Multiple Sclerosis Performance Test: Technical Development and Usability

Sex differences in brain resilience of individuals with multiple sclerosis

BACKGROUND

Brain resilience allows maintenance of neurocognitive function in the face of age or disease-related neural changes.

OBJECTIVE

Test the hypothesis that women and men with MS differ in brain resilience.

METHODS

This cross-sectional analysis of prospective cohort data included 11,297 patients. Linear mixed effects models predicted performance outcomes on tasks of fine motor dexterity and cognitive processing speed for MRI proxies of disease burden: brain parenchymal fraction (BPF), T2 lesion volume, volumes of deep gray, thalamus, white and cortical gray matter. Covariates were age, sex, age-by-sex, current disease-modifying therapy, disease phenotype, education, total brain volume, and total brain volume-by-sex. Sex-by-MRI metric terms tested primary hypothesis of differential brain-behavior relationships between men and women.

RESULTS

Final sample included 10,286 participants. Lower BPF was associated with worse performance (p's<0.001) in men and women; association was smaller for women than men for processing speed (βetaWomen-Men=-0.044, 95 % CI=[-0.087, -0.002], p = 0.041) and manual dexterity (βetaWomen-Men=-0.073, 95 % CI=[-0.124, -0.023], p = 0.005). For each MRI variable, women demonstrated better neurocognitive function controlling for disease burden.

DISCUSSION

Sex differences in brain metric-neurofunctional performance relationships of people with MS suggest women have higher resilience than men in the face of increased disease burden. Future work exploring mechanism is warranted.

From progression to progress: The future of multiple sclerosis

Significant advances have been made in the diagnosis and treatment of multiple sclerosis in recent years yet challenges remain. The current classification of MS phenotypes according to disease activity and progression, for example, does not adequately reflect the underlying pathophysiological mechanisms that may be acting in an individual with MS at different time points. Thus, there is a need for clinicians to transition to a management approach based on the underlying pathophysiological mechanisms that drive disability in MS. A Canadian expert panel convened in January 2023 to discuss priorities for clinical discovery and scientific exploration that would help advance the field. Five key areas of focus included: identifying a mechanism-based disease classification system; developing biomarkers (imaging, fluid, digital) to identify pathologic processes; implementing a data-driven approach to integrate genetic/environmental risk factors, clinical findings, imaging and biomarker data, and patient-reported outcomes to better characterize the many factors associated with disability progression; utilizing precision-based treatment strategies to target different disease processes; and potentially preventing disease through Epstein-Barr virus (EBV) vaccination, counselling about environmental risk factors (e.g. obesity, exercise, vitamin D/sun exposure, smoking) and other measures. Many of the tools needed to meet these needs are currently available. Further work is required to validate emerging biomarkers and tailor treatment strategies to the needs of individual patients. The hope is that a more complete view of the individual's pathobiology will enable clinicians to usher in an era of truly personalized medicine, in which more informed treatment decisions throughout the disease course achieve better long-term outcomes.

Disparities in DMT treatment: Demographic and neurocognitive differences between MS patients currently treated versus not treated with disease-modifying therapies

BACKGROUND

Current treatment guidelines recommend consideration of disease-modifying therapy (DMT) for all multiple sclerosis (MS) patients, but barriers to access have begun to be identified. In particular, prior studies have found that people with higher education have better access to DMTs, perhaps explained by the association of higher education with higher income. And while the majority of people with MS are women, being male is also associated with higher income. These factors argue for the need to better understand whether there are differences in DMT uptake based on sex and education. Finally, in addition to well-documented benefits of DMTs for slowing disease progression, there is growing evidence to suggest benefits of DMTs for cognitive functioning.

OBJECTIVE

Determine whether rates of DMT treatment differ based on education and sex. Secondarily, we investigate whether neurocognitive test performance differs in treated versus not treated groups.

METHODS

In cross-sectional data, mixed effects linear regression evaluated differences in education and sex of those treated versus not treated with DMTs. Models included the following predictors: age, disease duration, MS subtype, sex/education, disability, atrophy, and T2 lesion volume. Propensity score weights were extracted to obtain unbiased estimates of the relationship between DMT status and each outcome of interest. The same models evaluated performance differences between groups on an iPad-based processing speed test (PST) and manual dexterity test (MDT).

RESULTS

Controlling for covariates, individuals with less education (OR=1.09, 95 % CI=[1.03, 1.14], p = 0.003) and women (OR=0.80, 95 % CI=[0.72, 0.90], p < 0.001) were less likely to be currently treated with DMTs. Small effect size association was shown for DMT treatment with better performance on PST (beta=0.09, CI=[0.06, 0.13], p < 0.001) and MDT (beta=0.05, CI=[0.01,0.08], p = 0.011).

CONCLUSIONS

Women and people with lower education had a lower likelihood of being currently treated with DMTs. After controlling for all relevant variables, an independent (small) association of DMT treatment to better performance on tests of processing speed and fine motor dexterity was found. Reasons for disparities remain to be investigated in future work, and may include employment status, health insurance coverage, or sex differences in risk tolerance.

Managing cognitive impairment and its impact in multiple sclerosis: An Australian multidisciplinary perspective

Cognitive impairment in multiple sclerosis (MS) affects approximately 40-70% of patients and can have varying degrees of severity. Even mild cognitive impairment can impact on quality of life and productivity. Despite this, patients are not routinely screened or monitored for cognitive impairment in Australia due to a range of issues, with time and space being the main limiting factors. This Australian multidisciplinary perspective provides recommendations on cognition management in Australia. It gives a broad overview of cognition in MS, advice on the screening and monitoring tools available to clinicians, and strategies that can be implemented in clinics to help monitor for cognitive impairment in patients with MS. We suggest a routine baseline assessment and multidomain cognitive battery in regular intervals; a change should trigger a thorough investigation of the cause.

The Parkinson's disease waiting room of the future: measurements, not magazines

Utilizing technology to precisely quantify Parkinson's disease motor symptoms has evolved over the past 50 years from single point in time assessments using traditional biomechanical approaches to continuous monitoring of performance with wearables. Despite advances in the precision, usability, availability and affordability of technology, the "gold standard" for assessing Parkinson's motor symptoms continues to be a subjective clinical assessment as none of these technologies have been fully integrated into routine clinical care of Parkinson's disease patients. To facilitate the integration of technology into routine clinical care, the Develop with Clinical Intent (DCI) model was created. The DCI model takes a unique approach to the development and integration of technology into clinical practice by focusing on the clinical problem to be solved by technology rather than focusing on the technology and then contemplating how it could be integrated into clinical care. The DCI model was successfully used to develop the Parkinson's disease Waiting Room of the Future (WROTF) within the Center for Neurological Restoration at the Cleveland Clinic. Within the WROTF, Parkinson's disease patients complete the self-directed PD-Optimize application on an iPad. The PD-Optimize platform contains cognitive and motor assessments to quantify PD symptoms that are difficult and time-consuming to evaluate clinically. PD-Optimize is completed by the patient prior to their medical appointment and the results are immediately integrated into the electronic health record for discussion with the movement disorder neurologist. Insights from the clinical use of PD-Optimize has spurred the development of a virtual reality technology to evaluate instrumental activities of daily living in PD patients. This new technology will undergo rigorous assessment and validation as dictated by the DCI model. The DCI model is intended to serve as a health enablement roadmap to formalize and accelerate the process of bringing the advantages of cutting-edge technology to those who could benefit the most: the patient.

