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

Abstract

BackgroundPathology 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. Objectivesto 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. MethodologySCT 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. ResultsThe 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. ConclusionsThis 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.