The Czech National MS Registry (ReMuS): Data trends in multiple sclerosis patients whose first disease-modifying therapies were initiated from 2013 to 2021

AIMS

Multiple sclerosis treatment strategies are changing in the Czech Republic. According to data from 2013-2021, the proportion of patients starting high-efficacy disease-modifying therapies is increasing. In this survey, we describe the actual data trends in multiple sclerosis (MS) patients beginning their first disease‑modifying therapies (DMTs) from 2013 to 2021. The secondary objective was to present the history, data collection, and scientific potential of the Czech National MS registry (ReMuS).

METHODS

First, using descriptive statistics, we analysed the data for patients starting their first DMTs, either platform (including dimethyl fumarate) or high-efficacy DMTs (HE-DMTs), for each successive year. Second, a detailed description of the history, data collection, completeness, quality optimising procedures, and legal policies of ReMuS is provided.

RESULTS

Based on the dataset from December 31, 2021, the total number of monitored patients with MS in ReMuS increased from 9,019 in 2013 (referred from 7 of 15 MS centres) to 12,940 in 2016 (referred from all 15 Czech MS centres) to 17,478 in 2021. In these years, the percentage of patients treated with DMTs in the registry ranged from 76 to 83%, but the proportion of patients treated with HE-DMTs changed from 16.2% in 2013 to 37.1% in 2021. During the follow-up period, a total of 8,491 treatment-naive patients received DMTs. The proportion of patients (all MS phenotypes) starting HE-DMTs increased from 2.1% in 2013 to 18.5% in 2021.

CONCLUSION

Patient registries, including ReMuS, provide an essential quality data source, especially in light of the increasing percentage of patients on HE-DMTs. Although early initiation of HE-DMT can provide considerable benefits, it also carries greater potential risks. Consistent long-term follow-up of patients in real‑world clinical practice, which only registries allow, is therefore crucial to evaluate the efficacy and safety of therapeutic strategies, for epidemiological research and to assist decision making by healthcare providers and regulatory bodies.

From real world data to real world evidence to improve outcomes in neuro-ophthalmology

Real-world data (RWD) can be defined as all data generated during routine clinical care. This includes electronic health records, disease-specific registries, imaging databanks, and data linkage to administrative databases. In the field of neuro-ophthalmology, the intersection of RWD and clinical practice offers unprecedented opportunities to understand and treat rare diseases. However, translating RWD into real-world evidence (RWE) poses several challenges, including data quality, legal and ethical considerations, and sustainability of data sources. This review explores existing RWD sources in neuro-ophthalmology, such as patient registries and electronic health records, and discusses the challenges of data collection and standardisation. We focus on research questions that need to be answered in neuro-ophthalmology and provide an update on RWE generated from various RWD sources. We review and propose solutions to some of the key barriers that can limit translation of a collection of data into impactful clinical evidence. Careful data selection, management, analysis, and interpretation are critical to generate meaningful conclusions.

Machine-learning-based prediction of disability progression in multiple sclerosis: An observational, international, multi-center study

BACKGROUND

Disability progression is a key milestone in the disease evolution of people with multiple sclerosis (PwMS). Prediction models of the probability of disability progression have not yet reached the level of trust needed to be adopted in the clinic. A common benchmark to assess model development in multiple sclerosis is also currently lacking.

METHODS

Data of adult PwMS with a follow-up of at least three years from 146 MS centers, spread over 40 countries and collected by the MSBase consortium was used. With basic inclusion criteria for quality requirements, it represents a total of 15, 240 PwMS. External validation was performed and repeated five times to assess the significance of the results. Transparent Reporting for Individual Prognosis Or Diagnosis (TRIPOD) guidelines were followed. Confirmed disability progression after two years was predicted, with a confirmation window of six months. Only routinely collected variables were used such as the expanded disability status scale, treatment, relapse information, and MS course. To learn the probability of disability progression, state-of-the-art machine learning models were investigated. The discrimination performance of the models is evaluated with the area under the receiver operator curve (ROC-AUC) and under the precision recall curve (AUC-PR), and their calibration via the Brier score and the expected calibration error. All our preprocessing and model code are available at https://gitlab.com/edebrouwer/ms_benchmark, making this task an ideal benchmark for predicting disability progression in MS.

FINDINGS

Machine learning models achieved a ROC-AUC of 0⋅71 ± 0⋅01, an AUC-PR of 0⋅26 ± 0⋅02, a Brier score of 0⋅1 ± 0⋅01 and an expected calibration error of 0⋅07 ± 0⋅04. The history of disability progression was identified as being more predictive for future disability progression than the treatment or relapses history.

CONCLUSIONS

Good discrimination and calibration performance on an external validation set is achieved, using only routinely collected variables. This suggests machine-learning models can reliably inform clinicians about the future occurrence of progression and are mature for a clinical impact study.

Disease-modifying therapies in managing disability worsening in paediatric-onset multiple sclerosis: a longitudinal analysis of global and national registries

BACKGROUND

High-efficacy disease-modifying therapies have been proven to slow disability accrual in adults with relapsing-remitting multiple sclerosis. However, their impact on disability worsening in paediatric-onset multiple sclerosis, particularly during the early phases, is not well understood. We evaluated how high-efficacy therapies influence transitions across five disability states, ranging from minimal disability to gait impairment and secondary progressive multiple sclerosis, in people with paediatric-onset multiple sclerosis.

METHODS

Longitudinal data were obtained from the international MSBase registry, containing data from people with multiple sclerosis from 151 centres across 41 countries, and the Italian Multiple Sclerosis and Related Disorders Register, containing data from people with multiple sclerosis from 178 Italian multiple sclerosis centres. People younger than 18 years at the onset of multiple sclerosis symptoms were included, provided they had a confirmed diagnosis of relapsing-remitting multiple sclerosis and at least four Expanded Disability Status Scale (EDSS) scores recorded within 12-month intervals. The primary outcome was the time to change in disability state: minimal disability (EDSS scores 0, 1·0, and 1·5), mild disability (EDSS scores 2·0 and 2·5), moderate disability (EDSS scores 3·0 and 3·5), gait impairment (EDSS scores ≥4·0), and clinician diagnosed secondary progressive multiple sclerosis. A multi-state model was constructed to simulate the natural course of multiple sclerosis, modelling the probabilities of both disability worsening and improvement simultaneously. The impact of high-efficacy disease-modifying therapies (alemtuzumab, cladribine, daclizumab, fingolimod, mitoxantrone, natalizumab, ocrelizumab, rituximab, or autologous haematopoietic stem cell transplantation) and low-efficacy disease-modifying therapies (dimethyl fumarate, glatiramer acetate, interferon beta, or teriflunomide), compared with no treatment, on the course of disability was assessed. Apart from recruitment, individuals with lived experience of multiple sclerosis were not involved in the design and conduct of this study.

