Suchergebnisse

The Clonogenic Cells of the Rat Mammary and Thyroid Glands: Their Biology, Frequency of Initiation, and Promotion/Progression to Cancer -- The Somatic Mutational Component of Human Carcinogenesis -- Two-Event Carcinogenesis: Roles of Oncogenes and Antioncogenes -- Genetic Alterations during Carcinogenesis in Rodents: Implications for Cancer Risk Assessment -- Multistage Hepatocarcinogenesis in the Rat as a Basis for Models of Risk Assessment of Carcinogenesis -- Cell Proliferation and Hepatocarcinogenesis -- Cell Growth Dynamics and DNA Alterations in Carcinogenesis -- Two Mutation Model for Carcinogenesis: Relative Roles of Somatic Mutations and Cell Proliferation in Determining Risk -- Cancer Dose-Response Models Incorporating Clonal Expansion -- Transformation and Growth of Lung Adenomas in Mice Exposed to Urethane -- Cancer Modeling with Intermittent Exposures -- Possible Role of Selective Gap Junctional Intercellular Communication in Multistage Carcinogenesis -- Interindividual Variation in Human Chemical Carcinogenesis: Implications for Risk Assessment -- Utilizing Biologically Based Models to Estimate Carcinogenic Risk -- Variability of Unit Risk Estimates under Different Statistical Models and between Different Epidemiological Data Sets -- Carcinogenic Drugs: A Model Data-base for Human Risk Quantification -- Afterword: Some Thoughts on What Was Learned and Some Science Policy Issues.

Biologically‐based models of carcinogenesis were originally developed to explain certain quanti‐tative phenomena associated with carcinogenesis, and to provide a framework within which questions regarding the process could be addressed. Some limitations in the use of these models for quantitative cancer risk assessment are discussed.

A two‐mutation model for carcinogenesis is reviewed. General principles in fitting the model to epidemiologic and experimental data are discussed, and some examples are given. A general solution to the model with time‐dependent parameters is developed, and its use is illustrated by application to data from an experiment in which rats exposed to radon developed lung tumors.

In many animal model systems for carcinogenesis, well characterized putative premalignant lesions are observed. A much studied example is provided by the enzyme altered foci in rodent hepatocarcinogenesis experiments. In a recent paper, we proposed a method for the quantitative analysis of such premalignant lesions. The model used in that paper assumed that the mean growth of premalignant clones is exponential. However, it has been suggested that such a model is oversimplified. In this paper, we relax the assumption of exponential mean growth. The new model contains one extra parameter that measures departures from exponentiality. Use of the model is illustrated by analysis of ATPase deficient foci in the liver of rats given NNM (N‐nitrosomorpholine) in their drinking water. The analysis suggests that the clonal growth of altered cells is significantly accelerated (superexponential) for nontoxic doses of NNM. Finally, the hazard function of the two‐mutation model for carcinogenesis is briefly discussed under nonexponential (mean) growth of intermediate cells.

Background: A consortium of six research groups estimated the impact on lung cancer mortality of changes in smoking behavior that began around the publication of the Surgeon General's report (SGR). This chapter presents the results of that effort. We quantified the cumulative impact of changes in smoking behaviors on lung cancer mortality in the United States over the period 1975–2000. Methods: The six groups used common inputs and independent models to estimate the number of U.S. lung cancer deaths averted over the period 1975–2000 as a result of changes in smoking behavior beginning in the mid fifties, and the number of deaths that could have been averted if tobacco control had completely eliminated all smoking following issuance of the first SGR on Smoking and Health in 1964. Results: Approximately 795,000 deaths (550,000 men and 245,000 women) were averted over the period 1975–2000 as a result of changes in smoking behavior since in 1950s. In the year 2000 alone approximately 70,000 lung cancer deaths were averted (44,000 among men and 26,000 among women). However, these represent approximately 30% of lung cancer deaths that could have potentially been averted over the period 1975–2000 if smoking was eliminated completely. In the 10‐year period 1991–2000, this fraction increased to about 37%. Conclusions: Our results show the substantial impact of changes in smoking behavior since the 1950s. Despite a major impact of changing smoking behaviors, tobacco control effort are still needed to further reduce the burden of this disease.

