criteria, and the times to MS diagnosis and treatment initiation were evaluated. The age at which patients with MS reached an Expanded Disability Status Scale (EDSS) score ≥3.0 was assessed by Cox regression analysis according to diagnostic criteria periods. Last, to remove the classic Will Rogers phenomenon by which the use of different MS criteria over time might result in a changes of prognosis, the 2017 McDonald criteria were applied, and age at EDSS score ≥3.0 was assessed by Cox regression.

RESULTS

In total, 1,174 patients were included. The median time from CIS to MS diagnosis and from CIS to treatment initiation showed a 77% and 82% reduction from the Poser to the McDonald 2017 diagnostic criteria periods, respectively. Patients of a given age diagnosed in more recent diagnostic criteria periods had a lower risk of reaching an EDSS score ≥3.0 than patients of the same age diagnosed in earlier diagnostic periods (reference category Poser period): adjusted hazard ratio (aHR) 0.47 (95% confidence interval 0.24-0.90) for McDonald 2001, aHR 0.25 (0.12-0.54) for McDonald 2005, aHR 0.30 (0.12-0.75) for McDonald 2010, and aHR 0.07 (0.01-0.45) for McDonald 2017. Patients in the early-treatment group displayed an aHR of 0.53 (0.33-0.85) of reaching age at EDSS score ≥3.0 compared to those in the late-treatment group. Changes in prognosis together with early-treatment effect were maintained after the exclusion of possible bias derived from the use of different diagnostic criteria over time (Will Rogers phenomenon).

DISCUSSION

A continuous decrease in the time to MS diagnosis and treatment initiation was observed across diagnostic criteria periods. Overall, patients diagnosed in more recent diagnostic criteria periods displayed a lower risk of reaching disability. The prognostic improvement is maintained after the Will Rogers phenomenon is discarded, and early treatment appears to be the most likely contributing factor.

Multiple Sclerosis Therapy Consensus Group (MSTCG): position statement on disease-modifying therapies for multiple sclerosis (white paper)

Multiple sclerosis is a complex, autoimmune-mediated disease of the central nervous system characterized by inflammatory demyelination and axonal/neuronal damage. The approval of various disease-modifying therapies and our increased understanding of disease mechanisms and evolution in recent years have significantly changed the prognosis and course of the disease. This update of the Multiple Sclerosis Therapy Consensus Group treatment recommendation focuses on the most important recommendations for disease-modifying therapies of multiple sclerosis in 2021. Our recommendations are based on current scientific evidence and apply to those medications approved in wide parts of Europe, particularly German-speaking countries (Germany, Austria, and Switzerland).

[Multiple sclerosis treatment consensus group (MSTCG): position paper on disease-modifying treatment of multiple sclerosis 2021 (white paper)]

Die Multiple Sklerose ist eine komplexe, autoimmun vermittelte Erkrankung des zentralen Nervensystems, charakterisiert durch inflammatorische Demyelinisierung sowie axonalen/neuronalen Schaden. Die Zulassung verschiedener verlaufsmodifizierender Therapien und unser verbessertes Verständnis der Krankheitsmechanismen und -entwicklung in den letzten Jahren haben die Prognose und den Verlauf der Erkrankung deutlich verändert. Diese Aktualisierung der Behandlungsempfehlung der Multiple Sklerose Therapie Konsensus Gruppe konzentriert sich auf die wichtigsten Empfehlungen für verlaufsmodifizierende Therapien der Multiplen Sklerose im Jahr 2021. Unsere Empfehlungen basieren auf aktuellen wissenschaftlichen Erkenntnissen und gelten für diejenigen Medikamente, die in weiten Teilen Europas, insbesondere in den deutschsprachigen Ländern (Deutschland, Österreich, Schweiz), zugelassen sind.

Perturbed Microbiota/Immune Homeostasis in Multiple Sclerosis

Objective

Based on animal models and human studies, there is now strong suspicion that host/microbiota mutualism in the context of gut microbial dysbiosis could influence immunity and multiple sclerosis (MS) evolution. Our goal was to seek evidence of deregulated microbiota-induced systemic immune responses in patients with MS.

