Suppr超能文献

前列腺癌负担的全球流行病学趋势:来自《2021年全球疾病负担研究》的综合分析

Global epidemiological trends in prostate cancer burden: a comprehensive analysis from Global Burden of Disease Study 2021.

作者信息

Lin Xi, Zhi Yi

机构信息

Department of Urology, The Third Affiliated Hospital of Chongqing Medical University, Chongqing, China.

出版信息

Transl Androl Urol. 2025 May 30;14(5):1238-1252. doi: 10.21037/tau-2025-103. Epub 2025 May 27.

Abstract

BACKGROUND

Prostate cancer (PC) remains a major global health concern, with significant geographic and ethnic disparities in incidence and mortality. While the widespread use of prostate-specific antigen screening has improved early detection, ongoing debates regarding overdiagnosis and overtreatment raise concerns about its clinical utility and cost-effectiveness. Previous studies have examined regional variations in disease burden, yet gaps persist in understanding long-term epidemiological trends and the influence of sociodemographic factors. A standardized, comprehensive analysis is essential to guide evidence-based prevention and control strategies. This study investigated PC incidence, mortality, prevalence, and disability-adjusted life years (DALYs) between 1990 and 2021, providing a detailed assessment of its global burden. By analyzing temporal and regional trends, this study seeks to inform targeted prevention efforts and optimize healthcare resource allocation.

METHODS

Data were analyzed for annual incident cases, deaths, prevalence, DALYs, age-standardized incidence rates (ASIRs), age-standardized death rates (ASDRs), and age-standardized prevalence rates (ASPRs) for PC from 1990 to 2021, using data from the Global Burden of Disease (GBD) Study 2021. Temporal trends were assessed by calculating percentage changes in incident cases, deaths, and DALYs, along with estimated annual percentage changes (EAPCs) in ASIR, ASDR, ASPR, and DALYs. Pearson correlation analyses were conducted to evaluate the relationship between EAPCs and the socio-demographic index (SDI). Joinpoint regression was applied to identify significant shifts in these metrics over time.

RESULTS

The analysis reveals a 161.53% increase in global PC incidence and a 0.568% rise in prevalence, while mortality rates have declined by 0.83%. Regional variations are evident, with Eastern Europe and South Asia experiencing a higher burden of disease. Age distribution analysis shows that PC predominantly affects older populations, particularly individuals aged 70 years and above. SDI analysis indicates a positive correlation between SDI and PC prevalence, while the association with DALYs is comparatively weaker. Additionally, high-income regions such as Bermuda, Antigua, and Barbuda exhibit significant disparities in disease burden.

CONCLUSIONS

PC remains a growing global burden with significant regional and age-related disparities. While higher SDI regions show increased prevalence, the weaker correlation with DALYs suggests that healthcare access alone does not fully alleviate disease burden. These findings emphasize the need for targeted strategies that integrate early detection with equitable treatment and long-term management to reduce disparities and improve outcomes.

摘要

背景

前列腺癌(PC)仍然是全球主要的健康问题,在发病率和死亡率方面存在显著的地理和种族差异。虽然前列腺特异性抗原筛查的广泛应用提高了早期检测率,但关于过度诊断和过度治疗的持续争论引发了对其临床效用和成本效益的担忧。以往的研究已经考察了疾病负担的区域差异,但在理解长期流行病学趋势和社会人口因素的影响方面仍存在差距。进行标准化的综合分析对于指导基于证据的预防和控制策略至关重要。本研究调查了1990年至2021年间前列腺癌的发病率、死亡率、患病率和伤残调整生命年(DALYs),对其全球负担进行了详细评估。通过分析时间和区域趋势,本研究旨在为有针对性的预防工作提供信息,并优化医疗资源分配。

方法

利用《2021年全球疾病负担(GBD)研究》的数据,分析了1990年至2021年间前列腺癌的年度发病病例、死亡病例、患病率、DALYs、年龄标准化发病率(ASIRs)、年龄标准化死亡率(ASDRs)和年龄标准化患病率(ASPRs)。通过计算发病病例、死亡病例和DALYs的百分比变化,以及ASIR、ASDR、ASPR和DALYs的估计年度百分比变化(EAPCs)来评估时间趋势。进行Pearson相关分析以评估EAPCs与社会人口指数(SDI)之间的关系。应用Joinpoint回归来识别这些指标随时间的显著变化。

结果

分析显示全球前列腺癌发病率增加了161.53%,患病率上升了0.568%,而死亡率下降了0.83%。区域差异明显,东欧和南亚的疾病负担较高。年龄分布分析表明,前列腺癌主要影响老年人群,特别是70岁及以上的个体。SDI分析表明SDI与前列腺癌患病率呈正相关,而与DALYs的关联相对较弱。此外,百慕大、安提瓜和巴布达等高收入地区在疾病负担方面存在显著差异。

结论

前列腺癌仍然是一个不断增加的全球负担,存在显著的区域和年龄相关差异。虽然SDI较高的地区患病率有所上升,但与DALYs的较弱相关性表明,仅获得医疗服务并不能完全减轻疾病负担。这些发现强调需要采取有针对性的策略,将早期检测与公平治疗和长期管理相结合,以减少差异并改善结果。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d63d/12170203/3b0e00d0509f/tau-14-05-1238-f1.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验