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.

Public Health Relevance

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 applicant will complete the Post-doctoral Program at the Clinical Research Training Center of the Washington University School of Medicine to obtain a Master of Science in Clinical Investigation degree. To gain practical experience, the applicant will learn and utilize decision analytic modeling to study and predict post-treatment outcomes in lung cancer, the leading cause of cancer-related mortality in the United States.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Academic/Teacher Award (ATA) (K07)
Project #
1K07CA178120-01
Application #
8566243
Study Section
Subcommittee G - Education (NCI)
Program Officer
Perkins, Susan N
Project Start
2013-09-01
Project End
2018-08-31
Budget Start
2013-09-01
Budget End
2014-08-31
Support Year
1
Fiscal Year
2013
Total Cost
$157,287
Indirect Cost
$10,836
Name
Washington University
Department
Surgery
Type
Schools of Medicine
DUNS #
068552207
City
Saint Louis
State
MO
Country
United States
Zip Code
63130
Semenkovich, Tara R; Meyers, Bryan F; Kozower, Benjamin D et al. (2018) The role of a decision analysis in treatment of T2N0 esophageal cancer. J Thorac Dis 10:S3309-S3310
Semenkovich, Tara R; Samson, Pamela P; Hudson, Jessica L et al. (2018) Induction Radiation Therapy for Esophageal Cancer: Does Dose Affect Outcomes? Ann Thorac Surg :
Hudson, Jessica L; Bell, Jennifer M; Crabtree, Traves D et al. (2018) Office-Based Spirometry: A New Model of Care in Preoperative Assessment for Low-Risk Lung Resections. Ann Thorac Surg 105:279-286
Semenkovich, Tara R; Panni, Roheena Z; Hudson, Jessica L et al. (2018) Comparative effectiveness of upfront esophagectomy versus induction chemoradiation in clinical stage T2N0 esophageal cancer: A decision analysis. J Thorac Cardiovasc Surg 155:2221-2230.e1
Samson, Pamela; Keogan, Kathleen; Crabtree, Traves et al. (2017) Interpreting survival data from clinical trials of surgery versus stereotactic body radiation therapy in operable Stage I non-small cell lung cancer patients. Lung Cancer 103:6-10
Samson, Pamela; Puri, Varun; Broderick, Stephen et al. (2017) Extent of Lymphadenectomy Is Associated With Improved Overall Survival After Esophagectomy With or Without Induction Therapy. Ann Thorac Surg 103:406-415
Samson, Pamela; Crabtree, Traves; Broderick, Stephen et al. (2017) Quality Measures in Clinical Stage I Non-Small Cell Lung Cancer: Improved Performance Is Associated With Improved Survival. Ann Thorac Surg 103:303-311
Ahmad, Usman; Crabtree, Traves D; Patel, Aalok P et al. (2017) Adjuvant Chemotherapy Is Associated With Improved Survival in Locally Invasive Node Negative Non-Small Cell Lung Cancer. Ann Thorac Surg 104:303-307
Samson, Pamela; Puri, Varun; Broderick, Stephen et al. (2017) Adhering to Quality Measures in Esophagectomy Is Associated With Improved Survival in All Stages of Esophageal Cancer. Ann Thorac Surg 103:1101-1108
Samson, Pamela; Crabtree, Traves D; Robinson, Cliff G et al. (2017) Defining the Ideal Time Interval Between Planned Induction Therapy and Surgery for Stage IIIA Non-Small Cell Lung Cancer. Ann Thorac Surg 103:1070-1075

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