Methods

We investigated gut and systemic commensal-specific antibody responses in healthy controls (n = 32), patients with relapsing-remitting MS (n = 30), and individuals with clinically isolated syndromes (CISs) (n = 15). Gut microbiota composition and diversity were compared between controls and patients by analysis of 16S ribosomal ribonucleic acid (rRNA) sequencing. Autologous microbiota and cultivable bacterial strains were used in bacterial flow cytometry assays to quantify autologous serum IgG and secretory IgA responses to microbiota. IgG-bound bacteria were sorted by flow cytometry and identified using 16S rRNA sequencing.

Results

We show that commensal-specific gut IgA responses are drastically reduced in patients with severe MS, disease severity being correlated with the IgA-coated fecal microbiota fraction (r = −0.647, p < 0.0001). At the same time, IgA-unbound bacteria elicit qualitatively broad and quantitatively increased serum IgG responses in patients with MS and CIS compared with controls (4.1% and 2.5% vs 1.9%, respectively, p < 0.001).

Conclusions

Gut and systemic microbiota/immune homeostasis are perturbed in MS. Our results argue that defective IgA responses in MS are linked to a breakdown of systemic tolerance to gut microbiota leading to an enhanced triggering of systemic IgG immunity against gut commensals occurring early in MS.

Machine learning classifier to identify clinical and radiological features relevant to disability progression in multiple sclerosis

Objectives

To evaluate the accuracy of a data-driven approach, such as machine learning classification, in predicting disability progression in MS.

Methods

We analyzed structural brain images of 163 subjects diagnosed with MS acquired at two different sites. Participants were followed up for 2–6 years, with disability progression defined according to the expanded disability status scale (EDSS) increment at follow-up. T2-weighted lesion load (T2LL), thalamic and cerebellar gray matter (GM) volumes, fractional anisotropy of the normal appearing white matter were calculated at baseline and included in supervised machine learning classifiers. Age, sex, phenotype, EDSS at baseline, therapy and time to follow-up period were also included. Classes were labeled as stable or progressed disability. Participants were randomly chosen from both sites to build a sample including 50% patients showing disability progression and 50% patients being stable. One-thousand machine learning classifiers were applied to the resulting sample, and after testing for overfitting, classifier confusion matrix, relative metrics and feature importance were evaluated.

Results

At follow-up, 36% of participants showed disability progression. The classifier with the highest resulting metrics had accuracy of 0.79, area under the true positive versus false positive rates curve of 0.81, sensitivity of 0.90 and specificity of 0.71. T2LL, thalamic volume, disability at baseline and administered therapy were identified as important features in predicting disability progression. Classifiers built on radiological features had higher accuracy than those built on clinical features.

Conclusions

Disability progression in MS may be predicted via machine learning classifiers, mostly evaluating neuroradiological features.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00415-021-10605-7.

aHSCT is superior to alemtuzumab in maintaining NEDA and improving cognition in multiple sclerosis

Objective

Autologous hematopoietic stem cell transplantation (aHSCT) is increasingly recognized as a potential therapy for patients with highly active multiple sclerosis (MS). This study aims to assess outcome differences in disease activity in MS patients treated either with aHSCT or alemtuzumab.

Methods

We conducted a monocentric registry‐based cohort study by recording the clinical course (EDSS and relapses), MRI parameters (new T2 lesions), and neuropsychological assessment in all 19 MS patients receiving aHSCT, and all 21 patients receiving alemtuzumab between 2007 and 2018. We used survival analyses of no evidence of disease activity (NEDA) as the primary objective which was defined by no EDSS progression, no relapse, and no new T2 lesion on MRI. Secondary objectives were EDSS improvement and neurocognitive performance.

Results

Both treatment groups were similar in respect of age, gender, disability, and neurocognitive performance except for significantly longer disease duration in the alemtuzumab group. Mean follow‐up was 58.8 [range 29–140] months in the aHSCT group compared to 27.6 [range 11–52] months in the alemtuzumab‐treated group. We observed significantly more patients maintaining NEDA in the aHSCT group (p = 0.048) compared to the alemtuzumab‐treated patients. Furthermore, 37% of the aHSCT patients showed an improvement of EDSS compared to none in the alemtuzumab‐treated group (p = 0.033). It is of note that cognitive function was significantly improved in the aHSCT‐treated patients.

