Project 1

项目1

基本信息

批准号：
10411221
负责人：
KARLA M KERLIKOWSKE
金额：
$ 14.95万
依托单位：
UNIVERSITY OF CALIFORNIA AT DAVIS
依托单位国家：
美国
项目类别：
财政年份：
2011
资助国家：
美国
起止时间：
2011-09-27 至 2027-05-31
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10411221
关键词：
Advanced Malignant Neoplasm Age Algorithms American Joint Committee on Cancer Area Artificial Intelligence Biopsy Black race Breast Cancer Detection Breast Cancer Risk Factor Breast Cancer Surveillance Consortium Breast Microcalcification Cancer Intervention and Surveillance Modeling Network Cessation of life Characteristics Clinical Collaborations Community Practice Data Diagnosis Discrimination Effectiveness Ethnic Origin Focus Groups Frequencies Funding Goals Guidelines Harm Reduction High Risk Woman Image Incidence Intervention Interview Life Magnetic Resonance Imaging Mammographic screening Mammography Modality Modeling Modernization Outcome Output Pathologic Patient Self-Report Performance Physicians Population Provider Race Registries Risk Risk Factors Services Statistical Methods Woman Women&apos s Group advanced breast cancer aged artificial intelligence algorithm base breast cancer diagnosis breast imaging cancer health disparity cancer invasiveness cancer risk clinical practice clinical risk comparative effectiveness discrete time experience high risk improved improved outcome malignant breast neoplasm models and simulation mortality novel predictive modeling prognostic racial and ethnic disparities randomized trial risk prediction risk prediction model routine screening screening social health determinants targeted imaging

项目摘要

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.

项目摘要 – 项目 1 乳房 X 光检查可降低晚期乳腺癌的发病率，从而降低乳腺癌死亡率。在接受常规筛查的诊断为乳腺癌的女性中，约有 22% 发生晚期癌症，黑人女性的晚期癌症发生率比白人女性高 2 倍多。我们将晚期癌症发生率确定为关键的筛查结果，因为它可以最好地区分乳腺癌死亡风险最高的女性，并针对她们采取有效的筛查策略，可以降低乳腺癌死亡率。推进新的基于风险的确定女性绝对晚期癌症风险的筛查范式，为筛查强度和补充影像学决策提供信息目标 1) 使用乳腺癌监测联盟关于 40-74 岁女性和晚期乳腺癌筛查检查的数据，我们将开发、评估和评估。验证新的风险预测模型，以识别晚期乳腺癌高风险女性。我们将结合临床乳腺癌风险因素、自我报告的种族/民族、影像特征和人工智能输出来估计 6 年累积风险。使用新颖的离散时间生存模型结合现代数据自适应建模方法进行年度和每两年筛查，并按种族/民族检查模型预测公平性目标 2) 我们将在因果推理框架内模拟一项随机试验，以评估年度与每两年一次的筛查结果。根据晚期癌症风险，每两年对一般筛查人群进行乳腺癌死亡率筛查目标 3) 将使用三个已建立的乳腺癌模拟模型来评估长期效益（避免乳腺癌死亡和延长生命年）和。针对乳房 X 光检查频率（每年、每两年）和基于晚期癌症风险的补充 MRI 的人群水平筛查策略的危害（例如假阳性和活检）该提案将回答：1) 哪些接受乳房 X 线检查的女性面临高风险。晚期癌症，需要两年一次乳房 X 光检查的替代策略，哪些女性风险较低，可以减少筛查次数 2) 与两年一次乳房 X 光检查相比，哪些晚期癌症风险水平需要每年一次乳房 X 光检查？ 3) 与基于年龄的策略相比，使用晚期癌症风险来告知筛查频率和方式的基于风险的筛查策略是否可以改善结果？因此，该项目将为女性提供证据，指导和提供基于公平的筛查策略。晚期癌症风险，以最大限度地提高筛查效益，同时最大限度地减少危害。