Impact of Personalized Medicine on the Cost-Effectiveness of Prevention

描述(由申请人提供)：基于个人特定信息的量身定做的保健干预措施，包括家族病史和基因组学，有望在不久的将来改变临床实践。以预防疾病为目标的个性化药物前景广阔，因为它可以减少对昂贵治疗的需求，并提高国民的整体健康水平。因此，迫切需要评估个性化药物对健康结果和成本的预期影响。我们建议开发一个数学模型来确定这些预防性测试的潜在影响，并评估这些测试可能采用的阈值敏感度、特异度和成本，这将对推动这一领域走向更大的临床应用非常有益。个性化医疗的发展更加重视个人层面的决策，需要使用微观模拟技术的下一代建模。因此，我们建议研究个性化药物对预防成本-效果的影响，使用基于代理的模型(ABM)来模拟个人行为和相互作用，并在人口水平上评估它们的集体影响。我们将构建一个结直肠癌(CRC)预防和筛查的原型模型，以演示该建模方法的实用性和可行性。本研究的具体目标如下：具体目标1.开发一个进行微观模拟建模的框架，以评估个性化药物和基因组学对预防成本和收益的影响。具体目标2.创建一个预防儿童权利缺陷的原型模型，以证明开发一种评估个体水平差异的ABM的可行性。具体目标3.确定包括基因检测在内的预防儿童权利公约的个人化办法可能节约成本或具有成本效益的门槛。这项研究的总体目标是提供一个框架，可以促进ABM的使用，以研究个性化药物对预防各种疾病的成本效益的影响，包括其他癌症、糖尿病、心脏病和肥胖症。 公共卫生相关性：以预防疾病为目标的个性化药物前景光明，因为它可以减少对昂贵治疗的需求，并改善国民的整体健康。开发一个数学模型来确定这些预防性测试的潜在影响，并评估这些测试可能采用的阈值敏感度、特异度和成本，对于推动这一领域走向更广泛的临床应用将是极其有益的。我们将构建一个用于结直肠癌预防和筛查的原型模型，以演示该建模方法的实用性和可行性。

DESCRIPTION (provided by applicant): Tailored health care interventions based on information specific to an individual, including family history and genomics, are expected to transform clinical practice in the near future. Personalized medicine targeted at preventing diseases holds great promise because it can reduce the need for high-cost treatments and improve the overall health of the nation. Therefore, there is an imminent need to assess the projected impact of personalized medicine on both health outcomes and cost. We are proposing to develop a mathematical model for identifying the potential impacts of these preventive tests and to assess the threshold sensitivity, specificity, and cost under which these tests are likely to be adopted, which will be extremely beneficial in moving this field forward toward greater clinical application. The movement toward personalized medicine, which places greater importance on personal-level decision making, requires next-generation modeling using micro simulation techniques. Therefore, we are proposing to study the impact of personalized medicine on the cost-effectiveness of prevention using an agent-based model (ABM) to simulate individual behaviors and interactions and to assess their collective impacts at the population level. We will build a prototype model for colorectal cancer (CRC) prevention and screening to demonstrate the utility and feasibility of this modeling approach. The specific aims of this research are as follows: Specific Aim 1. Develop a framework for performing micro simulation modeling to assess the impact of personalized medicine and genomics on the costs and benefits of prevention. Specific Aim 2. Create a prototype model for CRC prevention to demonstrate the feasibility of developing an ABM to assess individual-level differences. Specific Aim 3. Identify the thresholds under which personalized approaches, including genetic testing, for CRC prevention could potentially be cost-saving or cost-effective. The overall goal of this research is to provide a framework that can foster the use of ABMs to study the impact of personalized medicine on the cost-effectiveness of prevention for a wide range of diseases, including other cancers, diabetes, heart disease, and obesity. PUBLIC HEALTH RELEVANCE: Personalized medicine targeted at preventing diseases holds great promise because it can reduce the need for high-cost treatments and improve the overall health of the nation. Developing a mathematical model to identify the potential impacts of these preventive tests and assessing the threshold sensitivity, specificity, and cost under which these tests are likely to be adopted will be extremely beneficial in moving this field forward toward greater clinical application. We will build a prototype model for colorectal cancer prevention and screening to demonstrate the utility and feasibility of this modeling approach.