Display options
Cite
Jouhet V, Mougin F, Bréchat B, et al. Building a model for disease classification integration in oncology, an approach based on the national cancer institute thesaurus. J Biomed Semantics. 2017;8(1):6doi: 10.1186/s13326-017-0114-4.
Jouhet, V., Mougin, F., Bréchat, B., & Thiessard, F. (2017). Building a model for disease classification integration in oncology, an approach based on the national cancer institute thesaurus. Journal of biomedical semantics, 8(1), 6. https://doi.org/10.1186/s13326-017-0114-4
Jouhet, Vianney, et al. "Building a model for disease classification integration in oncology, an approach based on the national cancer institute thesaurus." Journal of biomedical semantics vol. 8,1 (2017): 6. doi: https://doi.org/10.1186/s13326-017-0114-4
Jouhet V, Mougin F, Bréchat B, Thiessard F. Building a model for disease classification integration in oncology, an approach based on the national cancer institute thesaurus. J Biomed Semantics. 2017 Feb 07;8(1):6. doi: 10.1186/s13326-017-0114-4. PMID: 28173841; PMCID: PMC5294908.
Copy Download .nbib Format: NLM
Share it on

J Biomed Semantics. 2017 Feb 07;8(1):6. doi: 10.1186/s13326-017-0114-4.

Building a model for disease classification integration in oncology, an approach based on the national cancer institute thesaurus.

Journal of biomedical semantics

Vianney Jouhet, Fleur Mougin, Bérénice Bréchat, Frantz Thiessard

Affiliations

  1. CHU de Bordeaux, Pole de sante publiqueService d'information medicale, unit IAM, F-33000Bordeaux, France. [email protected].
  2. Univ. Bordeaux, Inserm, UMR 1219, Bordeaux, F-33000, France. [email protected].
  3. Univ. Bordeaux, Inserm, UMR 1219, Bordeaux, F-33000, France.
  4. CHU de Bordeaux, Pole de sante publiqueService d'information medicale, unit IAM, F-33000Bordeaux, France.

PMID: 28173841 PMCID: PMC5294908 DOI: 10.1186/s13326-017-0114-4

Abstract

BACKGROUND: Identifying incident cancer cases within a population remains essential for scientific research in oncology. Data produced within electronic health records can be useful for this purpose. Due to the multiplicity of providers, heterogeneous terminologies such as ICD-10 and ICD-O-3 are used for oncology diagnosis recording purpose. To enable disease identification based on these diagnoses, there is a need for integrating disease classifications in oncology. Our aim was to build a model integrating concepts involved in two disease classifications, namely ICD-10 (diagnosis) and ICD-O-3 (topography and morphology), despite their structural heterogeneity. Based on the NCIt, a "derivative" model for linking diagnosis and topography-morphology combinations was defined and built. ICD-O-3 and ICD-10 codes were then used to instantiate classes of the "derivative" model. Links between terminologies obtained through the model were then compared to mappings provided by the Surveillance, Epidemiology, and End Results (SEER) program.

RESULTS: The model integrated 42% of neoplasm ICD-10 codes (excluding metastasis), 98% of ICD-O-3 morphology codes (excluding metastasis) and 68% of ICD-O-3 topography codes. For every codes instantiating at least a class in the "derivative" model, comparison with SEER mappings reveals that all mappings were actually available in the model as a link between the corresponding codes.

CONCLUSIONS: We have proposed a method to automatically build a model for integrating ICD-10 and ICD-O-3 based on the NCIt. The resulting "derivative" model is a machine understandable resource that enables an integrated view of these heterogeneous terminologies. The NCIt structure and the available relationships can help to bridge disease classifications taking into account their structural and granular heterogeneities. However, (i) inconsistencies exist within the NCIt leading to misclassifications in the "derivative" model, (ii) the "derivative" model only integrates a part of ICD-10 and ICD-O-3. The NCIt is not sufficient for integration purpose and further work based on other termino-ontological resources is needed in order to enrich the model and avoid identified inconsistencies.

Keywords: ICD-10; ICD-O-3; NCI thesaurus; Oncology; Semantic integration; Terminology

References

  1. Bull World Health Organ. 2014 Sep 1;92(9):672-9 - PubMed
  2. JAMA. 2013 Apr 3;309(13):1351-2 - PubMed
  3. AMIA Jt Summits Transl Sci Proc. 2010 Mar 01;2010:1-5 - PubMed
  4. J Biomed Inform. 2013 Feb;46(1):128-38 - PubMed
  5. Methods Inf Med. 2009;48(1):38-44 - PubMed
  6. Methods Inf Med. 2005;44(4):498-507 - PubMed
  7. Nucleic Acids Res. 2004 Jan 1;32(Database issue):D267-70 - PubMed
  8. Artif Intell Med. 2007 Mar;39(3):183-95 - PubMed
  9. Summit Transl Bioinform. 2009 Mar 01;2009:116-20 - PubMed
  10. J Biomed Inform. 2011 Dec;44 Suppl 1:S94-102 - PubMed
  11. J Biomed Inform. 2009 Feb;42(1):1-10 - PubMed
  12. Proc AMIA Symp. 1998;:830-4 - PubMed
  13. Eur J Public Health. 2005 Dec;15(6):657-64 - PubMed
  14. Methods Inf Med. 2013;52(5):411-21 - PubMed
  15. J Am Med Inform Assoc. 2007 Jan-Feb;14(1):1-9 - PubMed
  16. Artif Intell Med. 2005 Jul;34(3):179-200 - PubMed
  17. Popul Health Metr. 2006 Sep 28;4:10 - PubMed
  18. AMIA Annu Symp Proc. 2011;2011:98-107 - PubMed
  19. J Biomed Inform. 2008 Feb;41(1):24-32 - PubMed
  20. AMIA Annu Symp Proc. 2010 Nov 13;2010:727-31 - PubMed

MeSH terms

Publication Types