How to measure the treatment response in progressive multiple sclerosis: Current perspectives and limitations in clinical settings'

New treatment options are available for active progressive multiple sclerosis (MS), including primary and secondary progressive forms. Several pieces of evidence have recently suggested a "window of beneficial treatment opportunities," principally in the early stages of progression. However, for progressive MS, which is characterised by an inevitable tendency to get worse, it is crucial to redefine the "response to treatment" beyond the concept of "no evidence of disease activity" (NEDA-3), which was initially conceived to evaluate disease outcomes in relapsing-remitting form, albeit it is currently applied to all MS cases in clinical practice. This review examines the current perspectives and limitations in assessing the effectiveness of DMTs and disease outcomes in progressive MS, the current criteria applied in defining the response to DMTs, and the strengths and limitations of clinical scales and tools for evaluating MS evolution and patient perception. Additionally, the impact of age and comorbidities on the assessment of MS outcomes was examined.

Remote Observational Research for Multiple Sclerosis: A Natural Experiment

BACKGROUND AND OBJECTIVES

Prospective, deeply phenotyped research cohorts monitoring individuals with chronic neurologic conditions, such as multiple sclerosis (MS), depend on continued participant engagement. The COVID-19 pandemic restricted in-clinic research activities, threatening this longitudinal engagement, but also forced adoption of televideo-enabled care. This offered a natural experiment in which to analyze key dimensions of remote research: (1) comparison of remote vs in-clinic visit costs from multiple perspectives and (2) comparison of the remote with in-clinic measures in cross-sectional and longitudinal disability evaluations.

METHODS

Between March 2020 and December 2021, 207 MS cohort participants underwent hybrid in-clinic and virtual research visits; 96 contributed 100 "matched visits," that is, in-clinic (Neurostatus-Expanded Disability Status Scale [NS-EDSS]) and remote (televideo-enabled EDSS [tele-EDSS]; electronic patient-reported EDSS [ePR-EDSS]) evaluations. Clinical, demographic, and socioeconomic characteristics of participants were collected.

RESULTS

The costs of remote visits were lower than in-clinic visits for research investigators (facilities, personnel, parking, participant compensation) but also for participants (travel, caregiver time) and carbon footprint (p < 0.05 for each). Median cohort EDSS was similar between the 3 modalities (NS-EDSS: 2, tele-EDSS: 1.5, ePR-EDSS: 2, range 0.6.5); the remote evaluations were each noninferior to the NS-EDSS within ±0.5 EDSS point (TOST for noninferiority, p < 0.01 for each). Furthermore, year to year, the % of participants with worsening/stable/improved EDSS scores was similar, whether each annual evaluation used NS-EDSS or whether it switched from NS-EDSS to tele-EDSS.

DISCUSSION

Altogether, the current findings suggest that remote evaluations can reduce the costs of research participation for patients, while providing a reasonable evaluation of disability trajectory longitudinally. This could inform the design of remote research that is more inclusive of diverse participants.

Deep gray matter substructure volumes and depressive symptoms in a large multiple sclerosis cohort

BACKGROUND

Consistent findings on underlying brain features or specific structural atrophy patterns contributing to depression in multiple sclerosis (MS) are limited.

OBJECTIVE

To investigate how deep gray matter (DGM) features predict depressive symptom trajectories in MS patients.

METHODS

We used data from the MS Partners Advancing Technology and Health Solutions (MS PATHS) network in which standardized patient information and outcomes are collected. We performed whole-brain segmentation using SLANT-CRUISE. We assessed if DGM structures were associated with elevated depressive symptoms over follow-up and with depressive symptom phenotypes.

RESULTS

We included 3844 participants (average age: 46.05 ± 11.83 years; 72.7% female) of whom 1905 (49.5%) experienced ⩾1 periods of elevated depressive symptoms over 2.6 ± 0.9 years mean follow-up. Higher caudate, putamen, accumbens, ventral diencephalon, thalamus, and amygdala volumes were associated with lower odds of elevated depressive symptoms over follow-up (odds ratio (OR) range per 1 SD (standard deviation) increase in volume: 0.88-0.94). For example, a 1 SD increase in accumbens or caudate volume was associated with 12% or 10% respective lower odds of having a period of elevated depressive symptoms over follow-up (for accumbens: OR: 0.88; 95% confidence interval (CI): 0.83-0.93; p < 0.001; for caudate: OR: 0.90; 95% CI: 0.85-0.96; p = 0.003).

CONCLUSION

Lower DGM volumes were associated with depressive symptom trajectories in MS.

Associations of sNfL with clinico-radiological measures in a large MS population

OBJECTIVE

Evaluation of serum neurofilament light chain (sNfL), measured using high-throughput assays on widely accessible platforms in large, real-world MS populations, is a critical step for sNfL to be utilized in clinical practice.

METHODS

Multiple Sclerosis Partners Advancing Technology and Health Solutions (MS PATHS) is a network of healthcare institutions in the United States and Europe collecting standardized clinical/imaging data and biospecimens during routine clinic visits. sNfL was measured in 6974 MS and 201 healthy control (HC) participants, using a high-throughput, scalable immunoassay.

RESULTS

Elevated sNfL levels for age (sNfL-E) were found in 1238 MS participants (17.8%). Factors associated with sNfL-E included male sex, younger age, progressive disease subtype, diabetes mellitus, impaired renal function, and active smoking. Higher body mass index (BMI) was associated with lower odds of elevated sNfL. Active treatment with disease-modifying therapy was associated with lower odds of sNfL-E. MS participants with sNfL-E exhibited worse neurological function (patient-reported disability, walking speed, manual dexterity, and cognitive processing speed), lower brain parenchymal fraction, and higher T2 lesion volume. Longitudinal analyses revealed accelerated short-term rates of whole brain atrophy in sNfL-E participants and higher odds of new T2 lesion development, although both MS participants with or without sNfL-E exhibited faster rates of whole brain atrophy compared to HC. Findings were consistent in analyses examining age-normative sNfL Z-scores as a continuous variable.

INTERPRETATION

Elevated sNfL is associated with clinical disability, inflammatory disease activity, and whole brain atrophy in MS, but interpretation needs to account for comorbidities including impaired renal function, diabetes, and smoking.

Benefits of early treatment with natalizumab: a real-world study

BACKGROUND

The impact of early versus later high-efficacy disease-modifying therapy (DMT) in patients with multiple sclerosis (MS) is uncertain. This study reported the association of early versus later natalizumab treatment with real-world clinical outcomes in MS patients.

METHODS

The study included 661 participants diagnosed with MS in 1994 or later from 7 US centers participating in the MS Partners Advancing Technology for Health Solutions (MS PATHS) network. Time to natalizumab treatment between diagnosis and first infusion (TTNT) was determined from the Tysabri Outreach: Unified Commitment to Health (TOUCH) registry. Clinical outcomes were defined using neuroperformance tests included in the Multiple Sclerosis Performance Test. Associations were tested using TTNT as a categorical and continuous variable. Linear mixed models addressed within-subject and within-site clustering.

RESULTS

TTNT varied from 0.1 to 19.8 years (median [interquartile range] 4.2 [1.8, 9.0] years). A significant association between later natalizumab use and worse outcomes was demonstrated for walking speed (p < 0.001), processing speed (p < 0.001), manual dexterity (p < 0.001), brain atrophy (p = 0.001), and T2 lesion volume (p = 0.02). Covariate-adjusted modelling of a sensitivity population diagnosed with MS in 2006 or later (n = 424) demonstrated significant associations between longer TTNT and worse walking speed (p < 0.05), processing speed (p < 0.001), and manual dexterity (p < 0.001).

CONCLUSION

Later initiation of natalizumab was associated with worse clinical and radiologic imaging outcomes. Thus, high-efficacy DMT may have greater benefit when started earlier in MS patients. These results provide a rationale for randomized controlled trials to further assess the impact of early highly-effective DMT use versus later escalation of therapy.

