Developing Approaches For Modeling Genomic And Proteomic Profiles In Lung Cancer
Pamela Markell Mcmahon
Massachusetts General Hospital
Grant 5K99CA126147-02 from National Cancer Institute, IRG: ZCA1
Abstract: 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
Keywords: lung, model, neoplasm /cancer, proteomics aging, base, bias, biomarker, cell type, choice, cost effectiveness, experience, growth /development, hospital, mass screening, metastasis, motivation, reduction, role, sex, smoking, statistics /biometry, therapy, work site clinical research
Project start date: 2007-08-01
Project end date: 2009-07-31
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Grants awarded to Pamela Markell Mcmahon
Developing Approaches For Modeling Genomic And Proteomic Profiles In Lung Cancer
Pamela Markell Mcmahon
Massachusetts General Hospital
Grant 5K99CA126147-02 from National Cancer Institute, IRG: ZCA1
Abstract: 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
Keywords: lung, model, neoplasm /cancer, proteomics aging, base, bias, biomarker, cell type, choice, cost effectiveness, experience, growth /development, hospital, mass screening, metastasis, motivation, reduction, role, sex, smoking, statistics /biometry, therapy, work site clinical research
Project start date: 2007-08-01
Project end date: 2009-07-31