Developing approaches for modeling genomic and proteomic profiles in lung cancer

开发肺癌基因组和蛋白质组图谱建模方法

• 批准号: 7902278
• 负责人: Pamela Markell McMahon
• 金额: $ 24.2万
• 依托单位: MASSACHUSETTS GENERAL HOSPITAL
• 依托单位国家: 美国
• 财政年份: 2007
• 资助国家: 美国
• 起止时间: 2007-08-01 至 2012-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7902278
• 关键词: Ablation; Address; Adherence; Advisory Committees; Age; Algorithms; American; Award; Benign; Biological Markers; Cancer Burden; Cancer Intervention; Characteristics; Clinical; Complex; Data; Development; Disease; Doctor of Philosophy; Effectiveness; Eligibility Determination; Future; Gender; General Hospitals; Genomics; Goals; Growth and Development function; Guidelines; Image; Imaging technology; Individual; Institutes; Investments; Lesion; Life; Malignant Neoplasms; Malignant neoplasm of lung; Mass Screening; Massachusetts; Measurable; Mentors; Mentorship; Methods; Modeling; Molecular Profiling; Natural History; Neoplasm Metastasis; Outcome; Patients; Phase; Policies; Population; Population Dynamics; Positioning Attribute; Proteomics; Race; Relative (related person); Research; Research Personnel; Risk; Role; Screening for cancer; Screening procedure; Simulate; Site; Smoke; Smoking; Smoking History; Smoking Status; Source; Specific qualifier value; Spiral Computed Tomography; Staging; Structure; Technology Assessment; Time; Workplace; base; cell type; cohort; cost; cost effectiveness; design; experience; follow-up; improved; interest; lung cancer screening; meetings; models and simulation; mortality; novel; programs; statistics; tool

DESCRIPTION (provided by applicant): Despite recent decreases in smoking rates, lung cancer claimed more than 163,000 American lives in 2005. Interest in possible lung cancer screening programs is intense; several large ongoing trials are evaluating imaging technologies to detect early-stage lung cancer. In addition, public and private investment in genomic and proteomic research may add biomarkers to the list of tools for lung cancer screening. Decisions about the appropriate roles of imaging and biomarkers in lung cancer screening programs can be informed by modeling, a formal, transparent way to integrate available data. In the proposed independent phase, I will incorporate genomic and proteomic profiles into the Lung Cancer Policy Model, a comprehensive microsimulation model of lung cancer designed to evaluate the cost, effectiveness, and cost-effectiveness of screening programs. I am an outcomes researcher with experience in developing complex disease simulation models, including the natural history model at the core of the Lung Cancer Policy Model. My long term research agenda is to develop methods and approaches to making disease simulation models more robust and useful to decision makers. Specifically, future approaches for cancer screening, treatment, and surveillance promise to be increasingly tailored to the individual patient. Modeling cancer interventions will require much more detail on individual characteristics and clinical algorithms than is now typical in disease simulation models. The site of the proposed study, the Institute for Technology Assessment (ITA) at Massachusetts General Hospital, offers a rich combination of facilities, expertise, and mentorship. The proposed Sponsor, G. Scott Gazelle, MD MPH PhD, became my primary mentor when I joined the ITA in 1998 as a research assistant, and recently chaired my doctoral dissertation committee. We have established a comfortable and productive work environment and have developed a mentoring plan that will allow me to complete my transition to an independent researcher role. Protected time for coursework, meetings with an Advisory Committee of clinical and modeling experts, and completion of ongoing analyses involving the Lung Cancer Policy Model will position me appropriately to undertake the proposed research and apply for an independent research award.

描述（由申请人提供）：尽管吸烟率最近降低，但肺癌在2005年夺取了163,000多名美国人的生命。对可能的肺癌筛查计划的兴趣却很紧张；一些大型正在进行的试验正在评估成像技术以检测早期肺癌。此外，对基因组和蛋白质组学研究的公共和私人投资可能会在肺癌筛查工具列表中增加生物标志物。关于成像和生物标志物在肺癌筛查计划中的适当作用的决定可以通过建模来告知，这是一种正式的，透明的透明方式来集成可用的数据。在拟议的独立阶段，我将将基因组和蛋白质组学特征纳入肺癌策略模型，这是一个全面的肺癌微仿真模型，旨在评估筛查计划的成本，有效性和成本效益。 我是一名具有开发复杂疾病仿真模型的经验的研究人员，包括肺癌政策模型核心的自然历史模型。我的长期研究议程是开发方法和方法，以使疾病模拟模型对决策者更强大和有用。具体而言，未来的癌症筛查，治疗和监测的方法有望越来越针对个体患者量身定制。与现在的疾病模拟模型中的典型情况相比，对癌症干预进行建模将需要更多的个人特征和临床算法的细节。 拟议研究的地点是马萨诸塞州综合医院的技术评估研究所（ITA），提供了丰富的设施，专业知识和指导。拟议的赞助商G. Scott Gazelle，MD MPH博士学位，当我在1998年加入ITA担任研究助理时，成为我的主要导师，最近主持了我的博士学位论文委员会。我们已经建立了一个舒适而富有成效的工作环境，并制定了一项指导计划，使我能够完成向独立研究人员角色的过渡。受保护的课程工作时间，与临床和建模专家的咨询委员会会议以及涉及肺癌政策模型的正在进行的分析的完成，将适当地定位我，以进行拟议的研究并申请独立研究奖。