Digitizing a Therapeutic: Development of an Augmented Reality Dual-Task Training Platform for Parkinson's Disease

Augmented reality (AR) may be a useful tool for the delivery of dual-task training. This manuscript details the development of the Dual-task Augmented Reality Treatment (DART) platform for individuals with Parkinson's disease (PD) and reports initial feasibility, usability, and efficacy of the DART platform in provoking dual-task interference in individuals with PD. The DART platform utilizes the head-mounted Microsoft HoloLens2 AR device to deliver concurrent motor and cognitive tasks. Biomechanical metrics of gait and cognitive responses are automatically computed and provided to the supervising clinician. To assess feasibility, individuals with PD (N = 48) completed a bout of single-task and dual-task walking using the DART platform. Usability was assessed by the System Usability Scale (SUS). Dual-task interference was assessed by comparing single-task walking and walking during an obstacle course while performing a cognitive task. Average gait velocity decreased from 1.06 to 0.82 m/s from single- to dual-task conditions. Mean SUS scores were 81.3 (11.3), which placed the DART in the "good" to "excellent" category. To our knowledge, the DART platform is the first to use a head-mounted AR system to deliver a dual-task paradigm and simultaneously provide biomechanical data that characterize cognitive and motor performance. Individuals with PD were able to successfully use the DART platform with satisfaction, and dual-task interference was provoked. The DART platform should be investigated as a platform to treat dual-task declines associated with PD.

Community-based high-intensity cycling improves disease symptoms in individuals with Parkinson's disease: A six-month pragmatic observational study

Participation in supervised, laboratory-based aerobic exercise protocols holds promise in slowing the progression of Parkinson's disease (PD). Gaps remain regarding exercise adherence and effectiveness of laboratory protocols translated to community-based programs. The aim of the project was to monitor exercise behaviour and evaluate its effect on disease progression over a 6 month period in people with PD participating in a community-based Pedalling for Parkinson's (PFP) cycling program. A pragmatic, observational study design was utilised to monitor exercise behaviour at five community sites. The Movement Disorders Society-Unified Parkinson's disease Rating Scale Motor III (MDS-UPDRS-III) and other motor and non-motor outcomes were gathered at enrollment and following 6 months of exercise. Attendance, heart rate, and cadence data were collected for each exercise session. On average, people with PD (N = 41) attended nearly 65% of the offered PFP classes. Average percent of age-estimated maximum heart rate was 69.3 ± 11.9%; average cadence was 74.9 ± 9.0 rpms. The MDS-UPDRS III significantly decreased over the 6-month exercise period (37.2 ± 11.7 to 33.8 ± 11.7, p = 0.001) and immediate recall significantly improved (42.3 ± 12.4 to 47.1 ± 12.7, p = 0.02). Other motor and non-motor metrics did not exhibit significant improvement. Participants who attended ~74% or more of available PFP classes experienced the greatest improvement in MDS-UPDRS III scores; of those who attended less than 74% of classes, cycling greater than or equal to 76 rpms lead to  improvement. Attendance and exercise intensity data indicated that a laboratory-based exercise protocol can be successfully translated to a community setting. Consistent attendance and pedalling at a relatively high cadence may be key variables to PD symptom mitigation. Improvement in clinical ratings coupled with lack of motor and non-motor symptom progression over 6 months provides rationale for further investigation of the real-world, disease-modifying potential of aerobic exercise for people with PD.

Real-world effectiveness of dimethyl fumarate versus fingolimod in a cohort of patients with multiple sclerosis using standardized, quantitative outcome metrics

Background

Prior studies suggest comparable effectiveness of dimethyl fumarate (DMF) and fingolimod (FTY) in multiple sclerosis (MS) using relapse, Expanded Disability Status Score (EDSS), and magnetic resonance imaging (MRI) lesion metrics.

Objective

Compare the real-world effectiveness of DMF versus FTY using quantitative, validated neuroperformance tests, MRI, and serum neurofilament light chain (sNfL) outcomes while controlling for between-group differences.

Methods

Patients were eligible if on DMF or FTY when first enrolled in the MS Partners Advancing Technology and Health Solutions (MS PATHS) network and had ≥1-year follow-up in MS PATHS. Sensitivity analysis included a subgroup who started DMF/FTY ≤2 years from enrolment. After propensity score weighting, differences in means and in mean 1-year change of neuroperformance and MRI outcomes were compared. sNfL levels were assessed. This was a non-randomized comparison.

Results

In the overall cohort, no significant differences were observed between DMF (n = 702) and FTY (n = 600) in neuroperformance or MRI outcomes including brain volume loss; mean time (SD) since treatment initiation was 1.98 (0.68) years for DMF and 2.02 (0.75) years for FTY. A sensitivity analysis controlling for DMF and FTY treatment duration yielded similar results.

Conclusion

In this study, DMF and FTY demonstrated similar effects on physical and cognitive neuroperformance and MRI outcomes. Direct comparisons to other fumarates and S1P receptor modulators were not conducted.

Clinical Evaluation of Siponimod for the Treatment of Secondary Progressive Multiple Sclerosis: Pathophysiology, Efficacy, Safety, Patient Acceptability and Adherence

INTRODUCTION

A number of disease-modifying therapies have been approved for use in relapsing-remitting multiple sclerosis (MS) in the past two decades. However, only few treatment options are available for patients with secondary progressive multiple sclerosis (SPMS). Siponimod has recently been approved for use in patients with active forms of SPMS (who experience clinical relapses or new lesions on MRI superimposed on secondary progression independent of relapse activity).

OBJECTIVE

The aim of this article is to provide a comprehensive review on the mechanism of action, efficacy, safety, cost effectiveness and patient adherence with siponimod.

METHODS

We performed a PubMed search using the search terms: "siponimod", "secondary progressive multiple sclerosis", "sphingosine 1-phosphate modulators". Titles and abstract were screened and selected for relevance to the key section of this article.

FINDINGS

Siponimod is an oral sphingosine-1-phosphate receptor (S1PR) modulator with selectivity to S1PR-1 and 5. Modulation of this receptor on lymphocytes causes its internalization and degradation, preventing their egress from lymphoid tissues to the blood. In the pivotal Phase 3 randomized controlled trial EXPAND, siponimod was superior to placebo in reducing the risk of disability progression confirmed at 3 and 6 months, as well as the development of new MRI lesions and the rate of brain volume loss. Secondary analysis also showed a benefit on measures of cognitive functioning. The risk of lymphopenia and first-dose bradycardia appears to be lower with siponimod compared to non-selective S1P1R modulators. Different CYP2C9 genotypes affect the metabolism of siponimod; hence, genetic testing is required to adapt the titration and final dose accordingly.

CONCLUSION

Long-term extension and real-world studies will allow further evaluation of efficacy and safety in this population. Future research should focus on better defining SPMS, and identifying biomarkers of progression and outcome measures of treatment response in this category of patients.

Clinical and Research Applications of the Electronic Medical Record in Multiple Sclerosis: A Narrative Review of Current Uses and Future Applications

BACKGROUND

The electronic medical record (EMR) has revolutionized health care workflow and delivery. It has evolved from a clinical adjunct to a multifaceted tool, with uses relevant to patient care and research.

METHODS

A MEDLINE literature review was conducted to identify data regarding the use of EMR for multiple sclerosis (MS) clinical care and research.

RESULTS

Of 282 relevant articles identified, 29 were included. A variety of EMR integrated platforms with features specific to MS have been designed, with options for documenting disease course, disability status, and treatment. Research efforts have focused on early diagnosis identification, relapse prediction, and surrogates for disability status.

