Mammographic Densities: In the Pathway to Breast Cancer?

乳房X光密度：导致乳腺癌的途径？

• 批准号: 6838870
• 负责人: KARIN A ROSENBLATT
• 金额: $ 7.47万
• 依托单位: UNIVERSITY OF ILLINOIS AT URBANA-CHAMPAIGN
• 依托单位国家: 美国
• 财政年份: 2004
• 资助国家: 美国
• 起止时间: 2004-08-15 至 2006-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6838870
• 关键词: breast neoplasms; calcification; cancer risk; data collection methodology /evaluation; density; human data; mammary gland; mammography; mathematical model; statistics /biometry

DESCRIPTION (provided by applicant): Women with dense areas and calcifications, observed on mammograms, have a higher risk of breast cancer. High-risk breast density patterns and the percentage of the breast which is dense have been associated with factors related to the risk of breast cancer among women without breast cancer (age, menopausal status, age at first live birth, parity, body mass index, hormone replacement therapy, alcohol use, frequency of exercise, family history of breast cancer and others). We have the opportunity to investigate whether mammographic densities and calcifications are in the pathway by which these factors are related to breast cancer. A combined data set, from four studies performed in western Washington state, contains 547 breast cancer cases (ascertained from a SEER registry) and 472 controls (ascertained by random digit dialing). Initial mammograms performed, before age 50, on study subjects were evaluated by a reference radiologist by Wolfe's classification (for breast density), percent breast density, and characteristics of calcifications. Previous analyses from this study have shown associations between the aforementioned mammographic characteristics and breast cancer (Thomas et al., 2002). We intend to extend analysis of this data to determine whether controlling for these mammographic features alters the association which factors that have been associated with breast cancer (ex. parity) have with breast cancer. The extent of this alteration of association will be evaluated through multivariate logistic regression models and techniques previously used in clinical trials to assess the value of surrogate endpoints. In addition, nested models, utilizing path modeling and mediator analysis will be used to establish pathways by which these factors associated with breast cancer may cause breast cancer, considering the possible mediating effect of mammographic patterns.

描述（由申请人提供）： 通过乳房X光检查观察到，具有密集区域和钙化的女性患乳腺癌的风险较高。高风险乳房密度模式和致密乳房的百分比与未患乳腺癌的女性患乳腺癌的风险相关因素（年龄、绝经状态、首次活产年龄、产次、体重指数、激素替代疗法、饮酒、运动频率、乳腺癌家族史等）。我们有机会研究乳房X线照相密度和钙化是否在这些因素与乳腺癌相关的途径中。来自华盛顿州西部进行的四项研究的综合数据集包含 547 例乳腺癌病例（通过 SEER 登记确定）和 472 例对照（通过随机数字拨号确定）。研究对象在 50 岁之前进行的初始乳房 X 光检查由参考放射科医生根据 Wolfe 分类（乳腺密度）、乳腺密度百分比和钙化特征进行评估。这项研究之前的分析显示了上述乳房 X 光检查特征与乳腺癌之间的关联（Thomas 等，2002）。我们打算扩展对这些数据的分析，以确定控制这些乳房X线照相特征是否会改变与乳腺癌相关的因素（例如产次）与乳腺癌的关联。这种关联改变的程度将通过多变量逻辑回归模型和先前在临床试验中使用的技术来评估，以评估替代终点的价值。此外，考虑到乳房X线照相模式可能的中介作用，利用路径建模和中介分析的嵌套模型将用于建立这些与乳腺癌相关的因素可能导致乳腺癌的途径。