Developing approaches for modeling genomic and proteomic profiles in lung cancer

描述(申请人提供)：尽管吸烟率最近有所下降，但肺癌在2005年夺走了超过16.3万美国人的生命。人们对可能的肺癌筛查项目兴趣浓厚；几项正在进行的大型试验正在评估检测早期肺癌的成像技术。此外，公共和私人对基因组和蛋白质组研究的投资可能会将生物标记物添加到肺癌筛查工具的清单中。关于成像和生物标记物在肺癌筛查项目中的适当作用的决定可以通过建模来获得信息，这是一种整合现有数据的正式、透明的方式。在提议的独立阶段，我将把基因组和蛋白质组图谱合并到肺癌政策模型中，这是一个全面的肺癌微观模拟模型，旨在评估筛查计划的成本、效果和成本效益。 我是一名成果研究员，在开发复杂的疾病模拟模型方面有经验，包括肺癌政策模型核心的自然病史模型。我的长期研究议程是开发方法和途径，使疾病模拟模型更健壮，对决策者更有用。具体地说，未来癌症筛查、治疗和监测的方法有望越来越多地针对个别患者量身定做。与现在疾病模拟模型中的典型情况相比，对癌症干预措施的建模将需要关于个体特征和临床算法的更多细节。 这项拟议研究的地点是麻省总医院的技术评估研究所(ITA)，提供丰富的设施、专业知识和指导。建议的赞助人G·斯科特·加泽尔是医学硕士博士，1998年我作为研究助理加入ITA时，他成为了我的主要导师，最近还担任了我的博士论文委员会的主席。我们已经建立了一个舒适和富有成效的工作环境，并制定了一个指导计划，使我能够完成向独立研究人员角色的过渡。受保护的课业时间，与临床和建模专家咨询委员会的会议，以及完成正在进行的涉及肺癌政策模型的分析，将使我适合承担拟议的研究并申请独立研究奖。

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.