CONCLUSIONS

The available platforms and associated research support the utility of harnessing EMR for MS care. The adoption of a core set of discrete EMR elements should be considered to support future research efforts and the ability to harmonize data across institutions.

Digital Biomarkers in Multiple Sclerosis

For incurable diseases, such as multiple sclerosis (MS), the prevention of progression and the preservation of quality of life play a crucial role over the entire therapy period. In MS, patients tend to become ill at a younger age and are so variable in terms of their disease course that there is no standard therapy. Therefore, it is necessary to enable a therapy that is as personalized as possible and to respond promptly to any changes, whether with noticeable symptoms or symptomless. Here, measurable parameters of biological processes can be used, which provide good information with regard to prognostic and diagnostic aspects, disease activity and response to therapy, so-called biomarkers Increasing digitalization and the availability of easy-to-use devices and technology also enable healthcare professionals to use a new class of digital biomarkers-digital health technologies-to explain, influence and/or predict health-related outcomes. The technology and devices from which these digital biomarkers stem are quite broad, and range from wearables that collect patients' activity during digitalized functional tests (e.g., the Multiple Sclerosis Performance Test, dual-tasking performance and speech) to digitalized diagnostic procedures (e.g., optical coherence tomography) and software-supported magnetic resonance imaging evaluation. These technologies offer a timesaving way to collect valuable data on a regular basis over a long period of time, not only once or twice a year during patients' routine visit at the clinic. Therefore, they lead to real-life data acquisition, closer patient monitoring and thus a patient dataset useful for precision medicine. Despite the great benefit of such increasing digitalization, for now, the path to implementing digital biomarkers is widely unknown or inconsistent. Challenges around validation, infrastructure, evidence generation, consistent data collection and analysis still persist. In this narrative review, we explore existing and future opportunities to capture clinical digital biomarkers in the care of people with MS, which may lead to a digital twin of the patient. To do this, we searched published papers for existing opportunities to capture clinical digital biomarkers for different functional systems in the context of MS, and also gathered perspectives on digital biomarkers under development or already existing as a research approach.

Effectiveness of a Long-Term, Home-Based Aerobic Exercise Intervention on Slowing the Progression of Parkinson Disease: Design of the Cyclical Lower Extremity Exercise for Parkinson Disease II (CYCLE-II) Study

OBJECTIVE

Previous short duration studies have demonstrated that high-intensity aerobic exercise improves aspects of motor and non-motor function in people with Parkinson disease (PwPD); however, the effectiveness of a long-term exercise intervention on slowing disease progression is unknown. The primary aim of this study is to determine the disease-altering effects of high-intensity aerobic exercise, administered on an upright stationary cycle, on the progression of PD. A secondary aim is to develop a prognostic model for 12-month changes in the Movement Disorder Society Unified Parkinson's Disease Rating Scale III (MDS-UPDRS III) of PwPD undergoing an aerobic exercise intervention.

METHODS

This pragmatic, multisite, single-rater blinded, randomized controlled trial will recruit PwPD from 2 large, urban, academic medical centers. Participants (N = 250 PwPD) will be randomized to (1) home-based aerobic exercise or (2) usual and customary care. Those in the aerobic exercise arm will be asked to complete in-home aerobic exercise sessions at 60% to 80% of heart rate reserve 3 times per week for 12 months utilizing a commercially available upright exercise cycle. The usual and customary care group will continue normal activity levels. Daily activity will be monitored for both groups throughout the 12-month study period. The primary outcome, both to assess disease-modifying response to aerobic exercise and for prognostic modeling in the aerobic exercise arm, is 12-month rate of change in the MDS-UPDRS III. Clinical and biomechanical measures will also be used to assess upper and lower extremity motor function as well as non-motor functions.

IMPACT

Should long-term aerobic exercise demonstrate disease-modifying capability, this study will provide evidence that "Exercise is Medicine" for PwPD. Further, the derived prognostic model will inform a patient-specific exercise prescription for PwPD and expected effects on PD progression.

The Canadian prospective cohort study to understand progression in multiple sclerosis (CanProCo): rationale, aims, and study design

Background

Neurological disability progression occurs across the spectrum of people living with multiple sclerosis (MS). Although there are a handful of disease-modifying treatments approved for use in progressive phenotypes of MS, there are no treatments that substantially modify the course of clinical progression in MS. Characterizing the determinants of clinical progression can inform the development of novel therapeutic agents and treatment approaches that target progression in MS, which is one of the greatest unmet needs in clinical practice. Canada, having one of the world’s highest rates of MS and a publicly-funded health care system, represents an optimal country to achieve in-depth analysis of progression. Accordingly, the overarching aim of the Canadian Prospective Cohort Study to Understand Progression in MS (CanProCo) is to evaluate a wide spectrum of factors associated with the clinical onset and rate of disease progression in MS, and to describe how these factors relate to one another to influence progression.

Methods

CanProCo is a prospective, observational cohort study with investigators specializing in epidemiology, neuroimaging, neuroimmunology, health services research and health economics. CanProCo’s study design was approved by an international review panel, comprised of content experts and key stakeholders. One thousand individuals with radiologically-isolated syndrome, relapsing-remitting MS, and primary-progressive MS within 10–15 years of disease onset will be recruited from 5 academic MS centres in Canada. Participants will undergo detailed clinical evaluation annually over 5 years (including advanced, app-based clinical data collection). In a subset of participants within 5–10 years of disease onset (n = 500), blood, cerebrospinal fluid, and research MRIs will be collected allowing an integrated, in-depth evaluation of factors contributing to progression in MS from multiple perspectives. Factors of interest range from biological measures (e.g. single-cell RNA-sequencing), MRI-based microstructural assessment, participant characteristics (self-reported, performance-based, clinician-assessed, health-system based), and micro and macro-environmental factors.

Discussion

Halting the progression of MS remains a fundamental need to improve the lives of people living with MS. Achieving this requires leveraging transdisciplinary approaches to better characterize why clinical progression occurs. CanProCo is a pioneering multi-dimensional cohort study aiming to characterize these determinants to inform the development and implementation of efficacious and effective interventions.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12883-021-02447-7.

Vascular comorbidity is associated with lower brain volumes and lower neuroperformance in a large multiple sclerosis cohort

OBJECTIVE

The objective of this study is to assess the association between vascular comorbidity burden with clinical and imaging features of disease burden in a large population of people with multiple sclerosis (MS).

METHODS

We included participants from the MS Partners Advancing Technology Health Solutions (MS PATHS) cohort. We evaluated if vascular comorbidities (diabetes, hypertension, and dyslipidemia) or a composite sum of comorbidities was associated with MS characteristics, including objective neurologic function assessments and quantitative brain magnetic resonance imaging (MRI) measurements in propensity score-weighted models.

RESULTS

In total, 11,506 participants (6409 (55%) with brain MRI) were included. Individuals with 2+ vascular comorbidities had slower walking speed (standard deviation (SD) = -0.49; 95% confidence interval (CI) = -0.78, -0.19; p = 0.001), slower manual dexterity (SD = -0.41; 95% CI = -0.57, -0.26; p < 0.0001), and fewer correct scores on cognitive processing speed (SD = -0.11; 95% CI = -0.20, -0.02; p = 0.02) versus those with no comorbidities. Those with 2+ had lower brain parenchymal (-0.41%, 95% CI = -0.64, -0.17) and gray matter fractions (-0.30%, 95% CI = -0.49, -0.10), including reduced cortical (-10.10 mL, 95% CI = -15.42, -4.78) and deep (-0.44 mL, 95% CI = -0.84, -0.04) gray matter volumes versus those with no comorbidity.

