A pooled analysis of mammographic density and breast cancer risk

描述（由申请人提供）：乳房x线摄影图像中评估的乳腺密度是乳腺癌风险的一个强有力的预测因子，但这种关联的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指标时，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线照相术密度和乳腺癌风险的病例对照研究的现有数据。拟议项目的具体目的是检查不同体重指数（BMI）和乳房大小水平的乳房x光检查密度与乳腺癌风险的关系；阐明在比较不同位置和使用不同技术获得的乳房x线摄影图像时的方法学问题；并发起一个工作组合作研究乳房x线摄影密度。该项目将结合四项关于乳房x线摄影密度的病例对照研究的数据。受试者总数为4229例，其中1747例，对照2482例，种族分布为高加索人45%，亚洲人38%，非洲裔美国人8%，其他9%，BMI和乳房大小差异很大。数据库将基于所有感兴趣的变量的通用格式，乳腺癌状态和阶段，乳房密度百分比和绝对密度，人体测量和生殖变量。每个受试者的一张乳房x光片将由一名读者评估，以确保使用定量评估方法进行研究的密度读数的可比性。我们将采用一般线性模型，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。乳腺癌风险与不同BMI和乳房大小水平的百分比密度相关，将使用SUDAAN逻辑回归程序并调整混杂因素进行估计。研究人员将计划合作研究，并考虑邀请其他研究人员提供其乳房x线摄影数据的可能性，以用于未来乳房x线摄影密度的创新研究。这个项目将提供关于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。

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.