Unraveling treatment response in multiple sclerosis: A clinical and MRI challenge

Artificial intelligence in multiple sclerosis management: Challenges in a new era

Multiple sclerosis poses diagnostic and therapeutic challenges for healthcare professionals, with a high risk of misdiagnosis and difficulties in assessing therapeutic effectiveness. Artificial intelligence, particularly machine learning and deep neural networks, emerges as a promising tool to address these challenges. These technologies have the capability to analyze a wide range of data, from magnetic resonance imaging to genetic information, to provide more accurate diagnoses, classify multiple sclerosis subtypes, and predict disease progression and treatment response with extraordinary precision. However, their implementation raises ethical dilemmas, such as accountability in case of errors and the risk of excessive reliance on healthcare personnel. That said, this manuscript aims to urge healthcare professionals dedicated to the care and research of multiple sclerosis patients to recognize artificial intelligence as a valuable and complementary resource in their clinical practice. It also seeks to emphasize the importance of integrating this type of technology safely and responsibly, thereby ensuring the ethics and welfare of patients.

Prediction of disease activity and treatment failure in relapsing-remitting MS patients initiating daily oral DMTs

BACKGROUND

Limited data exist regarding treatment response prediction to oral disease-modifying therapies (DMTs) in multiple sclerosis (MS).

OBJECTIVES

We assessed the capacity of available scoring systems to anticipate disease activity parameters in naïve relapsing-remitting MS (RRMS) patients initiating daily oral DMTs, hypothesizing that they exhibit different predictive potentials.

METHODS

We conducted a retrospective study and applied the Rio Score (RS), modified Rio Score (mRS), and MAGNIMS Score 12 months after DMT initiation. At 36 months, we examined their ability to predict evidence of disease activity (EDA) components and treatment failure by logistic regression analysis.

RESULTS

Notably, 218 patients (62.4% females) initiating dimethyl fumarate, teriflunomide, and fingolimod were included. At 36 months, the RS high-risk group predicted evidence of clinical activity (odds ratio (OR) 10 [2.7-36.9]) and treatment failure (OR 10.6 [3.4-32.5]) but did not predict radiological activity (OR 1.9 [0.7-5]). The mRS non-responders group did not predict EDA and treatment failure. RS, mRS, and MAGNIMS 0 categories showed significantly lower EDA and treatment failure than the remainder.

CONCLUSION

Scoring systems present different predictive abilities for disease activity parameters at 36 months in MS patients initiating daily oral therapies, warranting further adjustments (i.e. introduction of fluid biomarkers) to depict disease activity status fully.

Adult and pediatric relapsing multiple sclerosis phase II and phase III trial design and their primary end points: A systematic review

No systematic review of trial designs in patients with relapsing multiple sclerosis (RMS) was reported. This systematic review was conducted on the trial designs and primary end points (PEs) of phase II and III trials intended to modify the natural course of the disease in patients with RMS. The purpose of the study is to explore trends/topics and discussion points in clinical trial design and PE, comparing them to regulatory guidelines and expert recommendations. Three trial registration systems, ClinicalTrials.gov, the EU Clinical Trials Register, and the Japan Registry of Clinical Trials, were used and 60 trials were evaluated. The dominant clinical trial design was a randomized controlled parallel-arms trial and other details were as follows: in adult phase III confirmatory trials (n = 32), active-controlled double-blind trial (DBT) (53%) and active-controlled open-label assessor-masking trial (16%); in adult phase II dose-finding trials (n = 9), placebo- and active-controlled DBT (44%), placebo-controlled DBT (22%), and placebo-controlled add-on DBT (22%); and in pediatric phase III confirmatory trials (n = 8), active-controlled DBT (38%) and active-controlled open-label non-masking trial (25%). The most common PEs were as follows: in adult confirmatory trials, annual relapse rate (ARR) (56%) and no evidence of disease activity-3 (NEDA-3) (13%); in adult dose-finding trials, the cumulative number of T1 gadolinium-enhancing lesions (56%), combined unique active lesions (22%), and overall disability response score (22%); and in pediatric confirmatory trials, ARR (38%) and time to first relapse (25%). It was suggested that some parts of the regulatory guidelines and expert recommendations need to be revised.

Prognostic factors for disease activity in newly diagnosed teriflunomide-treated patients with multiple sclerosis: a nationwide Danish study

BACKGROUND

Clinicians frequently rely on relapse counts, T2 MRI lesion load (T2L) and Expanded Disability Status Scale (EDSS) scores to guide treatment decisions for individuals diagnosed with multiple sclerosis (MS). This study evaluates how these factors, along with age and sex, influence prognosis during treatment with teriflunomide (TFL).

METHODS

We conducted a nationwide cohort study using data from the Danish Multiple Sclerosis Registry.Eligible participants had relapsing-remitting MS or clinically isolated syndrome and initiated TFL as their first treatment between 2013 and 2019. The effect of age, pretreatment relapses, T2L and EDSS scores on the risk of disease activity on TFL were stratified by sex.

RESULTS

In total, 784 individuals were included (57.4% females). A high number of pretreatment relapses (≥2) was associated with an increased risk of disease activity in females only (OR and (95% CI): 1.76 (1.11 to 2.81)). Age group 50+ was associated with a lower risk of disease activity in both sexes (OR females=0.28 (0.14 to 0.56); OR males=0.22 (0.09 to 0.55)), while age 35-49 showed a different impact in males and females (OR females=0.79 (0.50 to 1.23); OR males=0.42 (0.24 to 0.72)). EDSS scores and T2L did not show any consistent associations.

CONCLUSION

A high number of pretreatment relapses was only associated with an increased risk of disease activity in females, while age had a differential impact on the risk of disease activity according to sex. Clinicians may consider age, sex and relapses when deciding on TFL treatment.

Magnetic Resonance Imaging Evidence Supporting the Efficacy of Cladribine Tablets in the Treatment of Relapsing-Remitting Multiple Sclerosis

Numerous therapies are currently available to modify the disease course of multiple sclerosis (MS). Magnetic resonance imaging (MRI) plays a pivotal role in assessing treatment response by providing insights into disease activity and clinical progression. Integrating MRI findings with clinical and laboratory data enables a comprehensive assessment of the disease course. Among available MS treatments, cladribine is emerging as a promising option due to its role as a selective immune reconstitution therapy, with a notable impact on B cells and a lesser effect on T cells. This work emphasizes the assessment of MRI's contribution to MS treatment, particularly focusing on the influence of cladribine tablets on imaging outcomes, encompassing data from pivotal and real-world studies. The evidence highlights that cladribine, compared with placebo, not only exhibits a reduction in inflammatory imaging markers, such as T1-Gd+, T2 and combined unique active (CUA) lesions, but also mitigates the effect on brain volume loss, particularly within grey matter. Importantly, cladribine reveals early action by reducing CUA lesions within the first months of treatment, regardless of a patient's initial conditions. The selective mechanism of action, and sustained efficacy beyond year 2, combined with its early onset of action, collectively position cladribine tablets as a pivotal component in the therapeutic paradigm for MS. Overall, MRI, along with clinical measures, has played a substantial role in showcasing the effectiveness of cladribine in addressing both the inflammatory and neurodegenerative aspects of MS.

Assessing robustness and generalization of a deep neural network for brain MS lesion segmentation on real-world data

OBJECTIVES

Evaluate the performance of a deep learning (DL)-based model for multiple sclerosis (MS) lesion segmentation and compare it to other DL and non-DL algorithms.

METHODS

This ambispective, multicenter study assessed the performance of a DL-based model for MS lesion segmentation and compared it to alternative DL- and non-DL-based methods. Models were tested on internal (n = 20) and external (n = 18) datasets from Latin America, and on an external dataset from Europe (n = 49). We also examined robustness by rescanning six patients (n = 6) from our MS clinical cohort. Moreover, we studied inter-human annotator agreement and discussed our findings in light of these results. Performance and robustness were assessed using intraclass correlation coefficient (ICC), Dice coefficient (DC), and coefficient of variation (CV).

RESULTS

Inter-human ICC ranged from 0.89 to 0.95, while spatial agreement among annotators showed a median DC of 0.63. Using expert manual segmentations as ground truth, our DL model achieved a median DC of 0.73 on the internal, 0.66 on the external, and 0.70 on the challenge datasets. The performance of our DL model exceeded that of the alternative algorithms on all datasets. In the robustness experiment, our DL model also achieved higher DC (ranging from 0.82 to 0.90) and lower CV (ranging from 0.7 to 7.9%) when compared to the alternative methods.

CONCLUSION

Our DL-based model outperformed alternative methods for brain MS lesion segmentation. The model also proved to generalize well on unseen data and has a robust performance and low processing times both on real-world and challenge-based data.

CLINICAL RELEVANCE STATEMENT

Our DL-based model demonstrated superior performance in accurately segmenting brain MS lesions compared to alternative methods, indicating its potential for clinical application with improved accuracy, robustness, and efficiency.

KEY POINTS

• Automated lesion load quantification in MS patients is valuable; however, more accurate methods are still necessary. • A novel deep learning model outperformed alternative MS lesion segmentation methods on multisite datasets. • Deep learning models are particularly suitable for MS lesion segmentation in clinical scenarios.

Consensus recommendations for diagnosis and treatment of Multiple Sclerosis: 2023 revision of the MENACTRIMS guidelines

With evolving diagnostic criteria and the advent of new oral and parenteral therapies for Multiple Sclerosis (MS), most current diagnostic and treatment algorithms need revision and updating. The diagnosis of MS relies on incorporating clinical and paraclinical findings to prove dissemination in space and time and exclude alternative diseases that can explain the findings at hand. The differential diagnostic workup should be guided by clinical and laboratory red flags to avoid unnecessary tests. Appropriate selection of MS therapies is critical to maximize patient benefit. The current guidelines review the current diagnostic criteria for MS and the scientific evidence supporting treatment of acute relapses, radiologically isolated syndrome, clinically isolated syndrome, relapsing remitting MS, progressive MS, pediatric cases and pregnant women. The purpose of these guidelines is to provide practical recommendations and algorithms for the diagnosis and treatment of MS based on current scientific evidence and clinical experience.

