ArticleFrontiers in neurology2023
Claims-based algorithm to estimate the Expanded Disability Status Scale for multiple sclerosis in a German health insurance fund: a validation study using patient medical records.
Article in Frontiers in neurology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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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
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Who cites it
2 citing papers in PubMed.
- FreeSurfer-Based MRI Volumetry Reveals Thalamic and Hippocampal Atrophy as Significant Correlates of Disability in Multiple Sclerosis.Medicina (Kaunas, Lithuania) · 2026Article
- Neural networks to estimate multiple sclerosis disability and predict progression using routinely collected healthcare data.Multiple sclerosis (Houndmills, Basingstoke, England) · 2025Article
Corrections and comments
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: The Expanded Disability Status Scale (EDSS) quantifies disability and measures disease progression in multiple sclerosis (MS), however is not available in administrative claims databases. Objectives: To develop a claims-based algorithm for deriving EDSS and validate it against a clinical dataset capturing true EDSS values from medical records. Methods: We built a unique linked dataset combining claims data from the German AOK PLUS sickness fund and medical records from the Multiple Sclerosis Management System 3D (MSDS Results: We recruited 100 people with MS insured by AOK PLUS who had ≥1 EDSS measure in MSDS Conclusion: Generally, EDSS was underestimated by the algorithm as mild-to-moderate symptoms were poorly captured in claims across all functional systems. While the proxy-based approach using claims data may not allow for granular description of MS disability, broader severity groupings show good predictive performance.
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