Role of Advanced Screening Technologies in Early Detection of Breast Cancer

先进筛查技术在乳腺癌早期检测中的作用

• 批准号: 7827475
• 负责人: Sandra J Lee
• 金额: $ 43.24万
• 依托单位: DANA-FARBER CANCER INST
• 依托单位国家: 美国
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-09-30 至 2011-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7827475
• 关键词: Address; Age; Area; Breast; Breast Cancer Detection; Breast Cancer Early Detection; Cancer Intervention and Surveillance Modeling Network; Clinical Trials; Contralateral; Data; Detection; Diagnosis; Digital Mammography; Disease; Early Diagnosis; Effectiveness; Family history of; Film; Genetic Predisposition to Disease; Goals; Grant; Image; Lead; Magnetic Resonance Imaging; Mammography; Modality; Modeling; Natural History; Population; Process; Progressive Disease; Randomized Clinical Trials; Randomized Controlled Clinical Trials; Recommendation; Reporting; Research; Risk; Risk Factors; Role; Savings; Schedule; Screening procedure; Specific qualifier value; Staging; Targeted Research; Technology; Time; Woman; abstracting; base; breast cancer diagnosis; breast density; cancer risk; comparative effectiveness; digital; disease natural history; effectiveness research; high risk; improved; malignant breast neoplasm; mathematical model; mortality; pre-clinical; programs; public health relevance; transmission process

DESCRIPTION (provided by applicant): Role of Advanced Screening Technologies for Early Detection of Breast Cancer Project Summary/Abstract This application addresses broad Challenge Area (05): Comparative Effectiveness Research and specific Challenge Topic, 05-CA-105 CISNET (The Cancer Intervention and Surveillance Modeling Network). The goals of this research are targeted at evaluating the benefits associated with advanced screening technologies for breast cancer screening. It is planned to apply the stochastic model developed by Lee and Zelen (2008) to address the effectiveness of advanced screening technologies in the early detection of breast cancer. The Lee-Zelen model (2008) has been developed as part of the CISNET breast group. The model predicts breast cancer mortality as a function of the disease natural history and detection process. The principal assumptions of the model are that: i) breast cancer is a progressive disease and ii) mortality benefit from screening is due to a stage shift in diagnosis. Among the rapidly emerging advanced screening technologies, digital mammography (DM) and magnetic resonance imaging (MRI) have been reported to be more sensitive in diagnosing breast cancer. However the mortality benefit associated with these screening modalities has not been evaluated. This grant will focus on evaluating the mortality benefit from DM and MRI screening. The digital mammographic imaging screening trial showed that DM was significantly more sensitive than film mammography in screening women under age 50 or women of any age with very dense breasts (Pisano et al., 2005). MRI has been shown to be more sensitive than mammography in detecting breast cancer in women with inherited susceptibility to breast cancer (Kreige et al., 2004; Leach et al., 2005). An important issue which will be investigated deals with optimal screening strategies using DM and MRI. A screening program is characterized by: i) the age to begin a screening program, ii) the times between examinations and 3) possibly the age to end screening. There are so many potential permutations of these variables that clinical trials cannot possibly examine all of the possible permutations. Furthermore randomized trials are not feasible. The only way to investigate the problem is to have an analytical model of the screening process which incorporates the main features of the disease and the screening process. The potential savings of having screening programs based on risk are enormous. Specifically it is planned to: Estimate the mortality benefit of DM in women under age 50 and women of any age with dense breasts. Estimate the potential mortality benefit of DM if disseminated in the U.S. population. Estimate the mortality benefit of MRI in women with elevated risk of developing breast cancer. Find optimal screening exam schedules which depend on breast density. Investigate optimal screening strategies by risk status for DM and MRI screening modalities. Role of Advanced Screening Technologies for Early Detection of Breast Cancer PUBLIC HEALTH RELEVANCE: Magnetic resonance imaging (MRI) may be utilized for breast cancer screening in high risk populations and digital mammography may be advantageous for screening women with dense breasts. This project will use the Lee-Zelen's (2008) mathematical model to evaluate mortality benefit as well as to find optimal screening strategies for these advanced screening modalities. As it is difficult to investigate these problems using randomized clinical trials, mathematical models can make a significant contribution in understanding the potential gain from these screening modalities.

描述（由申请人提供）：先进筛查技术在乳腺癌早期检测中的作用 项目摘要/摘要 本申请涉及广泛的挑战领域 (05)：比较有效性研究和具体挑战主题，05-CA-105 CISNET（癌症干预和监测建模网络）。这项研究的目标是评估先进的乳腺癌筛查技术的益处。计划应用 Lee 和 Zelen (2008) 开发的随机模型来解决先进筛查技术在乳腺癌早期检测中的有效性。 Lee-Zelen 模型 (2008) 是作为 CISNET 乳房组的一部分开发的。该模型根据疾病自然史和检测过程来预测乳腺癌死亡率。该模型的主要假设是：i) 乳腺癌是一种进行性疾病，ii) 筛查带来的死亡率获益是由于诊断的阶段性转变。据报道，在迅速兴起的先进筛查技术中，数字乳房X线摄影（DM）和磁共振成像（MRI）在诊断乳腺癌方面更为敏感。然而，与这些筛查方式相关的死亡率益处尚未得到评估。这笔赠款将重点评估 DM 和 MRI 筛查对死亡率的益处。数字乳房 X 光成像筛查试验表明，在筛查 50 岁以下女性或任何年龄的乳房非常致密的女性时，DM 比胶片乳房 X 光检查更敏感（Pisano 等，2005）。在检测具有乳腺癌遗传易感性的女性中，MRI 已被证明比乳房 X 光检查更敏感（Kreige 等，2004 年；Leach 等，2005 年）。将要研究的一个重要问题涉及使用 DM 和 MRI 的最佳筛查策略。筛查计划的特征在于：i) 开始筛查计划的年龄，ii) 检查之间的时间，以及 3) 可能结束筛查的年龄。这些变量有如此多的潜在排列，临床试验不可能检查所有可能的排列。此外，随机试验也是不可行的。研究该问题的唯一方法是建立一个筛查过程的分析模型，其中包含疾病的主要特征和筛查过程。基于风险的筛查计划的潜在节省是巨大的。具体计划是： 估计 50 岁以下女性和任何年龄的乳房致密女性的死亡率获益。估计如果糖尿病在美国人群中传播，其潜在的死亡率益处。估计 MRI 对患乳腺癌风险较高的女性的死亡率益处。根据乳腺密度找到最佳的筛查检查时间表。根据 DM 和 MRI 筛查方式的风险状态研究最佳筛查策略。先进筛查技术在乳腺癌早期检测中的作用 公共卫生相关性：磁共振成像 (MRI) 可用于高危人群的乳腺癌筛查，数字乳房 X 光检查可能有利于筛查乳房致密的女性。该项目将使用 Lee-Zelen (2008) 的数学模型来评估死亡率效益，并为这些先进的筛查方式找到最佳筛查策略。由于使用随机临床试验很难调查这些问题，数学模型可以为理解这些筛查方式的潜在收益做出重大贡献。