FINDINGS

A total of 5224 people (3686 [70·6%] female and 1538 [29·4%] male) with mean age at onset of multiple sclerosis 15·24 years (SD 2·52) were included. High-efficacy therapies reduced the hazard of disability worsening across the disability states. The largest reduction (hazard ratio 0·41 [95% CI 0·31-0·53]) was observed in participants who were treated with high-efficacy therapies while in the minimal disability state, compared with those remained untreated. The benefit of high-efficacy therapies declined with increasing disability. Young people with minimal disability who received low-efficacy therapy also experienced a reduced hazard (hazard ratio 0·65 [95% CI 0·54-0·77]) of transitioning to mild disability, in contrast to those who remained untreated.

INTERPRETATION

Treatment of paediatric-onset relapsing-remitting multiple sclerosis with high-efficacy therapy substantially reduces the risk of reaching key disability milestones. This reduction in risk is most pronounced among young people with minimal or mild disability when treatment began. Children with relapsing-remitting multiple sclerosis should be treated early with high-efficacy therapy, before developing significant neurological impairments, to better preserve their neurological capacity.

FUNDING

National Health and Medical Research Council, Australia; MSBase Foundation Fellowship; MS Australia Postdoctoral Fellowship.

Comparative Effectiveness of Natalizumab, Fingolimod, and Injectable Therapies in Pediatric-Onset Multiple Sclerosis: A Registry-Based Study

BACKGROUND AND OBJECTIVES

Patients with pediatric-onset multiple sclerosis (POMS) typically experience higher levels of inflammation with more frequent relapses, and though patients with POMS usually recover from relapses better than adults, patients with POMS reach irreversible disability at a younger age than adult-onset patients. There have been few randomized, placebo-controlled clinical trials of multiple sclerosis (MS) disease-modifying therapies (DMTs) in patients with POMS, and most available data are based on observational studies of off-label use of DMTs approved for adults. We assessed the effectiveness of natalizumab compared with fingolimod using injectable platform therapies as a reference in pediatric patients in the global MSBase registry.

METHODS

This retrospective study included patients with POMS who initiated treatment with an injectable DMT, natalizumab, or fingolimod between January 1, 2006, and May 3, 2021. Patients were matched using inverse probability treatment weighting. The primary outcome was time to first relapse from index therapy initiation. Secondary study outcomes included annualized relapse rate; proportions of relapse-free patients at 1, 2, and 5 years; time to treatment discontinuation; and times to 24-week confirmed disability worsening and confirmed disability improvement.

RESULTS

A total of 1,218 patients with POMS were included in this analysis. Patients treated with fingolimod had a significantly lower risk of relapse than patients treated with injectable DMTs (hazard ratio [HR], 0.49; 95% confidence interval [CI], 0.29-0.83; p = 0.008). After adjustment for prior DMT experience in the unmatched sample, patients treated with natalizumab had a significantly lower risk of relapse than patients treated either with injectable DMTs (HR, 0.15; 95% CI 0.07-0.31; p < 0.001) or fingolimod (HR, 0.37; 95% CI 0.14-1.00; p = 0.049). The adjusted secondary study outcomes were generally consistent with the primary outcome or with previous observations. The findings in the inverse probability treatment weighting-adjusted patient populations were confirmed in multiple sensitivity analyses.

DISCUSSION

Our analyses of relapse risk suggest that natalizumab is more effective than fingolimod in the control of relapses in this population with high rates of new inflammatory activity, consistent with previous studies of natalizumab and fingolimod in adult-onset patients and POMS. In addition, both fingolimod and natalizumab were more effective than first-line injectable therapies.

CLASSIFICATION OF EVIDENCE

This study provides Class II evidence that patients with POMS treated with natalizumab had a lower risk of relapse than those with fingolimod.

Sample Entropy Improves Assessment of Postural Control in Early-Stage Multiple Sclerosis

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

Predictors of treatment switching in the Big Multiple Sclerosis Data Network

Background

Treatment switching is a common challenge and opportunity in real-world clinical practice. Increasing diversity in disease-modifying treatments (DMTs) has generated interest in the identification of reliable and robust predictors of treatment switching across different countries, DMTs, and time periods.

Objective

The objective of this retrospective, observational study was to identify independent predictors of treatment switching in a population of relapsing-remitting MS (RRMS) patients in the Big Multiple Sclerosis Data Network of national clinical registries, including the Italian MS registry, the OFSEP of France, the Danish MS registry, the Swedish national MS registry, and the international MSBase Registry.

Methods

In this cohort study, we merged information on 269,822 treatment episodes in 110,326 patients from 1997 to 2018 from five clinical registries. Patients were included in the final pooled analysis set if they had initiated at least one DMT during the relapsing-remitting MS (RRMS) stage. Patients not diagnosed with RRMS or RRMS patients not initiating DMT therapy during the RRMS phase were excluded from the analysis. The primary study outcome was treatment switching. A multilevel mixed-effects shared frailty time-to-event model was used to identify independent predictors of treatment switching. The contributing MS registry was included in the pooled analysis as a random effect.

Results

Every one-point increase in the Expanded Disability Status Scale (EDSS) score at treatment start was associated with 1.08 times the rate of subsequent switching, adjusting for age, sex, and calendar year (adjusted hazard ratio [aHR] 1.08; 95% CI 1.07-1.08). Women were associated with 1.11 times the rate of switching relative to men (95% CI 1.08-1.14), whilst older age was also associated with an increased rate of treatment switching. DMTs started between 2007 and 2012 were associated with 2.48 times the rate of switching relative to DMTs that began between 1996 and 2006 (aHR 2.48; 95% CI 2.48-2.56). DMTs started from 2013 onwards were more likely to switch relative to the earlier treatment epoch (aHR 8.09; 95% CI 7.79-8.41; reference = 1996-2006).

Conclusion

Switching between DMTs is associated with female sex, age, and disability at baseline and has increased in frequency considerably in recent years as more treatment options have become available. Consideration of a patient's individual risk and tolerance profile needs to be taken into account when selecting the most appropriate switch therapy from an expanding array of treatment choices.

Neuroimaging to monitor worsening of multiple sclerosis: advances supported by the grant for multiple sclerosis innovation

Key unmet needs in multiple sclerosis (MS) include detection of early pathology, disability worsening independent of relapses, and accurate monitoring of treatment response. Collaborative approaches to address these unmet needs have been driven in part by industry-academic networks and initiatives such as the Grant for Multiple Sclerosis Innovation (GMSI) and Multiple Sclerosis Leadership and Innovation Network (MS-LINK™) programs. We review the application of recent advances, supported by the GMSI and MS-LINK™ programs, in neuroimaging technology to quantify pathology related to central pathology and disease worsening, and potential for their translation into clinical practice/trials. GMSI-supported advances in neuroimaging methods and biomarkers include developments in magnetic resonance imaging, positron emission tomography, ocular imaging, and machine learning. However, longitudinal studies are required to facilitate translation of these measures to the clinic and to justify their inclusion as endpoints in clinical trials of new therapeutics for MS. Novel neuroimaging measures and other biomarkers, combined with artificial intelligence, may enable accurate prediction and monitoring of MS worsening in the clinic, and may also be used as endpoints in clinical trials of new therapies for MS targeting relapse-independent disease pathology.

