Project 1

项目概要-项目1 筛查性乳房X线摄影通过降低晚期乳腺癌的发病率而降低乳腺癌死亡率。晚期癌症发生在约22%的常规筛查诊断为乳腺癌的女性中，黑人女性的晚期癌症发生率比白色女性高出2倍以上。我们将晚期癌症率确定为一个关键的筛查结果，因为它最能区分谁具有最高的乳腺癌死亡风险。识别晚期癌症风险增加的妇女并针对她们采取有效的筛查策略可以降低乳腺癌死亡率。因此，项目1旨在推进一种新的基于风险的筛查模式，确定女性的绝对晚期癌症风险，以告知筛查强度和补充成像决策。目的1）使用乳腺癌监测联盟对40-74岁女性和晚期乳腺癌筛查检查的数据，我们将开发，评估和验证新的风险预测模型，以识别晚期乳腺癌高危女性。我们将结合联合收割机临床乳腺癌风险因素、自我报告的人种/种族、影像学特征和人工智能输出，使用新型离散时间生存模型估计累积的6年晚期癌症风险，该模型结合了用于年度和两年一次筛查的现代数据自适应建模方法，并按人种/种族检查模型预测的公平性。目的2）我们将在因果推理框架内统计学模拟一项随机试验，以评估根据晚期癌症风险在一般筛查人群中进行年度与两年期乳房X线摄影筛查对乳腺癌死亡率的影响。目标3）三个已建立的乳腺癌模拟模型将用于评估长期效益（避免乳腺癌死亡和增加生命年）和危害（例如，假阳性和活组织检查）的人群水平的筛查策略，目标乳房X光检查频率（每年，两年一次）和补充MRI的基础上先进的癌症风险。这一建议将回答：1）哪些接受筛查性乳房X光检查的女性患晚期癌症的风险较高，需要采取替代两年一次的乳房X光检查的策略，哪些女性风险较低，可以减少筛查次数？2)什么样的晚期癌症风险水平需要每年进行一次乳房X光检查与两年一次乳房X光检查来降低乳腺癌死亡率？3)与基于年龄的筛查策略相比，基于风险的筛查策略使用晚期癌症风险来告知筛查频率和方式是否改善了结果？因此，该项目将提供证据，指导妇女和提供者根据晚期癌症风险采取公平的筛查策略，以最大限度地提高筛查效益，同时最大限度地减少危害。

PROJECT SUMMARY – Project 1 Screening mammography results in lower breast cancer mortality by reducing the incidence of advanced breast cancer. Advanced cancer occurs in about 22% of routinely screened women diagnosed with breast cancer, with advanced cancer rates more than 2-fold higher in Black vs. White women. We have identified advanced cancer rate as a key screening outcome because it best discriminates who has the highest risk of breast cancer death. Identifying women at increased advanced cancer risk and targeting them with effective screening strategies could reduce breast cancer mortality. Thus, Project 1 aims to advance a new risk-based screening paradigm that identifies women’s absolute advanced cancer risk to inform screening intensity and supplemental imaging decisions. Aim 1) Using Breast Cancer Surveillance Consortium data on screening exams from women aged 40-74 years, and advanced breast cancers, we will develop, evaluate, and validate new risk prediction models to identify women at high risk of advanced breast cancer. We will combine clinical breast cancer risk factors, self-reported race/ethnicity, imaging features, and Artificial Intelligence output to estimate cumulative 6-year advanced cancer risk using novel discrete time survival models incorporating modern data-adaptive modeling approaches for annual and biennial screeners and examine model predictive equity by race/ethnicity. Aim 2) We will statistically emulate a randomized trial within a causal inference framework to evaluate annual vs. biennial mammography screening on breast cancer mortality among the general screening population according to advanced cancer risk. Aim 3) Three established breast cancer simulation models will be used to evaluate the long-term benefits (breast cancer deaths averted, and life years gained) and harms (e.g., false positives and biopsies) of population-level screening strategies that target mammography frequency (annual, biennial) and supplemental MRI based on advanced cancer risk. This proposal will answer: 1) Which women undergoing screening mammography are at high risk of advanced cancer and require an alternative strategy to biennial mammography, and which women are at low risk and can be screened less often? 2) What advanced cancer risk levels require annual mammography vs. biennial mammography for similar reductions in breast cancer mortality? 3) Does a risk-based screening strategy using advanced cancer risk to inform screening frequency and modality improve outcomes compared to an agebased strategy? Therefore, this project will provide evidence to guide women and providers towards equitable screening strategies based on advanced cancer risk to maximize screening benefits while minimizing harms.