Suppr超能文献

在欧洲前列腺癌筛查随机研究(ERSPC)鹿特丹分部的筛查组与对照组中生化进展率的比较。

Biochemical progression rates in the screen arm compared to the control arm of the Rotterdam Section of the European Randomized Study of Screening for Prostate Cancer (ERSPC).

作者信息

Roemeling Stijn, Roobol Monique J, Gosselaar Claartje, Schröder Fritz H

机构信息

Department of Urology, Erasmus MC, University Medical Center, Rotterdam, the Netherlands.

出版信息

Prostate. 2006 Jul 1;66(10):1076-81. doi: 10.1002/pros.20391.

Abstract

BACKGROUND

The European Randomized study of Screening for Prostate Cancer (ERSPC) investigates the feasibility of population-based screening. This report compares the preliminary outcome of cancers detected in the screen and the control arm of its Rotterdam section, by means of biochemical progression rates.

METHODS

In the screen arm of this study (21,210 men), screening was applied according to well-established protocols, and a 4-year screen interval was chosen. Widely accepted biochemical progression-criteria were used to evaluate the diagnosed cancers over time.

RESULTS

Although more cancers were detected in the screen than in the control arm (1,339 vs. 298, P < 0.001), their clinico-pathological features were more favorable. Furthermore, screened men had higher 5-year survival rates for biochemical progression after surgery (84.4% vs. 58.9% in controls), radiotherapy (71.0% vs. 58.0%), and endocrine therapy (40.5% vs. 16.3%).

CONCLUSIONS

The higher biochemical progression-free survival can at least in part be explained by lead and length-time. How screening will effect the mortality remains unclear.

摘要

背景

欧洲前列腺癌筛查随机研究(ERSPC)探讨了基于人群筛查的可行性。本报告通过生化进展率比较了其鹿特丹分部筛查组和对照组中检测到的癌症的初步结果。

方法

在本研究的筛查组(21210名男性)中,按照既定方案进行筛查,并选择了4年的筛查间隔。采用广泛接受的生化进展标准来长期评估诊断出的癌症。

结果

尽管筛查组中检测到的癌症比对照组多(1339例对298例,P<0.001),但其临床病理特征更有利。此外,接受筛查的男性在手术后生化进展的5年生存率更高(84.4%对对照组的58.9%),放疗后(71.0%对58.%),内分泌治疗后(40.5%对16.3%)。

结论

较高的无生化进展生存率至少部分可以由领先时间和延长时间来解释。筛查如何影响死亡率仍不清楚。

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