Strandberg Rickard, Abrahamsson Linda, Isheden Gabriel, Humphreys Keith
Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, 171 77 Stockholm, Sweden.
Center for Primary Health Care Research, Lund University, 205 02 Malmö, Sweden.
Cancers (Basel). 2023 Jan 31;15(3):912. doi: 10.3390/cancers15030912.
With the advent of nationwide mammography screening programmes, a number of natural history models of breast cancers have been developed and used to assess the effects of screening. The first half of this article provides an overview of a class of these models and describes how they can be used to study latent processes of tumour progression from observational data. The second half of the article describes a simulation study which applies a continuous growth model to illustrate how effects of extending the maximum age of the current Swedish screening programme from 74 to 80 can be evaluated. Compared to no screening, the current and extended programmes reduced breast cancer mortality by 18.5% and 21.7%, respectively. The proportion of screen-detected invasive cancers which were overdiagnosed was estimated to be 1.9% in the current programme and 2.9% in the extended programme. With the help of these breast cancer natural history models, we can better understand the latent processes, and better study the effects of breast cancer screening.
随着全国性乳腺钼靶筛查项目的出现，人们开发了一些乳腺癌自然史模型，并用于评估筛查效果。本文前半部分概述了这类模型中的一种，并描述了如何利用它们从观察数据中研究肿瘤进展的潜在过程。文章后半部分描述了一项模拟研究，该研究应用连续增长模型来说明如何评估将瑞典当前筛查项目的最大年龄从74岁延长至80岁的效果。与不进行筛查相比，当前项目和延长后的项目分别将乳腺癌死亡率降低了18.5%和21.7%。据估计，当前项目中筛查发现的浸润性癌症被过度诊断的比例为1.9%，延长后的项目中这一比例为2.9%。借助这些乳腺癌自然史模型，我们可以更好地理解潜在过程，并更好地研究乳腺癌筛查的效果。
