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Updated: Mar 7, 2026
Quantitative Magnetic Resonance Imaging of Skeletal Muscle Disease
Published on: December 18, 2016
Standardized Interoperable Data Collection for Myositis Research: Developing Expert Consensus on Common Data Elements
Didem Saygin1, Matthew Diller2, Varsha Surampudi3
1Rush University Medical Center, Chicago, Illinois.
Objective:
Recent progress has been made in developing validated myositis outcome measures. However, critical deficiencies remain for data standardization across myositis registries. Although the National Institutes of Health (NIH) Common Data Elements (CDE) Repository has been developed to facilitate standardized data collection and sharing, few myositis-specific CDEs currently exist. We developed CDEs for myositis outcome measures using novel data science strategies.
Methods:
Data dictionaries of myositis registries were examined to understand how outcome measures are currently captured. We used the Linked data Modeling Language, an open-source data modeling framework, to develop computable CDEs. After drafting CDEs for myositis core set measures (CSMs), an international conference was held with an expert myositis panel to reach consensus on the coding of CDEs and prioritize additional measures for CDE creation, using Delphi and modified nominal group techniques. This workflow was repeated for the prioritized measures in the second phase.
Results:
A workflow was established for CDE creation. CDEs for 10 myositis CSMs were drafted. After receiving comments to improve their coding, universal agreement among participants was reached for CSM CDEs. The prioritized measures for future CDEs included myositis response and classification criteria, damage measures, physical function measures, and Patient-Reported Outcomes Measurement Information System instruments. CDEs for 18 additional measures were discussed at a second consensus conference. Similarly, high agreement rates were achieved, except for flare criteria. Altogether, 852 new CDEs were created for 27 myositis forms and achieved consensus, readying their deposit in the NIH CDE Repository.
Conclusion:
Leveraging multispecialty expertise in myositis and its patient communities and data science expertise of the National Library of Medicine, the first myositis-specific CDEs have been developed to accelerate the ability to conduct interoperable myositis clinical studies and therapeutic trials. The workflow established here should also benefit creation of CDEs and data sharing for other autoimmune diseases.