CONCLUSION

Increased vascular comorbidity burden was associated with clinical and imaging markers of neurologic dysfunction and neurodegeneration in MS. Strategies to optimize comorbidity management in people with MS are warranted.

Prediction in treatment outcomes in multiple sclerosis: challenges and recent advances

INTRODUCTION

Multiple Sclerosis (MS) is a chronic autoimmune and neurodegenerative disease of the central nervous system with a course dependent on early treatment response. Increasing evidence also suggests that despite eliminating disease activity (relapses and lesions), many patients continue to accrue disability, highlighting the need for a more comprehensive definition of treatment success. Optimizing disability outcome measures, as well as continuously improving our understanding of neuroinflammatory and neurodegenerative biomarkers is required.

AREAS COVERED

This review describes the challenges inherent in classifying and monitoring disease phenotype in MS. The review also provides an assessment of clinical, radiological, and blood biomarker tools for current and future practice.

EXPERT OPINION

Emerging MRI techniques and standardized patient outcome assessments will increase the accuracy of initial diagnosis and understanding of disease progression.

Mobile health (mHealth) usage, barriers, and technological considerations in persons with multiple sclerosis: a literature review

OBJECTIVES

Persons with multiple sclerosis (MS) can face a number of potential healthcare-related barriers, for which mobile health (mHealth) technology can be potentially beneficial. This review aimed to understand the frequency, current uses, and potential barriers with mHealth usage among persons with MS.

METHODS

A query string was used to identify articles on PubMed, MEDLINE, CINAHL, and IEEE Xplore that were published in English between January 2010 and December 2019. Abstracts were reviewed and selected based on a priori inclusion and exclusion criteria. Fifty-nine peer-reviewed research studies related to the study questions are summarized.

RESULTS

The majority of persons with MS were reported as using smartphones, although rates of mHealth utilization varied widely. mHealth usage was grouped into 3 broad categories: (1) disability and symptom measurement; (2) interventions and symptom management; and (3) tracking and promoting adherence. While there have been an increasing number of mHealth options, certain limitations associated with MS (eg, poor dexterity, memory problems) may affect usage, although including persons with MS in the design process can address some of these issues.

DISCUSSION

Given the increased attention to mHealth in this population and the current need for telehealth and at home devices, it is important that persons with MS and healthcare providers are involved in the development of new mHealth tools to ensure that the end product meets their needs. Considerations for addressing the potential mHealth use barriers in persons with MS are discussed.

Comprehensive Approach to Management of Multiple Sclerosis: Addressing Invisible Symptoms-A Narrative Review

Multiple sclerosis (MS) is a chronic autoimmune inflammatory disease of the central nervous system, leading to neurodegeneration and manifesting as a variety of symptoms. These can include "invisible" symptoms, not externally evident to others, such as fatigue, mood disorders, cognitive impairments, pain, bladder/bowel dysfunction, sexual dysfunction, and vision changes. Invisible symptoms are highly prevalent in people living with MS, with multifactorial etiology and potential to impact the disease course. Patient experiences of these symptoms include both physical and psychosocial elements, which when unaddressed negatively influence many aspects of quality of life and perception of health. Despite the high impact on patient lives, gaps persist in awareness and management of these hidden symptoms. The healthcare provider and patient author experiences brought together here serve to raise the profile of invisible symptoms and review strategies for a team-based approach to comprehensive MS care. We summarize the current literature regarding the prevalence and etiology of invisible symptoms to convey the high likelihood that a person living with MS will contend with one or more of these concerns. We then explore how open communication between people living with MS and their care team, stigma mitigation, and shared decision-making are key to comprehensive management of invisible symptoms. We recommend validated screening tools and technological advancements that may be incorporated into MS care to regularly monitor these symptoms, offering insight into how healthcare providers can both educate and listen to patients, with the goal of improved patient quality of life. By pairing clinical knowledge with an understanding and consideration of the patient perspective, providers will be equipped to foster a patient-centered dialogue that encourages shared decision-making. Invisible symptoms of MS.

Digital Technology in Clinical Trials for Multiple Sclerosis: Systematic Review

Clinical trials in multiple sclerosis (MS) have been including digital technology tools to overcome limitations in treatment delivery and disease monitoring. In March 2020, we conducted a systematic search on pubmed.gov and clinicaltrials.gov databases (with no restrictions) to identify all relevant published and unpublished clinical trials, in English language, including MS patients, in which digital technology was applied. We used “multiple sclerosis” and “clinical trial” as the main search words, and “app”, “digital”, “electronic”, “internet” and “mobile” as additional search words, separately. Digital technology is part of clinical trial interventions to deliver psychotherapy and motor rehabilitation, with exergames, e-training, and robot-assisted exercises. Digital technology has been used to standardise previously existing outcome measures, with automatic acquisitions, reduced inconsistencies, and improved detection of symptoms (e.g., electronic recording of motor performance). Other clinical trials have been using digital technology for monitoring symptoms that would be otherwise difficult to detect (e.g., fatigue, balance), for measuring treatment adherence and side effects, and for self-assessment purposes. Collection of outcome measures is progressively shifting from paper-based on site, to internet-based on site, and, in the future, to internet-based at home, with the detection of clinical and treatment features that would have remained otherwise invisible. Similarly, remote interventions provide new possibilities of motor and cognitive rehabilitation.

Quantitative signal properties from standardized MRIs correlate with multiple sclerosis disability

OBJECTIVE

To enable use of clinical magnetic resonance images (MRIs) to quantify abnormalities in normal appearing (NA) white matter (WM) and gray matter (GM) in multiple sclerosis (MS) and to determine associations with MS-related disability. Identification of these abnormalities heretofore has required specialized scans not routinely available in clinical practice.

METHODS

We developed an analytic technique which normalizes image intensities based on an intensity atlas for quantification of WM and GM abnormalities in standardized MRIs obtained with clinical sequences. Gaussian mixture modeling is applied to summarize image intensity distributions from T1-weighted and 3D-FLAIR (T2-weighted) images from 5010 participants enrolled in a multinational database of MS patients which collected imaging, neuroperformance and disability measures.

RESULTS

Intensity distribution metrics distinguished MS patients from control participants based on normalized non-lesional signal differences. This analysis revealed non-lesional differences between relapsing MS versus progressive MS subtypes. Further, the correlation between our non-lesional measures and disability was approximately three times greater than that between total lesion volume and disability, measured using the patient derived disease steps. Multivariate modeling revealed that measures of extra-lesional tissue integrity and atrophy contribute uniquely, and approximately equally, to the prediction of MS-related disability.

INTERPRETATION

These results support the notion that non-lesional abnormalities correlate more strongly with MS-related disability than lesion burden and provide new insight into the basis of abnormalities in NA WM. Non-lesional abnormalities distinguish relapsing from progressive MS but do not distinguish between progressive subtypes suggesting a common progressive pathophysiology. Image intensity parameters and existing biomarkers each independently correlate with MS-related disability.

Development and Validation of a Mobile Application to Detect Visual Dysfunction Following Mild Traumatic Brain Injury

INTRODUCTION

Following mild traumatic brain injury, visual dysfunction is a common occurrence, yet the condition often goes undiagnosed. A mobile application was developed to measure aspects of visual acuity and oculomotor function. The aim of this project was to validate the newly developed suite of outcomes conducive for use in the field to detect visual dysfunction.

MATERIALS AND METHODS

A custom mobile application was developed on an Apple iPad using iOS operating system software version 11.0 in Objective C to measure near point of convergence (NPC), distance visual acuity, reading fluency, and self-rated convergence insufficiency (CI). To determine construct validity, 50 healthy young adults were administered NPC and distance visual acuity assessments using the iPad and standard clinical approaches. A ruler measurement was obtained simultaneous to the iPad NPC measurement to determine measurement accuracy. All testing was administered by a licensed optometrist and the order of testing (iPad versus clinical) was randomized.

