Integrating Mammograms in Analyses of Genes and Environment in Sisters (IMAGES)

将乳房 X 光检查融入姐妹基因和环境分析中（图像）

基本信息

批准号：
9235542
负责人：
Parisa Tehranifar
金额：
$ 49.01万
依托单位：
COLUMBIA UNIVERSITY HEALTH SCIENCES
依托单位国家：
美国
项目类别：
财政年份：
2017
资助国家：
美国
起止时间：
2017-02-06 至 2021-01-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/9235542
关键词：
Address Affect Age Area Behavior Therapy Breast Breast Cancer Model Breast Cancer Risk Assessment Tool Breast Cancer Risk Factor Breast Cancer Surveillance Consortium CA-125 Antigen Categories Cessation of life Chemoprevention Clinical Clinical assessments Cohort Studies Data Diagnosis Discrimination Enrollment Environment Epidemiology Exposure to Family Family Cancer History Family history of First Degree Relative Frequencies Genes Genetic Genetic Markers Genetic screening method Genetic study Heterogeneity High Risk Woman Incidence Individual Intervention Investigation Life Magnetic Resonance Imaging Malignant Neoplasms Malignant neoplasm of ovary Mammographic Density Mammography Mastectomy Measurement Measures Menopause Methods Modeling Monitor Nature Operative Surgical Procedures Ovariectomy Performance Population Postmenopause Premenopause Prevention program Prevention strategy Preventive Preventive Intervention Preventive care Probability Prospective cohort Puerto Rican Radiology Specialty Recommendation Recording of previous events Relative Risks Research Retrieval Risk Risk Assessment Risk Estimate Risk Factors Risk stratification Sister Standardization Statistical Models Statutes and Laws Surveillance Program Time Tissues Woman base cancer risk case control clinical decision-making clinical practice clinical risk cost design experience follow-up improved malignant breast neoplasm predictive modeling prospective rate of change screening success

项目摘要

ABSTRACT Accurate breast cancer risk assessment has the potential to distinguish women at higher risk who need enhanced screening, preventive or risk-reducing therapies and surgeries from women at lower risk who can be spared interventions that yield little benefit and may cause harm. Breast cancer risk assessment is currently hampered by limited precision and accuracy of existing risk prediction models. Women with a family history of breast (FHBC) have the greatest need for better risk assessment as they often receive the same clinical recommendations despite substantial heterogeneity in the underlying risk by the extent of FHBC. Integration of mammographic breast density (MBD), a strong and readily assessable risk factor for breast cancer, in combination with detailed FHBC data, offers an exceptional opportunity for enhancing existing risk assessment methods. MBD generally declines with age, but the rate of change varies considerably between women, and may be particularly important to breast cancer risk; we have demonstrated that women who remain at high MBD over time are more likely to be diagnosed with breast cancer than women whose MBD decreases. Attempts to improve risk prediction models by incorporating MBD has had limited success as studies have used one-time measures of MBD and included mostly postmenopausal women for whom the largest changes in MBD may have already occurred. We propose to investigate within-individual changes in MBD over a 10- year period in relation to incident breast cancer by the extent of FHBC (Aim 1), and evaluate how changes in MBD may improve several clinical risk prediction models (Aim 2) and clinical risk stratification forming the basis for risk-based surveillance and preventive care (Aim 3). We will address these aims by building upon the U.S. Sister Study, a prospective cohort of 50,884 women with one or more sisters diagnosed with breast cancer who were personally breast cancer-free at enrollment in 2003-2009; active annual follow-up is conducted for at least 10 years with each woman. Using a nested case-control design, we will retrieve existing mammograms for all incident breast cancer cases diagnosed at ages ≤ 60 years (n=1,242 cases to date) and controls matched on age and enrollment year (2 controls selected per case at the time of case identification). We will undertake a comprehensive assessment of MBD, using both clinically available qualitative measures used in clinical practice, and assessing quantitative measures that allow for measurement of smaller changes and different components of MBD (e.g., dense, nondense tissue) that are independently associated with breast cancer risk. Our team’s experience in leading studies of MBD and prospective available data in the Sister Study will afford an unparalleled investigation of prospective MBD changes in relation to breast cancer risk, modifiable and genetic factors, and how to use this information to enhance risk assessment in women with FHBC. These results are necessary to inform personalized risk-based surveillance and prevention programs.

抽象的准确的乳腺癌风险评估有可能区分出需要哪些高风险女性对风险较低的女性进行强化筛查、预防性或降低风险的治疗和手术目前，乳腺癌风险评估中的干预措施收效甚微，并可能造成危害。现有风险预测模型的精确度和准确性有限，有家族史的女性受到限制。乳腺癌 (FHBC) 最需要更好的风险评估，因为它们经常接受相同的临床治疗尽管存在大量建议，但 FHBC 的整合程度存在潜在风险。乳房 X 光检查乳腺密度 (MBD) 是乳腺癌的一个强大且易于评估的危险因素，与详细的 FHBC 数据相结合，为增强现有风险评估提供了绝佳的机会 MBD 通常随着年龄的增长而下降，但女性之间的变化率差异很大，并且我们已经证明，处于高乳腺癌风险的女性可能尤其重要；随着时间的推移，MBD 比 MBD 降低的女性更有可能被诊断为乳腺癌。通过纳入 MBD 来改进风险预测模型的尝试取得了有限的成功，因为研究表明使用一次性 MBD 测量，主要包括绝经后妇女，她们的变化最大 MBD 的变化可能已经发生，我们建议调查 10 年内 MBD 的个体变化。年期间与乳腺癌发病率的关系（目标 1），并评估乳腺癌发生率的变化 MBD 可以改进多种临床风险预测模型（目标 2），并为临床风险分层奠定基础基于风险的监测和预防性护理（目标 3）。我们将在美国的基础上实现这些目标。姐妹研究，一项由 50,884 名女性组成的前瞻性队列，其中一名或多名姐妹被诊断患有乳腺癌 2003-2009 年入组时个人未患乳腺癌的人进行了积极的年度随访；使用嵌套病例对照设计，我们将检索每位女性至少 10 年的现有乳房 X 光检查。对于年龄≤ 60 岁诊断的所有乳腺癌病例（迄今为止 n=1,242 例）和对照我们将根据年龄和入学年份进行匹配（在病例识别时为每个病例选择 2 个对照）。使用临床上可用的定性测量方法对 MBD 进行全面评估临床实践，并评估定量措施，以测量较小的变化和与乳房独立相关的 MBD 的不同组成部分（例如致密组织、非致密组织）我们团队在 MBD 的领先研究方面的经验以及 Sister 的前瞻性可用数据。研究将对与乳腺癌风险相关的前瞻性 MBD 变化进行无与伦比的调查，可改变的遗传因素，以及如何利用这些信息来加强对患有此类疾病的女性的风险评估 FHBC。这些结果对于为基于风险的个性化监测和预防计划提供信息是必要的。