PREDICTIVE MODELING IN LUNG CANCER

点击翻译按钮获取中文摘要

DESCRIPTION (provided by applicant): An estimated 201,000 new cases of lung cancer will be diagnosed in the United States in 2012. Lung cancer, the most common cause of cancer-related mortality, causes nearly 150,000 deaths annually. It is estimated that the costs of taking care of patients with lung cancer exceed $40 billion annually. Despite the tremendous impact of lung cancer on society, there are no reliable, clinically applicable methods to predict post-treatment outcomes in lung cancer patients. It has been shown that survival after diagnosis of lung cancer depends on both patient and tumor characteristics. Type of treatment or operation also impacts survival. Previous attempts at creating predictive models for survival after treatment for lung cancer have been severely limited by lack of detailed patient information, methodologic issues, and lack of validation. This career development proposal is designed to provide training and support for the applicant to become an independent clinical researcher focused on evaluating and modeling outcomes in thoracic oncology. The career development goals of this proposal are; 1. Obtain didactic training for a strong foundation in responsible conduct of research, research design, statistics, modeling methodology, decision analysis, and communication of risk to patients and providers. 2. Develop expertise in creating predictive models to assess competing therapies for common thoracic cancers and performing cost-effectiveness analyses. 3. Develop the skills necessary to communicate and disseminate results of the studies, implement research findings in practice, and influence change in policy and healthcare delivery to improve outcomes. The short-term career development goals will be accomplished by completing a Master of Science in Clinical Investigation degree at Washington University. To develop the practical skill set, the applicant will utilize decision analytic modelig to evaluate and predict long-term survival after surgery or radiation therapy for patients with early-stage lung cancer. Similar methods will be used to study the effectiveness and cost- effectiveness of treatment options for locally advanced lung cancer. The clinical objective is to develop and disseminate tools that can predict survival after treatment for lung cancer and to evaluate the cost-effectiveness of treatment options. The models will be made available to clinicians and the public on the Washington University website via an electronic, user-friendly interface. The models will support investigators seeking to assess prognosis for patients. Our results will also serve as baseline for assessing the value of new and emerging tests like genetic studies, which could be compared to and incorporated into the models. The career objective of the proposal is to develop the candidate into an independent investigator, who can implement modeling approaches to assess the impact of interventions on clinical care in oncology.