RESULTS

The correlation coefficient between the iPad and clinical measurements of NPC was 0.893, while iPad and ruler measurement was 0.947. Modest accordance was found between iPad and wall chart measures assessing distance visual acuity. A ceiling effect was evident with use of a wall chart to determine distance visual acuity. Healthy young adults scored a mean (SD) of 13.0 (7.4) on the Convergence Insufficiency Symptom Survey. Reading fluency was highly variable with a mean (SD) of 291 (119) words per minute.

CONCLUSIONS

iPad measures of NPC were highly correlated with clinical measures, while visual acuity measured with the iPad showed modest correlation. Nonetheless, the suite of visual assessments provide value as screening tools, and when used in combination with reading fluency assessment and self-reported CI may be effective in identifying visual dysfunction following mild traumatic brain injury.

Impact of natalizumab on quality of life in a real-world cohort of patients with multiple sclerosis: Results from MS PATHS

Background

Optimizing multiple sclerosis treatment warrants understanding of changes in physical, mental, and social health.

Objective

To assess the impact of natalizumab on Quality of Life in Neurological Disorders (Neuro-QoL) scores.

Methods

Annualized change in T-scores and likelihood of ≥5-point improvement over baseline were calculated for each Neuro-QoL domain after natalizumab initiation. Comparisons with ocrelizumab-treated patients were conducted after propensity score weighting and adjustment for relevant co-medications, year, and drug-year interaction.

Results

Among 164 natalizumab patients analyzed, 8 of 12 Neuro-QoL domains improved significantly, with greater improvement in patients with abnormal baseline Neuro-QoL. In the subgroup comparison of natalizumab-treated (n = 145) and ocrelizumab-treated (n = 520) patients, significant improvement occurred in 9 of 12 and 4 of 12 domains, respectively. The difference between groups was statistically significant for positive affect and well-being (p = 0.02), sleep (p = 0.003), and satisfaction with social roles and activities (SRA) (p = 0.03) in the overall population and for emotional and behavioral dyscontrol (p = 0.01), participation in SRA (p = 0.0001), and satisfaction with SRA (p = 0.02) in patients with abnormal baseline Neuro-QoL.

Conclusions

Natalizumab can produce clinically meaningful improvements in mental and social health. Such improvements are unlikely to be primarily driven by expectation bias, as their magnitude exceeded improvements with another high-efficacy therapy, ocrelizumab.

Use of a Smartphone to Gather Parkinson's Disease Neurological Vital Signs during the COVID-19 Pandemic

Introduction

To overcome travel restrictions during the COVID-19 pandemic, consumer-based technology was rapidly deployed to the smartphones of individuals with Parkinson's disease (PD) participating in a 12-month exercise trial. The aim of the project was to determine the feasibility of utilizing a combined synchronous and asynchronous self-administered smartphone application to characterize PD symptoms.

Methods

A synchronous video virtual visit was completed for the administration of virtual Movement Disorder Society-Unified Parkinson's Disease Rating Scale III (vMDS-UPDRS III). Participants asynchronously completed a mobile application consisting of a measure of upper extremity bradykinesia (Finger Tapping Test) and information processing.

Results

Twenty-three individuals completed the assessments. The mean vMDS-UPDRS III was 23.65 ± 8.56 points. On average, the number of taps was significantly greater for the less affected limb, 97.96 ± 17.77 taps, compared to the more affected, 89.33 ± 18.66 taps (p = 0.025) with a significantly greater number of freezing episodes for the more affected limb (p < 0.05). Correlation analyses indicated the number of errors and the number of freezing episodes were significantly related to clinical ratings of vMDS-UPDRS III bradykinesia (Rho = 0.44, p < 0.01; R = 0.43, p < 0.01, resp.) and finger tapping performance (Rho = 0.31, p = 0.03; Rho = 0.32, p = 0.03, resp.). Discussion. The objective characterization of bradykinesia, akinesia, and nonmotor function and their relationship with clinical disease metrics indicate smartphone technology provides a remote method of characterizing important aspects of PD performance. While theoretical and position papers have been published on the potential of telemedicine to aid in the management of PD, this report translates the theory into a viable reality.

Isolated Cognitive Decline in Neurologically Stable Patients with Multiple Sclerosis

(1) Background: Cognitive deterioration is an important marker of disease activity in multiple sclerosis (MS). It is vital to detect cognitive decline as soon as possible. Cognitive deterioration can take the form of isolated cognitive decline (ICD) with no other clinical signs of disease progression present. (2) Methods: We investigated 1091 MS patients from the longitudinal GQ (Grant Quantitative) study, assessing their radiological, neurological, and neuropsychological data. Additionally, the confirmatory analysis was conducted. Clinical disease activity was defined as the presence of new relapse or disability worsening. MRI activity was defined as the presence of new or enlarged T2 lesions on brain MRI. (3) Results: Overall, 6.4% of patients experienced cognitive decline and 4.0% experienced ICD without corresponding clinical activity. The vast majority of cognitively worsening patients showed concomitant progression in other neurological and radiologic measures. There were no differences in disease severity between completely stable patients and cognitively worsening patients but with normal cognition at baseline. (4) Conclusions: Only a small proportion of MS patients experience ICD over short-term follow-up. Patients with severe MS are more prone to cognitive decline; however, patients with normal cognitive performance and mild MS might benefit from the early detection of cognitive decline the most.

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.

Clinical characteristics of a large multi-center cohort of people with multiple sclerosis over age 60

BACKGROUND

As the peak prevalence of multiple sclerosis (MS) shifts due to an aging patient population, understanding the characteristics that define this older cohort to improve overall management is critical. We sought to determine the clinical characteristics of people with MS over age 60.

METHODS

Demographics, clinical characteristics, MS disease history, and Multiple Sclerosis Performance Test (MSPT) patient-reported outcomes and neuroperformance tests (NPTs) were collected from 10 academic MS centers in the US and Europe participating in the MS Partners Advancing Technology Health Solutions (MS PATHS) system. We characterized demographic and disease characteristics of included participants using descriptive statistics. We characterized prevalence of comorbidities and compared with estimated prevalences from the National Health and Nutrition Examination Survey (NHANES) respondents aged ≥60 years in 2017-2018.

RESULTS

We identified 2738 individuals over age 60 from MS PATHS, with 58.1% relapsing-remitting (RR) and 41.9% progressive. Our results showed median age (RR=65.7 years, progressive=66.0 years), age of symptom onset (RR and progressive=40.9 years), and disease duration (RR=22.8 years, progressive=23.3 years). Over two-thirds of individuals in our cohort were treated with DMTs. The most common DMT used in RR patients were interferons (17.6%) and glatiramer acetate (16.3%), while glatiramer acetate was the most common (12.0%) in progressive patients. Progressive patients had higher disability (higher median PDDS scores, worse Neuro-Qol T-scores, and worse NPTs) compared to the RR group. Pain was the most common comorbidity, followed by cardiac disease, depression, hypertension, dyslipidemia, and obesity. Compared to older NHANES participants, older people with MS were more likely to have depression (MS PATHS: 51.5% [95% CI: 49.5% to 53.5%] vs. NHANES: 21.7% [95% CI: 1619.3% to 22.2%]) and osteoporosis (MS PATHS: 12.7% [95% CI: 11.3% to 14.1%] vs. NHANES: 8.2% [95% CI: 6.2% to 10.3%]); they were less likely to be obese (MS PATHS: 29.4% [95% CI: 27.7% to 31.2%] vs. NHANES: 45.1% [95% CI: 38.9% to 51.3%]) and have diabetes (MS PATHS: 12.3% [95% CI: 11.1% to 13.6%] vs. NHANES: 22.5% [95% CI: 18.8% to 25.7%]).