Disability accrual in primary and secondary progressive multiple sclerosis

BACKGROUND

Some studies comparing primary and secondary progressive multiple sclerosis (PPMS, SPMS) report similar ages at onset of the progressive phase and similar rates of subsequent disability accrual. Others report later onset and/or faster accrual in SPMS. Comparisons have been complicated by regional cohort effects, phenotypic differences in sex ratio and management and variable diagnostic criteria for SPMS.

METHODS

We compared disability accrual in PPMS and operationally diagnosed SPMS in the international, clinic-based MSBase cohort. Inclusion required PPMS or SPMS with onset at age ≥18 years since 1995. We estimated Andersen-Gill hazard ratios for disability accrual on the Expanded Disability Status Scale (EDSS), adjusted for sex, age, baseline disability, EDSS score frequency and drug therapies, with centre and patient as random effects. We also estimated ages at onset of the progressive phase (Kaplan-Meier) and at EDSS milestones (Turnbull). Analyses were replicated with physician-diagnosed SPMS.

RESULTS

Included patients comprised 1872 with PPMS (47% men; 50% with activity) and 2575 with SPMS (32% men; 40% with activity). Relative to PPMS, SPMS had older age at onset of the progressive phase (median 46.7 years (95% CI 46.2-47.3) vs 43.9 (43.3-44.4); p<0.001), greater baseline disability, slower disability accrual (HR 0.86 (0.78-0.94); p<0.001) and similar age at wheelchair dependence.

CONCLUSIONS

We demonstrate later onset of the progressive phase and slower disability accrual in SPMS versus PPMS. This may balance greater baseline disability in SPMS, yielding convergent disability trajectories across phenotypes. The different rates of disability accrual should be considered before amalgamating PPMS and SPMS in clinical trials.

Patient-reported outcomes in multiple sclerosis: a prospective registry cohort study

Registries have the potential to tackle some of the current limitations in determining the long-term impact of multiple sclerosis. Online assessments using patient-reported outcomes can streamline follow-up enabling large-scale, long-term, cost-effective, home-based, and patient-focused data collection. However, registry data are sparsely sampled and the sensitivity of patient-reported outcomes relative to clinician-reported scales is unknown, making it hard to fully leverage their unique scope and scale to derive insights. This retrospective and prospective cohort study over 11 years involved 15 976 patients with multiple sclerosis from the United Kingdom Multiples Sclerosis Register. Primary outcomes were changes in two patient-reported outcomes: Multiple Sclerosis Impact Scale motor component, and Multiple Sclerosis Walking Scale. First, we investigated their validity in measuring the impact of physical disability in multiple sclerosis, by looking at their sensitivity to disease subtype and duration. We grouped the available records (91 351 for Multiple Sclerosis Impact Scale motor and 68 092 for Multiple Sclerosis Walking Scale) by these two factors, and statistically compared the resulting groups using a novel approach based on Monte Carlo permutation analysis that was designed to cope with the intrinsic sparsity of registry data. Next, we used the patient-reported outcomes to draw novel insights into the developmental time course of subtypes; in particular, the period preceding the transition from relapsing to progressive forms. We report a robust main effect of disease subtype on the patient-reported outcomes and interactions of disease subtype with duration (all P < 0.0001). Specifically, patient-reported outcomes worsen with disease duration for all subtypes (all P < 0.0001) apart from benign multiple sclerosis (Multiple Sclerosis Impact Scale motor: P = 0.796; Multiple Sclerosis Walking Scale: P = 0.983). Furthermore, the patient-reported outcomes of each subtype are statistically different from those of the other subtypes at all time bins (Multiple Sclerosis Impact Scale motor: all P < 0.05; Multiple Sclerosis Walking Scale: all P < 0.01) except when comparing relapsing-remitting multiple sclerosis with benign multiple sclerosis and primary progressive multiple sclerosis with secondary progressive multiple sclerosis. Notably, there were statistically significant differences between relapsing-remitting and progressive subtypes at disease onset. Critically, the patient-reported outcomes are sensitive to future transitions to progressive subtypes, with individuals who transition presenting with higher patient-reported outcomes in their relapsing-remitting phase compared to individuals who don't transition since onset (all P < 0.0001). Patient-reported outcomes capture different patterns of physical worsening over disease length and across subtypes; therefore, they are a valid tool to measure the physical impact of multiple sclerosis over the long-term and cost-effectively. Furthermore, more advanced physical disability manifests years before clinical detection of progressive subtypes, adding evidence to the presence of a multiple sclerosis prodrome.

How does Nogo receptor influence demyelination and remyelination in the context of multiple sclerosis?

Multiple sclerosis (MS) can progress with neurodegeneration as a consequence of chronic inflammatory mechanisms that drive neural cell loss and/or neuroaxonal dystrophy in the central nervous system. Immune-mediated mechanisms can accumulate myelin debris in the disease extracellular milieu during chronic-active demyelination that can limit neurorepair/plasticity and experimental evidence suggests that potentiated removal of myelin debris can promote neurorepair in models of MS. The myelin-associated inhibitory factors (MAIFs) are integral contributors to neurodegenerative processes in models of trauma and experimental MS-like disease that can be targeted to promote neurorepair. This review highlights the molecular and cellular mechanisms that drive neurodegeneration as a consequence of chronic-active inflammation and outlines plausible therapeutic approaches to antagonize the MAIFs during the evolution of neuroinflammatory lesions. Moreover, investigative lines for translation of targeted therapies against these myelin inhibitors are defined with an emphasis on the chief MAIF, Nogo-A, that may demonstrate clinical efficacy of neurorepair during progressive MS.

Serum Neurofilaments and OCT Metrics Predict EDSS-Plus Score Progression in Early Relapse-Remitting Multiple Sclerosis

(1) Background: Early disability accrual in RRMS patients is frequent and is associated with worse long-term prognosis. Correctly identifying the patients that present a high risk of early disability progression is of utmost importance, and may be aided by the use of predictive biomarkers. (2) Methods: We performed a prospective cohort study that included newly diagnosed RRMS patients, with a minimum follow-up period of one year. Biomarker samples were collected at baseline, 3-, 6- and 12-month follow-ups. Disability progression was measured using the EDSS-plus score. (3) Results: A logistic regression model based on baseline and 6-month follow-up sNfL z-scores, RNFL and GCL-IPL thickness and BREMSO score was statistically significant, with χ2(4) = 19.542, p < 0.0001, R2 = 0.791. The model correctly classified 89.1% of cases, with a sensitivity of 80%, a specificity of 93.5%, a positive predictive value of 85.7% and a negative predictive value of 90.62%. (4) Conclusions: Serum biomarkers (adjusted sNfL z-scores at baseline and 6 months) combined with OCT metrics (RNFL and GCL-IPL layer thickness) and the clinical score BREMSO can accurately predict early disability progression using the EDSS-plus score for newly diagnosed RRMS patients.