Mathematical expressions are derived, under different dosing patterns, for the number and size of premalignant clones within the framework of a two‐mutation model for carcinogenesis, which has previously been shown to be consistent with a large body of epidemiologic and experimental data.

We present a mathematical treatment of a two‐mutation model for carcinogenesis with time‐dependent parameters. This model has previously been shown to be consistent with epidemiologic and experimental data. An approximate hazard function used in previous papers is critically evaluated.

In 1984, based on epidemiological data on cohorts of coke oven workers, USEPA estimated a unit risk for lung cancer associated with continuous exposure from birth to 1 pg/m3 of coke oven emissions, of 6.2 × This risk assessment was based on information on the cohorts available through 1966. Follow‐up of these cohorts has now been extended to 1982 and, moreover, individual job histories, which were not available in 1984, have been constructed. In this study, lung cancer mortality in these cohorts of coke oven workers with extended follow‐up was analyzed using standard techniques of survival analysis and a new approach based on the two stage clonal expansion model of carcinogenesis. The latter approach allows the explicit consideration of detailed patterns of exposure of each individual in the cohort. The analyses used the extended follow‐up data through 1982 and the detailed job histories now available. Based on these analyses, the best estimate of unit risk is 1.5 × with 95% confidence interval = 1.2 × 10‐"1.8 X

We discuss the hazard function of the two‐mutation clonal expansion model with time‐dependent parameters, with particular emphasis on identifiability of the parameters. We explicitly construct identifiable parameter combinations, and illustrate the properties of the hazard function under perturbations of the underlying biological parameters.

In this chapter we review the epidemiology of lung cancer incidence and mortality among never smokers/nonsmokers and describe the never smoker lung cancer risk models used by the Cancer Intervention and Surveillance Network (CISNET) modelers. Our review focuses on those influences likely to have measurable population impact on never smoker risk, such as secondhand smoke, even though the individual‐level impact may be small. Occupational exposures may also contribute importantly to the population attributable risk of lung cancer. We examine the following risk factors in this chapter: age, environmental tobacco smoke, cooking fumes, ionizing radiation including radon gas, inherited genetic susceptibility, selected occupational exposures, preexisting lung disease, and oncogenic viruses. We also compare the prevalence of never smokers between the three CISNET smoking scenarios and present the corresponding lung cancer mortality estimates among never smokers as predicted by a typical CISNET model.

As a member of the Cancer Intervention and Surveillance Modeling Network (CISNET), the lung cancer (LC) group at Fred Hutchinson Cancer Research Center (FHCRC) developed a model for evaluating U.S. lung cancer mortality trends and the impact of changing tobacco consumption. Model components include a biologically based two‐stage clonal expansion (TSCE) model; a smoking simulator to generate smoking histories and other cause mortality; and adjustments for period and birth cohort to improve calibration to U.S. LC mortality. The TSCE model was first calibrated to five substantial cohorts: British doctors, American Cancer Society CPS‐I and CPS‐II, Health Professionals' Follow‐Up Study (HPFS), and Nurses' Health Study (NHS). The NHS and HPFS cohorts included the most detailed smoking histories and were chosen to represent the effects of smoking on U.S. LC mortality. The calibrated TSCE model and smoking simulator were used to simulate U.S. LC mortality. Further adjustments were necessary to account for unknown factors. This provided excellent fits between simulated and observed U.S. LC mortality for ages 30–84 and calendar years 1975–2000. The FHCRC LC model may be used to study the effects of public health information on U.S. LC trends and the impact of tobacco control policy. For example, we estimated that over 500,000 males and 200,000 females avoided LC death between 1975 and 2000 due to increasing awareness since the mid 1950s of the harmful effects of smoking. We estimated that 1.1 million male and 0.6 million female LC deaths were avoidable if smokers quit smoking in 1965.