CONCLUSIONS

Our study characterizes a large multi-center international cohort of people with MS over age 60. This contemporary cohort appears less disabled than prior studies, which may reflect long term impact of DMT availability on the natural history of MS. The burden of comorbidity in this population was generally high. Information on DMT use, comorbidity, and disability outcome measures will be beneficial in future studies evaluating the impact of therapeutic interventions in older individuals.

Comorbidity effect on processing speed test and MRI measures in multiple sclerosis patients

BACKGROUND

Comorbid conditions are known to affect the clinical course of multiple sclerosis (MS). Our objective was to determine the impact of comorbidities on the processing speed test (PST).

METHODS

We conducted a retrospective, longitudinal analysis of all patients who completed PST testing from June 2015 - August 2019 at our center. Our electronic medical record was queried to determine the presence of the following comorbidities: diabetes mellitus (DM), hypertension (HTN), hyperlipidemia (HLD), coronary artery disease, and depression. To help address baseline PST performance and practice effect, patients were also divided into four quartiles by baseline PST scores. Brain MRIs obtained within a 90-day window from the initial clinical assessment were quantitatively analyzed via fully-automated methods to calculate whole brain fraction (WBF), T2 lesion volume (T2LV), gray matter fraction (GMF), and thalamic volume (TV). Univariable and multivariable linear regression models were used to determine the relationship between the comorbidities, PST performance and MRI metrics over time.

RESULTS

A total of 4,344 patients (mean age 49.5 ± 12.4 years, 72.3% female, and 63.7% relapsing remitting MS) were included in the analysis with 13,375 individual patient encounters. Over half the cohort (52.4%) suffered from at least one comorbidity with the most common being depression (37.4%), HLD (20.9%), HTN (19.6%), and DM (6.4%). Patients with one or more comorbidity had lower baseline PST scores. Longitudinally, patients with two comorbidities lost 1.46 points on the PST per year relative to those with no comorbidities (95% CI -2.46 - -0.46, p = 0.004). Individuals with depression had lower PST scores than those without, and this difference persisted over time (β = -2.40, 95% CI -3.08 - -1.73, p < 0.001). At baseline, HLD patients had higher PST scores than non-HLD patients (β = 1.10, 95% CI 0.15 - 2.05, p = 0.022), but this difference did not remain over time. Individuals in the highest PST performance quartile were negatively impacted when diagnosed with depression, HTN, and DM relative to those without the comorbidities. There were no other correlations with PST scores and the remaining comorbidities. Depression was associated with lower baseline WBF (β = -0.0043, 95% CI -0.0084 - -0.0003, p = 0.033) and GMF (β = -0.0046, 95% CI -0.0078 - -0.0015, p = 0.004) along with larger T2LV (β = 0.1605, 95% CI 0.0082 - 0.3128, p = 0.039). HLD patients had more favorable baseline MRI measures, including higher WBF (β = 0.0076, 95% CI 0.0017 - 0.0135, p = 0.012) and TV (β = 0.0002, 95% CI 0.0000 - 0.0005, p = 0.041), with a lower T2LV (β = -0.2963, 95% CI -0.5219 - -0.0706, p = 0.010).

CONCLUSIONS

Comorbidities are common within a MS cohort and adversely impact processing speed. Depression adversely impacted PST scores with worse MRI outcomes. HLD was associated with lower longitudinal PST measures but favorable quantitative MRI metrics. MS patients with faster baseline processing speeds were most sensitive to comorbid conditions. Our findings suggest a complex interplay between cognition and comorbid conditions in MS patients.

Harnessing Real-World Data to Inform Decision-Making: Multiple Sclerosis Partners Advancing Technology and Health Solutions (MS PATHS)

Background: Multiple Sclerosis Partners Advancing Technology and Health Solutions (MS PATHS) is the first example of a learning health system in multiple sclerosis (MS). This paper describes the initial implementation of MS PATHS and initial patient characteristics.

Methods: MS PATHS is an ongoing initiative conducted in 10 healthcare institutions in three countries, each contributing standardized information acquired during routine care. Institutional participation required the following: active MS patient census of ≥500, at least one Siemens 3T magnetic resonance imaging scanner, and willingness to standardize patient assessments, share standardized data for research, and offer universal enrolment to capture a representative sample. The eligible participants have diagnosis of MS, including clinically isolated syndrome, and consent for sharing pseudonymized data for research. MS PATHS incorporates a self-administered patient assessment tool, the Multiple Sclerosis Performance Test, to collect a structured history, patient-reported outcomes, and quantitative testing of cognition, vision, dexterity, and walking speed. Brain magnetic resonance imaging is acquired using standardized acquisition sequences on Siemens 3T scanners. Quantitative measures of brain volume and lesion load are obtained. Using a separate consent, the patients contribute DNA, RNA, and serum for future research. The clinicians retain complete autonomy in using MS PATHS data in patient care. A shared governance model ensures transparent data and sample access for research.

Results: As of August 5, 2019, MS PATHS enrolment included participants (n = 16,568) with broad ranges of disease subtypes, duration, and severity. Overall, 14,643 (88.4%) participants contributed data at one or more time points. The average patient contributed 15.6 person-months of follow-up (95% CI: 15.5–15.8); overall, 166,158 person-months of follow-up have been accumulated. Those with relapsing–remitting MS demonstrated more demographic heterogeneity than the participants in six randomized phase 3 MS treatment trials. Across sites, a significant variation was observed in the follow-up frequency and the patterns of disease-modifying therapy use.

Conclusions: Through digital health technology, it is feasible to collect standardized, quantitative, and interpretable data from each patient in busy MS practices, facilitating the merger of research and patient care. This approach holds promise for data-driven clinical decisions and accelerated systematic learning.

Is Obesity Related to Processing Speed Impairment in Patients with Multiple Sclerosis: Results of a Large-Scale, Multicenter Study

Background

Obesity is linked to greater physical disability and increased comorbidities among patients with multiple sclerosis (MS). Its contribution to cognition in this group is unclear. This observational study examines the link between obesity and processing speed in a large sample of patients with MS (PwMS).

Methods

As part of routine clinical care at our center, PwMS completed the Processing Speed Test (PST), an electronic implementation of the Symbol Digit Modalities Test (SDMT). Height and weight were used to calculate body mass index (BMI). Bivariate correlations were conducted to examine the association between PST and BMI in the group overall and in subgroups based on demographic and clinical variables. A one-way ANOVA examined differences in PST by BMI categories (normal weight, overweight, obese).

Results

The sample included 8,713 patients. No association between PST and BMI was found in the entire sample (r = .01), nor within subgroups based on demographic and disease variables. No difference in PST score was found between BMI categories.

Conclusions

No association between BMI and processing speed was found among PwMS regardless of demographic or disease-specific patient characteristics.

Data Collection in Multiple Sclerosis: The MSDS Approach

Multiple sclerosis (MS) is a frequent chronic inflammatory disease of the central nervous system that affects patients over decades. As the monitoring and treatment of MS become more personalized and complex, the individual assessment and collection of different parameters ranging from clinical assessments via laboratory and imaging data to patient-reported data become increasingly important for innovative patient management in MS. These aspects predestine electronic data processing for use in MS documentation. Such technologies enable the rapid exchange of health information between patients, practitioners, and caregivers, regardless of time and location. In this perspective paper, we present our digital strategy from Dresden, where we are developing the Multiple Sclerosis Documentation System (MSDS) into an eHealth platform that can be used for multiple purposes. Various use cases are presented that implement this software platform and offer an important perspective for the innovative digital patient management in the future. A holistic patient management of the MS, electronically supported by clinical pathways, will have an important impact on other areas of patient care, such as neurorehabilitation.