The best and worst of times in therapy development for myasthenia gravis

Within the last 5 years, the US Food and Drug Administration (FDA) has approved complement and neonatal Fc receptor (FcRN) inhibitors for treatment of generalized myasthenia gravis, and several other therapies are in late-stage clinical trials or under regulatory review. However, questions about which patients are most likely to benefit from which therapies, and the relative effectiveness of these very expensive drugs, has resulted in uncertainty around the place that they should occupy in the existing therapeutic armamentarium. MGNet (a Rare Diseases Clinical Research Consortium funded by the National Institute of Neurological Diseases and Stroke) held two meetings during the 14th International Conference of the Myasthenia Gravis Foundation of America to discuss the most critical needs for clinical trial readiness and biomarker development in the context of therapy development for myasthenia gravis. Herein we provide a summary of these discussions, but not a consensus opinion, and offer a series of recommendations to guide focused research in the most critical areas. We welcome ongoing discussion through comments on this work.

The role of machine learning in developing non-magnetic resonance imaging based biomarkers for multiple sclerosis: a systematic review

BACKGROUND

Multiple sclerosis (MS) is a neurological condition whose symptoms, severity, and progression over time vary enormously among individuals. Ideally, each person living with MS should be provided with an accurate prognosis at the time of diagnosis, precision in initial and subsequent treatment decisions, and improved timeliness in detecting the need to reassess treatment regimens. To manage these three components, discovering an accurate, objective measure of overall disease severity is essential. Machine learning (ML) algorithms can contribute to finding such a clinically useful biomarker of MS through their ability to search and analyze datasets about potential biomarkers at scale. Our aim was to conduct a systematic review to determine how, and in what way, ML has been applied to the study of MS biomarkers on data from sources other than magnetic resonance imaging.

METHODS

Systematic searches through eight databases were conducted for literature published in 2014-2020 on MS and specified ML algorithms.

RESULTS

Of the 1, 052 returned papers, 66 met the inclusion criteria. All included papers addressed developing classifiers for MS identification or measuring its progression, typically, using hold-out evaluation on subsets of fewer than 200 participants with MS. These classifiers focused on biomarkers of MS, ranging from those derived from omics and phenotypical data (34.5% clinical, 33.3% biological, 23.0% physiological, and 9.2% drug response). Algorithmic choices were dependent on both the amount of data available for supervised ML (91.5%; 49.2% classification and 42.3% regression) and the requirement to be able to justify the resulting decision-making principles in healthcare settings. Therefore, algorithms based on decision trees and support vector machines were commonly used, and the maximum average performance of 89.9% AUC was found in random forests comparing with other ML algorithms.

CONCLUSIONS

ML is applicable to determining how candidate biomarkers perform in the assessment of disease severity. However, applying ML research to develop decision aids to help clinicians optimize treatment strategies and analyze treatment responses in individual patients calls for creating appropriate data resources and shared experimental protocols. They should target proceeding from segregated classification of signals or natural language to both holistic analyses across data modalities and clinically-meaningful differentiation of disease.

Impact of methodological choices in comparative effectiveness studies: application in natalizumab versus fingolimod comparison among patients with multiple sclerosis

Background

Natalizumab and fingolimod are used as high-efficacy treatments in relapsing–remitting multiple sclerosis. Several observational studies comparing these two drugs have shown variable results, using different methods to control treatment indication bias and manage censoring. The objective of this empirical study was to elucidate the impact of methods of causal inference on the results of comparative effectiveness studies.

Methods

Data from three observational multiple sclerosis registries (MSBase, the Danish MS Registry and French OFSEP registry) were combined. Four clinical outcomes were studied. Propensity scores were used to match or weigh the compared groups, allowing for estimating average treatment effect for treated or average treatment effect for the entire population. Analyses were conducted both in intention-to-treat and per-protocol frameworks. The impact of the positivity assumption was also assessed.

Results

Overall, 5,148 relapsing–remitting multiple sclerosis patients were included. In this well-powered sample, the 95% confidence intervals of the estimates overlapped widely. Propensity scores weighting and propensity scores matching procedures led to consistent results. Some differences were observed between average treatment effect for the entire population and average treatment effect for treated estimates. Intention-to-treat analyses were more conservative than per-protocol analyses. The most pronounced irregularities in outcomes and propensity scores were introduced by violation of the positivity assumption.

Conclusions

This applied study elucidates the influence of methodological decisions on the results of comparative effectiveness studies of treatments for multiple sclerosis. According to our results, there are no material differences between conclusions obtained with propensity scores matching or propensity scores weighting given that a study is sufficiently powered, models are correctly specified and positivity assumption is fulfilled.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12874-022-01623-8.

Multiple Sclerosis Severity Score (MSSS) improves the accuracy of individualized prediction in MS

Background:

The MSBase prediction model of treatment response leverages multiple demographic and clinical characteristics to estimate hazards of relapses, confirmed disability accumulation (CDA), and confirmed disability improvement (CDI). The model did not include Multiple Sclerosis Severity Score (MSSS), a disease duration-adjusted ranked score of disability.

Objective:

To incorporate MSSS into the MSBase prediction model and compare model accuracy with and without MSSS.

Methods:

The associations between MSSS and relapse, CDA, and CDI were evaluated with marginal proportional hazards models adjusted for three principal components representative of patients’ demographic and clinical characteristics. The model fit with and without MSSS was assessed with penalized r2 and Harrell C.

Results:

A total of 5866 MS patients were started on disease-modifying therapy during prospective follow-up (age 38.4 ± 10.6 years; 72% female; disease duration 8.5 ± 7.7 years). Including MSSS into the model improved the accuracy of individual prediction of relapses by 31%, of CDA by 23%, and of CDI by 24% (Harrell C) and increased the amount of variance explained for relapses by 49%, for CDI by 11%, and for CDA by 10% as compared with the original model.

Conclusion:

Addition of a single, readily available metric, MSSS, to the comprehensive MSBase prediction model considerably improved the individual accuracy of prognostics in MS.

