The Socio-Demographic Characteristics of Patients Diagnosed with Prostate Cancer Treated in South Africa’s Only Rural Central Hospital in 2020: A Cross-Sectional Study Protocol

TL;DR

This study examines the demographics and clinical features of prostate cancer patients in a rural South African hospital to guide better health strategies.

Contribution

The study provides a detailed epidemiological profile of prostate cancer patients in a high-burden rural South African setting.

Findings

The study will describe the age distribution and stage at diagnosis of prostate cancer patients.

It will highlight treatment patterns and health service utilization in the Eastern Cape Province.

Findings will inform targeted prevention and intervention strategies for prostate cancer.

Abstract

Background: Prostate cancer remains a significant public health burden globally, particularly in sub-Saharan Africa, where rising incidence rates are compounded by limited screening, late-stage diagnosis and disparities in healthcare access. In South Africa, the Eastern Cape Province reports high prostate cancer prevalence, with many patients presenting at advanced stages. Understanding the epidemiological profile of affected individuals is critical for developing targeted health strategies. Objectives: This sub-study aims to describe the epidemiological characteristics of patients diagnosed with prostate cancer, using secondary data from Nelson Mandela Academic Hospital (NMAH), focusing on patients seen between March 2020 and November 2021. Methods: A quantitative cross-sectional study design is employed. De-identified secondary data extracted from clinical records of male patients diagnosed with prostate cancer and managed at NMAH during the study period. Variables include demographic information, clinical characteristics, health service utilization indicators. Analysis: Data will be captured and coded in Microsoft excel 2013 (Microsoft corporation, Seattle, WA, USA). The data will then be exported to STATA 18 for analyses. Descriptive statistics will be used to summarize the data. Inferential analyses such as logistic regression and chi-square tests will be used to explore associations between variables and treatment outcomes. The study provides insights into the demographic and clinical profiles of prostate cancer patients in a high-burden setting. It is anticipated that findings will highlight the age distribution, stage at diagnosis, and treatment patterns among patients diagnosed with prostate cancer. This will inform future prevention and intervention strategies in the Eastern Cape Province. Conclusions: By mapping out the epidemiological patterns of prostate cancer in the Eastern Cape through this sub-study, the research contributes to evidence-based planning and resource allocation, ultimately supporting efforts to reduce prostate cancer morbidity and mortality in rural South Africa.