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英国风险分层乳腺癌筛查的成本效益。

The cost-effectiveness of risk-stratified breast cancer screening in the UK.

机构信息

School of Medicine and Population Health, University of Sheffield, Sheffield, England.

Lumanity Inc, Sheffield, England.

出版信息

Br J Cancer. 2023 Nov;129(11):1801-1809. doi: 10.1038/s41416-023-02461-1. Epub 2023 Oct 17.

Abstract

BACKGROUND

There has been growing interest in the UK and internationally of risk-stratified breast screening whereby individualised risk assessment may inform screening frequency, starting age, screening instrument used, or even decisions not to screen. This study evaluates the cost-effectiveness of eight proposals for risk-stratified screening regimens compared to both the current UK screening programme and no national screening.

METHODS

A person-level microsimulation model was developed to estimate health-related quality of life, cancer survival and NHS costs over the lifetime of the female population eligible for screening in the UK.

RESULTS

Compared with both the current screening programme and no screening, risk-stratified regimens generated additional costs and QALYs, and had a larger net health benefit. The likelihood of the current screening programme being the optimal scenario was less than 1%. No screening amongst the lowest risk group, and triannual, biennial and annual screening amongst the three higher risk groups was the optimal screening strategy from those evaluated.

CONCLUSIONS

We found that risk-stratified breast cancer screening has the potential to be beneficial for women at the population level, but the net health benefit will depend on the particular risk-based strategy.

摘要

背景

英国和国际上对风险分层的乳腺癌筛查越来越感兴趣,通过个体化风险评估可以告知筛查的频率、起始年龄、使用的筛查工具,甚至是否决定不进行筛查。本研究评估了与当前英国筛查计划和无国家筛查相比,八种风险分层筛查方案的成本效益。

方法

开发了一个基于个体的微观模拟模型,以估计在英国有资格接受筛查的女性人群的健康相关生活质量、癌症生存和 NHS 成本。

结果

与当前的筛查计划和不筛查相比,风险分层方案增加了成本和 QALYs,并有更大的净健康效益。当前筛查计划成为最佳方案的可能性小于 1%。对于最低风险组不进行筛查,对于三个较高风险组则进行每三年、每两年和每年筛查,是评估中最佳的筛查策略。

结论

我们发现,风险分层乳腺癌筛查有可能对人群水平的妇女有益,但净健康效益将取决于特定的基于风险的策略。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3a7e/10667489/b57c1ef021ab/41416_2023_2461_Fig1_HTML.jpg

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