Assessing treatment response to oral drugs for multiple sclerosis in real-world setting: a MAGNIMS Study

BACKGROUND

The assessment of treatment response is a crucial step for patients with relapsing-remitting multiple sclerosis on disease-modifying therapies (DMTs). We explored whether a scoring system developed within the MAGNIMS (MRI in Multiple Sclerosis) network to evaluate treatment response to injectable drugs can be adopted also to oral DMTs.

METHODS

A multicentre dataset of 1200 patients who started three oral DMTs (fingolimod, teriflunomide and dimethyl fumarate) was collected within the MAGNIMS network. Disease activity after the first year was classified by the 'MAGNIMS' score based on the combination of relapses (0-≥2) and/or new T2 lesions (<3 or ≥3) on brain MRI. We explored the association of this score with the following 3-year outcomes: (1) confirmed disability worsening (CDW); (2) treatment failure (TFL); (3) relapse count between years 1 and 3. The additional value of contrast-enhancing lesions (CELs) and lesion location was explored.

RESULTS

At 3 years, 160 patients experienced CDW: 12% of them scored '0' (reference), 18% scored '1' (HR=1.82, 95% CI 1.20 to 2.76, p=0.005) and 37% scored '2' (HR=2.74, 95% CI 1.41 to 5.36, p=0.003) at 1 year. The analysis of other outcomes provided similar findings. Considering the location of new T2 lesions (supratentorial vs infratentorial/spinal cord) and the presence of CELs improved the prediction of CDW and TFL, respectively, in patients with minimal MRI activity alone (one or two new T2 lesions).

CONCLUSIONS

Early relapses and substantial MRI activity in the first year of treatment are associated with worse short-term outcomes in patients treated with some of the oral DMTs.

No Evidence of Disease Activity (NEDA) as a Clinical Assessment Tool for Multiple Sclerosis: Clinician and Patient Perspectives [Narrative Review]

The emergence of high-efficacy therapies for multiple sclerosis (MS), which target inflammation more effectively than traditional disease-modifying therapies, has led to a shift in MS management towards achieving the outcome assessment known as no evidence of disease activity (NEDA). The most common NEDA definition, termed NEDA-3, is a composite of three related measures of disease activity: no clinical relapses, no disability progression, and no radiological activity. NEDA has been frequently used as a composite endpoint in clinical trials, but there is growing interest in its use as an assessment tool to help patients and healthcare professionals navigate treatment decisions in the clinic. Raising awareness about NEDA may therefore help patients and clinicians make more informed decisions around MS management and improve overall MS care. This review aims to explore the potential utility of NEDA as a clinical decision-making tool and treatment target by summarizing the literature on its current use in the context of the expanding treatment landscape. We identify current challenges to the use of NEDA in clinical practice and detail the proposed amendments, such as the inclusion of alternative outcomes and biomarkers, to broaden the clinical information captured by NEDA. These themes are further illustrated with the real-life perspectives and experiences of our two patient authors with MS. This review is intended to be an educational resource to support discussions between clinicians and patients on this evolving approach to MS-specialized care.

Changes in leukoencephalopathy and serum neurofilament after (neo)adjuvant chemotherapy for breast cancer

BACKGROUND

Previous case studies have provided evidence for chemotherapy-induced leukoencephalopathy in patients with breast cancer. However, prospective research is lacking. Hence, we investigated leukoencephalopathy before and after chemotherapy and its association with a serum neuroaxonal damage marker.

METHODS

This prospective cohort study included 40 patients receiving chemotherapy for breast cancer, and two age- and education-matched control groups, recruited between 2018 and 2021 (31-64 years of age). The latter control groups consisted of 39 chemotherapy-naïve patients and 40 healthy women. Fluid-attenuated inversion-recovery magnetic resonance imaging was used for lesion volumetry (total, juxtacortical, periventricular, infratentorial, and deep white matter) and blood serum to measure neurofilament light chain (NfL) levels. Acquisition took place pre-chemotherapy and three months and one-year post-chemotherapy, or at corresponding intervals. Within/between group differences were compared using robust mixed-effects modeling, and associations between total lesion volume and serum-NfL with linear regression.

RESULTS

Stronger increases in deep white matter lesion volumes were observed shortly post-chemotherapy, compared with healthy women (ßstandardized=0.09, pFDR<0.001). Increases in total lesion volume could mainly be attributed to enlargement of existing lesions (mean±SD, 0.12±0.16 mL), rather than development of new lesions (0.02±0.02 mL). A stronger increase in serum-NfL concentration was observed shortly post-chemotherapy compared with both control groups (ß>0.70, p<0.004), neither of which showed any changes over time, whereas a decrease was observed compared with healthy women one-year post-chemotherapy (ß=-0.54, p = 0.002). Serum-NfL concentrations were associated with lesion volume one-year post-chemotherapy (or at matched timepoint; ß=0.36, p = 0.010), whereas baseline or short-term post-therapy levels or changes were not.

CONCLUSION

These results underscore the possibility of chemotherapy-induced leukoencephalopathy months post-treatment, as well as the added value of serum-NfL as a prognostic marker for peripheral/central neurotoxicity.

TRANSLATIONAL RELEVANCE

Previous case studies have provided evidence of chemotherapy-induced leukoencephalopathy in patients with breast cancer. However, prospective studies to estimate longitudinal changes are currently missing. In this study, we used longitudinal fluid-attenuated inversion-recovery magnetic resonance imaging to assess white matter lesion volumes in patients treated for non-metastatic breast cancer and healthy women. Our findings demonstrate that chemotherapy-treated patients exhibit stronger increases in lesion volumes compared with healthy women, specifically in deep white matter, at three months post-chemotherapy. Increases could mainly be attributed to enlargement of existing lesions, rather than development of new lesions. Last, serum concentrations of neurofilament light chain, a neuroaxonal damage marker, increased shortly after chemotherapy and long-term post-chemotherapy levels were associated with lesion volumes. These findings highlight the potential of this non-invasive serum marker as a prognostic marker for peripheral and/or central neurotoxicity. Implementation in clinical practice could aid in therapeutic decisions, assessing disease activity, or monitoring treatment response.

Prevalence of 2-year "No evidence of disease activity" (NEDA-3 and NEDA-4) in relapsing-remitting multiple sclerosis. A real-world study

BACKGROUND

No evidence of disease activity (NEDA) is becoming a gold standard in the evaluation of disease modifying therapies (DMT) in relapsing-remitting multiple sclerosis (RRMS). NEDA-3 status is the absence of relapses, new activity on brain MRI, and disability progression. NEDA-4 meets all NEDA-3 criteria plus lack of brain atrophy.

OBJECTIVE

Aim of this study was to investigate the prevalence of two-year NEDA-3, NEDA-4, six-month delayed NEDA-3 (6mdNEDA-3), and six-month delayed NEDA-4 (6mdNEDA-4) in a cohort of patients with RRMS. Six-month delayed measures were introduced to consider latency of action of drugs.

METHODS

Observational retrospective monocentric study. All the patients with RRMS starting DMT between 2015 and 2018, and with 2-year of follow-up, were included. Annualized brain volume loss (a-BVL) was calculated by SIENA software.

RESULTS

We included 108 patients, the majority treated with first line DMT. At 2-year follow-up, 35 % of patients were NEDA-3 (50 % 6mdNEDA-3), and 17 % NEDA-4 (28 % 6mdNEDA-4). Loss of NEDA-3 status was mainly driven by MRI activity (70 %), followed by relapses (56 %), and only minimally by disability progression (7 %).

CONCLUSION

In our cohort 2-year NEDA status, especially including lack of brain atrophy, was hard to achieve. Further studies are needed to establish the prognostic value of NEDA-3 and NEDA4 in the long-term follow-up.

Effectiveness of teriflunomide on No Evidence of Disease Activity and cognition in relapsing remitting multiple sclerosis: results of the NEDA3PLUS study

BACKGROUND

Cognitive impairment (CI) is a prevalent and debilitating manifestation of multiple sclerosis (MS); however, it is not included in the widely used concept of No Evidence of Disease Activity (NEDA-3). We expanded the NEDA-3 concept to NEDA-3 + by encompassing CI assessed through the Symbol Digit Modality Test (SDMT) and evaluated the effect of teriflunomide on NEDA3 + in patients treated in a real-world setting. The value of NEDA-3 + in predicting disability progression was also assessed.

METHODS

This 96-weeks observational study enrolled patients already on treatment with teriflunomide for ≥ 24 weeks. The predictiveness of NEDA-3 and NEDA-3 + at 48 weeks on the change in motor disability at 96 weeks was compared through a two-sided McNemar test.

RESULTS

The full analysis set (n = 128; 38% treatment naïve) featured relatively low level of disability (baseline EDSS = 1.97 ± 1.33). NEDA-3 and NEDA-3 + statuses were achieved by 82.8% and 64.8% of patients, respectively at 48 weeks vs. baseline, and by 57.0% and 49.2% of patients, respectively at 96 weeks vs. baseline. All patients except one were free of disability progression at Week 96, and NEDA-3 and NEDA-3 + were equally predictive. Most patients were free of relapse (87.5%), disability progression (94.5%) and new MRI activity (67.2%) comparing 96 weeks with baseline. SDMT scores were stable in patients with baseline score ˃35 and improved significantly in those with baseline score ≤ 35. Treatment persistence was high (81.0% at Week 96).

