Role of Advanced Screening Technologies in Early Detection of Breast Cancer

摘要/摘要本申请涉及广泛的挑战领域（05）：比较有效性研究和特定挑战主题，05- ca -105 CISNET（癌症干预和监测建模网络）。这项研究的目的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发现中的有效性。Lee-Zelen模型（2008）是CISNET乳房组的一部分。该模型预测乳腺癌死亡率作为疾病自然史和检测过程的函数。该模型的主要假设是：i)乳腺癌是一种进行性疾病，ii)筛查对死亡率的好处是由于诊断阶段的转变。据报道，在新兴的先进筛查技术中，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效益尚未得到评估。该资助将侧重于评估糖尿病和MRI筛查对死亡率的益处。数字乳房x线摄影成像筛查试验表明，在筛查50岁以下的女性或任何年龄的乳房非常致密的女性时，DM明显比乳房x线摄影更敏感（Pisano et al., 2005）。在乳腺癌遗传易感性女性中，MRI检测乳腺癌的灵敏度高于乳房x光检查（Kreige et al., 2004; Leach et al., 2005）。将研究的一个重要问题是使用DM和MRI进行最佳筛选策略。筛查计划的特征包括：i)开始筛查计划的年龄，ii)两次检查之间的时间，以及3)可能结束筛查的年龄。这些变量有很多潜在的排列，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。调查这一问题的唯一方法是建立一个包含疾病的主要特征和筛选过程的筛选过程的分析模型。基于风险的筛查项目的潜在节省是巨大的。具体来说，它的计划是：估计糖尿病对50岁以下妇女和任何年龄的致密乳房妇女的死亡率益处。如果糖尿病在美国人群中传播，估计其潜在的死亡率益处。估计MRI对乳腺癌高危妇女的死亡率益处。根据乳腺密度找到最佳的筛查检查时间表。探讨糖尿病和MRI筛查方式的最佳筛查策略。先进筛查技术在早期发现乳腺癌中的作用

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.