Analysis of lung cancer incidence in the Nurses' Health and the Health Professionals' Follow-Up Studies using a multistage carcinogenesis model.
ABSTRACT We analyzed lung cancer incidence among non-smokers, continuing smokers, and ex-smokers in the Nurses Health Study (NHS) and the Health Professionals Follow-Up Study (HPFS) using the two-stage clonal expansion (TSCE) model. Age-specific lung cancer incidence rates among non-smokers are identical in the two cohorts. Within the framework of the model, the main effect of cigarette smoke is on the promotion of partially altered cells on the pathway to cancer. Smoking-related promotion is somewhat higher among women, whereas smoking-related malignant conversion is somewhat lower. In both cohorts the relative risk for a given daily level of smoking is strongly modified by duration. Among smokers, the incidence in NHS relative to that in HPFS depends both on smoking intensity and duration. The age-adjusted risk is somewhat larger in NHS, but not significantly so. After smokers quit, the risk decreases over a period of many years and the temporal pattern of the decline is similar to that reported in other recent studies. Among ex-smokers, the incidence in NHS relative to that in HPFS depends both on previous levels of smoking and on time since quitting. The age-adjusted risk among ex-smokers is somewhat higher in NHS, possibly due to differences in the age-distribution between the two cohorts.
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ABSTRACT: Carcinogenesis is the transformation of normal cells into cancer cells. This process has been shown to be of a multistage nature, with stem cells that go through a series of genetic and epigenetic changes that eventually lead to a malignancy. Since the origins of the multistage theory in the 1950s, mathematical modeling has played a prominent role in the investigation of the mechanisms of carcinogenesis. In particular, two stochastic (mechanistic) models, the Armitage-Doll and the two-stage clonal expansion (TSCE) model, are commonly used for cancer risk assessment and the analysis of cancer epidemiology and experimental data. In this mini-course, I will introduce some of the basic biological, epidemiological and mathematical concepts behind the theory of multistage carcinogenesis, and discuss in detail the Armitage-Doll model, the TSCE model and some generalizations. The use of these models for the analysis of cancer epidemiology and experimental data will be described in detail, and some examples will be discussed.
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ABSTRACT: tumourigenesis can be regarded as an evolutionary process, in which the transformation of a normal cell into a tumour cell involves a number of limiting genetic and epigenetic events. To study the progression process, time schemes have been proposed for studying the process of colorectal cancer based on extensive clinical investigations. Moreover, a number of mathematical models have been designed to describe this evolutionary process. These models assumed that the mutation rate of genes is constant during different stages. However, it has been pointed that the subsequent driver mutations appear faster than the previous ones and the cumulative time to have more driver mutations grows with the growing number of gene mutations. Thus it is still a challenge to calculate the time when the first mutation occurs and to determine the influence of tumour size on the mutation rate.BMC Systems Biology 01/2014; 8 Suppl 3:S2. DOI:10.1186/1752-0509-8-S3-S2 · 2.85 Impact Factor
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ABSTRACT: Background Implementing optimal lung cancer screening programs requires knowledge of the natural history and detectability of lung cancer. This information can be derived from the results of clinical trials with the aid of microsimulation models. Methods Data from the Surveillance Epidemiology and End Results (SEER) program and individual-level data from the National Lung Screening Trial (NLST) and the Prostate, Lung, Colon and Ovarian Cancer Screening trial (PLCO) were used to investigate the sensitivity (by histology and stage) of computed tomography (CT) and chest radiography (CXR) and the mean preclinical sojourn time (MPST) of lung cancer (by gender, histology and stage). The MISCAN-Lung model was used to reproduce the lung cancer incidence by method of detection (clinically or screen-detected), gender, histology and stage in both trials and SEER, by calibrating CT and CXR sensitivity and natural history parameters. Results CT sensitivity ranges from 8.83%-99.35% and CXR sensitivity from 2.51%-97.31%, depending on histology and stage. CT sensitivity for stage IA is more than threefold higher compared to CXR, for all histologies. The total MPST estimates for lung cancer progressing through preclinical stages IA to IV ranges from 3.09-5.32 years for men and 3.35-6.01 years for women. The largest difference in total MPST between genders was estimated for adenocarcinoma. Conclusions We estimate longer MPSTs for lung cancer compared to previous research, suggesting a greater window of opportunity for lung cancer screening. Impact This study provides detailed insights into the natural history of lung cancer and CT screening effectiveness.Cancer Epidemiology Biomarkers & Prevention 10/2014; 24(1). DOI:10.1158/1055-9965.EPI-14-0745 · 4.32 Impact Factor