Insights Into Disability and Disability Progression in People With Multiple Sclerosis Using Large‐Scale Healthcare Data Article Swipe
Onur Dereli
,
Jochen Behringer
,
Achim Berthele
,
Alexander Hapfelmeier
,
Bernhard Hemmer
,
Christiane Gasperi
·
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1111/ene.70124
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1111/ene.70124
Background Identifying predictors for disability progression is crucial for managing multiple sclerosis (MS). This study aims to explore levels of disability and informative factors for disability progression in people with MS (PwMS) using healthcare data without detailed clinical information. Methods We conducted a case–control/cohort study on data from Bavaria's largest health insurance organization. The dataset included records of assistive devices, nursing care, sick leaves, rehabilitation, drug therapies, and diagnoses for individuals with MS, Crohn's disease (CD), rheumatoid arthritis (RA), and controls (CTR) without these diseases. We used generalized linear models to compare healthcare service utilization between MS and other cohorts. A gradient‐boosting algorithm identified informative healthcare‐related factors associated with disability progression in PwMS, defined by increased nursing care utilization. Results PwMS ( N = 11,961) demonstrated higher healthcare utilization than CD ( N = 21,884), RA ( N = 105,450), and CTR ( N = 82,677) groups, even at young ages. Besides expected risk factors like age, smoking, diabetes, and psychiatric disorders, the prediction algorithm revealed that PwMS with specific gynecological disorders, upper tract infections, asthma, and thyroiditis were less likely to need higher levels of nursing care. Conclusions Leveraging healthcare data allows for an objective assessment of disability in PwMS and can identify informative factors for disability progression. Our approach can be applied to studies on disease progression in large cohorts without detailed clinical data and can be adapted to other diseases, disability measures, and healthcare systems. Higher utilization of healthcare resources even at young ages revealed an unmet need for improved treatment and management strategies for young adults with MS.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1111/ene.70124
- https://onlinelibrary.wiley.com/doi/pdfdirect/10.1111/ene.70124
- OA Status
- gold
- References
- 41
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4409016295
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4409016295Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1111/ene.70124Digital Object Identifier
- Title
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Insights Into Disability and Disability Progression in People With Multiple Sclerosis Using Large‐Scale Healthcare DataWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2025Year of publication
- Publication date
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2025-03-30Full publication date if available
- Authors
-
Onur Dereli, Jochen Behringer, Achim Berthele, Alexander Hapfelmeier, Bernhard Hemmer, Christiane GasperiList of authors in order
- Landing page
-
https://doi.org/10.1111/ene.70124Publisher landing page
- PDF URL
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https://onlinelibrary.wiley.com/doi/pdfdirect/10.1111/ene.70124Direct link to full text PDF
- Open access
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YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
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https://onlinelibrary.wiley.com/doi/pdfdirect/10.1111/ene.70124Direct OA link when available
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Medicine, Health care, Cohort, Disease, Physical therapy, Family medicine, Internal medicine, Economic growth, EconomicsTop concepts (fields/topics) attached by OpenAlex
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0Total citation count in OpenAlex
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41Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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| sustainable_development_goals[0].id | https://metadata.un.org/sdg/3 |
| sustainable_development_goals[0].score | 0.6000000238418579 |
| sustainable_development_goals[0].display_name | Good health and well-being |
| citation_normalized_percentile.value | 0.14058409 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |