Explore the vast range of titles available.

An individualized innovative disease management is of great importance for people with multiple sclerosis (pwMS) to cope with the complexity of this chronic, multidimensional disease. However, an individual state of the art strategy, with precise adjustment to the patient’s characteristics, is still far from being part of the everyday care of pwMS. The development of digital twins could decisively advance the necessary implementation of an individualized innovative management of MS. Through artificial intelligence-based analysis of several disease parameters – including clinical and para-clinical outcomes, multi-omics, biomarkers, patient-related data, information about the patient’s life circumstances and plans, and medical procedures – a digital twin paired to the patient’s characteristic can be created, enabling healthcare professionals to handle large amounts of patient data. This can contribute to a more personalized and effective care by integrating data from multiple sources in a standardized manner, implementing individualized clinical pathways, supporting physician-patient communication and facilitating a shared decision-making. With a clear display of pre-analyzed patient data on a dashboard, patient participation and individualized clinical decisions as well as the prediction of disease progression and treatment simulation could become possible. In this review, we focus on the advantages, challenges and practical aspects of digital twins in the management of MS. We discuss the use of digital twins for MS as a revolutionary tool to improve diagnosis, monitoring and therapy refining patients’ well-being, saving economic costs, and enabling prevention of disease progression. Digital twins will help make precision medicine and patient-centered care a reality in everyday life.

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.

Digital tools such as the self-administered Multiple Sclerosis Performance Test (MSPT) support structured monitoring of multiple sclerosis (MS) through standardized assessments of motor, visual, and cognitive functions. Despite clinical validity and adoption, real-world data on long-term user experiences and the consequences of discontinuing MSPT-based monitoring in routine care are lacking. This study aimed to assess multi-year user experiences with the MSPT among patients and neurologists, investigate patient perceptions following its discontinuation from clinical care, and evaluate preferences for future MSPT-like digital tools. This observational, repeated cross-sectional study involved three questionnaire-based surveys. In 2020, separate surveys of patients and neurologists (combined  = 210) evaluated sustained MSPT use in routine care. Following the cessation of funding and subsequent discontinuation of MSPT from clinical workflows in 2023, a patient survey was conducted in 2024 (  = 144) to evaluate the impact of this withdrawal and preferences for future digital monitoring tools. Quantitative analyses included frequency distributions, Net Promoter Score (NPS) categorization, correlational analyses, and descriptive data visualization. Patients reported high satisfaction with MSPT usability, utility for disease monitoring, administration frequency, time efficiency, physical and cognitive demands, and suitability for unsupervised tablet-based use. Most viewed discontinuation from their clinical care negatively and favored reintroducing similar tools, either in clinic (85.5%) or at home (78.6%). Those who dissented cited time savings and sufficient physician feedback. Prolonged MSPT use is associated with strong patient and clinician acceptance. Findings support the continued integration of digital monitoring tools into MS care and emphasize the importance of patient perspectives in their design.

Multiple sclerosis (MS) is a chronic neuroinflammatory disease characterized by central nervous system demyelination and axonal degeneration. Fatigue affects a major portion of MS patients, significantly impairing their daily activities and quality of life. Despite its prevalence, the mechanisms underlying fatigue in MS are poorly understood, and measuring fatigue remains a challenging task. This study evaluates the efficacy of automated speech analysis in detecting fatigue in MS patients. MS patients underwent a detailed clinical assessment and performed a comprehensive speech protocol. Using features from three different free speech tasks and a proprietary cognition score, our support vector machine model achieved an AUC on the ROC of 0.74 in detecting fatigue. Using only free speech features evoked from a picture description task we obtained an AUC of 0.68. This indicates that specific free speech patterns can be useful in detecting fatigue. Moreover, cognitive fatigue was significantly associated with lower speech ratio in free speech ( ρ  = −0.283, p  = 0.001), suggesting that it may represent a specific marker of fatigue in MS patients. Together, our results show that automated speech analysis, of a single narrative free speech task, offers an objective, ecologically valid and low-burden method for fatigue assessment. Speech analysis tools offer promising potential applications in clinical practice for improving disease monitoring and management.

The SARS-CoV-2 pandemic profoundly impacted people with multiple sclerosis (pwMS). Disease-related aspects and demographic factors may influence vaccination rates, infection susceptibility, and severity. Despite prior research, comprehensive real-world data obtained throughout the pandemic remain limited. We investigated SARS-CoV-2 vaccination and infection patterns in a large monocentric real-world cohort. We collected prospective data from medical visits at the MS Center Dresden, Germany, from the pandemic’s beginning until 31 May 2022. Logistic regression and rank correlation analyses were used to explore associations between SARS-CoV-2 outcomes and patient characteristics. Of 2115 pwMS assessed (mean age 46.5, SD ± 12.9; median expanded disability status scale 2.5), 77.9% were under disease-modifying treatment (DMT), primarily B-cell depletion (25.4%). A total of 35.5% reported SARS-CoV-2 infections, and 77.4% were fully vaccinated. PwMS with increased disability, older age, and comorbidities were associated with higher vaccination rates, possibly due to the awareness of these populations regarding complications of SARS-CoV-2 infections. Infections were more common in younger females, people with a lower degree of disability, those with relapsing MS, and those who were not vaccinated. PwMS on B-cell depletion reported more infections than untreated pwMS and those receiving other types of disease-modifying therapy, despite higher vaccination rates. Most infections were mild, with no severity differences according to demographic or disease-related factors, except for gender. Notably, all fatal cases occurred in unvaccinated pwMS. Our studies suggest that demographic and disease-related factors, especially age and the use of B-cell depletion, significantly influenced SARS-CoV-2 vaccination and infection rates in our cohort. These factors may be considered in future preventive campaigns in further pandemics.

