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A new mapping connects the International Classification of Diseases, 10th Revision (ICD-10) cancer codes with the detailed OncoTree classification system. This bridge improves cancer data consistency and research, achieving 86.18% accuracy.

Keywords:
FHIRICD-10OncoTreeSNOMED CTmappingpostcoordination

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Area of Science:

  • Oncology
  • Medical Informatics
  • Bioinformatics

Background:

  • The International Classification of Diseases, 10th Revision (ICD-10) is widely used for tumor classification in clinical practice.
  • The OncoTree classification system offers a more granular, molecularly-informed tumor hierarchy essential for research and clinical trials.
  • A discrepancy exists between the broadness of ICD-10 and the detailed nature of OncoTree, hindering data integration.

Purpose of the Study:

  • To develop a robust mapping between the ICD-10 and OncoTree cancer classification systems.
  • To facilitate improved data comparison and clinical trial enrollment using standardized cancer terminology.
  • To address the need for a unified approach to cancer coding in research and clinical settings.

Main Methods:

  • A mapping strategy was devised utilizing Systematized Nomenclature of Medicine — Clinical Terms (SNOMED CT) as an intermediary due to structural differences between ICD-10 and OncoTree.
  • The mapping process involved aligning concepts from both coding systems through SNOMED CT.
  • Challenges related to structural dissimilarities and mapping inaccuracies were identified and addressed during development.

Main Results:

  • A mapping between ICD-10 and OncoTree was successfully developed.
  • The mapping achieved a satisfactory accuracy rate of 86.18%.
  • The developed mapping demonstrates the feasibility of integrating these distinct cancer classification systems.

Conclusions:

  • The creation of an ICD-10 to OncoTree mapping is a significant step towards harmonizing cancer data.
  • The achieved accuracy rate indicates the potential utility of this mapping in research and clinical applications.
  • Further refinement of the mapping process is recommended for seamless integration into production systems and broader adoption.