A reference set of curated biomedical data and metadata from clinical case reports

Area of Science:

• Medical Informatics
• Clinical Data Management
• Rare Disease Research

Background:

• Clinical case reports (CCRs) are vital for sharing unique patient cases but contain unstructured data, hindering information retrieval.
• Existing indexing methods are not optimized for the specific needs of CCRs, limiting their utility.
• Effective mining of CCRs is crucial for advancing medical knowledge and patient care.

Purpose of the Study:

• To develop a standardized metadata template for clinical case reports.
• To create a structured resource (MACCRs) from curated CCRs for improved data accessibility.
• To enhance the findability, accessibility, interoperability, and reusability (FAIR) of clinical case report data.

Main Methods:

• Curated 3,100 clinical case reports across 15 disease groups, including over 750 rare disease reports.
• Developed a standardized metadata template to identify key clinical concepts within reports.
• Extracted and organized metadata, including demographics, disease presentation, treatments, and outcomes, creating the MACCRs dataset.
• Assigned ICD-10 diagnostic codes to a subset of reports on mitochondrial diseases.

Main Results:

• The Metadata Acquired from Clinical Case Reports (MACCRs) dataset provides structured information from a large corpus of CCRs.
• The metadata includes details on demographics, disease presentation, treatments, and patient outcomes.
• The developed template and MACCRs dataset significantly improve the FAIRness of clinical case report data.

Conclusions:

• The standardized metadata template and MACCRs dataset enhance the utility of clinical case reports for research and clinical practice.
• This resource supports various stakeholders, including researchers, clinicians, and policymakers.
• Improved data accessibility from CCRs can accelerate medical discoveries and inform clinical trial design.