ArticleMultiple sclerosis (Houndmills, Basingstoke, England)2021
Characterisation of MS phenotypes across the age span using a novel data set integrating 34 clinical trials (NO.MS cohort): Age is a key contributor to presentation.
Article in Multiple sclerosis (Houndmills, Basingstoke, England), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers, 1 of them a synthesis that pooled it.
What it found
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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
24 citing papers in PubMed, 1 synthesis or guideline pooled it, 40 citations in OpenAlex.
- Disease activity in primary progressive multiple sclerosis: a systematic review and meta-analysis.Frontiers in neurology · 2023Pooled it
- Efficacy and safety of ofatumumab in recently diagnosed, treatment-naive patients with multiple sclerosis: Results from ASCLEPIOS I and II.Multiple sclerosis (Houndmills, Basingstoke, England) · 2022Trial
- The use of cladribine tablets in patients with MS beyond the age of 50: experiences from a large tertiary German centre.Neurological research and practice · 2026Article
- Building Towards Initiation, Moderation, De-Escalation and Cessation of Disease-Modifying Treatments for Multiple Sclerosis in Greece: An Expert Panel Consensus Meeting.Brain sciences · 2026Article
- Severe attacks and worse prognosis in patients with late-onset neuromyelitis optica spectrum disorder highlight the need for early highly effective treatment.Journal of neurology · 2025Article
- Clinical validation of a novel in vitro diagnostic neurofilament light chain assay for the prognostication of disease activity in people with relapsing multiple sclerosis.Multiple sclerosis (Houndmills, Basingstoke, England) · 2025Article
- AI-driven reclassification of multiple sclerosis progression.Nature medicine · 2025Article
- Evolving Recommendations for Patient Populations Among Oncology Medicines: A Quantitative and Qualitative Analysis.Clinical pharmacology and therapeutics · 2025Article
- AI-assisted identification of disability patterns within identical EDSS grades.Multiple sclerosis (Houndmills, Basingstoke, England) · 2025Article
- Multifaceted Biomarkers Suggest a Similar Profile of CNS Pathology in Relapsing and Progressive MS.European journal of neurology · 2025Article
- Association of Clinical Relapses With Disease Outcomes in Multiple Sclerosis Patients Older Than 50 Years.Neurology · 2024Article
- A scalable approach for continuous time Markov models with covariates.Biostatistics (Oxford, England) · 2024Article
- CXCL10/IgG1 Axis in Multiple Sclerosis as a Potential Predictive Biomarker of Disease Activity.Neurology(R) neuroimmunology & neuroinflammation · 2024Article
- New views on the complex interplay between degeneration and autoimmunity in multiple sclerosis.Frontiers in cellular neuroscience · 2024Article
- The association between disability progression, relapses, and treatment in early relapse onset MS: an observational, multi-centre, longitudinal cohort study.Scientific reports · 2023Observational
- Efficacy of Dimethyl Fumarate in Young Adults with Relapsing-Remitting Multiple Sclerosis: Analysis of the DEFINE, CONFIRM, and ENDORSE Studies.Neurology and therapy · 2023Article
- Synergy between health technology assessments and clinical guidelines for multiple sclerosis.Clinical and translational science · 2023Article
- How patients with multiple sclerosis acquire disability.Brain : a journal of neurology · 2022Article
- MSProDiscuss™ Clinical Decision Support Tool for Identifying Multiple Sclerosis Progression.Journal of clinical medicine · 2022Review
- Subtypes of relapsing-remitting multiple sclerosis identified by network analysis.Frontiers in digital health · 2022Article
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 6 institutions in 5 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe Oxford Big Data Institute, multiple sclerosis (MS) physicians and Novartis aim to address unresolved questions in MS with a novel comprehensive clinical trial data set.
objectiveThe objective of this study is to describe the Novartis-Oxford MS (NO.MS) data set and to explore the relationships between age, disease activity and disease worsening across MS phenotypes.
methodsWe report key characteristics of NO.MS. We modelled MS lesion formation, relapse frequency, brain volume change and disability worsening cross-sectionally, as a function of patients' baseline age, using phase III study data (≈8000 patients).
resultsNO.MS contains data of ≈35,000 patients (>200,000 brain images from ≈10,000 patients), with >10 years follow-up. (1) Focal disease activity is highest in paediatric patients and decreases with age, (2) brain volume loss is similar across age and phenotypes and (3) the youngest patients have the lowest likelihood (<25%) of disability worsening over 2 years while risk is higher (25%-75%) in older, disabled or progressive MS patients. Young patients benefit most from treatment.
conclusionNO.MS will illuminate questions related to MS characterisation, progression and prognosis. Age modulates relapse frequency and, thus, the phenotypic presentation of MS. Disease worsening across all phenotypes is mediated by age and appears to some extent be independent from new focal inflammatory activity.
Indexed as
Identifiers
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.