CONCLUSION

Teriflunomide confirmed its real-world efficacy and was found to have a potentially beneficial effect on cognition.

Assessing Sustained B-Cell Depletion and Disease Activity in a French Multiple Sclerosis Cohort Treated by Long-Term IV Anti-CD20 Antibody Therapy

Few studies have investigated sustained B-cell depletion after long-term intravenous (IV) anti-CD20 B-cell depleting therapy (BCDT) in multiple sclerosis (MS) with respect to strict and/or minimal disease activity. The main objective of this study was to investigate how sustained B-cell depletion after BCDT influences clinical and radiological stability as defined by "no evidence of disease activity" (NEDA-3) and "minimal evidence of disease activity" (MEDA) status in MS patients at 12 and 18 months. Furthermore, we assessed the frequency of serious adverse events (SAE), and the influence of prior lymphocytopenia-inducing treatment (LIT) on lymphocyte subset counts and gammaglobulins in MS patients receiving long-term BCDT. We performed a retrospective, prospectively collected, study in a cohort of 192 MS patients of all clinical phenotypes treated by BCDT between January 2014 and September 2021. Overall, 84.2% and 96.9% of patients attained NEDA-3 and MEDA status at 18 months, respectively. Sustained CD19+ depletion was observed in 85.8% of patients at 18 months. No significant difference was observed when comparing patients achieving either NEDA-3 or MEDA at 18 months and sustained B-cell depletion. Compared to baseline levels, IgM and IgG levels on BCDT significantly decreased at 6 months and 30 months, respectively. Patients receiving LIT prior to BCDT showed significant CD4+ lymphocytopenia and lower IgG levels compared to non-LIT patients. Grade 3 or above SAEs were rare. As nearly all patients achieved MEDA at 18 months, we suggest tailoring IV BCDT after 18 months given the occurrence of lymphocytopenia, hypogammaglobulinemia, and SAE after this time point.

Building a monitoring matrix for the management of multiple sclerosis

Multiple sclerosis (MS) has a longitudinal and heterogeneous course, with an increasing number of therapy options and associated risk profiles, leading to a constant increase in the number of parameters to be monitored. Even though important clinical and subclinical data are being generated, treating neurologists may not always be able to use them adequately for MS management. In contrast to the monitoring of other diseases in different medical fields, no target-based approach for a standardized monitoring in MS has been established yet. Therefore, there is an urgent need for a standardized and structured monitoring as part of MS management that is adaptive, individualized, agile, and multimodal-integrative. We discuss the development of an MS monitoring matrix which can help facilitate data collection over time from different dimensions and perspectives to optimize the treatment of people with MS (pwMS). In doing so, we show how different measurement tools can combined to enhance MS treatment. We propose to apply the concept of patient pathways to disease and intervention monitoring, not losing track of their interrelation. We also discuss the use of artificial intelligence (AI) to improve the quality of processes, outcomes, and patient safety, as well as personalized and patient-centered care. Patient pathways allow us to track the patient's journey over time and can always change (e.g., when there is a switch in therapy). They therefore may assist us in the continuous improvement of monitoring in an iterative process. Improving the monitoring process means improving the care of pwMS.

Rs205764 and rs547311 in linc00513 may influence treatment responses in multiple sclerosis patients: A pharmacogenomics Egyptian study

Background

Multiple sclerosis (MS) is characterized by a complex etiology that is reflected in the lack of consistently predictable treatment responses across patients of seemingly similar characteristics. Approaches to demystify the underlying predictors of aberrant treatment responses have made use of genome-wide association studies (GWAS), with imminent progress made in identifying single nucleotide polymorphisms (SNPs) associated with MS risk, disease progression, and treatment response. Ultimately, such pharmacogenomic studies aim to utilize the approach of personalized medicine to maximize patient benefit and minimize rate of disease progression.

Objective

Very limited research is available around the long intergenic non-coding RNA (linc)00513, recently being reported as a novel positive regulator of the type-1 interferon (IFN) pathway, following its overexpression in the presence of two polymorphisms: rs205764 and rs547311 in the promoter region of this gene. We attempt to provide data on the prevalence of genetic variations at rs205764 and rs547311 in Egyptian MS patients, and correlate these polymorphisms with the patients' responses to disease-modifying treatments.

Methods

Genomic DNA from 144 RRMS patients was isolated and analyzed for genotypes at the positions of interest on linc00513 using RT-qPCR. Genotype groups were compared with regards to their response to treatment; additional secondary clinical parameters including the estimated disability status score (EDSS), and onset of the disease were examined in relation to these polymorphisms.

Results

Polymorphisms at rs205764 were associated with a significantly higher response to fingolimod and a significantly lower response to dimethylfumarate. Moreover, the average EDSS of patients carrying polymorphisms at rs547311 was significantly higher, whereas no correlation appeared to exist with the onset of MS.

Conclusion

Understanding the complex interplay of factors influencing treatment response is pivotal in MS. One of the factors contributing to a patient's response to treatment, as well as disease disability, may be polymorphisms on non-coding genetic material, such as rs205764 and rs547311 on linc00513. Through this work, we propose that genetic polymorphisms may partially drive disease disability and inconsistent responses to treatment in MS; we also aim to draw attention towards genetic approaches, such as screening for specific polymorphisms, to possibly direct treatment choices in such a complex disease.

Peripheral myeloid-derived suppressor cells are good biomarkers of the efficacy of fingolimod in multiple sclerosis

Background

The increasing number of treatments that are now available to manage patients with multiple sclerosis (MS) highlights the need to develop biomarkers that can be used within the framework of individualized medicine. Fingolimod is a disease-modifying treatment that belongs to the sphingosine-1-phosphate receptor modulators. In addition to inhibiting T cell egress from lymph nodes, fingolimod promotes the immunosuppressive activity of myeloid-derived suppressor cells (MDSCs), whose monocytic subset (M-MDSCs) can be used as a biomarker of disease severity, as well as the degree of demyelination and extent of axonal damage in the experimental autoimmune encephalomyelitis (EAE) model of MS. In the present study, we have assessed whether the abundance of circulating M-MDSCs may represent a useful biomarker of fingolimod efficacy in EAE and in the clinical context of MS patients.

Methods

Treatment with vehicle or fingolimod was orally administered to EAE mice for 14 days in an individualized manner, starting the day when each mouse began to develop clinical signs. Peripheral blood from EAE mice was collected previous to treatment and human peripheral blood mononuclear cells (PBMCs) were collected from fingolimod to treat MS patients’ peripheral blood. In both cases, M-MDSCs abundance was analyzed by flow cytometry and its relationship with the future clinical affectation of each individual animal or patient was assessed.

Results

Fingolimod-treated animals presented a milder EAE course with less demyelination and axonal damage, although a few animals did not respond well to treatment and they invariably had fewer M-MDSCs prior to initiating the treatment. Remarkably, M-MDSC abundance was also found to be an important and specific parameter to distinguish EAE mice prone to better fingolimod efficacy. Finally, in a translational effort, M-MDSCs were quantified in MS patients at baseline and correlated with different clinical parameters after 12 months of fingolimod treatment. M-MDSCs at baseline were highly representative of a good therapeutic response to fingolimod, i.e., patients who met at least two of the criteria used to define non-evidence of disease activity-3 (NEDA-3) 12 months after treatment.

Conclusion

Our data indicate that M-MDSCs might be a useful predictive biomarker of the response of MS patients to fingolimod.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12974-022-02635-3.

Rebaseline no evidence of disease activity (NEDA-3) as a predictor of long-term disease course in a Norwegian multiple sclerosis population

INTRODUCTION

No evidence of disease activity with three components (NEDA-3) is achieved if the person with MS (pwMS) has no new MRI lesions, no new relapses and no change in Expanded disability status scale (EDSS) over 1 year. Whether NEDA-3 is a good tool in measuring disease activity is up for discussion, but it is superior to the individual parameters separately and user-friendly. There is disagreement on whether NEDA-3 is a good predictor of long-term disability.

METHODS

This is a retrospective cohort study using real-world data with limited selection bias from the complete MS population at two hospitals in the southeast of Norway. We included pwMS diagnosed between 2006 and 2017 who had enough information to determine time to failure of NEDA-3 after diagnosis.

RESULTS

Of 536 pwMS, only 38% achieved NEDA 1 year after diagnosis. PwMS achieving NEDA were more likely to be started on a high efficacy drug as the initial drug, but there were no demographic differences. Mean time to NEDA failure was 3.3 (95% CI 2.9-3.7) years. Starting a high efficiacy therapy was associated with an increased risk of sustaining NEDA as compared to those receiving moderate efficacy therapy. PwMS who achieved NEDA at year one had a mean time to EDSS 6 of 33.8 (95% CI 30.9-36.8) years vs. 30.8 (95% CI 25.0-36.6) years in pwMS who did not achieve NEDA, p < 0.001. When rebaselining NEDA 1 year after diagnosis, 52.2% achieved NEDA in the 1st year after rebaseline, mean time to NEDA failure was 3.4 (95% CI 3.0-3.7) years and mean time to EDSS 6 was 44.5 (95% CI 40.4-48.5) years in pwMS achieving NEDA vs. 29.6 (95% CI 24.2-35.0) years in pwMS not achieving NEDA, p < 0.001. After rebaseline, pwMS with a high efficacy therapy as the initial drug had a mean time from diagnosis to NEDA fail of 4.8 years (95% CI 3.9-5.8) vs. 3.1 years (95% CI 2.7-3.5) in pwMS started on a moderate efficacy therapy, p < 0.001. In pwMS with NEDA failure at year one, 70% failed one, 28% failed two and 2% failed three components. New MRI lesions were the most common cause of NEDA failure (63%), followed by new relapses (50%) and EDSS change (25%).

