A pooled analysis of mammographic density and breast cancer risk

乳房X光密度和乳腺癌风险的汇总分析

基本信息

批准号：
7660546
负责人：
GERTRAUD MASKARINEC
金额：
$ 7.88万
依托单位：
UNIVERSITY OF HAWAII AT MANOA
依托单位国家：
美国
项目类别：
财政年份：
2009
资助国家：
美国
起止时间：
2009-03-01 至 2011-02-28
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/7660546
关键词：
Address Adipose tissue Affect African American Appearance Area Asians Body Weight Body mass index Breast Breast Cancer Prevention Case-Control Studies Categories Caucasians Caucasoid Race Classification Scheme Collaborations Data Databases Epidemiologic Studies Epithelial Ethnic Origin Future Genetic Goals Grant Heterogeneity Hormonal Image Intention Intervention Studies Investigation Knowledge Light Linear Models Location Logistic Regressions Mammographic Density Mammography Meta-Analysis Methods Modification Obesity Pathologic Pathway interactions Pattern Population Population Study Procedures Publishing Reader Reading Research Research Personnel Risk Estimate Source Staging Subgroup Technology Thick Time Tissues Variant Woman anticancer research base breast density cancer epidemiology cancer risk density experience high risk innovation interest malignant breast neoplasm reproductive working group

项目摘要

DESCRIPTION (provided by applicant): Breast density as assessed in mammographic images is a strong predictor of breast cancer risk, but the strength of the association may differ with body weight. It is important to understand these sources of heterogeneity when breast density is used as an intermediate endpoint in intervention studies and as a predictor of individualized breast cancer risk. The proposed project makes use of existing data from previous case-control studies on mammographic density and breast cancer risk. The specific aims of the proposed project are to examine breast cancer risk associated with mammographic density across levels of body mass index (BMI) and breast size; to elucidate methodologic issues in comparing mammographic images that were obtained from different locations and using different technologies; and to initiate a working group to collaborate on studies of mammographic densities. This project will combine data from four case-control studies on mammographic densities. The total number of subjects will be 4,229 with 1,747 cases and 2,482 controls with an ethnic distribution of 45% Caucasian, 38% Asian, 8% African- American, and 9% Others and a wide variation in BMI and breast size. The data base will be based on a common format for all variables of interest, breast cancer status and stage, breast density as percent and as absolute density, anthropometric, and reproductive variables. One mammogram for each subject will be assessed by one reader to assure the comparability of density readings across studies using a quantitative assessment method. We will apply general linear models to compare the previous density readings obtained through different methods with the new standardized readings. Breast cancer risk associated with percent density for different levels of BMI and breast size will be estimated using the SUDAAN logistic regression procedure and adjusting for confounders. The investigators will plan collaborative studies and consider the possibility of inviting additional researchers to contribute their mammographic data for future innovative investigations of mammographic density. This project will provide new information on how body weight affects breast cancer risk related to breast density. These findings will be useful for breast cancer risk estimation and breast cancer prevention.

描述（由申请人提供）：乳房 X 光检查图像中评估的乳房密度是乳腺癌风险的有力预测因子，但关联强度可能因体重而异。当乳腺密度被用作干预研究的中间终点和个体化乳腺癌风险的预测因子时，了解这些异质性来源非常重要。拟议的项目利用了先前关于乳房X光密度和乳腺癌风险的病例对照研究的现有数据。该项目的具体目标是检查与不同体重指数（BMI）和乳房大小水平的乳房X线照相密度相关的乳腺癌风险；阐明比较从不同地点和使用不同技术获得的乳房X线照相图像的方法学问题；并成立一个工作组来合作研究乳房X光密度。该项目将结合四项关于乳腺 X 光密度病例对照研究的数据。受试者总数为 4,229 人，其中 1,747 名病例和 2,482 名对照者，种族分布为 45% 白种人、38% 亚洲人、8% 非裔美国人和 9% 其他人，BMI 和乳房大小差异很大。该数据库将基于所有感兴趣变量、乳腺癌状态和分期、乳腺密度百分比和绝对密度、人体测量和生殖变量的通用格式。每个受试者的一张乳房X光照片将由一名读数器进行评估，以确保使用定量评估方法进行的研究中密度读数的可比性。我们将应用一般线性模型将以前通过不同方法获得的密度读数与新的标准化读数进行比较。将使用 SUDAAN 逻辑回归程序并调整混杂因素来估计与不同 BMI 水平和乳房大小的密度百分比相关的乳腺癌风险。研究人员将计划合作研究，并考虑邀请更多研究人员为未来乳腺 X 线密度创新研究贡献其乳腺 X 线摄影数据的可能性。该项目将提供有关体重如何影响与乳腺密度相关的乳腺癌风险的新信息。这些发现将有助于乳腺癌风险评估和乳腺癌预防。