All-cause mortality versus cancer-specific mortality as outcome in cancer screening trials: A review and modeling study

癌症筛查试验中全因死亡率与癌症特异性死亡率作为结局指标:一项综述和建模研究

阅读:1

Abstract

BACKGROUND: All-cause mortality has been suggested as an end-point in cancer screening trials in order to avoid biases in attributing the cause of death. The aim of this study was to investigate which sample size and follow-up is needed to find a significant reduction in all-cause mortality. METHODS: A literature review was conducted to identify previous studies that modeled the effect of screening on all-cause mortality. Microsimulation modeling was used to simulate breast cancer, lung cancer, and colorectal cancer screening trials. Model outputs were: cancer-specific deaths, all-cause deaths, and life-years gained per year of follow-up. RESULTS: There were large differences between the evaluated cancers. For lung cancer, when 40 000 high-risk people are randomized to each arm, a significant reduction in all-cause mortality could be expected between 11 and 13 years of follow-up. For breast cancer, a significant reduction could be found between 16 and 26 years of follow-up for a sample size of over 300 000 women in each arm. For colorectal cancer, 600 000 persons in each arm were required to be followed for 15-20 years. Our systematic literature review identified seven papers, which showed highly similar results to our estimates. CONCLUSION: Cancer screening trials are able to demonstrate a significant reduction in all-cause mortality due to screening, but require very large sample sizes. Depending on the cancer, 40 000-600 000 participants per arm are needed to demonstrate a significant reduction. The reduction in all-cause mortality can only be detected between specific years of follow-up, more limited than the timeframe to detect a reduction in cancer-specific mortality.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。