CONCLUSION

NEDA-3 from rebaseline after 1 year, once treatment is stabilized, can predict the long-term disease course in MS. Starting a high efficacy DMT is associated with longer time to NEDA failure than moderate therapies. Finally, most pwMS only fail one component and new MRI lesions are the most likely cause of NEDA failure.

Association of NEDA-4 With No Long-term Disability Progression in Multiple Sclerosis and Comparison With NEDA-3: A Systematic Review and Meta-analysis

Background and Objectives

No evidence of disease activity (NEDA)-4 has been suggested as a treatment target for disease-modifying therapy (DMT) in relapsing-remitting multiple sclerosis (RRMS). However, the ability of NEDA-4 to discriminate long-term outcomes in MS and how its performance compares with NEDA-3 remain uncertain. We conducted a systematic review and meta-analysis to evaluate (1) the association between NEDA-4 and no long-term disability progression in MS and (2) the comparative performance of NEDA-3 and NEDA-4 in predicting no long-term disability progression.

Methods

English-language abstracts and manuscripts were systematically searched in MEDLINE, Embase, and the Cochrane databases from January 2006 to November 2021 and reviewed independently by 2 investigators. We selected studies that assessed NEDA-4 at 1 or 2 years after DMT start and had at least 4 years of follow-up for determination of no confirmed disability progression. We conducted a meta-analysis using random-effects model to determine the pooled odds ratio (OR) for no disability progression with NEDA-4 vs EDA-4. For the comparative analysis, we selected studies that evaluated both NEDA-3 and NEDA-4 with at least 4 years of follow-up and examined the difference in the association of NEDA-3 and NEDA-4 with no disability progression.

Results

Five studies of 1,000 patients (3 interferon beta and 2 fingolimod) met inclusion criteria for both objectives. The median duration of follow-up was 6 years (interquartile range: 4–6 years). The prevalence of NEDA-4 ranged from 4.2% to 13.9% on interferon beta therapy and 24.9% to 25.1% on fingolimod therapy. The pooled OR for no long-term confirmed disability progression with NEDA-4 vs EDA-4 was 2.14 (95% confidence interval: 1.36–3.37; I² = 0). We did not observe any significant difference between NEDA-4 and NEDA-3 in the comparative analyses.

Discussion

In patients with RRMS, NEDA-4 at 1–2 years was associated with 2 times higher odds of no long-term disability progression, at 6 years compared with EDA-4, but offered no advantage over NEDA-3.

Evaluation of Disability Progression in Multiple Sclerosis via Magnetic-Resonance-Based Deep Learning Techniques

Short-term disability progression was predicted from a baseline evaluation in patients with multiple sclerosis (MS) using their three-dimensional T1-weighted (3DT1) magnetic resonance images (MRI). One-hundred-and-eighty-one subjects diagnosed with MS underwent 3T-MRI and were followed up for two to six years at two sites, with disability progression defined according to the expanded-disability-status-scale (EDSS) increment at the follow-up. The patients’ 3DT1 images were bias-corrected, brain-extracted, registered onto MNI space, and divided into slices along coronal, sagittal, and axial projections. Deep learning image classification models were applied on slices and devised as ResNet50 fine-tuned adaptations at first on a large independent dataset and secondly on the study sample. The final classifiers’ performance was evaluated via the area under the curve (AUC) of the false versus true positive diagram. Each model was also tested against its null model, obtained by reshuffling patients’ labels in the training set. Informative areas were found by intersecting slices corresponding to models fulfilling the disability progression prediction criteria. At follow-up, 34% of patients had disability progression. Five coronal and five sagittal slices had one classifier surviving the AUC evaluation and null test and predicted disability progression (AUC > 0.72 and AUC > 0.81, respectively). Likewise, fifteen combinations of classifiers and axial slices predicted disability progression in patients (AUC > 0.69). Informative areas were the frontal areas, mainly within the grey matter. Briefly, 3DT1 images may give hints on disability progression in MS patients, exploiting the information hidden in the MRI of specific areas of the brain.

Association of No Evidence of Disease Activity With No Long-term Disability Progression in Multiple Sclerosis: A Systematic Review and Meta-analysis

BACKGROUND AND OBJECTIVES

We conducted a systematic review and meta-analysis to evaluate the relationship between no evidence of disease activity (NEDA) and no long-term disability progression on low- and high-efficacy therapy in relapsing-remitting multiple sclerosis (RRMS).

METHODS

MEDLINE, Embase, and the Cochrane Database were searched from January 1, 2006, to January 26, 2021. We selected studies that evaluated NEDA-3 (no relapse, new MRI lesion, or confirmed disability progression) at 1 or 2 years and had a minimum of 4 years of follow-up for determination of disability progression. Data were extracted by 2 independent reviewers and were meta-analyzed with a random-effects model. Primary outcome of no disability progression was defined as no confirmed progression on the Expanded Disability Status Scale during follow-up. We assessed the odds ratio (OR) for no disability progression with NEDA vs evidence of disease activity (EDA). Positive predictive value (PPV) of NEDA for no disability progression was summarized for studies with prevalence of no progression >80% vs ≤80% separately.

RESULTS

We included 29 studies in our qualitative synthesis, of which 27 (16 low efficacy, 11 high efficacy) were included in the meta-analysis (N = 10,935 participants). Median follow-up was 5.6 years (interquartile range 4.3-8.0 years). The pooled ORs for no progression with NEDA-3 vs EDA were 2.32 (95% CI 1.58-3.42; I 2 = 73%) for low-efficacy therapy and 3.19 (95% CI 1.86-5.47; I 2 = 86%) for high-efficacy therapy. Among studies with prevalence of no progression at follow-up >80%, the pooled PPV for low efficacy therapy was 91% (95% CI 89%-93%) and for high-efficacy therapy was 92% (95% CI 88%-94%). Among studies with prevalence of no progression ≤80%, the pooled PPV for low-efficacy therapy was 81% (95% CI 75%-86%) and for high-efficacy therapy was 86% (95% CI 80%-90%).

DISCUSSION

NEDA-3 is associated with no long-term disability progression in RRMS on both low- and high-efficacy therapies. Further studies of early composite outcome measures incorporating easily measurable biomarkers and longer follow-up may help to improve the prognostic value of NEDA-3 in RRMS.

TRIAL REGISTRATION INFORMATION

International Prospective Register of Systematic Reviews Identifier: CRD42020189316.

Immunotherapy for people with clinically isolated syndrome or relapsing-remitting multiple sclerosis: treatment response by demographic, clinical, and biomarker subgroups (PROMISE)-a systematic review protocol

BACKGROUND

Multiple sclerosis (MS) is an inflammatory and degenerative disease of the central nervous system with an increasing worldwide prevalence. Since 1993, more than 15 disease-modifying immunotherapies (DMTs) have been licenced and have shown moderate efficacy in clinical trials. Based on the heterogeneity of the disease and the partial effectiveness of therapies, a personalised medicine approach would be valuable taking individual prognosis and suitability of a chosen therapy into account to gain the best possible treatment effect. The primary objective of this review is to assess the differential treatment effects of all approved DMTs in subgroups of adults with clinically isolated syndrome or relapsing forms of MS. We will analyse possible treatment effect modifiers (TEM) defined by baseline demographic characteristics (gender, age), and diagnostic (i.e. MRI measures) and clinical (i.e. relapses, disability level) measures of MS disease activity.

METHODS

We will include all published and accessible unpublished primary and secondary analyses of randomised controlled trials (RCTs) with a follow-up of at least 12 months investigating the efficacy of at least one approved DMT, with placebo or other approved DMTs as control intervention(s) in subgroups of trial participants. As the primary outcome, we will address disability as defined by the Expanded Disability Status Scale or multiple sclerosis functional composite scores followed by relapse frequency, quality of life measures, and side effects. MRI data will be analysed as secondary outcomes. MEDLINE, EMBASE, CINAHL, LILACS, CENTRAL and major trial registers will be searched for suitable studies. Titles and abstracts and full texts will be screened by two persons independently using Covidence. The risk of bias will be analysed based on the Cochrane "Risk of Bias 2" tool, and the certainty of evidence will be assessed using GRADE. Treatment effects will be reported as rate ratio or odds ratio. Primary analyses will follow the intention-to-treat principle. Meta-analyses will be carried out using random-effects models.

DISCUSSION

Given that individual patient data from clinical studies are often not available, the review will allow to analyse the evidence on TEM in MS immunotherapy and thus support clinical decision making in individual cases.

SYSTEMATIC REVIEW REGISTRATION

PROSPERO CRD42021279665 .

Predicting disease activity in patients with multiple sclerosis: An explainable machine‐learning approach in the Mavenclad trials

Multiple sclerosis (MS) is among the most common autoimmune disabling neurological conditions of young adults and affects more than 2.3 million people worldwide. Predicting future disease activity in patients with MS based on their pathophysiology and current treatment is pivotal to orientate future treatment. In this respect, we used machine learning to predict disease activity status in patients with MS and identify the most predictive covariates of this activity. The analysis is conducted on a pooled population of 1935 patients enrolled in three cladribine tablets clinical trials with different outcomes: relapsing–remitting MS (from CLARITY and CLARITY‐Extension trials) and patients experiencing a first demyelinating event (from the ORACLE‐MS trial). We applied gradient‐boosting (from XgBoost library) and Shapley Additive Explanations (SHAP) methods to identify patients' covariates that predict disease activity 3 and 6 months before their clinical observation, including patient baseline characteristics, longitudinal magnetic resonance imaging readouts, and neurological and laboratory measures. The most predictive covariates for early identification of disease activity in patients were found to be treatment duration, higher number of new combined unique active lesion count, higher number of new T1 hypointense black holes, and higher age‐related MS severity score. The outcome of this analysis improves our understanding of the mechanism of onset of disease activity in patients with MS by allowing their early identification in clinical settings and prompting preventive measures, therapeutic interventions, or more frequent patient monitoring.