Comparative Effectiveness and Cost-Effectiveness of Natalizumab and Fingolimod in Patients with Inadequate Response to Disease-Modifying Therapies in Relapsing-Remitting Multiple Sclerosis in the United Kingdom

BACKGROUND

Patients with highly active relapsing-remitting multiple sclerosis inadequately responding to first-line therapies (interferon-based therapies, glatiramer acetate, dimethyl fumarate, and teriflunomide, known collectively as "BRACETD") often switch to natalizumab or fingolimod.

OBJECTIVE

The aim was to estimate the comparative effectiveness of switching to natalizumab or fingolimod or within BRACETD using real-world data and to evaluate the cost-effectiveness of switching to natalizumab versus fingolimod using a United Kingdom (UK) third-party payer perspective.

METHODS

Real-world data were obtained from MSBase for patients relapsing on BRACETD in the year before switching to natalizumab or fingolimod or within BRACETD. Three-way-multinomial-propensity-score-matched cohorts were identified, and comparisons between treatment groups were conducted for annualised relapse rate (ARR) and 6-month-confirmed disability worsening (CDW6M) and improvement (CDI6M). Results were applied in a cost-effectiveness model over a lifetime horizon using a published Markov structure with health states based on the Expanded Disability Status Scale. Other model parameters were obtained from the UK MS Survey 2015, published literature, and publicly available UK sources.

RESULTS

The MSBase analysis found a significant reduction in ARR (rate ratio [RR] = 0.64; 95% confidence interval [CI] 0.57-0.72; p < 0.001) and an increase in CDI6M (hazard ratio [HR] = 1.67; 95% CI 1.30-2.15; p < 0.001) for switching to natalizumab compared with BRACETD. For switching to fingolimod, the reduction in ARR (RR = 0.91; 95% CI 0.81-1.03; p = 0.133) and increase in CDI6M (HR = 1.30; 95% CI 0.99-1.72; p = 0.058) compared with BRACETD were not significant. Switching to natalizumab was associated with a significant reduction in ARR (RR = 0.70; 95% CI 0.62-0.79; p < 0.001) and an increase in CDI6M (HR = 1.28; 95% CI 1.01-1.62; p = 0.040) compared to switching to fingolimod. No evidence of difference in CDW6M was found between treatment groups. Natalizumab dominated (higher quality-adjusted life-years [QALYs] and lower costs) fingolimod in the base-case cost-effectiveness analysis (0.453 higher QALYs and £20,843 lower costs per patient). Results were consistent across sensitivity analyses.

CONCLUSIONS

This novel real-world analysis suggests a clinical benefit for therapy escalation to natalizumab versus fingolimod based on comparative effectiveness results, translating to higher QALYs and lower costs for UK patients inadequately responding to BRACETD.

A Quantitative Synthesis of Eight Decades of Global Multiple Sclerosis Research Using Bibliometrics

Bibliometric studies on the field of multiple sclerosis (MS) research are scarce. The aim of this study is to offer an overarching view of the body of knowledge about MS research over eight decades–from 1945 to 2021–by means of a bibliometric analysis. We performed a quantitative analysis of a massive dataset based on Web of Science. The analysis included frequencies, temporal trends, collaboration networks, clusters of research themes, and an in-depth qualitative analysis. A total of 48,356 articles, with 1,766,086 citations were retrieved. Global MS research showed a steady increase with an annual growth rate of 6.4%, with more than half of the scientific production published in the last decade. Published articles came from 98 different countries by 123,569 authors in 3,267 journals, with the United States ranking first in a number of publications (12,770) and citations (610,334). A co-occurrence network analysis formed four main themes of research, covering the pathophysiological mechanisms, neuropsychological symptoms, diagnostic modalities, and treatment of MS. A noticeable increase in research on cognition, depression, and fatigue was observed, highlighting the increased attention to the quality of life of patients with MS. This bibliometric analysis provided a comprehensive overview of the status of global MS research over the past eight decades. These results could provide a better understanding of this field and help identify new directions for future research.

Long-term outcomes in patients presenting with optic neuritis: Analyses of the MSBase registry

BACKGROUND

Short-term outcomes of optic neuritis (ON) have been well characterized. Limited data exists on longer-term visual outcomes in patients who present with ON. The large MSBase registry allows for characterization of long-term visual outcomes after ON.

METHODS

Via the MSBase Registry, data on patients from 41 centers was collected during routine clinical and research visits. Physical and visual disability were measured using the expanded disability status scale (EDSS) and the visual function score (VFS). Inclusion criteria for this analysis included age ≥ 18 years, clinically isolated syndrome (CIS), ON-onset, baseline visit within 6 months of onset, and at least one follow-up visit. Survival analysis was used to evaluate the association of disease-modifying treatment with time to conversion to clinically definite MS or sustained EDSS/VFS progression.

RESULTS

Data from 60,933 patients were obtained from the MSBase registry in July 2019. Of these, 1317 patients met inclusion criteria; 935 were treated at some point in disease course, while 382 were never treated. At baseline, mean age was 32.3 ± 8.8 years, 74% were female, median EDSS was 2 (IQR 1-2), and median VFS was 1 (IQR 0-2). Median follow-up time was 5.2 years (IQR 2.4-9.3). Treatment was associated with reduced risk and delayed conversion to clinically definite MS (HR = 0.70, p < 0.001), sustained EDSS progression (HR = 0.46, p < 0.0001) and sustained VFS (HR = 0.41, p < 0.001) progression.

CONCLUSIONS

In the MSBase cohort, treatment after ON was associated with better visual and neurological outcomes compared to no treatment. These results support early treatment for patients presenting with ON as the first manifestation of MS.

Natalizumab Versus Fingolimod in Patients with Relapsing-Remitting Multiple Sclerosis: A Subgroup Analysis From Three International Cohorts

INTRODUCTION

Natalizumab has proved to be more effective than fingolimod in reducing disease activity in relapsing-remitting multiple sclerosis (RRMS). Whether this association is universal for all patient groups remains to be determined.

OBJECTIVE

The aim of this study was to compare the relative effectiveness of natalizumab and fingolimod in RRMS subgroups defined by the baseline demographic and clinical characteristics of interest.

METHODS

Patients with RRMS who were given natalizumab or fingolimod were identified in a merged cohort from three international registries. Efficacy outcomes were compared across subgroups based on patients' sex, age, disease duration, Expanded Disability Status Scale (EDSS) score, and disease and magnetic resonance imaging (MRI) activity 12 months prior to treatment initiation. Study endpoints were number of relapses (analyzed with weighted negative binomial generalized linear model) and 6-month confirmed disability worsening and improvement events (weighted Cox proportional hazards model), recorded during study therapy. Each patient was weighted using inverse probability of treatment weighting based on propensity score.

