Suppr超能文献

乳腺筛查中的风险分层研讨会

Risk stratification in breast screening workshop.

作者信息

Anderson Andrew, Visintin Cristina, Antoniou Antonis, Pashayan Nora, Gilbert Fiona J, Hackshaw Allan, Bhatt Rikesh, Hill Harry, Wright Stuart, Payne Katherine, Rogers Gabriel, Shinkins Bethany, Taylor-Phillips Sian, Given-Wilson Rosalind

机构信息

UK NSC secretariat, Sheffield/London, UK.

University of Cambridge, Cambridge, UK.

出版信息

BMC Proc. 2024 Oct 24;18(Suppl 19):22. doi: 10.1186/s12919-024-00306-0.

Abstract

Population screening for breast cancer (BC) is currently offered in the UK for women aged 50 to 71 with the aim of reducing mortality. There is additional screening within the national programme for women identified as having a very high risk of BC. There is growing interest in further risk stratification in breast screening, which would require a whole population risk assessment and the subsequent offer of screening tailored to the individual's risk. Some women would be offered more intensive screening than others or no screening. This might provide a better balance of screening benefits and harms for each individual than the current population age-based programme alone. The UK National Screening Committee (UK NSC) is considering using decision-analytic and other models to evaluate different risk stratification screening strategies and identify remaining gaps in evidence. This paper reports the proceedings of a UK NSC workshop where experts in the field discussed both risk prediction models, as well as decision-analytic models providing a benefit-harm analysis/economic evaluation of risk-stratified screening programmes (see Table 1). The aim of the meeting was to present and discuss the current work of experts, including some data which had not been published at the time of the meeting, to inform the UK NSC. The workshop was not intended to present a balanced evaluation of how to deliver screening in future. Areas for further work identified included methods for comparing models to assess accuracy, the optimum risk assessment tools, the digital screening infrastructure, acceptability of stratification, choice of screening test and reducing inequalities. A move to risk stratification of the whole programme would require a careful phased introduction with continuing assessment of real-world evidence during deployment.

摘要

目前,英国为年龄在50至71岁之间的女性提供乳腺癌(BC)群体筛查,目的是降低死亡率。在国家项目中,还为被确定为乳腺癌高危的女性提供额外筛查。在乳腺癌筛查中,对进一步的风险分层的兴趣日益浓厚,这将需要对整个人口进行风险评估,并随后根据个人风险提供量身定制的筛查。一些女性将接受比其他女性更密集的筛查,或者不接受筛查。与仅基于当前人口年龄的项目相比,这可能会为每个人提供更好的筛查益处与危害的平衡。英国国家筛查委员会(UK NSC)正在考虑使用决策分析模型和其他模型来评估不同的风险分层筛查策略,并找出证据方面的剩余差距。本文报告了UK NSC一次研讨会的会议记录,该领域的专家在会上讨论了风险预测模型以及提供风险分层筛查项目益处-危害分析/经济评估的决策分析模型(见表1)。会议的目的是介绍和讨论专家们目前的工作,包括一些在会议召开时尚未发表的数据,以便为UK NSC提供信息。该研讨会并非旨在对未来如何开展筛查进行全面评估。确定的进一步工作领域包括比较模型以评估准确性的方法、最佳风险评估工具、数字筛查基础设施、分层的可接受性、筛查测试的选择以及减少不平等。转向整个项目的风险分层需要谨慎地分阶段引入,并在实施过程中持续评估实际证据。

相似文献

1
Risk stratification in breast screening workshop.
BMC Proc. 2024 Oct 24;18(Suppl 19):22. doi: 10.1186/s12919-024-00306-0.
2
4
10

本文引用的文献

1
A structured process for the validation of a decision-analytic model: application to a cost-effectiveness model for risk-stratified national breast screening.
Appl Health Econ Health Policy. 2024 Jul;22(4):527-542. doi: 10.1007/s40258-024-00887-z. Epub 2024 May 16.
2
Population screening requires robust evidence-genomics is no exception.
Lancet. 2024 Feb 10;403(10426):583-586. doi: 10.1016/S0140-6736(23)02295-X. Epub 2023 Dec 6.
3
The cost-effectiveness of risk-stratified breast cancer screening in the UK.
Br J Cancer. 2023 Nov;129(11):1801-1809. doi: 10.1038/s41416-023-02461-1. Epub 2023 Oct 17.
4
Estimating the Cost of 3 Risk Prediction Strategies for Potential Use in the United Kingdom National Breast Screening Program.
MDM Policy Pract. 2023 May 4;8(1):23814683231171363. doi: 10.1177/23814683231171363. eCollection 2023 Jan-Jun.
5
Progress and Remaining Gaps in the Early Detection and Treatment of Breast Cancer.
Curr Oncol. 2023 Mar 8;30(3):3201-3205. doi: 10.3390/curroncol30030242.
6
Long-Term Performance of an Image-Based Short-Term Risk Model for Breast Cancer.
J Clin Oncol. 2023 May 10;41(14):2536-2545. doi: 10.1200/JCO.22.01564. Epub 2023 Mar 17.
8
Prospective validation of the BOADICEA multifactorial breast cancer risk prediction model in a large prospective cohort study.
J Med Genet. 2022 Dec;59(12):1196-1205. doi: 10.1136/jmg-2022-108806. Epub 2022 Sep 26.
9
Enhancing the BOADICEA cancer risk prediction model to incorporate new data on , , updates to tumour pathology and cancer incidence.
J Med Genet. 2022 Dec;59(12):1206-1218. doi: 10.1136/jmedgenet-2022-108471. Epub 2022 Sep 26.
10
Differences in cancer incidence by broad ethnic group in England, 2013-2017.
Br J Cancer. 2022 Jun;126(12):1765-1773. doi: 10.1038/s41416-022-01718-5. Epub 2022 Mar 2.

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