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Data harmonization for collaborative research among MS registries: A case study in employment.

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Summary
This summary is machine-generated.

Data harmonization across multiple sclerosis registries is feasible, showing a 57% employment rate. Higher disability levels correlated with lower employment, highlighting the need for supportive employment strategies for persons with MS.

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Multiple sclerosisharmonizationregistry

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Area of Science:

  • Neurology
  • Public Health
  • Data Science

Background:

  • Multiple sclerosis (MS) research often relies on data from disparate registries.
  • Collaborative efforts and data harmonization are crucial for robust analysis and broader insights into MS patient populations.

Purpose of the Study:

  • To evaluate the feasibility of retrospective data harmonization across three distinct multiple sclerosis registries.
  • To investigate employment status and associated factors among individuals with MS using harmonized data.

Main Methods:

  • Utilized Maelstrom guidelines for retrospective data harmonization of the North American Research Committee on MS (NARCOMS), German MS Register (GMSR), and United Kingdom MS (UK-MS) Register.
  • Employed a meta-analytic approach to pool logistic regression estimates for employment status, adjusting for age, sex, education, and disability level.

Main Results:

  • Successfully harmonized employment status and related demographic/clinical data across the three registries.
  • Overall employment rate was 57% (11,143/19,562 persons with MS), with variations across registries (GMSR 66.2%, UK-MS 55.2%, NARCOMS 43.0%).
  • A significant inverse relationship was observed between disability level and employment status.

Conclusions:

  • Retrospective data harmonization across multiple sclerosis registries is feasible and effective.
  • The Maelstrom guidelines offer a structured approach for high-quality data harmonization projects.
  • Pooling data from multiple registries presents a powerful strategy for advancing multiple sclerosis research.