RESULTS

A total of 5148 patients (natalizumab 1989; fingolimod 3159) were included, with a mean ± standard deviation age at baseline of 38 ± 10 years, and the majority (72%) were women. The median on-treatment follow-up was 25 (quartiles 15-41) months. Natalizumab was associated with fewer relapses than fingolimod (incidence rate ratio [IRR]; 95% confidence interval [CI]) in women (0.76; 0.65-0.88); in those aged ≤ 38 years (0.64; 0.54-0.76); in those with disease duration ≤ 7 years (0.63; 0.53-0.76); in those with EDSS score < 4 (0.75; 0.64-0.88), < 6 (0.80; 0.70-0.91), and ≥ 6 (0.52; 0.31-0.86); and in patients with pre-baseline relapses (0.74; 0.64-0.86). A higher probability of confirmed disability improvement on natalizumab versus fingolimod (hazard ratio [HR]; 95% CI) was observed among women (1.36; 1.10-1.66); those aged > 38 years (1.34; 1.04-1.73); those with disease duration > 7 years (1.33; 1.01-1.74); those with EDSS score < 6 (1.21; 1.01-1.46) and ≥ 6 (1.93; 1.11-3.34); and patients with no new MRI lesion (1.73; 1.19-2.51).

CONCLUSIONS

Overall, in women, younger patients, those with shorter disease durations, and patients with pre-treatment relapses, natalizumab was associated with a lower frequency of multiple sclerosis relapses than fingolimod. It was also associated with an increased chance of recovery from disability among most patients, particularly women and those with no recent MRI activity.

NARCOMS and Other Registries in Multiple Sclerosis: Issues and Insights

Observational studies and registries can play a critical role in elucidating the natural and treated history of multiple sclerosis (MS) and identifying factors associated with outcomes such as disability and health-related quality of life. The North American Research Committee on Multiple Sclerosis (NARCOMS) Registry is one of multiple registries worldwide that focuses on people with MS, but one of the very few patient-driven MS registries. On the 25th anniversary of the first data collection for the NARCOMS Registry, we discuss the importance of disease registries in the MS field, describe key concepts related to registry design and management, and highlight findings from MS registries relevant to clinical care or health policy.

Utilization of Multiple Sclerosis Therapies in the Middle East Over a Decade: 2009-2018

BACKGROUND

The multiple sclerosis (MS) landscape has changed over the past two decades across the world and in the Middle East. The Middle East is an ethnically diverse region located between 12° and 42° of latitude and 35° and 54° of longitude and varying altitudes. The magnitude of the shifts observed in the epidemiology and management of MS differ in each region and from country to country.

OBJECTIVES

The aim of this study was to provide a clinicodemographic overview of the cohorts of patients contributed to MSBase, a large international MS registry, in the Middle East and describe disease-modifying treatment (DMT) utilization in the different countries within the region. Understanding the differences between these cohorts is integral to interpretation of the studies conducted using registry data and provides insight into clinical practice in these cohorts.

METHODS

The MSBase registry was searched for patients with MS or clinically isolated syndrome from the Middle Eastern countries with data captured between 2009 and 2018. In 2-year epochs, and with special focus on the most recent epoch (2017-2018), we explored the demographic, clinical characteristics and treatment exposures of the studied cohorts and reported the results using standard descriptive statistics.

RESULTS

Over the 10-year study period, 13,356 patients from 17 centers in 8 Middle Eastern countries fulfilled the inclusion criteria. The represented countries were Egypt, Iran, Kuwait, Lebanon, Oman, Saudi Arabia, Turkey and the United Arab Emirates. Overall, the represented cohort was young (median 36 years, quartiles 29-45) and captured relatively early after the onset of MS (median disease duration < 10 years, quartiles 3-12). The relapsing-remitting phenotype was the most prevalent phenotype in all countries (73-97%) and the highest proportion of progressive MS was reported in Saudi Arabia (12%). Median Expanded Disability Status Scale (EDSS) ranged from 0 to 3, depicting a mildly disabled cohort, with the exception of Saudi Arabia where the median EDSS was 4 (quartiles 1.5-6.5). The median relapse frequency was highest in Lebanon (median 1.03, 95% CI 0.94-1.16) followed by Egypt (median 1.02, 95% CI 0.89-1.24) and lowest in Saudi Arabia (median 0.70, 95% CI 0.58-0.95) and Kuwait (median 0.75, 95% CI 0.71-0.80). The treatment landscape greatly varied between different countries. Platform injectable therapies were mostly utilized in Egypt, Iran and Turkey (86%, 79% and 53%, respectively), while oral therapies and monoclonal antibodies were more commonly used in Kuwait, Lebanon and the United Arab Emirates (87.2%, 67.3% and 58.7%, respectively).

CONCLUSION

Patients in the Middle East enrolled in a large multinational registry are representative of the general MS population. The spectrum of therapies used in the individual countries, however, is highly variable. Further studies that include rural and non-academic practices are needed to enhance our understanding of the MS cohorts in the Middle East.

RNA-Seq profiling of leukocytes reveals a sex-dependent global circular RNA upregulation in multiple sclerosis and 6 candidate biomarkers

Multiple sclerosis (MS) is a chronic autoimmune disease of the central nervous system, with higher prevalence in women, that leads to neurological disability. The disease course and clinical phenotype are highly variable, and therefore, biomarkers for the diagnosis, classification, monitoring of the disease and treatment assessment are needed. Studies have shown a dysregulation in the coding and non-coding RNAs and proposed some as biomarkers. However, still none of them have reached the clinical practice. Recently, circular RNAs (circRNAs) have emerged as new players in the transcriptome that hold a great potential as biomarkers in several diseases. Leukocytes from 30 MS patients and 20 healthy controls (HCs) were RNA-sequenced to study the linear and circular transcriptome. Differential expression analysis was performed by DESeq, and circRNA candidates were studied in a second cohort (70 MS and 46 HC) by RT-qPCR and in paired samples drawn during the relapse and remission phases (20 patients). Among the differentially expressed circRNAs, 96.1% are upregulated in patients compared with controls, but similar circRNA profiles are found between MS types. The same upregulation trend was observed in females but not in males or in the linear transcriptome. The upregulation of 6 circRNAs was validated, and a change in their expression was found between relapse and remission. The 6 circRNAs showed a good performance to discriminate patients from HC with a combined area under the curve of 0.852. There is global, specific and sex-dependent increase of circRNA expression in MS, and 6 circRNAs are proposed as potential biomarkers.

Effects of High and Low Efficacy Therapy in Secondary Progressive Multiple Sclerosis

OBJECTIVE

To compare the clinical effectiveness of high- and low-efficacy treatments in patients with recently active and inactive secondary progressive multiple sclerosis (SPMS) after accounting for therapeutic lag.

