Histopathological patterns and topographic distribution of endometriosis: A 10-year retrospective study at a South African tertiary institution
Observational
OA: diamond
CC0
Abstract
Background: Endometriosis affects approximately 190 million women globally; however, despite this, epidemiological data on endometriosis from Africa remain scarce. Understanding regional disease patterns, histopathological characteristics, and anatomical distribution is essential for improving diagnostic accuracy and clinical management. Methods: A retrospective cross-sectional study was conducted using archival data from the Department of Anatomical Pathology at the Dr George Mukhari Academic Laboratory, Ga-Rankuwa, South Africa, from 01 January 2012 to 31 December 2021. Histopathologically confirmed cases of endometriosis were identified using SNOMED codes. Demographic and clinical data were analysed using Stata 14, with Chi-square and Fisher’s exact tests to assess associations (p < 0.05). Results: Of 93 804 female specimens examined, 156 cases of endometriosis were confirmed (histopathological diagnostic frequency = 0.166%). The mean age at diagnosis was 36.97 years. The most common histopathological pattern (60.3%) demonstrated all three classic features. The ovary was the most frequently affected site (36.5%). Synchronous involvement at multiple sites occurred in 9.6% of cases, predominantly affecting the adnexa. Endometriotic cysts were identified in 28.8% of patients. Cervical endometriosis was associated with older age (≥ 50 years), although based on a small number of cases (p = 0.008). Associated lesions were identified in 24.4% of the cases. Conclusion: These findings contribute to the limited epidemiological data on endometriosis in Africa and emphasise the need for heightened clinical awareness, particularly for extrauterine manifestations that may present diagnostic challenges. Contribution: This study contributes to the limited South African data by providing detailed insights into the histopathological diagnostic frequency, anatomical distribution and histopathological patterns, enhancing understanding of disease patterns.
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