Humanized Anti-RGMa Antibody Treatment Promotes Repair of Blood-Spinal Cord Barrier Under Autoimmune Encephalomyelitis in Mice

The lack of established biomarkers which reflect dynamic neuropathological alterations in multiple sclerosis (MS) makes it difficult to determine the therapeutic response to the tested drugs and to identify the key biological process that mediates the beneficial effect of them. In the present study, we applied high-field MR imaging in locally-induced experimental autoimmune encephalomyelitis (EAE) mice to evaluate dynamic changes following treatment with a humanized anti-repulsive guidance molecule-a (RGMa) antibody, a potential drug for MS. Based on the longitudinal evaluation of various MRI parameters including white matter, axon, and myelin integrity as well as blood-spinal cord barrier (BSCB) disruption, anti-RGMa antibody treatment exhibited a strong and prompt therapeutic effect on the disrupted BSCB, which was paralleled by functional improvement. The antibody’s effect on BSCB repair was also suggested via GeneChip analysis. Moreover, immunohistochemical analysis revealed that EAE-induced vascular pathology which is characterized by aberrant thickening of endothelial cells and perivascular type I/IV collagen deposits were attenuated by anti-RGMa antibody treatment, further supporting the idea that the BSCB is one of the key therapeutic targets of anti-RGMa antibody. Importantly, the extent of BSCB disruption detected by MRI could predict late-phase demyelination, and the predictability of myelin integrity based on the extent of acute-phase BSCB disruption was compromised following anti-RGMa antibody treatment. These results strongly support the concept that longitudinal MRI with simultaneous DCE-MRI and DTI analysis can be used as an imaging biomarker and is useful for unbiased prioritization of the key biological process that mediates the therapeutic effect of tested drugs.

Nonlesional Sources of Contrast Enhancement on Postgadolinium "Black-Blood" 3D T1-SPACE Images in Patients with Multiple Sclerosis

BACKGROUND AND PURPOSE

We hypothesized that 3D T1-TSE "black-blood" images may carry an increased risk of contrast-enhancing lesion misdiagnosis in patients with MS because of the misinterpretation of intraparenchymal vein enhancement. Thus, the occurrence of true-positive and false-positive findings was compared between standard MPRAGE and volumetric interpolated brain examination techniques.

MATERIALS AND METHODS

Sampling perfection with application-optimized contrasts by using different flip-angle evolution (SPACE) images obtained from 232 patients with MS, clinically isolated syndrome, or radiologically isolated syndrome were compared with standard MPRAGE and volumetric interpolated brain examination images. The intraparenchymal vein contrast-to-noise ratio was estimated at the level of the thalami. Contrast-enhancing lesions were blindly detected by 2 expert readers and 1 beginner reader. True- and false-positives were determined by senior readers' consensus. True-positive and false-positive frequency differences and patient-level diagnosis probability were tested with the McNemar test and OR. The contrast-to-noise ratio and morphology were compared using the Mann-Whitney U and χ² tests.

RESULTS

The intraparenchymal vein contrast-to-noise ratio was higher in SPACE than in MPRAGE and volumetric interpolated brain examination images (P < .001, both). There were 66 true-positives and 74 false-positives overall. SPACE detected more true-positive and false-positive results (P range < .001-.07) but did not increase the patient's true-positive likelihood (OR = 1 1.29, P = .478-1). However, the false-positive likelihood was increased (OR = 3.03-3.55, P = .008-.027). Venous-origin false-positives (n = 59) with contrast-to-noise ratio and morphology features similar to small-sized (≤14 mm³ P = .544) true-positives occurred more frequently in SPACE images (P < .001).

CONCLUSIONS

Small intraparenchymal veins may confound the diagnosis of enhancing lesions on postgadolinium black-blood SPACE images.

Effectiveness and Cost-Effectiveness of 360 Disease-Modifying Treatment Escalation Sequences in Multiple Sclerosis

OBJECTIVES

The rapid expansion in treatment options for relapsing-remitting multiple sclerosis (RRMS) of the past decade requires clinical decision making on the sequential prescription of these treatments. Here, we compare 360 treatment escalation sequences for patients with RRMS in terms of health outcomes and societal costs in The Netherlands.

METHODS

We use a microsimulation model with a societal perspective, developed in collaboration with MS neurologists, to estimate the effectiveness and cost-effectiveness of 360 treatment sequences starting with first-line therapies in RRMS. This model integrated data on disease progression, disease-modifying treatment efficacy, clinical decision rules, age-dependent relapse rates, quality of life, healthcare, and societal costs.

RESULTS

Costs and health outcomes were overlapping among different treatment escalation sequences. In our model for RRMS treatment, optimal lifetime health outcomes (20.24 ± 1.43 quality-adjusted life-years [QALYs], 6.11 ± 0.30 relapses) were achieved with the sequence peginterferon-dimethyl fumarate-ocrelizumab-natalizumab-alemtuzumab. The most cost-effective sequence (peginterferon-glatiramer acetate-ocrelizumab-cladribine-alemtuzumab) yielded numerically worse health outcomes per patient (19.59 ± 1.43 QALYs, 6.64 ± 0.43 relapses), but resulted in €98 127 ± €19 134 less costs than the most effective treatment sequence.

CONCLUSIONS

Effectiveness estimates of treatments have overlapping confidence intervals but the treatment sequence that yields most QALYs is not the most cost-effective option, also when taking uncertainty into account. It is important that neurologists are aware of cost constraints and its relationship with prescription behavior, but treatment decisions should be individually tailored.

Early use of high-efficacy disease‑modifying therapies makes the difference in people with multiple sclerosis: an expert opinion

Multiple sclerosis (MS) is a chronic and progressive neurological disease that is characterized by neuroinflammation, demyelination and neurodegeneration occurring from the earliest phases of the disease and that may be underestimated. MS patients accumulate disability through relapse-associated worsening or progression independent of relapse activity. Early intervention with high-efficacy disease-modifying therapies (HE-DMTs) may represent the best window of opportunity to delay irreversible central nervous system damage and MS-related disability progression by hindering underlying heterogeneous pathophysiological processes contributing to disability progression. In line with this, growing evidence suggests that early use of HE-DMTs is associated with a significant greater reduction not only of inflammatory activity (clinical relapses and new lesion formation at magnetic resonance imaging) but also of disease progression, in terms of accumulation of irreversible clinical disability and neurodegeneration compared to delayed HE-DMT use or escalation strategy. These beneficial effects seem to be associated with acceptable long-term safety risks, thus configuring this treatment approach as that with the most positive benefit/risk profile. Accordingly, it should be mandatory to treat people with MS early with HE-DMTs in case of prognostic factors suggestive of aggressive disease, and it may be advisable to offer an HE-DMT to MS patients early after diagnosis, taking into account drug safety profile, disease severity, clinical and/or radiological activity, and patient-related factors, including possible comorbidities, family planning, and patients’ preference in agreement with the EAN/ECTRIMS and AAN guidelines. Barriers for an early use of HE-DMTs include concerns for long-term safety, challenges in the management of treatment initiation and monitoring, negative MS patients’ preferences, restricted access to HE-DMTs according to guidelines and regulatory rules, and sustainability. However, these barriers do not apply to each HE-DMT and none of these appear insuperable.

Predictive value of number and volume of demyelinating plaques in treatment response in patients with multiple sclerosis treated with INF-B

BACKGROUND

Multiple Sclerosis (MS) is an autoimmune, inflammatory disease of the central nervous system. Magnetic resonance imaging (MRI) findings are associated with disease clinical activity and response to treatment. This study aimed to evaluate the future value of plaque number and volume in MRI as radiological criteria in determining the treatment response to INF-B in patients with MS.

METHODS

This is a cross-sectional study performed in 2016-2021 in Iran on patients with the newly diagnosed (less than one year) relapsing-remitting MS. Brain MRI was taken for all patients. The number and volumes of the MS plaques were evaluated from FLAIR images by the two radiologists. Patients were treated with INF-B1a with a dosage of 12 million units equal to 44 micrograms subcutaneously, three times per week. Patients were visited monthly by neurologists to examine their clinical status. After one year, the brain MRI was conducted with the similar characteristics to the beginning of the study, and the number and volume of MS plaques were measured again.

RESULTS

The study population consisted of 33 males and 90 females with a mean age of 28.37 ± 6.29 years. The mean Expanded Disability Status Scale (EDSS) of the patients was 3.16 ± 0.23 at the beginning of the study. The specificity for a 50% reduction in the number and volume of plaques as two separate criteria was the same and equal to 100%. The sensitivity of the number and volume of plaques were 65.5% and 90.6%, respectively. In addition, considering 10% as the cut-off point of the number of plaques, the sensitivity of the number of plaques as a criterion was equal to the sensitivity of the plaque volume.

CONCLUSION

The results of this study showed that imaging criteria provide a more objective tool for evaluating the effectiveness of treatment. These findings indicate that the number and volume of plaques could be two reliable MRI imaging criteria for assessing therapy response. The number of plaques was less accurate than the volume of plaques.

Retinal inner nuclear layer thinning is decreased and associates with the clinical outcome in ocrelizumab-treated primary progressive multiple sclerosis

BACKGROUND

Ocrelizumab was found to decrease brain atrophy rate in primary progressive multiple sclerosis (PPMS), but no data are currently available on the effect of ocrelizumab on retinal layer thicknesses in the PPMS population.