METHODS

Patients treated with high- (natalizumab, alemtuzumab, mitoxantrone, ocrelizumab, rituximab, cladribine, fingolimod) or low-efficacy (interferon β, glatiramer acetate, teriflunomide) therapies after SPMS onset were selected from MSBase and OFSEP, two large observational cohorts. Therapeutic lag was estimated for each patient based on their demographic and clinical characteristics. Propensity score was used to match patients treated with high and low-efficacy therapies. Outcomes after disregarding the period of therapeutic lag were compared in paired, pairwise-censored analyses.

RESULTS

1000 patients were included in the primary analysis. Patients with active SPMS treated with high-efficacy therapy experienced less frequent relapses than those on low-efficacy therapy (hazard ratio [HR] 0.7, p=0.006). In patients with inactive SPMS, there was no evidence for a difference in relapse frequency between groups (HR=0.8,p=0.39). No evidence for a difference in the risk of disability progression was observed.

CONCLUSION

In treated patients with SPMS, high-efficacy therapy is superior to low-efficacy therapy in reducing relapses in patients with active, but not those with inactive, SPMS. However, more potent therapies do not offer an advantage in reducing disability progression in this patient group.

CLASSIFICATION OF EVIDENCE

This study provides class III evidence that high-efficacy therapy is superior to low-efficacy therapy in reducing relapses in patients with active SPMS whilst we did not find a difference in disability progression between patients treated with high- and low-efficacy therapy.

Natalizumab, Fingolimod and Dimethyl Fumarate Use and Pregnancy-Related Relapse and Disability in Women With Multiple Sclerosis

OBJECTIVE

To investigate pregnancy-related disease activity in a contemporary multiple sclerosis (MS) cohort.

METHODS

Using data from the MSBase Registry, we included pregnancies conceived after 31 Dec 2010 from women with relapsing-remitting MS or clinically isolated syndrome. Predictors of intrapartum relapse, and postpartum relapse and disability progression were determined by clustered logistic regression or Cox regression analyses.

RESULTS

We included 1998 pregnancies from 1619 women with MS. Preconception annualized relapse rate (ARR) was 0.29 (95% CI 0.27-0.32), fell to 0.19 (0.14-0.24) in third trimester, and increased to 0.59 (0.51-0.67) in early postpartum. Among women who used fingolimod or natalizumab, ARR before pregnancy was 0.37 (0.28-0.49) and 0.29 (0.22-0.37), respectively, and increased during pregnancy. Intrapartum ARR decreased with preconception dimethyl fumarate use. ARR spiked after delivery across all DMT groups. Natalizumab continuation into pregnancy reduced the odds of relapse during pregnancy (OR 0.76 per month [0.60-0.95], p=0.017). DMT re-initiation with natalizumab protected against postpartum relapse (HR 0.11 [0.04-0.32], p<0.0001). Breastfeeding women were less likely to relapse (HR 0.61 [0.41-0.91], p=0.016). 5.6% of pregnancies were followed by confirmed disability progression, predicted by higher relapse activity in pregnancy and postpartum.

CONCLUSION

Intrapartum and postpartum relapse probabilities increased among women with MS after natalizumab or fingolimod cessation. In women considered to be at high relapse risk, use of natalizumab before pregnancy and continued up to 34 weeks gestation, with early re-initiation after delivery is an effective option to minimize relapse risks. Strategies of DMT use have to be balanced against potential fetal/neonatal complications.

Digital Dementia Registry Bavaria-digiDEM Bayern: study protocol for a multicentre, prospective, longitudinal register study

INTRODUCTION

Dementia is one of the most relevant widespread diseases, with a prevalence of currently 50 million people with dementia worldwide. The care of people with dementia will be one of the major challenges for healthcare systems worldwide. Digitalisation offers new possibilities to improve both dementia healthcare and health outcomes research as a fundament for national healthcare planning. The 'Digital Dementia Registry Bavaria-digiDEM Bayern' aims to improve the understanding of the complexity and long-term progression of dementia and the current care situation in Bavaria. Moreover, by offering digital services, digiDEM will actively contribute to improving the care situation in Bavaria. METHODS AND ANALYSIS: digiDEM will recruit people with dementia and their family caregivers in all administrative regions of Bavaria. All participants will undergo dementia screening prior to study inclusion in order to identify people with mild cognitive impairment and mild-to-moderate dementia. Participants will be followed up over a period of three years. Sociodemographic data, type of dementia, symptoms, diagnosis, cognitive trajectories, activities of daily living, behavioural and psychological symptoms, falls, resource utilisation, caregiver burden, quality of life, needs of people with dementia and their caregivers, mobility, use of media and sources of information will be assessed. The project will implement a digital web-based platform for data collection. Data will be collected by means of standardised online or face-to-face interviews.

ETHICS AND DISSEMINATION

The study obtained ethical approval from the Ethics Committee of the Medical Faculty of Friedrich-Alexander-University Erlangen-Nürnberg (FAU) (application number: 253_20 B). Findings will be used for evidence-based decision-making for health decision-makers in order to optimise dementia healthcare in the state of Bavaria. Specific analyses will be conducted for the participating research partners. Results of the study will be published in peer-reviewed journals.

Approaches and challenges in the diagnosis and management of secondary progressive multiple sclerosis: A Central Eastern European perspective from healthcare professionals

Secondary progressive multiple sclerosis (SPMS) is a debilitating condition characterized by gradual worsening after an initial relapsing disease course. Despite the recent advances in our understanding of the disease, the diagnosis and treatment of SPMS continue to be challenging in routine clinical practice. The aim of this review article is to present the views of leading MS experts on the challenges in the diagnosis and management of SPMS and clinicians' perspectives in Central and Eastern Europe. This article also provides recommendations of MS experts to improve the situation with diagnosis and management of SPMS. Many countries within Central and Eastern Europe have high prevalence of MS (>100 per 100,000 population). Consistent with the global trend, in the absence of reliable tests or biomarkers, SPMS at early stage remains undiagnosed. Due to diagnostic uncertainty and lack of a universally accepted disease definition, clinicians rely more on retrospective analysis of the clinical symptoms to confirm the diagnosis. With the lack of awareness and poor understanding of the timing of the onset of SPMS, clinicians may tend to direct attention to relapses than the symptoms of progression, which leads to underestimation of SPMS. Although several predictors of progression to SPMS have been identified, their predictive value is highly variable. Therefore, defining the transitioning period as a separate stage of MS is essential. According to experts' opinion, frequent follow-up of patients and periodic assessment of progression are recommended for the timely identification of patients transitioning from RRMS to SPMS. MSProDiscuss Tool is an example of a quick assessment tool for identifying patients progressing from RRMS to SPMS. MS progression is usually assessed by changes in Expanded Disability Status Scale (EDSS) scores. As EDSS scores tend to fluctuate when measured in the short term (3-6 months), a longer period (≥12 months) may be needed to confirm the progression. Assessment of cognitive function is also important for evaluating secondary progression. Compartmentalization of inflammation within the central nervous system is an important reason behind the limited success of disease-modifying therapies (DMTs) for treating SPMS. Most of the DMTs fail to cross the blood-brain barrier; only 38% of the tested DMTs achieved their primary endpoint in SPMS. In Europe, siponimod is the first oral treatment for adults with active SPMS. Particularly, in Central and Eastern Europe, patients with SPMS are still being prescribed less efficacious DMTs and interferons. The absence of alternative treatments in SPMS supports the use of new products (siponimod and others); however the decision to initiate siponimod therapy in more severe patients (EDSS score of 7 or higher) should be individualized in consultation with the payers. The focus should be on early treatment initiation to delay disease progression.

