Musinzi Joel, Sseruwagi Timon M, Kalanda Sharon, Lewis Nicole, Lewis Catherine
General Practice, St. Joseph's Hospital Kitovu, Masaka, UGA.
Orthopaedic Surgery, Kampala International University, Ishaka-Bushenyi, UGA.
Cureus. 2025 Apr 24;17(4):e82937. doi: 10.7759/cureus.82937. eCollection 2025 Apr.
Background Prostate cancer is the most common malignancy in African men and is increasing in low- and middle-income countries. Prostate-specific antigen (PSA) is a tumor marker for prostate cancer. However, PSA alone does not provide sufficient sensitivity and specificity in assessing prostate malignancy. Previous studies have demonstrated a correlation between age, PSA, and prostate malignancy. Objective We sought to determine the correlation between age, PSA, prostate volume (PV), and histology. Methods We conducted a retrospective review of male patients at a rural Ugandan hospital who had undergone prostate biopsy. Age, presence of lower urinary tract symptoms (LUTS), PSA, and PV were recorded. A univariate logistic regression model was used to test the probability of PSA, PV, and age to predict benign or malignant prostate histology. A value of <0.05 was considered statistically significant. Results PSA and age were shown to be significant predictors of histology. PSA values >78 ng/mL were also shown to be predictive of malignancy. PV was not a significant predictor of malignant prostate histology. Conclusions Our analysis demonstrates that increasing age and elevated PSA levels are significant predictors of prostate malignancy. Larger analyses are needed to determine the correlation between age, PSA, PV, and histology.
前列腺癌是非洲男性中最常见的恶性肿瘤,在低收入和中等收入国家中呈上升趋势。前列腺特异性抗原(PSA)是前列腺癌的一种肿瘤标志物。然而,仅靠PSA在评估前列腺恶性肿瘤时并不具备足够的敏感性和特异性。先前的研究已经证明年龄、PSA与前列腺恶性肿瘤之间存在关联。目的:我们试图确定年龄、PSA、前列腺体积(PV)和组织学之间的相关性。方法:我们对乌干达一家乡村医院接受前列腺活检的男性患者进行了回顾性研究。记录年龄、下尿路症状(LUTS)的存在情况、PSA和PV。使用单因素逻辑回归模型来测试PSA、PV和年龄预测前列腺良性或恶性组织学的概率。P值<0.05被认为具有统计学意义。结果:PSA和年龄被证明是组织学的重要预测指标。PSA值>78 ng/mL也被证明可预测恶性肿瘤。PV不是前列腺恶性组织学的重要预测指标。结论:我们的分析表明,年龄增长和PSA水平升高是前列腺恶性肿瘤的重要预测指标。需要进行更大规模的分析来确定年龄、PSA、PV和组织学之间的相关性。