ReviewBrain sciences2021
Digital Biomarkers in Multiple Sclerosis.
Review in Brain sciences, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 65 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
65 citing papers in PubMed, 1 synthesis or guideline pooled it, 110 citations in OpenAlex.
- Mobile health interventions in multiple sclerosis: A systematic review.Multiple sclerosis (Houndmills, Basingstoke, England) · 2023Pooled it
- Digital diagnostics, biomarkers and therapeutics in an evolving healthcare system: From promise to practice.British journal of clinical pharmacology · 2026Review
- Detecting progressing events in multiple sclerosis clinics in real-time is possible: No.Multiple sclerosis (Houndmills, Basingstoke, England) · 2026Article
- AI-enabled Living Labs: Accelerating innovation in multiple sclerosis care and research.Multiple sclerosis (Houndmills, Basingstoke, England) · 2026Review
- Digital monitoring of disease activity in relapsing-remitting multiple sclerosis.Journal of neurology · 2026Article
- MS360°: a conceptual digital-first, data-driven hybrid care framework for personalised multiple sclerosis management.NPJ digital medicine · 2026Review
- Deep learning in imaging analysis for multiple sclerosis: Diagnosis and monitoring.Caspian journal of internal medicine · 2026Review
- Monitoring cognition in multiple sclerosis via adaptive smartphone games-first insights from a validation study.Frontiers in digital health · 2026Article
- MSPEECH (multiple sclerosis monitoring through speech interaction in clinic and at home): a Living Lab study protocol for co-created, speech-based digital biomarkers in multiple sclerosis.Frontiers in digital health · 2026Article
- Advances in ocular motor and pupil biomarkers for neurological disorders.Brain communications · 2026Review
- Sensors in Multiple Sclerosis.Current neurology and neuroscience reports · 2025Review
- Integrating big data and artificial intelligence to predict progression in multiple sclerosis: challenges and the path forward.Journal of neuroengineering and rehabilitation · 2025Review
- Digital Twin Cognition: AI-Biomarker Integration in Biomimetic Neuropsychology.Biomimetics (Basel, Switzerland) · 2025Review
- Digital biomechanical assessment of gait in patients with peripheral neuropathies.Journal of neuroengineering and rehabilitation · 2025Article
- Experiences of People with Multiple Sclerosis in Sensor-Based Jump Assessment.Bioengineering (Basel, Switzerland) · 2025Article
- Article
- A roadmap for safe, regulation-compliant Living Labs for AI and digital health development.Science advances · 2025Review
- Patient Perspectives on Healthcare Utilization During the COVID-19 Pandemic in People with Multiple Sclerosis-A Longitudinal Analysis.Healthcare (Basel, Switzerland) · 2025Article
- Big data for neuroscience in the context of predictive, preventive, and personalized medicine.The EPMA journal · 2025Review
- From Steps to Context: Optimizing Digital Phenotyping for Physical Activity Monitoring in Older Adults by Integrating Wearable Data and Ecological Momentary Assessment.Sensors (Basel, Switzerland) · 2025Article
5 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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.
Indexed as
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.