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: 7944030
• 负责人: Sandra J Lee
• 金额: $ 40.21万
• 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 2012-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7944030
• 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; 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; randomized trial; 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）：高级筛查技术在乳腺癌项目摘要/摘要的早期检测中的作用此申请解决了广泛的挑战领域（05）：比较有效性研究和特定挑战主题，05-CA-105 CISNET（癌症干预和监视模型网络）。这项研究的目标旨在评估与乳腺癌筛查的先进筛查技术相关的收益。计划应用Lee和Zelen（2008）开发的随机模型来解决晚期筛查技术在早期检测乳腺癌中的有效性。 Lee-Zelen模型（2008）已作为Cisnet乳房组的一部分开发。该模型预测乳腺癌死亡率与疾病自然病史和检测过程的关系。该模型的主要假设是：i）乳腺癌是一种进行性疾病，ii）筛查的死亡率益处是由于诊断的阶段变化。在快速新兴的晚期筛查技术中，据报道，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。但是，尚未评估与这些筛查方式相关的死亡率益处。该赠款将着重于评估DM和MRI筛查的死亡率益处。数字乳腺X线摄影成像筛查试验表明，在50岁以下的妇女或任何具有非常密集的乳房的女性中，DM比电影乳房X线摄影更敏感（Pisano等，2005）。在对乳腺癌易感性易感性的女性中检测乳腺癌的乳腺癌中，MRI比乳房X线摄影更敏感（Kreige等，2004； Leach等，2005）。将对使用DM和MRI进行最佳筛选策略的协议进行调查的一个重要问题。筛选程序的特征是：i）开始筛选程序的年龄，ii）考试之间的时间和3）可能是结束筛查的年龄。这些变量有很多潜在的排列，以至于临床试验不可能检查所有可能的排列。此外，随机试验是不可行的。研究问题的唯一方法是拥有筛查过程的分析模型，该模型结合了疾病的主要特征和筛查过程。根据风险进行筛查计划的潜在节省是巨大的。具体而言，它计划：估计DM在50岁以下的女性中的死亡率益处，以及任何年龄较大的乳房的妇女。估计如果在美国人口中传播，DM的潜在死亡率受益。估计MRI在患乳腺癌风险升高的女性中的死亡率益处。查找取决于乳房密度的最佳筛查时间表。根据DM和MRI筛选方式调查最佳筛查策略。高级筛查技术在早期发现乳腺癌的作用 公共卫生相关性：磁共振成像（MRI）可能用于高风险种群中的乳腺癌筛查，数字乳房摄影可能对筛查乳房密集的女性有利。该项目将使用Lee-Zelen（2008）的数学模型来评估死亡率益处，并为这些高级筛选方式找到最佳的筛选策略。由于很难使用随机临床试验研究这些问题，因此数学模型可以为了解这些筛查方式的潜在增益做出重大贡献。