A new standardized data collection system for interdisciplinary thyroid cancer management: Thyroid COBRA

Area of Science:

• Oncology
• Medical Informatics
• Data Science

Background:

• Big data and machine learning offer powerful tools for advancing evidence-based medicine, particularly in complex disease management like cancer.
• The Italian Association of Radiation Oncology's Metabolic Radiotherapy Working Group recognized the need for structured data collection in thyroid cancer.
• A multicentre consortium approach was initiated to address the challenges of large-scale data management in oncology.

Purpose of the Study:

• To develop a standardized, web-based data collection system for thyroid cancer management.
• To establish a multicentre consortium (Thyroid CoBRA) for collaborative data analysis and application of machine learning.
• To create a privacy-respecting data storage system (C-SS) for sensitive patient information.

Main Methods:

• A multicentre working group defined agreement conditions, data ontology, and software services.
• Six Italian cancer centers collaborated to establish the Thyroid COBRA consortium and agreement.
• The COBRA-Storage System (C-SS) was designed for secure, direct data extraction from individual centers, ensuring data privacy and encryption.

Main Results:

• The COBRA-Storage System (C-SS) proved to be time-efficient and privacy-preserving.
• Automatic data archiving capabilities were integrated with existing hospital storage and radiotherapy planning systems.
• The C-SS architecture supports both cloud storage and distributed learning for predictive modeling.

Conclusions:

• The Thyroid COBRA data storage system is a feasible tool for complex, privacy-saving data sharing in thyroid cancer management.
• This multicentre consortium approach enables the development of clinical decision support tools.
• The system's architecture holds potential for application to other cancer types in the future.