Interpretation

aHSCT suppresses inflammatory activity more effectively than alemtuzumab and might enable improvement of overall disability and cognition in MS.

[Neuropsychological and MRI diagnostics in secondary progressive multiple sclerosis]

Hintergrund

Die Multiple Sklerose ist im longitudinalen Verlauf oft ein Krankheitskontinuum mit initial schubförmig-remittierender Phase (RRMS) und späterer sekundärer Progredienz (SPMS). Die meisten bisher zugelassenen Therapien sind bei SPMS nicht ausreichend wirksam. Die frühe Erkennung der SPMS-Konversion ist daher entscheidend für die Therapiewahl. Wichtige Entscheidungshilfen können dabei die Testung kognitiver Teilleistungen und die Magnetresonanztomographie (MRT) sein.

Ziel der Arbeit

Darstellung der Bedeutung kognitiver Testungen und von MRT-Untersuchungen für Prädiktion und Erfassung der SPMS-Konversion. Ausarbeitung von Strategien der Verlaufsbeobachtung und Therapiesteuerung in der Praxis, insbesondere in der ambulanten Versorgung.

Material und Methoden

Übersichtsarbeit auf Basis einer unsystematischen Literaturrecherche.

Ergebnisse

Standardisierte kognitive Testung kann für die frühe SPMS-Diagnose hilfreich sein und die Verlaufsbewertung erleichtern. Eine jährliche Anwendung sensitiver Screeningtests wie Symbol Digit Modalities Test (SDMT) und Brief Visual Memory Test-Revised (BVMT‑R) oder der Brief International Cognitive Assessment for MS (BICAMS)-Testbatterie ist empfehlenswert. Persistierende inflammatorische Aktivität im MRT in den ersten drei Jahren der Erkrankung sowie das Vorhandensein kortikaler Läsionen sind prädiktiv für eine SPMS-Konversion. Ein standardisiertes MRT-Monitoring auf Merkmale einer progressiven MS kann den klinisch und neurokognitiv begründeten SPMS-Verdacht stützen.

Diskussion

Die interdisziplinäre Versorgung von MS-Patienten durch klinisch versierte Neurologen, unterstützt durch neuropsychologische Testung und MRT, hat einen hohen Stellenwert für die SPMS-Prädiktion und Diagnose. Letztere erlaubt eine frühe Umstellung auf geeignete Therapien, da bei SPMS andere Interventionen als für die RRMS notwendig sind. Nach erfolgter medikamentöser Umstellung erlaubt die klinische, neuropsychologische und bildgebende Vigilanz ein stringentes Monitoring auf neuroinflammatorische und -degenerative Aktivität sowie Therapiekomplikationen.

Cortical involvement determines impairment 30 years after a clinically isolated syndrome

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.

Implications of extreme serum neurofilament light chain levels for the management of patients with relapsing multiple sclerosis

BACKGROUND

Serum neurofilament light chain (sNfL) is a promising biomarker to complement the decision-making process in multiple sclerosis (MS) patients. However, although sNfL levels are able to detect disease activity and to predict future disability, the growing evidence has not yet been translated into practicable recommendations for an implementation into clinical routine.

METHODS

The observation of a patient with extensive inflammatory activity in magnetic resonance imaging (MRI) along with an extremely high sNfL level in the absence of any clinical symptoms prompted us to investigate common characteristics of our MS patients with the highest sNfL levels in a retrospective cohort study. The 97.5th percentile was chosen as a cut-off value because the mean sNfL level of the resulting extreme neurofilament light chain (NfL) cohort corresponded well to the sNfL level of the presented case. Patient characterization included clinical and MRI assessment with a focus on disease activity markers. sNfL levels were determined by single molecule array.

