Grant Number:	5U01CA097431-08 Interpret this number
Primary Investigator:	Kimmel, Marek
Organization:	Rice University
Project Title:	Lung Cancer Model: Risk, Progression and Intervention
Fiscal Year:	2009

DESCRIPTION (provided by applicant): In the course of previous CISNET funding period, we developed two complementary models of lung cancer: (i) Model of carcinogenesis, extended to include genetic susceptibility and impact of smoking pattern, (ii) Model of progression, detection and treatment, based on stochastic tumor growth and stochastic stage transitions. The main trust of the research planned will be focused on two Aims: Aim 1. To determine population impact of interventions such as: (a) Smoking cessation and prevention of initiation, (b) Early detection of lung cancer by periodic screening using helical CT, in a high-risk population, followed by therapy, (c) Lifestyle interventions (e.g., dietary), removal of exposures (ETS, asbestos, radon). Aim 2. Predict the population impact of novel interventions, not yet developed, such as genetic screening of heavy smokers and other high-risk groups, detection using new biomarkers, new treatment modalities and so forth..While the impact of smoking on lung cancer is generally well understood, there are certain aspects of this modeling which are still a major challenge, e.g., gaining a better understanding of the process of carcinogenesis for those who have quit smoking and understanding trends in lung cancer among nonsmokers. This implies our Aim 3. To model carcinogenesis and natural history of lung cancer in former smokers and never smokers. Modeling is the only method that allows extrapolation of results of controlled cancer intervention studies to estimates of US population and community effectiveness. Current models, as it is seen from the review above, do not address existing inter-individual variability in susceptibility, natural history, response to treatment, and so forth. The individual-based approach to modeling, which we are taking in this application, will allow addressing this variability. The individual-based approach is also suitable for modeling of interventions, which do not yet exist such as new treatments.




Modeling the natural history and detection of lung cancer based on smoking behavior.
Authors: Chen X. , Foy M. , Kimmel M. , Gorlova O.Y. .
Source: Plos One, 2014; 9(4), p. e93430.
PMID: 24705368
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Small Median Tumor Diameter At Cure Threshold (<20 Mm) Among Aggressive Non-small Cell Lung Cancers In Male Smokers Predicts Both Chest X-ray And Ct Screening Outcomes In A Novel Simulation Framework
Authors: Goldwasser D.L. , Kimmel M. .
Source: International Journal Of Cancer, 2013-01-01 00:00:00.0; 132(1), p. 189-97.
PMID: 22510979
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Chapter 1:The impact of the reduction in tobacco smoking on U.S. lung cancer mortality, 1975-2000: an introduction to the problem.
Authors: Feuer E.J. , Levy D.T. , McCarthy W.J. .
Source: Risk Analysis : An Official Publication Of The Society For Risk Analysis, 2012 Jul; 32 Suppl 1, p. S6-S13.
PMID: 22882893
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Impact of reduced tobacco smoking on lung cancer mortality in the United States during 1975-2000.
Authors: Moolgavkar S.H. , Holford T.R. , Levy D.T. , Kong C.Y. , Foy M. , Clarke L. , Jeon J. , Hazelton W.D. , Meza R. , Schultz F. , et al. .
Source: Journal Of The National Cancer Institute, 2012-04-04 00:00:00.0; 104(7), p. 541-8.
EPub date: 2012-04-04 00:00:00.0.
PMID: 22423009
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Initial medical attention on patients with early-stage non-small cell lung cancer.
Authors: Chen X. , Gorlov I.P. , Ying J. , Merriman K.W. , Kimmel M. , Lu C. , Reyes-Gibby C.C. , Gorlova O.Y. .
Source: Plos One, 2012; 7(3), p. e32644.
PMID: 22412901
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Association of smoking with tumor size at diagnosis in non-small cell lung cancer.
Authors: Chen X. , Gorlov I.P. , Merriman K.W. , Weng S.F. , Foy M. , Keener G. , Amos C.I. , Spitz M.R. , Kimmel M. , Gorlova O.Y. .
Source: Lung Cancer (amsterdam, Netherlands), 2011 Dec; 74(3), p. 378-83.
PMID: 21645942
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A Smoking-based Carcinogenesis Model For Lung Cancer Risk Prediction
Authors: Foy M. , Spitz M.R. , Kimmel M. , Gorlova O.Y. .
Source: International Journal Of Cancer, 2011-10-15 00:00:00.0; 129(8), p. 1907-13.
PMID: 21140453
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Modeling The Mortality Reduction Due To Computed Tomography Screening For Lung Cancer
Authors: Foy M. , Yip R. , Chen X. , Kimmel M. , Gorlova O.Y. , Henschke C.I. .
Source: Cancer, 2011-06-15 00:00:00.0; 117(12), p. 2703-8.
PMID: 21656748
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Adjusting a cancer mortality-prediction model for disease status-related eligibility criteria.
Authors: Foy M. , Chen X. , Kimmel M. , Gorlova O.Y. .
Source: Bmc Medical Research Methodology, 2011-05-11 00:00:00.0; 11, p. 64.
EPub date: 2011-05-11 00:00:00.0.
PMID: 21569346
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Modeling Excess Lung Cancer Risk Among Screened Arm Participants In The Mayo Lung Project
Authors: Goldwasser D.L. , Kimmel M. .
Source: Cancer, 2010-01-01 00:00:00.0; 116(1), p. 122-31.
PMID: 19918924
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Estimation Of The Effects Of Smoking And Dna Repair Capacity On Coefficients Of A Carcinogenesis Model For Lung Cancer
Authors: Deng L. , Kimmel M. , Foy M. , Spitz M. , Wei Q. , Gorlova O. .
Source: International Journal Of Cancer, 2009-05-01 00:00:00.0; 124(9), p. 2152-8.
PMID: 19123470
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Candidate Pathways And Genes For Prostate Cancer: A Meta-analysis Of Gene Expression Data
Authors: Gorlov,I.P. , Byun,J. , Gorlova,O.Y. , Aparicio,A.M. , Efstathiou,E. , Logothetis,C.J. .
Source: Bmc Medical Genomics, 2009; 2, p. 48.
PMID: 19653896
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