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Accepted for/Published in: JMIR Medical Informatics

Date Submitted: Apr 20, 2023
Date Accepted: Sep 30, 2023

The final, peer-reviewed published version of this preprint can be found here:

The Journey of Data Within a Global Data Sharing Initiative: A Federated 3-Layer Data Analysis Pipeline to Scale Up Multiple Sclerosis Research

Pirmani A, De Brouwer E, Geys L, Parciak T, Moreau Y, Peeters LM

The Journey of Data Within a Global Data Sharing Initiative: A Federated 3-Layer Data Analysis Pipeline to Scale Up Multiple Sclerosis Research

JMIR Med Inform 2023;11:e48030

DOI: 10.2196/48030

PMID: 37943585

PMCID: 10667980

The journey of data within a Global Data Sharing Initiative: A federated three-layer data analysis pipeline to scale up multiple sclerosis research

  • Ashkan Pirmani; 
  • Edward De Brouwer; 
  • Lotte Geys; 
  • Tina Parciak; 
  • Yves Moreau; 
  • Liesbet M. Peeters

ABSTRACT

Background:

Investigating low-prevalence diseases, such as multiple sclerosis (MS), is challenging because of limited patient availability and the scattering of real-world data (RWD) across numerous sources. These obstacles impair data integration, standardization, and analysis, which negatively impacts the generation of significant meaningful clinical evidence.

Objective:

This study aims to present a comprehensive, research question-agnostic, multistakeholder-driven end-to-end data analysis pipeline that accommodates three prevalent data sharing streams: individual data sharing, core dataset sharing, and federated data sharing.

Methods:

A demand-driven methodology is employed for preprocessing and standardization, followed by three tiers of data acquisition, a data integration procedure, and a concluding analysis stage to fulfill RWD sharing requirements. The pipeline's effectiveness was demonstrated through its successful implementation in the COVID-19 and MS Global Data Sharing Initiative (GDSI).

Results:

The GDSI has yielded multiple scientific publications and provided extensive worldwide guidance for the MS community. The pipeline facilitated the gathering of pertinent data from various sources, accommodating distinct sharing streams and assimilating them into a unified dataset for subsequent statistical analysis or secure data examination. Our pipeline contributed to the assembly of the largest dataset of people with MS infected with COVID-19.

Conclusions:

The proposed data analysis pipeline exemplifies the potential of global stakeholder collaboration and underlines the significance of evidence-based decision-making. It serves as a paradigm for how data sharing initiatives can propel advancements in healthcare, emphasizing its adaptability and capacity to address diverse research inquiries.


 Citation

Please cite as:

Pirmani A, De Brouwer E, Geys L, Parciak T, Moreau Y, Peeters LM

The Journey of Data Within a Global Data Sharing Initiative: A Federated 3-Layer Data Analysis Pipeline to Scale Up Multiple Sclerosis Research

JMIR Med Inform 2023;11:e48030

DOI: 10.2196/48030

PMID: 37943585

PMCID: 10667980

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