Simulation of lung cancer by introducing genetic risk factors to carcinogenesis process in large population
Lung cancer is one of the most common cancers found in the United States and worldwide and is the second-leading cause of death in the US, trailing only behind heart diseases. Lung cancer kills more people in the US each year than any other cancer, mostly because it is usually detected at a later stage when treatment is not effective. Common risk factors for lung cancer include cigarette consumption, age, sex, family history, environmental hazards, exposure to secondhand smoke, as well as genetic risk factors. Currently there is a great interest in determining the role of genetic risk factors in the carcinogenesis process of lung cancer and exploring the efficient use of individual genetic information for the prevention of this disease. In this project, we extend a microsimulation model that simulates the initiation and progression of lung cancer using a Two-Stage Clonal Expansion (TSCE) model. Genetic risk factors that are consistent with existing and hypothetical genetic risk factors are introduced to the baseline TSCE model. Statistics such as incidence and incidence rate are collected for each sex, and carrier groups. The models are calibrated using observations from the Surveillance Epidemiology and End Results (SEER). The incidence data from both baseline model and most extensive simulations are consistent with SEER observations. Furthermore, extensive simulations indicate that carrier incidences increase with the increasing number of disease alleles of similar relative risk and frequency, and the carrier rate decreases in varying degrees according to relative risks.
Qiao, Min, "Simulation of lung cancer by introducing genetic risk factors to carcinogenesis process in large population" (2013). Texas Medical Center Dissertations (via ProQuest). AAI1552506.