Zhang Wei, Jiang Xin, Jia Zhisheng, Tian Hua, Wang Renjie, Ma Yuepeng, Ma Zhifang, Wang Xin, Hu Caoyang
Department of Urology, First Hospital of Shanxi Medical University, Taiyuan, Shanxi, China.
Department of Neurology, First Hospital of Shanxi Medical University, Taiyuan, Shanxi, China.
Expert Opin Drug Saf. 2024 Dec;23(12):1515-1522. doi: 10.1080/14740338.2024.2405577. Epub 2024 Sep 18.
Prostate cancer is one of the most common malignancies in men worldwide, and prostate-specific antigen (PSA) screening is widely used for its early detection. Drug use may affect PSA levels, but the effect for most drugs is currently unknown.
This study first investigated drugs related to PSA changes through the Food and Drug Administration Adverse Event Reporting System (FAERs) database, and then used a Mendelian randomization (MR) method to explore the causal relationship between specific drugs and PSA changes using a genome-wide association study (GWAS) data. The statistical analysis software SAS and R were used in the study.
Through analysis of the FAERs database, 22 drugs were found to be associated with an increase in PSA, and 14 drugs were associated with a decrease in PSA. MR analysis showed that the use of tamsulosin may lead to an increase in PSA. Heterogeneity test, horizontal pleiotropy test and leave-one-out Analysis verified the stability of the results. MR analyses for other drugs did not show statistical significance.
This study provided a basis for better understanding the impact of medications on prostate health, helping to avoid overdiagnosis or underdiagnosis of high-risk patients. However, research still requires larger-scale validation and in-depth exploration.
前列腺癌是全球男性中最常见的恶性肿瘤之一,前列腺特异性抗原(PSA)筛查被广泛用于其早期检测。药物使用可能会影响PSA水平,但目前大多数药物的影响尚不清楚。
本研究首先通过美国食品药品监督管理局不良事件报告系统(FAERS)数据库调查与PSA变化相关的药物,然后使用孟德尔随机化(MR)方法,利用全基因组关联研究(GWAS)数据探索特定药物与PSA变化之间的因果关系。研究中使用了统计分析软件SAS和R。
通过对FAERS数据库的分析,发现22种药物与PSA升高有关,14种药物与PSA降低有关。MR分析表明,使用坦索罗辛可能导致PSA升高。异质性检验、水平多效性检验和留一法分析验证了结果的稳定性。其他药物的MR分析未显示统计学意义。
本研究为更好地理解药物对前列腺健康的影响提供了依据,有助于避免高危患者的过度诊断或诊断不足。然而,研究仍需要更大规模的验证和深入探索。