OBJECTIVE

To assess retinal layer changes in ocrelizumab-treated PPMS and test their possible application as biomarkers of therapy response.

METHODS

36 PPMS patients, treated with ocrelizumab for at least 6 months, and 39 sex- and age-matched healthy controls (HC) were included in a blind, longitudinal study. Spectrum-domain optical coherence tomography (SD-OCT) was performed at study entry (T0) and after 6 (T6) and 12 months (T12). At month 24 (T24), patients were divided into responders (no evidence of 1-year confirmed disability progression, 1y-CDP) and non-responders (evidence of 1y-CDP).

RESULTS

At T24, 23/36 (64%) patients were considered responders and 13/36 (36%) non-responders. At T0, peripapillary retinal nerve fiber layer (pRNFL) thickness, macular ganglion cell-inner plexiform layer (GCIPL) and inner retinal layer (IRL) volume were significantly lower in PPMS compared to HC (p = 0.001 for all comparisons). At T6 and T12, non-responders significantly differed in the inner nuclear layer (INL) thinning rate compared to responders (p = 0.005 at both time-points).

CONCLUSIONS

Ocrelizumab significantly slows down INL thinning rate in PPMS responders. The longitudinal analysis of retina layer changes by means of OCT may be a promising prognostic test, and merits further investigations.

Treatment response scoring systems to assess long-term prognosis in self-injectable DMTs relapsing-remitting multiple sclerosis patients

BACKGROUND AND OBJECTIVES

Different treatment response scoring systems in treated MS patients exist. The objective was to assess the long-term predictive value of these systems in RRMS patients treated with self-injectable DMTs.

METHODS

RRMS-treated patients underwent brain MRI before the onset of therapy and 12 months thereafter, and neurological assessments every 6 months. Clinical and demographic characteristics were collected at baseline. After the first year of treatment, several scoring systems [Rio score (RS), modified Rio score (MRS), MAGNIMS score (MS), and ROAD score (RoS)] were calculated. Cox-Regression and survival analyses were performed to identify scores predicting long-term disability.

RESULTS

We included 319 RRMS patients. Survival analyses showed that patients with RS > 1 and RoS > 3 had a significant risk of reaching an EDSS of 4.0 and 6.0 The score with the best sensitivity (61%) was the RoS, while the MRS showed the best specificity (88%). The RS showed the best positive predictive value (42%) and the best accuracy (81%).

CONCLUSIONS

The combined measures integrated into different scores have an acceptable prognostic value for identifying patients with long-term disability. Thus, these data reinforce the concept of early treatment optimization to minimize the risk of long-term disability.

Assessment of automatic decision-support systems for detecting active T2 lesions in multiple sclerosis patients

BACKGROUND

Active (new/enlarging) T2 lesion counts are routinely used in the clinical management of multiple sclerosis. Thus, automated tools able to accurately identify active T2 lesions would be of high interest to neuroradiologists for assisting in their clinical activity.

OBJECTIVE

To compare the accuracy in detecting active T2 lesions and of radiologically active patients based on different visual and automated methods.

METHODS

One hundred multiple sclerosis patients underwent two magnetic resonance imaging examinations within 12 months. Four approaches were assessed for detecting active T2 lesions: (1) conventional neuroradiological reports; (2) prospective visual analyses performed by an expert; (3) automated unsupervised tool; and (4) supervised convolutional neural network. As a gold standard, a reference outcome was created by the consensus of two observers.

RESULTS

The automated methods detected a higher number of active T2 lesions, and a higher number of active patients, but a higher number of false-positive active patients than visual methods. The convolutional neural network model was more sensitive in detecting active T2 lesions and active patients than the other automated method.

CONCLUSION

Automated convolutional neural network models show potential as an aid to neuroradiological assessment in clinical practice, although visual supervision of the outcomes is still required.

Charting a global research strategy for progressive MS-An international progressive MS Alliance proposal

BACKGROUND

Progressive forms of multiple sclerosis (MS) affect more than 1 million individuals globally. Recent approvals of ocrelizumab for primary progressive MS and siponimod for active secondary progressive MS have opened the therapeutic door, though results from early trials of neuroprotective agents have been mixed. The recent introduction of the term 'active' secondary progressive MS into the therapeutic lexicon has introduced potential confusion to disease description and thereby clinical management.

OBJECTIVE

This paper reviews recent progress, highlights continued knowledge and proposes, on behalf of the International Progressive MS Alliance, a global research strategy for progressive MS.

METHODS

Literature searches of PubMed between 2015 and May, 2021 were conducted using the search terms "progressive multiple sclerosis", "primary progressive multiple sclerosis", "secondary progressive MS". Proposed strategies were developed through a series of in-person and virtual meetings of the International Progressive MS Alliance Scientific Steering Committee.

RESULTS

Sustaining and accelerating progress will require greater understanding of underlying mechanisms, identification of potential therapeutic targets, biomarker discovery and validation, and conduct of clinical trials with improved trial design. Encouraging developments in symptomatic and rehabilitative interventions are starting to address ongoing challenges experienced by people with progressive MS.

CONCLUSION

We need to manage these challenges and realise the opportunities in the context of a global research strategy, which will improve quality of life for people with progressive MS.

The use of Modified Rio score for determining treatment failure in patients with multiple sclerosis: retrospective descriptive case series study

Predicting treatment failure and switching effective treatment immediately in patients with multiple sclerosis (MS) is important. We aimed to evaluate the usefulness of Modified Rio score (MRS) in predicting treatment failure in MS patients. This is a retrospective study, which was conducted in two University Hospital. 129 MS patients treated with İnterferon or glatiramer-acetate from 2 clinical sites, were retrospectively selected. MRS was calculated after the first year of therapy. Treatment failure was defined as the presence of a 1 point increase in EDSS, 2 clinical attacks, 1 clinical attack and progression, 1 clinical attack and new lesion on MRI except associated with an attack, or new lesion in 2 different MRI taken at least 3 months apart. The sensitivity, specificity, positive and negative predictive values of the MRS in predicting treatment failure were determined. 71 (55%) patients with score '0', 41 (31.8%) patients with score '1', 11 (8.5%) patients with score '2', 6 (4.7%) patients with score '3' were detected. 14 patients needed treatment switching during the first three years of the treatment. Sensitivity was 57%, specificity was 92%, positive predictive value was 95%, negative predictive value was 47% and accuracy was 89%. Modified Rio score (MRS) was found to be effective in determining the treatment failure as mentioned before. This study will be useful for clinicians who evaluate the treatment failure like us, and this study revealed that the MRS may also help predict treatment failure.

Position of Cladribine Tablets in the Management of Relapsing-Remitting Multiple Sclerosis: An Expert Narrative Review From the United Arab Emirates

The use of immune reconstitution therapies (IRT) in patients with relapsing-remitting multiple sclerosis (RRMS) is associated with a prolonged period of freedom from relapses in the absence of continuously applied therapy. Cladribine tablets is a disease-modifying treatment (DMT) indicated for highly active relapsing multiple sclerosis (MS) as defined by clinical or imaging features. Treatment with cladribine tablets is effective and well tolerated in patients with active MS disease and have a low burden of monitoring during and following treatment. In this article, an expert group of specialist neurologists involved in the care of patients with MS in the United Arab Emirates provides their consensus recommendations for the practical use of cladribine tablets according to the presenting phenotype of patients with RRMS. The IRT approach may be especially useful for patients with highly active MS insufficiently responsive to treatment with a first-line DMT, those who are likely to adhere poorly to a continuous therapeutic regimen, treatment-naïve patients with high disease activity at first presentation, or patients planning a family who are prepared to wait until at least 6 months after the end of treatment. Information available to date does not suggest an adverse interaction between cladribine tablets and COVID-19 infection. Data are unavailable at this time regarding the efficacy of COVID-19 vaccination in patients treated with cladribine tablets. Robust immunological responses to COVID-19 infection or to other vaccines have been observed in patients receiving this treatment, and treatment with cladribine tablets per se should not represent a barrier to this vaccination.

The no evidence of disease activity (NEDA) concept in MS: impact of spinal cord MRI

BACKGROUND

Measures to define treatment response, such as no evidence of disease activity (NEDA), are routinely used in multiple sclerosis (MS) clinical practice. Although spinal cord involvement is a frequent feature of MS, its magnetic resonance imaging (MRI) monitoring is not routinely performed.

OBJECTIVE

To assess the impact of spinal cord MRI in the definition of NEDA in a cohort of people with MS (pwMS) with available spinal cord imaging performed as for routine monitoring.

METHODS

We included 115 pwMS undergoing treatment with first-line disease-modifying therapies (DMTs) and retrospectively analyzed the presence of NEDA in the whole cohort, either considering or not spinal cord imaging.

RESULTS

When considering only clinical and brain MRI measures, 97 out of 115 pwMS (84.3%) satisfied the criteria for NEDA. In the same cohort, the number of pwMS with NEDA significantly decreased to 88 (76.5%) (p < 0.01) when considering also spinal cord imaging.

CONCLUSION

These findings suggest that, in routine clinical practice, spinal cord MRI monitoring in pwMS under first-line DMTs leads to a slight but significant change in the proportion of subjects classified as clinically and radiologically stable according to the NEDA definition.

