Using Systematized Nomenclature of Medicine clinical term codes to assign histological findings for prostate biopsies in the Gauteng province, South Africa: Lessons learnt

African Journal of Laboratory Medicine

 
 
Field Value
 
Title Using Systematized Nomenclature of Medicine clinical term codes to assign histological findings for prostate biopsies in the Gauteng province, South Africa: Lessons learnt
 
Creator Cassim, Naseem Ahmad, Ahsan Wadee, Reubina George, Jaya A. Glencross, Deborah K.
 
Subject Anatomical Pathology;Cancer;Pathology; prostate biopsy; Systemized Nomenclature of Medicine; SNOMED; morphology; topography; prostate cancer and adenocarcinoma
Description Background: Prostate cancer (PCa) is a leading male neoplasm in South Africa.Objective: The aim of our study was to describe PCa using Systemized Nomenclature of Medicine (SNOMED) clinical terms codes, which have the potential to generate more timely data.Methods: The retrospective study design was used to analyse prostate biopsy data from our laboratories using SNOMED morphology (M) and topography (T) codes where the term ’prostate’ was captured in the narrative report. Using M code descriptions, the diagnosis, sub-diagnosis, sub-result and International Classification of Diseases for Oncology (ICD-O-3) codes were assigned using a lookup table. Topography code descriptions identified biopsies of prostatic origin. Lookup tables were prepared using Microsoft Excel and combined with the data extracts using Access. Contingency tables reported M and T codes, diagnosis and sub-diagnosis frequencies.Results: An M and T code was reported for 88% (n = 22 009) of biopsies. Of these, 20 551 (93.37%) were of prostatic origin. A benign diagnosis (ICD-O-3:8000/0) was reported for 10 441 biopsies (50.81%) and 45.26% had a malignant diagnosis (n = 9302). An adenocarcinoma (8140/3) sub-diagnosis was reported for 88.16% of malignant biopsies (n = 8201). An atypia diagnosis was reported for 760 biopsies (3.7%). Inflammation (39.03%) and hyperplasia (20.82%) were the predominant benign sub-diagnoses.Conclusion: Our study demonstrated the feasibility of generating PCa data using SNOMED codes from national laboratory data. This highlights the need for extending the results of our study to a national level to deliver timeous monitoring of PCa trends.
 
Publisher AOSIS
 
Contributor
Date 2020-09-28
 
Type info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion — Cross sectional
Format text/html application/epub+zip text/xml application/pdf
Identifier 10.4102/ajlm.v9i1.909
 
Source African Journal of Laboratory Medicine; Vol 9, No 1 (2020); 9 pages 2225-2010 2225-2002
 
Language eng
 
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https://ajlmonline.org/index.php/ajlm/article/view/909/1633 https://ajlmonline.org/index.php/ajlm/article/view/909/1632 https://ajlmonline.org/index.php/ajlm/article/view/909/1634 https://ajlmonline.org/index.php/ajlm/article/view/909/1631
 
Coverage Gauteng province;South Africa Chronological Age;Race group;
Rights Copyright (c) 2020 Naseem Cassim, Ahsan Ahmad, Reubina Wadee, Jaya A. George, Deborah K. Glencross https://creativecommons.org/licenses/by/4.0
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