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随你喜欢:同一数据如何能支持乳腺癌筛查中多种过度诊断的观点。

As you like it: How the same data can support manifold views of overdiagnosis in breast cancer screening.

机构信息

Department of Public Health Programmes, Randers Regional Hospital, Randers, Denmark.

Department of Clinical Epidemiology, Aarhus University, Aarhus, Denmark.

出版信息

Int J Cancer. 2018 Sep 15;143(6):1287-1294. doi: 10.1002/ijc.31420. Epub 2018 Apr 25.

DOI:10.1002/ijc.31420
PMID:29633249
Abstract

Overdiagnosis estimates have varied substantially, causing confusion. The discussions have been complicated by the fact that population and study design have varied substantially between studies. To help assess the impact of study design choices on the estimates, we compared them on a single population. A cohort study from Funen County, Denmark, recently suggested little (∼1%) overdiagnosis. It followed previously screened women for up to 14 years after screening had ended. Using publically available data from Funen, we recreated the designs from five high-estimate, highly cited studies from various countries. Selected studies estimated overdiagnosis to be 25-54%. Their designs were adapted only to the extent that they reflect the start of screening in Funen in 1993. The reanalysis of the Funen data resulted in overdiagnosis estimates that were remarkably similar to those from the original high-estimate age-period studies, 21-55%. In additional analyses, undertaken to elucidate the effect of the individual components of the study designs, overdiagnosis estimates were more than halved after the most likely changes in the background risk were accounted for and decreased additionally when never-screened birth cohorts were excluded from the analysis. The same data give both low and high estimates of overdiagnosis, it all depends on the study design. This stresses the need for a careful scrutiny of the validity of the assumptions underpinning the estimates. Age-period analyses of breast cancer overdiagnosis suggesting very high frequencies of overdiagnosis rested on unmet assumptions. This study showed that overdiagnosis estimates should in the future be requested to adequately control for the background risk and include an informative selection of the studied population to achieve valid and comparable estimates of overdiagnosis.

摘要

过度诊断的估计值差异很大,导致了混淆。由于研究之间的人群和研究设计存在很大差异,讨论变得复杂。为了帮助评估研究设计选择对估计值的影响,我们在单一人群中对它们进行了比较。丹麦菲英郡的一项队列研究最近表明,过度诊断的情况很少(约 1%)。该研究在筛查结束后对之前接受过筛查的女性进行了长达 14 年的随访。利用菲英郡的公开数据,我们根据来自不同国家的五项高估计值、高引用率的研究重新设计了方案。选定的研究估计过度诊断率为 25-54%。它们的设计只在一定程度上反映了 1993 年在菲英郡开始筛查的情况。对菲英郡数据的重新分析得出的过度诊断估计值与原始高估计值的年龄-时期研究非常相似,为 21-55%。在额外的分析中,为了阐明研究设计各个组成部分的影响,在考虑到背景风险最可能变化的情况下,过度诊断的估计值减少了一半以上,当从未接受过筛查的出生队列被排除在分析之外时,该估计值进一步减少。相同的数据给出了过度诊断的低估计值和高估计值,这完全取决于研究设计。这强调了需要仔细审查支撑这些估计值的假设的有效性。基于乳腺癌过度诊断的年龄-时期分析表明,过度诊断的频率非常高,这是基于未满足的假设。本研究表明,未来应该要求过度诊断的估计值充分控制背景风险,并包括对所研究人群的信息选择,以实现对过度诊断的有效和可比的估计值。

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