Multiple Sclerosis Performance Test: validation of self-administered neuroperformance modules

BACKGROUND AND PURPOSE

The purpose was to determine the test-retest reliability, practice effects, convergent validity and sensitivity to multiple sclerosis (MS) disability of neuroperformance subtests from the patient self-administered Multiple Sclerosis Performance Test (MSPT) designed to assess low contrast vision (Contrast Sensitivity Test, CST), upper extremity motor function (Manual Dexterity Test, MDT) and lower extremity motor function (Walking Speed Test, WST) and to introduce the concept of regression-based norms to aid clinical interpretation of performance scores using the MSPT cognition test (Processing Speed Test, PST) as an example.

METHODS

Substudy 1 assessed test-retest reliability, practice effects and convergent validity of the CST, MDT and WST in 30 MS patients and 30 healthy controls. Substudy 2 examined sensitivity to MS disability in over 600 MS patients as part of their routine clinic assessment. Substudy 3 compared performance on the PST in research volunteers and clinical samples.

RESULTS

The CST, MDT and WST were shown to be reliable, valid and sensitive to MS outcomes. Performance was comparable to technician-administered testing. PST performance was poorer in the clinical sample compared with the research volunteer sample.

CONCLUSIONS

The self-administered MSPT neuroperformance modules produce reliable, objective metrics that can be used in clinical practice and support outcomes research. Published studies which require patient voluntary consent may underestimate the rate of cognitive dysfunction observed in a clinical setting.

Leveraging real-world data to investigate multiple sclerosis disease behavior, prognosis, and treatment

Randomized controlled clinical trials and real-world observational studies provide complementary information but with different validity. Some clinical questions (disease behavior, prognosis, validation of outcome measures, comparative effectiveness, and long-term safety of therapies) are often better addressed using real-world data reflecting larger, more representative populations. Integration of disease history, clinician-reported outcomes, performance tests, and patient-reported outcome measures during patient encounters; imaging and biospecimen analyses; and data from wearable devices increase dataset utility. However, observational studies utilizing these data are susceptible to many potential sources of bias, creating barriers to acceptance by regulatory agencies and the medical community. Therefore, data standardization and validation within datasets, harmonization across datasets, and application of appropriate analysis methods are important considerations. We review approaches to improve the scope, quality, and analyses of real-world data to advance understanding of multiple sclerosis and its treatment, as an example of opportunities to better support patient care and research.

Technology-enabled comprehensive characterization of multiple sclerosis in clinical practice

BACKGROUND

Objective and longitudinal measurements of disability in patients with multiple sclerosis (MS) are desired in order to monitor disease status and response to disease-modifying and symptomatic therapies. Technology-enabled comprehensive assessment of MS patients, including neuroperformance tests (NPTs), patient-reported outcome measures (PROMs), and MRI, is incorporated into clinical care at our center. The relationships of each NPT with PROMs and MRI measures in a real-world setting are incompletely studied, particularly in larger datasets.

OBJECTIVES

To demonstrate the utility of comprehensive neurological assessment and determine the association between NPTs, PROMs, and quantitative MRI measures in a large MS clinical cohort.

METHODS

NPTs (processing speed [PST], contrast sensitivity [CST], manual dexterity [MDT], and walking speed [WST]) and physical disability-related PROMs (Quality of Life in Neurological Disorders [Neuro-QoL], Patient Determined Disease Steps [PDDS], and Patient-Reported Outcomes Measurement Information System Global-10 [PROMIS-10] physical) were collected as part of routine clinical care. Fully-automated MRI analysis calculated T2-lesion volume (T2LV), whole brain fraction (WBF), thalamic volume (TV), and cervical spinal cord cross-sectional area (CA) for brain MRIs completed within 3 months of a clinic visit during which NPTs and PROMs were assessed. Spearman's rank correlation coefficients evaluated the cross-sectional associations of NPTs with PROMs and MRI measures. Linear regression was utilized to determine which combination of clinical characteristics, patient demographics, MRI measures, and PROMs best cross-sectionally explained each NPT result.

RESULTS

997 unique patients (age 47.7 ± 11.4 years, 71.8% female) who underwent assessments over a 2-year period were included. Correlations among NPTs and PROMs were moderate. PST correlations were strongest for Neuro-QoL upper extremity (NQ-UE) (Spearman's rho = 0.43) and lower extremity (NQ-LE) (0.47). CST correlations were strongest for NQ-UE (0.33), NQ-LE (0.36), and PDDS (-0.31). MDT correlations were strongest for NQ-UE (-0.53), NQ-LE (-0.54), and PDDS (0.53). WST correlations were strongest for PDDS (0.64) and NQ-LE (-0.65). NPTs also had moderate correlations with MRI metrics, the strongest of which were observed with PST (with T2LV (-0.44) and WBF (0.49)). Spearman's rho for other NPT-MRI correlations ranged from 0.23 to 0.36. Linear regression identified age, disease duration, PROMIS-10 physical, NQ-UE, NQ-LE, T2LV and WBF as significant cross-sectional explanatory variables for PST (adjusted R²=0.46). For CST, significant variables included age and NQ-LE (adjusted R² = 0.30). For MDT, significant variables included PDDS, PROMIS-10 physical, NQ-UE, NQ-LE, T2LV, and WBF (adjusted R²=0.37). For WST, significant variables included sex, PDDS, NQ-LE, T2LV, and CA (adjusted R²=0.39).

CONCLUSIONS

Impaired performance on NPTs correlated with worse physical disability-related PROMs and MRI disease severity, but the strongest cross-sectional explanatory variables for each NPT component varied. This study supports the use of comprehensive, objective quantification of MS status in clinical and research settings. Future longitudinal analyses can determine predictors of treatment response and disability worsening.

MSCopilot, a new multiple sclerosis self-assessment digital solution: results of a comparative study versus standard tests

BACKGROUND AND PURPOSE

Assessing patients' disability in multiple sclerosis (MS) requires time-consuming batteries of hospital tests. MSCopilot is a software medical device for the self-assessment of patients with MS (PwMS), combining four tests: walking, dexterity, cognition and low contrast vision. The objective was to validate MSCopilot versus the Multiple Sclerosis Functional Composite (MSFC).

METHODS

This multicentre, open-label, randomized, controlled, crossover study enrolled 141 PwMS and 76 healthy controls (HCs). All participants performed MSCopilot and MSFC tests at day 0. To assess reproducibility, 46 PwMS performed the same tests at day 30 ± 3. The primary end-point was the validation of MSCopilot versus MSFC for the identification of PwMS against HCs, quantified using the area under the curve (AUC). The main secondary end-point was the correlation of MSCopilot z-scores with MSFC z-scores.

RESULTS

In all, 116 PwMS and 69 HCs were analysed. The primary end-point was achieved: MSCopilot performance was non-inferior to that of MSFC (AUC 0.92 and 0.89 respectively; P = 0.3). MSCopilot and MSFC discriminated PwMS and HCs with 81% and 76% sensitivity and 82% and 88% specificity respectively. Digital and standard test scores were highly correlated (r = 0.81; P < 0.001). The test-retest study demonstrated the good reproducibility of MSCopilot.

CONCLUSION

This study confirms the reliability of MSCopilot and its usability in clinical practice for the monitoring of MS-related disability.