A pooled analysis of mammographic density and breast cancer risk

描述(申请人提供)：在乳房X光摄影图像中评估的乳房密度是乳腺癌风险的强烈预测因子，但这种关联的强度可能因体重而不同。当乳腺密度被用作干预性研究的中间终点和预测个体乳腺癌风险时，了解这些异质性的来源是很重要的。拟议的项目利用了以前关于乳房X光检查密度和乳腺癌风险的病例对照研究的现有数据。拟议项目的具体目标是检查与不同体重指数和乳房大小的乳房X光检查密度有关的乳腺癌风险；阐明比较从不同地点和使用不同技术获得的乳房X光检查图像的方法学问题；以及发起一个工作组合作研究乳房X光检查密度。该项目将结合四项关于乳房X光检查密度的病例对照研究的数据。受试者总数将为4,229人，其中1,747人为病例，2,482人为对照，种族分布为45%的高加索人，38%的亚洲人，8%的非裔美国人和9%的其他人，体重指数和乳房大小差异很大。该数据库将基于所有感兴趣变量的通用格式，包括乳腺癌状态和分期、乳房密度百分比以及绝对密度、人体测量和生殖变量。每个受试者的一张乳房X光照片将由一名读者评估，以确保使用定量评估方法在不同研究中的密度读数的可比性。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读数进行比较。与不同BMI水平和乳房大小的百分比密度相关的乳腺癌风险将使用SUDAAN Logistic回归程序并对混杂因素进行调整来估计。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房X光检查密度的创新研究贡献他们的乳房X光检查数据的可能性。该项目将提供体重如何影响乳腺癌风险与乳房密度相关的新信息。这些发现将有助于乳腺癌风险评估和乳腺癌预防。

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.