A Clinically-Compatible Workflow for Computer-Aided Assessment of Brain Disease Activity in Multiple Sclerosis Patients

Over the last 10 years, the number of approved disease modifying drugs acting on the focal inflammatory process in Multiple Sclerosis (MS) has increased from 3 to 10. This wide choice offers the opportunity of a personalized medicine with the objective of no clinical and radiological activity for each patient. This new paradigm requires the optimization of the detection of new FLAIR lesions on longitudinal MRI. In this paper, we describe a complete workflow—that we developed, implemented, deployed, and evaluated—to facilitate the monitoring of new FLAIR lesions on longitudinal MRI of MS patients. This workflow has been designed to be usable by both hospital and private neurologists and radiologists in France. It consists of three main components: (i) a software component that allows for automated and secured anonymization and transfer of MRI data from the clinical Picture Archive and Communication System (PACS) to a processing server (and vice-versa); (ii) a fully automated segmentation core that enables detection of focal longitudinal changes in patients from T1-weighted, T2-weighted and FLAIR brain MRI scans, and (iii) a dedicated web viewer that provides an intuitive visualization of new lesions to radiologists and neurologists. We first present these different components. Then, we evaluate the workflow on 54 pairs of longitudinal MRI scans that were analyzed by 3 experts (1 neuroradiologist, 1 radiologist, and 1 neurologist) with and without the proposed workflow. We show that our workflow provided a valuable aid to clinicians in detecting new MS lesions both in terms of accuracy (mean number of detected lesions per patient and per expert 1.8 without the workflow vs. 2.3 with the workflow, p = 5.10⁻⁴) and of time dedicated by the experts (mean time difference 2′45″, p = 10⁻⁴). This increase in the number of detected lesions has implications in the classification of MS patients as stable or active, even for the most experienced neuroradiologist (mean sensitivity was 0.74 without the workflow and 0.90 with the workflow, p-value for no difference = 0.003). It therefore has potential consequences on the therapeutic management of MS patients.

Impact of disease-modifying therapies on MRI and neurocognitive outcomes in relapsing-remitting multiple sclerosis: a protocol for a systematic review and network meta-analysis

INTRODUCTION

Disease-modifying therapies (DMTs) are the mainstay of treatment for relapsing-remitting multiple sclerosis (RRMS). There is established evidence that DMTs are effective at reducing relapse rate and disease progression in RRMS, but there has been less consideration to the synthesis of MRI and neurocognitive outcomes, which play an increasingly important role in treatment decisions. The aim of this systematic review and network meta-analysis is to examine the relative efficacy, acceptability and tolerability of DMTs for RRMS, using MRI and neurocognitive outcomes.

METHODS AND ANALYSIS

We will search electronic databases, including MEDLINE, Embase and the Cochrane Central Register of Controlled Trials, with no date restrictions. We will also search the websites of international regulatory bodies for pharmaceuticals and international trial registries. We will include parallel group randomised controlled trials of DMTs including interferon beta-1a intramuscular, interferon beta-1a subcutaneous, interferon beta-1b, peginterferon beta-1a, glatiramer acetate, natalizumab, ocrelizumab, alemtuzumab, dimethyl fumarate, teriflunomide, fingolimod, cladribine, ozanimod, mitoxantrone and rituximab, either head-to-head or against placebo in adults with RRMS. Primary outcomes include efficacy (MRI outcomes including new T1/hypointense lesions and T2/hyperintense lesions) and acceptability (all-cause dropouts). Secondary outcomes include gadolinium-enhancing lesions, cerebral atrophy and tolerability (dropouts due to adverse events). Neurocognitive measures across three domains including processing speed, working memory and verbal learning will be included as exploratory outcomes. Data will be analysed using a random-effects pairwise meta-analysis and a Bayesian hierarchical random effects network meta-analysis to evaluate the efficacy, acceptability and tolerability of the included DMTs. Subgroup and sensitivity analyses will be conducted to assess the robustness of the findings. The review will be reported using the Preferred Reporting Items for Systematic Reviews incorporating Network Meta-Analyses statement.

ETHICS AND DISSEMINATION

This protocol does not require ethics approval. Results will be disseminated in a peer-reviewed academic journal.

PROSPERO REGISTRATION NUMBER

CRD42021239630.

Prognostic Accuracy of NEDA-3 in Long-term Outcomes of Multiple Sclerosis

Background and Objectives

To estimate the proportions of patients with relapsing-remitting multiple sclerosis who despite achieving the no evidence of disease activity-3 (NEDA-3) status in the first 2 treatment years experienced relapse-associated worsening (RAW) or progression independent from relapse activity (PIRA) in the following years.

Methods

We selected patients with NEDA-3—defined as no relapse, no disability worsening, and no MRI activity—in the first 2 years of either glatiramer acetate or interferon beta as initial treatment. We estimated the long-term probability of subsequent RAW and PIRA (considered as 2 contrasting outcomes) by cumulative incidence functions. Competing risk regressions were used to identify the baseline (i.e., at treatment start) predictors of RAW and PIRA.

Results

Of 687 patients, 224 (32.6%) had NEDA-3 in the first 2 treatment years. After a median follow-up time of 12 years from treatment start, 58 patients (26%) experienced disability accrual: 31 (14%) had RAW and 27 (12%) had PIRA. RAW was predicted by the presence of >9 T2 lesions (subdistribution hazard ratio [SHR] = 3.92, p = 0.012) and contrast-enhancing lesions (SHR = 2.38, p = 0.047) on baseline MRI scan and either temporary or permanent discontinuation of the initial treatment (SHR = 1.11, p = 0.015). PIRA was predicted by advancing age (SHR = 1.05, p = 0.036 for each year increase) and presence of ≥1 spinal cord lesion on baseline MRI scan (SHR = 4.08, p = 0.016).

Discussion

The adoption of NEDA-3 criteria led to prognostic misclassification in 1 of 4 patients. Different risk factors were associated with RAW and PIRA, suggesting alternative mechanisms for disability accrual.

Classification of Evidence

This study provides Class II evidence that in patients with RRMS who attained NEDA-3 status, subsequent RAW was associated with baseline MRI activity and discontinuation of treatment and PIRA was associated with age and the presence of baseline spinal cord lesions.

Laboratory biomarkers of Multiple Sclerosis (MS)

Multiple Sclerosis (MS) is a neurological disease that affects the central nervous system (CNS). The diagnosis of the disease is quite challenging due to its variation among patients. As a result, the need to enhance diagnostic procedures, evaluate objective prognostic markers and promote effective monitoring of patients' responses to treatment has prompted the identification of many biomarkers. To present up-to-date knowledge on potential biomarkers for MS used to assess disease activity, progression, and therapeutic responses. The search for articles was conducted in various databases, namely, PubMed, Cochrane Library, and CINAHL, using an identical search strategy and terms that included "Multiple Sclerosis," "MS," "biomarkers," "potential," "magnetic resonance spectroscopy," "progress," "marker," "predict," "disability," "indicator," and "mass spectrometry." Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines were followed when scrutinizing the articles for inclusion in the study. The search process identified 75 articles that were used in this systematic review. MS biomarkers consisted of laboratory biomarkers, imaging biomarkers, and genetic and immunogenetic biomarkers. The efficacy, which leads to their potential classification, relies on numerous factors, such as sensitivity, specificity, clinical rationale, predictability, practicality, biological rationale, reproducibility, and correlations with prognosis and disability. Oligoclonal bands (OCBs) and magnetic resonance imaging (MRI) features are the most established biomarkers so far, although kappa free light chains (kFLCs), the measles-rubella-zoster (MRZ) reaction, and neurofilament light chains (NfLs) might show potential in the near future after more studies are conducted.

The Potential Impact of Digital Biomarkers in Multiple Sclerosis in The Netherlands: An Early Health Technology Assessment of MS Sherpa

(1) Background: Monitoring of Multiple Sclerosis (MS) with eHealth interventions or digital biomarkers provides added value to the current care path. Evidence in the literature is currently scarce. MS sherpa is an eHealth intervention with digital biomarkers, aimed at monitoring symptom progression and disease activity. To show the added value of digital biomarker-based eHealth interventions to the MS care path, an early Health Technology Assessment (eHTA) was performed, with MS sherpa as an example, to assess the potential impact on treatment switches. (2) Methods: The eHTA was performed according to the Dutch guidelines for health economic evaluations. A decision analytic MS model was used to estimate the costs and benefits of MS standard care with and without use of MS sherpa, expressed in incremental cost-effectiveness ratios (ICERs) from both societal and health care perspectives. The efficacy of MS sherpa on early detection of active disease and the initiation of a treatment switch were modeled for a range of assumed efficacy (5%, 10%, 15%, 20%). (3) Results: From a societal perspective, for the efficacy of 15% or 20%, MS sherpa became dominant, which means cost-saving compared to the standard of care. MS sherpa is cost-effective in the 5% and 10% scenarios (ICERs EUR 14,535 and EUR 4069, respectively). From the health care perspective, all scenarios were cost-effective. Sensitivity analysis showed that increasing the efficacy of MS sherpa in detecting active disease early leading to treatment switches be the most impactful factor in the MS model. (4) Conclusions: The results indicate the potential of eHealth interventions to be cost-effective or even cost-saving in the MS care path. As such, digital biomarker-based eHealth interventions, like MS sherpa, are promising cost-effective solutions in optimizing MS disease management for people with MS, by detecting active disease early and helping neurologists in decisions on treatment switch.

Decreased Cerebrospinal Fluid Antioxidative Capacity Is Related to Disease Severity and Progression in Early Multiple Sclerosis

Background: Oxidative stress-induced neuronal damage in multiple sclerosis (MS) results from an imbalance between toxic free radicals and counteracting antioxidants, i.e., antioxidative capacity (AOC). The relation of AOC to outcome measures in MS still remains inconclusive. We aimed to compare AOC in cerebrospinal fluid (CSF) and serum between early MS and controls and assess its correlation with clinical/radiological measures. Methods: We determined AOC (ability of CSF and serum of patients to inhibit 2,2′-azobis(2-amidinopropane) dihydrochloride-induced oxidation of dihydrorhodamine) in clinically isolated syndrome (CIS)/early relapsing-remitting MS (RRMS) (n = 55/11) and non-inflammatory neurological controls (n = 67). MS patients underwent clinical follow-up (median, 4.5; IQR, 5.2 years) and brain MRI at 3 T (baseline/follow-up n = 47/34; median time interval, 3.5; IQR, 2.1 years) to determine subclinical disease activity. Results: CSF AOC was differently regulated among CIS, RRMS and controls (p = 0.031) and lower in RRMS vs. CIS (p = 0.020). Lower CSF AOC correlated with physical disability (r = −0.365, p = 0.004) and risk for future relapses (exp(β) = 0.929, p = 0.033). No correlations with MRI metrics were found. Conclusion: Decreased CSF AOC was associated with increased disability and clinical disease activity in MS. While our finding cannot prove causation, they should prompt further investigations into the role of AOC in the evolution of MS.