We present the results of a quantitative assessment of the lung cancer risk associated with occupational exposure to refractory ceramic fibers (RCF). The primary sources of data for our risk assessment were two long‐term oncogenicity studies in male Fischer rats conducted to assess the potentialpathogenic effects associated with prolonged inhalation of RCF. An interesting feature of the data was the availability of the temporal profile of fiber burden in the lungs of experimental animals. Because of this information, we were able to conduct both exposure‐response and dose‐response analyse. Our risk assessment was conducted within the framework of a biologically based model for carcinogenesis, the two‐stage clonal expansion model, which allows for the explicit incorporation of the concepts of initiation and promotion in the analyses. We found that a model positing that RCF was an initiator had the highest likelihood. We proposed an approach based on biological considerations for the extrapolation of risk to humans. This approach requires estimation of human lung burdens for specific exposure scenarios, which we did by using an extension of a model due to Yu. Our approach acknowledges that the risk associated with exposure to RCF depends on exposure to other lung carcinogens. We present estimates of risk in two populations: (1)a population of nonsmokers and (2) an occupational cohort of steelworkers not exposed to coke oven emissions, a mixed population that includes both smokers and nonsmokers.

The International Agency for Research on Cancer (IARC) in 2012 upgraded its hazard characterization of diesel engine exhaust (DEE) to "carcinogenic to humans." The Diesel Exhaust in Miners Study (DEMS) cohort and nested case‐control studies of lung cancer mortality in eight U.S. nonmetal mines were influential in IARC's determination. We conducted a reanalysis of the DEMS case‐control data to evaluate its suitability for quantitative risk assessment (QRA). Our reanalysis used conditional logistic regression and adjusted for cigarette smoking in a manner similar to the original DEMS analysis. However, we included additional estimates of DEE exposure and adjustment for radon exposure. In addition to applying three DEE exposure estimates developed by DEMS, we applied six alternative estimates. Without adjusting for radon, our results were similar to those in the original DEMS analysis: all but one of the nine DEE exposure estimates showed evidence of an association between DEE exposure and lung cancer mortality, with trend slopes differing only by about a factor of two. When exposure to radon was adjusted, the evidence for a DEE effect was greatly diminished, but was still present in some analyses that utilized the three original DEMS DEE exposure estimates. A DEE effect was not observed when the six alternative DEE exposure estimates were utilized and radon was adjusted. No consistent evidence of a DEE effect was found among miners who worked only underground. This article highlights some issues that should be addressed in any use of the DEMS data in developing a QRA for DEE.

AbstractThe basic assumptions of the Cox proportional hazards regression model are rarely questioned. This study addresses whether hazard ratio, i.e., relative risk (RR), estimates using the Cox model are biased when these assumptions are violated. We investigated also the dependence of RR estimates on temporal exposure characteristics, and how inadequate control for a strong, time‐dependent confounder affects RRs for a modest, correlated risk factor. In a realistic cohort of 500,000 adults constructed using the National Cancer Institute Smoking History Generator, we used the Cox model with increasing control of smoking to examine the impact on RRs for smoking and a correlated covariate X. The smoking‐associated RR was strongly modified by age. Pack‐years of smoking did not sufficiently control for its effects; simultaneous control for effect modification by age and time‐dependent cumulative exposure, exposure duration, and time since cessation improved model fit. Even then, residual confounding was evident in RR estimates for covariate X, for which spurious RRs ranged from 0.980 to 1.017 per unit increase. Use of the Cox model to control for a time‐dependent strong risk factor yields unreliable RR estimates unless detailed, time‐varying information is incorporated in analyses. Notwithstanding, residual confounding may bias estimated RRs for a modest risk factor.