How cancer registries can detect neoplasms in pathology laboratories that code with SNOMED CT terminology? An actual, simple and flexible solution.

BACKGROUND: Pathology laboratories are one of the main information sources for cancer registries and have traditionally been coded with SNOMED; some of them are migrating to SNOMED CT (SCT). Cancer registries encode topography and morphology of neoplasms by the International Classification of Diseases for Oncology (ICD-O). ICD-O updates morphology with WHO Classification of Tumors (Blue-Books). Morphological codes of the ICD-O, Blue-Books and SNOMED (former SNOMEDID) have always coincided. In 2017, SCT removed the SNOMEDID. OBJECTIVES: to define neoplastic and topographic subsets in SCT and map them to ICD-O-3.1/Blue-Books; reduce the original number of SCT concepts; correctly identify neoplasms in the laboratories in accordance with international cancer registry rules. METHODOLOGY: SCT neoplastic concepts were identified by manual revision and SCT resources ("is a", "Associated morphology" relationships; Simple Map Reference Set). Topographic concepts were extracted from the body structure hierarchy of SCT. Both subsets were mapped to ICD-O-3.1/Blue-Books, afterwards. Updating algorithms were designed to automate and update each subset with every SCT release. The process of neoplasms identification was validated in a sample of 5212 specimens with 7378 records from 8 Catalan hospitals. RESULTS: The number of concepts in neoplastic and topographic subsets (16,448 and 32,278) was reduced after the mapping to ICD-O-3.1/Blue-Books (2115 and 330, respectively). Neoplastic subset classified the specimens correctly in the 98.6% of the specimens. CONCLUSIONS: This article presents a flexible tool to exhaustively identify neoplasms in pathology laboratories that code with SCT, following international PBCRs standards and in line with the pathologists, oncologists and epidemiologists' needs.

Definition of a SNOMED CT pathology subset and microglossary, based on 1.17 million biological samples from the Catalan Pathology Registry.

SNOMED CT terminology is not backed by standard norms of encoding among pathologists. The vast number of concepts ordered in hierarchies and axes, together with the lack of rules of use, complicates the functionality of SNOMED CT for coding, extracting, and analyzing the data. Defining subgroups of SNOMED CT by discipline could increase its functionality. The challenge lies in how to choose the concepts to be included in a subset from a total of over 300,000. Besides, SNOMED CT does not cover daily need, as the clinical reality is dynamic and changing. To adapt SNOMED CT to needs in a flexible way, the possibility exists to create extensions. In Catalonia, most pathology departments have been migrating from SNOMED II to SNOMED CT in a bid to advance the development of the Catalan Pathology Registry, which was created in 2014 as a repository for all the pathological diagnoses. This article explains the methodology used to: (a) identify the clinico-pathological entities and the molecular diagnostic procedures not included in SNOMED CT; (b) define the theoretical subset and microglossary of pathology; (c) describe the SNOMED CT concepts used by pathologists of 1.17 million samples of the Catalan Pathology Registry; and (d) adapt the theoretical subset and the microglossary according to the actual use of SNOMED CT. Of the 328,365 concepts available for coding the diagnoses (326,732 in SNOMED CT and 1576 in Catalan extension), only 2% have been used. Combining two axes of SNOMED CT, body structure and clinical findings, has enabled coding most of the morphologies.