Our objective was to analyze longitudinal cellular and humoral immune responses to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccination in people with multiple sclerosis (pwMS) on B-cell depleting treatment (BCDT) compared to pwMS without immunotherapy. We further evaluated the impact of COVID-19 infection and vaccination timing. PwMS (n = 439) on BCDT (ocrelizumab, rituximab, ofatumumab) or without immunotherapy were recruited for this prospective cohort study between June 2021 and June 2022. SARS-CoV-2 spike-specific antibodies and interferon-γ release of CD4 and CD8 T-cells upon stimulation with spike protein peptide pools were analyzed at different timepoints (after primary vaccination, 3 and 6 months after primary vaccination, after booster vaccination, 3 months after booster). Humoral response to SARS-CoV-2 was consistently lower whereas T-cell response was higher in patients with BCDT compared to controls. Cellular and humoral responses decreased over time after primary vaccination and increased again upon booster vaccination, with significantly higher antibody titers after booster than after primary vaccination in both untreated and B-cell-depleted pwMS. COVID-19 infection further led to a significant increase in SARS-CoV-2-specific responses. Despite attenuated B-cell responses, a third vaccination for patients with BCDT seems recommendable, since at least partial protection can be expected from the strong T-cell response. Moreover, our data show that an assessment of T-cell responses may be helpful in B-cell-depleted patients to evaluate the efficacy of SARS-CoV-2 vaccination.

(1) Background: Persons with multiple sclerosis (pwMS) are often characterized as ideal adopters of new digital healthcare trends, but it is worth thinking about whether and which pwMS will be targeted and served by a particular eHealth service like a patient portal. With our study, we wanted to explore needs and barriers for subgroups of pwMS and their caregivers when interacting with eHealth services in care and daily living. (2) Methods: This study comprises results from two surveys: one collecting data from pwMS and their relatives (as informal caregivers) and another one providing information on the opinions and attitudes of healthcare professionals (HCPs). Data were analyzed descriptively and via generalized linear models. (3) Results: 185 pwMS, 25 informal caregivers, and 24 HCPs in the field of MS participated. Nine out of ten pwMS used information technology on a daily base. Individual impairments like in vision and cognition resulted in individual needs like the desire to actively monitor their disease course or communicate with their physician in person. HCPs reported that a complete medication overview, additional medication information, overview of future visits and a reminder of medication intake would be very helpful eHealth features for pwMS, while they themselves preferred features organizing and enriching future visits. (4) Conclusions: A closer look at the various profiles of eHealth adoption in pwMS and their caregivers indicated that there is a broad and robust enthusiasm across several subgroups that does not exclude anyone in general, but constitutes specific areas of interest. For pwMS, the focus was on eHealth services that connect previously collected information and make them easily accessible and understandable.

Real-world evidence in multiple sclerosis (MS) is limited by the availability of data elements in individual real-world datasets. We introduce a novel, growing database which links administrative claims and medical records from an MS patient management system, allowing for the complete capture of patient profiles. Using the AOK PLUS sickness fund and the Multiple Sclerosis Documentation System MSDS3D from the Center of Clinical Neuroscience (ZKN) in Germany, a linked MS-specific database was developed (MSDS-AOK PLUS). Patients treated at ZKN and insured by AOK PLUS were recruited and asked for informed consent. For linkage, insurance IDs were mapped to registry IDs. After the deletion of insurance IDs, an anonymized dataset was provided to a university-affiliate, IPAM e.V., for further research applications. The dataset combines a complete record of patient diagnoses, treatment, healthcare resource use, and costs (AOK PLUS), with detailed clinical parameters including functional performance and patient-reported outcomes (MSDS3D). The dataset currently captures 500 patients; however, is actively expanding. To demonstrate its potential, we present a use case describing characteristics, treatment, resource use, and costs of a patient subsample. By linking administrative claims to clinical information in medical charts, the novel MSDS-AOK PLUS database can increase the quality and scope of real-world studies in MS.

The assessment of neuropsychological functions and especially dual-tasking abilities is considered to be increasingly relevant in the assessment of neurological disease, and Multiple Sclerosis (MS) in particular. However, the assessment of dual-tasking abilities is hindered by specific software requirements and extensive testing times. We designed a novel e-health (progressive web application-based) device for the assessment of dual-tasking abilities usable in “bedside” and outpatient clinic settings and examined its reliability in a sample of N = 184 MS patients in an outpatient setting. Moreover, we examined the relevance of dual-tasking assessment using this device with respect to clinically relevant parameters in MS. We show that a meaningful assessment of dual-tasking is possible within 6 min and that the behavioral readouts overall show good reliability depending on dual-tasking difficulty. We show that dual-tasking readouts were correlated with clinically relevant parameters (e.g., EDSS, disease duration, processing speed) and were not affected by fatigue levels. We consider the tested dual-tasking assessment device suitable for routine clinical neuropsychological assessments of dual-tasking abilities. Future studies may further evaluate this test regarding its suitability in the long-term follow up assessments and to assess dual-tasking abilities in other neurological and psychiatric disorders.