ArticleAdvanced science (Weinheim, Baden-Wurttemberg, Germany)2026
Assessing the Relative Importance of Imaging and Serum Biomarkers in Capturing Disability, Cognitive Impairment, and Clinical Progression in Multiple Sclerosis.
Article in Advanced science (Weinheim, Baden-Wurttemberg, Germany), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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.
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Who cites it
3 citing papers in PubMed.
- From Phenotypes to Spectrum: Rethinking RRMS, SPMS and PPMS in the Era of PIRA-A Framework Integrating PIRA, Smouldering-Associated Worsening, and Neurologic Reserve to Facilitate Earlier Recognition of Progression.Neurology international · 2026Review
- Personalizing Relapsing-Remitting Multiple Sclerosis Monitoring: Patient Acceptance of Serum Neurofilament Light Chain and the Role of Disease Knowledge.Journal of personalized medicine · 2026Article
- Assessing the Relative Importance of Imaging and Serum Biomarkers in Capturing Disability, Cognitive Impairment, and Clinical Progression in Multiple Sclerosis.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
Corrections and comments
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Authors and funding
18 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The heterogeneity of multiple sclerosis (MS) pathology calls for robust biomarkers to predict disability and progression, particularly progression independent of relapse activity (PIRA). Here, we aimed to identify the most informative MRI and serum biomarkers for predicting clinical outcomes in people with MS (pwMS), including disability severity, cognitive impairment, disease phenotype, and risk of PIRA. We applied a machine learning-based feature selection approach to cross-sectional and longitudinal data from two independent pwMS cohorts. Cohort 1 (n = 120) included 57 MRI biomarkers, incorporating advanced quantitative MRI (qMRI). Cohort 2 (n = 279) included 35 MRI biomarkers derived from conventional MRI. Both cohorts obtained serum neurofilament light chain (sNfL) and glial fibrillary acidic protein (sGFAP) measurements. Spinal cord atrophy consistently emerged as the strongest predictor of disability severity and predicted PIRA, along with cortical thinning and subcortical atrophy - particularly in deep gray matter. sNfL, sGFAP, and qMRI metrics independently contributed to the prediction of PIRA and progressive disease phenotype. In conclusion, our findings show that spinal cord atrophy and cortical degeneration are the most robust and consistent predictors of MS severity and progression. Serum biomarkers of neuroaxonal and astrocytic damage, together with qMRI-derived tissue metrics, provide independent and complementary value for outcome prediction.
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Registered trials
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