Impact of Personalized Medicine on the Cost-Effectiveness of Prevention

个性化医疗对预防成本效益的影响

基本信息

批准号：
8179733
负责人：
SUJHA SUBRAMANIAN
金额：
$ 26.55万
依托单位：
RESEARCH TRIANGLE INSTITUTE
依托单位国家：
美国
项目类别：
财政年份：
2011
资助国家：
美国
起止时间：
2011-09-23 至 2013-08-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/8179733
关键词：
Address Adopted Area Attitude Behavior Biological Markers Caring Characteristics Colorectal Cancer Costs and Benefits Decision Making Diabetes Mellitus Diagnostic Disease Family Fostering Funding Opportunities Future Genetic screening method Genomics Goals Health Health Care Costs Healthcare Heart Diseases Individual International Intervention Malignant Neoplasms Medical Medicine Modeling Molecular Profiling Movement Obesity Outcome Persons Play Population Prevention Preventive Prophylactic treatment Provider Public Health Informatics Recommendation Recording of previous events Research Role Screening procedure Sensitivity and Specificity Simulate Specific qualifier value Techniques Technology Testing Therapeutic Intervention Treatment Cost base clinical application clinical practice colorectal cancer prevention colorectal cancer screening cost cost effective cost effectiveness disorder prevention disorder risk improved mathematical model models and simulation next generation preference prevent prototype response simulation tool

项目摘要

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.

描述（由申请人提供）：基于个人特定信息（包括家族史和基因组学）的定制医疗保健干预措施预计将在不久的将来改变临床实践。以预防疾病为目标的个性化医疗前景广阔，因为它可以减少对高成本治疗的需求并改善国民的整体健康。因此，迫切需要评估个性化医疗对健康结果和成本的预计影响。我们建议开发一个数学模型来识别这些预防性测试的潜在影响，并评估可能采用这些测试的阈值敏感性、特异性和成本，这将非常有利于推动该领域向更广泛的方向发展。临床应用。个性化医疗的发展更加重视个人层面的决策，需要使用微仿真技术进行下一代建模。因此，我们建议使用基于代理的模型（ABM）来研究个性化医疗对预防成本效益的影响，以模拟个体行为和相互作用，并评估其在人群水平上的集体影响。我们将建立一个结直肠癌（CRC）预防和筛查的原型模型，以证明这种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. 开发一个执行微观模拟建模的框架，以评估个性化医疗和基因组学对预防成本和效益的影响。具体目标 2. 创建 CRC 预防原型模型，以证明开发 ABM 来评估个体差异的可行性。具体目标 3. 确定用于预防 CRC 的个性化方法（包括基因检测）可能节省成本或具有成本效益的阈值。这项研究的总体目标是提供一个框架，促进 ABM 的使用，以研究个性化医疗对预防多种疾病（包括其他癌症、糖尿病、心脏病和肥胖症）的成本效益的影响。公共卫生相关性：以预防疾病为目标的个性化医疗前景广阔，因为它可以减少对高成本治疗的需求并改善国民的整体健康状况。开发一个数学模型来识别这些预防性测试的潜在影响，并评估可能采用这些测试的阈值敏感性、特异性和成本，将非常有利于推动该领域朝着更大的临床应用方向发展。我们将建立一个结直肠癌预防和筛查的原型模型，以证明这种建模方法的实用性和可行性。