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.

Predicting Aggressive Multiple Sclerosis With Intrathecal IgM Synthesis Among Patients With a Clinically Isolated Syndrome

Objective

To determine the best method to measure intrathecal immunoglobulin (Ig) M synthesis (ITMS), a biomarker of worse prognosis in multiple sclerosis (MS). We compared the ability for predicting a poor evolution of 4 methods assessing ITMS (IgM oligoclonal bands [OCMBs], lipid-specific OCMBs [LS-OCMBs], Reibergram, and IgM index) in patients with a clinically isolated syndrome (CIS).

Methods

Prospective study with consecutive patients performed at a referral MS center. We used unadjusted and multivariate Cox regressions for predicting a second relapse, Expanded Disability Status Scale (EDSS) scores of 4 and 6, and development of secondary progressive MS (SPMS).

Results

A total of 193 patients were included, with a median (interquartile range) age of 31 (25–38) years and a median follow-up of 12.9 years. Among all methods, only OCMB, LS-OCMB, and Reibergram significantly identified patients at risk of some of the pre-established outcomes, being LS-OCMB the technique with the strongest associations. Adjusted hazard ratio (aHR) of LS-OCMB for predicting a second relapse was 2.50 (95% CI 1.72–3.64, p < 0.001). The risk of reaching EDSS scores of 4 and 6 and SPMS was significantly higher among patients with LS-OCMB (aHR 2.96, 95% CI 1.54–5.71, p = 0.001; aHR 4.96, 95% CI 2.22–11.07, p < 0.001; and aHR 2.31, 95% CI 1.08–4.93, p = 0.03, respectively).

Conclusions

ITMS predicts an aggressive MS at disease onset, especially when detected as LS-OCMB.

Classification of Evidence

This study provides Class II evidence that lipid-specific IgM oligoclonal bands can predict progression from CIS to MS and a worse disease course over a follow-up of at least 2 years.

Walk Your Talk: Real-World Adherence to Guidelines on the Use of MRI in Multiple Sclerosis

(1) Although guidelines about the use of MRI sequences for Multiple Sclerosis (MS) diagnosis and follow-up are available, variability in acquisition protocols is not uncommon in everyday clinical practice. The aim of this study was to evaluate the real-world application of MS imaging guidelines in different settings to clarify the level of adherence to these guidelines. (2) Via an on-line anonymous survey, neuroradiologists (NR) were asked about MRI protocols and parameters routinely acquired when MS patients are evaluated in their center, both at diagnosis and follow-up. Furthermore, data about report content and personal opinions about emerging neuroimaging markers were also retrieved. (3) A total of 46 participants were included, mostly working in a hospital or university hospital (80.4%) and with more than 10 years of experience (47.9%). We found a relatively good adherence to the suggested MRI protocols regarding the use of T2-weighted sequences, although almost 10% of the participants routinely acquired 2D sequences with a slice thickness superior to 3 mm. On the other hand, a wider degree of heterogeneity was found regarding gadolinium administration, almost routinely performed at follow-up examination (87.0% of cases) in contrast with the current guidelines, as well as a low use of a standardized reporting system (17.4% of cases). (4) Although the MS community is getting closer to a standardization of MRI protocols, there is still a relatively wide heterogeneity among NR, with particular reference to contrast administration, which must be overcome to guarantee an adequate quality of patients’ care in MS.

A Pilot Study of 24-h Motor Activity Patterns in Multiple Sclerosis: Pre-Planned Follow-Up at 2 Years

Early multiple sclerosis (MS) predictive markers of disease activity/prognosis have been proposed but are not universally accepted. Aim of this pilot prospective study is to verify whether a peculiar hyperactivity, observed at baseline (T0) in early relapsing-remitting (RR) MS patients, could represent a further prognostic marker. Here we report results collected at T0 and at a 24-month follow-up (T1). Eighteen RRMS patients (11 females, median Expanded Disability Status Scale-EDSS score 1.25, range EDSS score 0–2) were monitored at T0 (mean age 32.33 ± 7.51) and T1 (median EDSS score 1.5, range EDSS score 0–2.5). Patients were grouped into two groups: responders (R, 14 patients) and non-responders (NR, 4 patients) to treatment at T1. Each patient wore an actigraph for one week to record the 24-h motor activity pattern. At T0, NR presented significantly lower motor activity than R between around 9:00 and 13:00. At T1, NR were characterized by significantly lower motor activity than R between around 12:00 and 17:00. Overall, these data suggest that through the 24-h motor activity pattern, we can fairly segregate at T0 patients who will show a therapeutic failure, possibly related to a more active disease, at T1. These patients are characterized by a reduced morning level of motor activation. Further studies on larger populations are needed to confirm these preliminary findings.

2021 MAGNIMS-CMSC-NAIMS consensus recommendations on the use of MRI in patients with multiple sclerosis

The 2015 Magnetic Resonance Imaging in Multiple Sclerosis and 2016 Consortium of Multiple Sclerosis Centres guidelines on the use of MRI in diagnosis and monitoring of multiple sclerosis made an important step towards appropriate use of MRI in routine clinical practice. Since their promulgation, there have been substantial relevant advances in knowledge, including the 2017 revisions of the McDonald diagnostic criteria, renewed safety concerns regarding intravenous gadolinium-based contrast agents, and the value of spinal cord MRI for diagnostic, prognostic, and monitoring purposes. These developments suggest a changing role of MRI for the management of patients with multiple sclerosis. This 2021 revision of the previous guidelines on MRI use for patients with multiple sclerosis merges recommendations from the Magnetic Resonance Imaging in Multiple Sclerosis study group, Consortium of Multiple Sclerosis Centres, and North American Imaging in Multiple Sclerosis Cooperative, and translates research findings into clinical practice to improve the use of MRI for diagnosis, prognosis, and monitoring of individuals with multiple sclerosis. We recommend changes in MRI acquisition protocols, such as emphasising the value of three dimensional-fluid-attenuated inversion recovery as the core brain pulse sequence to improve diagnostic accuracy and ability to identify new lesions to monitor treatment effectiveness, and we provide recommendations for the judicious use of gadolinium-based contrast agents for specific clinical purposes. Additionally, we extend the recommendations to the use of MRI in patients with multiple sclerosis in childhood, during pregnancy, and in the post-partum period. Finally, we discuss promising MRI approaches that might deserve introduction into clinical practice in the near future.

Network Damage Predicts Clinical Worsening in Multiple Sclerosis: A 6.4-Year Study

OBJECTIVE

In multiple sclerosis (MS), clinical impairment is likely due to both structural damage and abnormal brain function. We assessed the added value of integrating structural and functional network MRI measures to predict 6.4-year MS clinical disability deterioration.

METHODS

Baseline 3D T1-weighted and resting-state functional MRI scans were obtained from 233 patients with MS and 77 healthy controls. Patients underwent a neurologic evaluation at baseline and at 6.4-year median follow-up (interquartile range = 5.06-7.51 years). At follow-up, patients were classified as clinically stable/worsened according to disability changes. In relapsing-remitting (RR) MS, secondary progressive (SP) MS conversion was evaluated. Global brain volumetry was obtained. Furthermore, independent component analysis identified the main functional connectivity (FC) and gray matter (GM) network patterns.

RESULTS

At follow-up, 105/233 (45%) patients were clinically worsened; 26/157 (16%) patients with RRMS evolved to SPMS. The treatment-adjusted random forest model identified normalized GM and brain volumes, decreased FC between default-mode networks, increased FC of the left precentral gyrus in the sensorimotor network (SMN), and GM atrophy in the fronto-parietal network (false discovery rate [FDR]-corrected p = range 0.01-0.09) as predictors of clinical worsening (out-of-bag [OOB] accuracy = 0.74). An expected contribution of baseline disability was also present (FDR-p = 0.01). Baseline disability, normalized GM volume, and GM atrophy in the SMN (FDR-p = range 0.01-0.09) were independently associated with SPMS conversion (OOB accuracy = 0.84). At receiver operating characteristic analysis, including network MRI variables improved disability worsening (p = 0.05) and SPMS conversion (p = 0.02) prediction.

CONCLUSIONS

Integration of MRI network measures helped determining the relative contributions of global/local GM damage and functional reorganization to clinical deterioration 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.

Identification of patients with relapsing multiple sclerosis eligible for high-efficacy therapies

Relapsing multiple sclerosis (RMS) presents a highly variable clinical evolution among patients, and its management should be personalized. Although there is no cure at present, effective disease-modifying therapies (DMTs) are available. Selection of the most appropriate DMT for each patient is influenced by several clinical, radiological and demographic aspects as well as personal preferences that, at times, are not covered in the regulatory criteria. This may be a source of difficulty, especially in certain situations where so-called 'high-efficacy DMTs' (usually considered second-line) could be of greater benefit to the patient. In this narrative review, we discuss evidence and experience, and propose a pragmatic guidance on decision-making with respect to the indication and management of high-efficacy DMT in adult patients with RMS based on expert opinion.