RESULTS

The 97.5th percentile of our MS cohort (958 sNfL measurements in 455 patients) corresponded to a threshold value of 46.1 pg/ml. The mean sNfL level of the extreme sNfL cohort (n = 24) was 95.6 pg/ml (standard deviation 68.4). Interestingly, only 15 patients suffered from a relapse at the time point of sample collection, whereas nine patients showed no signs of clinical disease activity. sNfL levels of patients with and without relapse did not differ [median 81.3 pg/ml (interquartile range [IQR] 48.0-128) versus 80.2 pg/ml (IQR 46.4-97.6), p = 0.815]. The proportion of patients with contrast-enhancing lesions was high and also did not differ between patients with and without relapse (92.9% versus 87.5%, p = 0.538); 78.9% of the patients not receiving a high-efficacious therapy had ongoing disease activity during a 2-year follow-up.

CONCLUSION

Extremely high sNfL levels are indicative of subclinical disease activity and might complement treatment decisions in ambiguous cases.

Autologous haematopoietic stem cell transplantation as a first-line disease-modifying therapy in patients with 'aggressive' multiple sclerosis

BACKGROUND

Autologous haematopoietic stem cell transplantation (AHSCT) is an effective treatment for patients with multiple sclerosis (MS) who have highly active disease, despite the use of standard disease-modifying therapies (DMTs). However, the optimal time for offering AHSCT to patients with 'aggressive' MS is yet to be established.

OBJECTIVES

The objective was to explore the safety and efficacy of AHSCT as a first-line DMT in patients with 'aggressive' MS.

METHODS

All patients with 'aggressive' MS who received AHSCT as a first-line DMT in five European and North American centres were retrospectively evaluated.

RESULTS

Twenty patients were identified. The median interval between diagnosis and AHSCT was 5 (1-20) months. All had multiple poor prognostic markers with a median pre-transplant Expanded Disability Status Scale (EDSS) score of 5.0 (1.5-9.5). After a median follow-up of 30 (12-118) months, the median EDSS score improved to 2.0 (0-6.5, p < 0.0001). No patient had further relapses. Three had residual magnetic resonance imaging (MRI) disease activities in the first 6 months post-transplant, but no further new or enhancing lesions were observed in subsequent scans.

CONCLUSION

AHSCT is safe and effective as a first-line DMT in inducing rapid and sustained remission in patients with 'aggressive' MS.

Aggressive multiple sclerosis (2): Treatment

The natural history of multiple sclerosis (MS) is highly heterogeneous. A subgroup of patients has what might be termed aggressive MS. These patients may have frequent, severe relapses with incomplete recovery and are at risk of developing greater and permanent disability at the earlier stages of the disease. Their therapeutic window of opportunity may be narrow, and while it is generally considered that they will benefit from starting early with a highly efficacious treatment, a unified definition of aggressive MS does not exist and data on its treatment are largely lacking. Based on discussions at an international focused workshop sponsored by the European Committee for Treatment and Research in Multiple Sclerosis (ECTRIMS), we review our current knowledge about treatment of individuals with aggressive MS. We analyse the available evidence, identify gaps in knowledge and suggest future research needed to fill those gaps. A companion paper details the difficulties in developing a consensus about what defines aggressive MS.

Aggressive multiple sclerosis (1): Towards a definition of the phenotype

While the major phenotypes of multiple sclerosis (MS) and relapsing-remitting, primary and secondary progressive MS have been well characterized, a subgroup of patients with an active, aggressive disease course and rapid disability accumulation remains difficult to define and there is no consensus about their management and treatment. The current lack of an accepted definition and treatment guidelines for aggressive MS triggered a 2018 focused workshop of the European Committee for Treatment and Research in Multiple Sclerosis (ECTRIMS) on aggressive MS. The aim of the workshop was to discuss approaches on how to describe and define the disease phenotype and its treatments. Unfortunately, it was not possible to come to consensus on a definition because of unavailable data correlating severe disease with imaging and molecular biomarkers. However, the workshop highlighted the need for future research needed to define this disease subtype while also focusing on its treatment and management. Here, we review previous attempts to define aggressive MS and present characteristics that might, with additional research, eventually help characterize it. A companion paper summarizes data regarding treatment and management.