E-health and multiple sclerosis

PURPOSE OF REVIEW

To outline recent applications of e-health data and digital tools for improving the care and management of healthcare for people with multiple sclerosis.

RECENT FINDINGS

The digitization of most clinical data, along with developments in communication technologies, miniaturization of sensors and computational advances are enabling aggregation and clinically meaningful analyses of real-world data from patient registries, digital patient-reported outcomes and electronic health records (EHR). These data are allowing more confident descriptions of prognoses for multiple sclerosis patients and the long-term relative benefits and safety of disease-modifying treatments (DMT). Registries allow detailed, multiple sclerosis-specific data to be shared between clinicians more easily, provide data needed to improve the impact of DMT and, with EHR, characterize clinically relevant interactions between multiple sclerosis and other diseases. Wearable sensors provide continuous, long-term measures of performance dynamics in relevant ecological settings. In conjunction with telemedicine and online apps, they promise a major expansion of the scope for patients to manage aspects of their own care. Advances in disease understanding, decision support and self-management using these Big Data are being accelerated by machine learning and artificial intelligence.

SUMMARY

Both health professionals and patients can employ e-health approaches and tools for development of a more patient-centred learning health system.

Standardization and digitization of clinical data in multiple sclerosis

Standardization is necessary to ensure the reliability of clinical data and to enable longitudinal and cross-sectional comparisons of data obtained in different centres and countries. In patients with multiple sclerosis (MS), standardized clinical data are needed for monitoring of disability and for collecting real-world evidence for use in research. This Perspective describes attempts to improve the standardization and digitization of clinical data in MS, including digital electronic health recording systems and applications that attempt to offer a comprehensive assessment of patients' neurological deficits and their effects on daily life. Despite the challenges raised by regulatory, ethical and data-privacy considerations, the standardization and digitization of clinical data in MS is expected to generate new insights into the pathophysiology of the disease and to contribute to personalized patient care.

Effect of Disease-Modifying Therapy on Disability in Relapsing-Remitting Multiple Sclerosis Over 15 Years

OBJECTIVE

To test the hypothesis that immunotherapy prevents long-term disability in relapsing-remitting multiple sclerosis (MS), we modeled disability outcomes in 14,717 patients.

METHODS

We studied patients from MSBase followed for ≥1 year, with ≥3 visits, ≥1 visit per year, and exposed to MS therapy, and a subset of patients with ≥15-year follow-up. Marginal structural models were used to compare the cumulative hazards of 12-month confirmed increase and decrease in disability, Expanded Disability Status Scale (EDSS) step 6, and the incidence of relapses between treated and untreated periods. Marginal structural models were continuously readjusted for patient age, sex, pregnancy, date, disease course, time from first symptom, prior relapse history, disability, and MRI activity.

RESULTS

A total of 14,717 patients were studied. During the treated periods, patients were less likely to experience relapses (hazard ratio 0.60, 95% confidence interval [CI] 0.43-0.82, p = 0.0016), worsening of disability (0.56, 0.38-0.82, p = 0.0026), and progress to EDSS step 6 (0.33, 0.19-0.59, p = 0.00019). Among 1,085 patients with ≥15-year follow-up, the treated patients were less likely to experience relapses (0.59, 0.50-0.70, p = 10^-9) and worsening of disability (0.81, 0.67-0.99, p = 0.043).

CONCLUSION

Continued treatment with MS immunotherapies reduces disability accrual by 19%-44% (95% CI 1%-62%), the risk of need of a walking aid by 67% (95% CI 41%-81%), and the frequency of relapses by 40-41% (95% CI 18%-57%) over 15 years. This study provides evidence that disease-modifying therapies are effective in improving disability outcomes in relapsing-remitting MS over the long term.

CLASSIFICATION OF EVIDENCE

This study provides Class IV evidence that, for patients with relapsing-remitting MS, long-term exposure to immunotherapy prevents neurologic disability.

Delay from treatment start to full effect of immunotherapies for multiple sclerosis

In multiple sclerosis, treatment start or switch is prompted by evidence of disease activity. Whilst immunomodulatory therapies reduce disease activity, the time required to attain maximal effect is unclear. In this study we aimed to develop a method that allows identification of the time to manifest fully and clinically the effect of multiple sclerosis treatments (‘therapeutic lag’) on clinical disease activity represented by relapses and progression-of-disability events. Data from two multiple sclerosis registries, MSBase (multinational) and OFSEP (French), were used. Patients diagnosed with multiple sclerosis, minimum 1-year exposure to treatment, minimum 3-year pretreatment follow-up and yearly review were included in the analysis. For analysis of disability progression, all events in the subsequent 5-year period were included. Density curves, representing incidence of relapses and 6-month confirmed progression events, were separately constructed for each sufficiently represented therapy. Monte Carlo simulations were performed to identify the first local minimum of the first derivative after treatment start; this point represented the point of stabilization of treatment effect, after the maximum treatment effect was observed. The method was developed in a discovery cohort (MSBase), and externally validated in a separate, non-overlapping cohort (OFSEP). A merged MSBase-OFSEP cohort was used for all subsequent analyses. Annualized relapse rates were compared in the time before treatment start and after the stabilization of treatment effect following commencement of each therapy. We identified 11 180 eligible treatment epochs for analysis of relapses and 4088 treatment epochs for disability progression. External validation was performed in four therapies, with no significant difference in the bootstrapped mean differences in therapeutic lag duration between registries. The duration of therapeutic lag for relapses was calculated for 10 therapies and ranged between 12 and 30 weeks. The duration of therapeutic lag for disability progression was calculated for seven therapies and ranged between 30 and 70 weeks. Significant differences in the pre- versus post-treatment annualized relapse rate were present for all therapies apart from intramuscular interferon beta-1a. In conclusion we have developed, and externally validated, a method to objectively quantify the duration of therapeutic lag on relapses and disability progression in different therapies in patients more than 3 years from multiple sclerosis onset. Objectively defined periods of expected therapeutic lag allows insights into the evaluation of treatment response in randomized clinical trials and may guide clinical decision-making in patients who experience early on-treatment disease activity. This method will subsequently be applied in studies that evaluate the effect of patient and disease characteristics on therapeutic lag.