Session Schedule & Abstracts


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Common abbreviations

W4-D
Symposium: Cancer Risk Assessment

Room: Galerie 4, 2nd Floor   3:30 pm–5:10 pm

Chair(s): Andrey Korchevskiy   akorchevskiy@c-ih.com

Sponsored by Dose Response SG and Occupational Health and Safety SG

Cancer risk assessment is in high demand from the professionals in various areas, related to occupational, environmental, and general public health. However, very often risk assessors still encounter a significant methodological hurdle when cancer risks should be extrapolated to a very low level of exposure. Is there a way to quantitatively establish a threshold for some types of cancers? What mathematical methods can be used to extrapolate linear and non-linear cancer risk models below the epidemiologically observed doses? What conditions should be satisfied to distinguish between background exposure and exposure of a specific individual? Can “No Safe Level” concept be confirmed or rejected utilizing available epidemiological data and advanced mathematical apparatus? The session will explore those issues, using different examples. In particular, the “take home” exposure to mineral fibers will be evaluated to demonstrate typical approaches of low-dose lung cancer and mesothelioma risk calculations. The results of Monte Carlo simulation of background exposure to asbestos fibers in the United States will be compared with other examples of



W4-D.1    3:30 pm Background Cancer Rates and Background Exposure: Theoretical and Practical Considerations. Rasmuson EJ*; Chemistry & Industrial Hygiene, Inc.   erasmuson@c-ih.com

Abstract: Assessing mesothelioma risk at low-level cumulative lifetime exposures to elongate mineral particles (EMPs) has proven difficult and is laden with significant uncertainties and variability. Based upon the precautionary principle, no-threshold linearized multistage models to predict mesothelioma rates have been used to characterize excess mesothelioma incidence rates. However, difficulties persist in the use of these mathematical models. Specifically, differentiating the background incidence rate of mesotheliomas in the general population from calculated excess incidence rates from low-level cumulative lifetime EMP exposures cannot effectively be performed. Literature has demonstrated that random DNA replication errors during transcription are major contributing factors in the development of cancer. Additionally, it has been shown that there are approximately 1 to 3 background cases of mesothelioma per million population per year. This incidence rate translates to 70 to 210 cases per 70-year lifetime. Using a linearized model to describe excess lifetime mesothelioma risks, it has been demonstrated that lifetime cumulative chrysotile exposure yields 0.00001 excess cases of mesotheliomas per 1 f/cc-years. Using this relationship, it can be shown that lifetime cumulative exposures from 7 to 21 f/cc-years are required to double the relative risk of mesothelioma, possibly suggesting that chrysotile exposures within this range cannot be differentiated from the background incidence rate of the disease in the general population.

W4-D.2    3:50 pm Mathematics of Extrapolation: Validation of Dose-response Relationships at the Low Exposure Levels. Korchevskiy A*, Rasmuson J; Chemistry & Industrial Hygiene, Inc.   akorchevskiy@c-ih.com

Abstract: Cancer risk assessment for low dose exposure levels remains a complex and controversial area of epidemiological, toxicological, and mathematical modeling studies. The extrapolation below lowest observable exposure range is needed to predict human cancer risk, and a shape of the dose-response curve (linear with zero intercept; linear with threshold; supra- or sublinear etc.) should be assumed prior to the statistical fitting of data. This talk will explore approaches that can be used to validate different dose-response models for low exposures (e.g., in the case of general population background exposure). In particular, it will be demonstrated how lung burden of asbestos fibers, along with reasonable assumptions regarding fiber deposition and clearance rate, can be utilized to reconstruct cumulative exposure and subsequently to evaluate parameters of the dose-response models. Advantages of choosing linearity vs. non-linearity as the dose-response model assumption will be also explored using Monte Carlo simulation. European case-control studies data and other sources will be used to demonstrate the modeling approach. This methodology should be helpful to improve our general understanding of low-exposure cancer risks for various occupational and environmental agents (like nanoparticles and silica dust).

W4-D.3    4:10 pm Bayesian Analysis of Residual Risk: This is What We Mean by Safe. Pagone FJ*; RHP Risk Management Inc.   fpagone@rhprisk.com

Abstract: The Occupational Safety and Health Administration (OSHA) do not define “safe” as being “free from harm or risk” because many activities considered “safe” entail some “risk” (National Research Council of The National Academies, 2004). Safe could then be defined as the state for which risks are judged to be acceptable based on available science, research, and practice (i.e., not unacceptable risk). The risk that persists below levels defined as safe can be called “residual risk”. The goal of our analysis is to provide updated research surrounding the characterization of residual risk as well as the importance of communicating the extent and practical significance of these risks. Human health risk assessments are the primary tool used to determine the magnitude of risk to human health caused by various exposures to carcinogenic chemicals and agents. The results of these assessments are then compared to acceptable risk levels. The National Institute for Occupational Safety and Health (NIOSH) and OSHA generally follow an acceptable risk level of 1 x 10-3 (1:1000) from exposures to carcinogens. If an occupational risk assessment of a known carcinogen results in an excess cancer risk of 10-6 (1:1,000,000), this would then indicate an acceptable risk level and be considered safe due to the presence of residual risk. For many carcinogens, this definition continues to be under debate. Following Bayesian inference, as more evidence surrounding risk becomes available we can strengthen our risk communication and management. Each risk characterization step must be approached with a unique mindset and understanding that proper risk communication to both the research community and general public are vital.

W4-D.4    4:30 pm Asbestos Lung Burden Analysis: What We Know About Background Levels in Non-exposed Individuals. Carney JM*, Pavlisko EN, Sporn TA, Roggli VL; Duke University Medical Center   john.carney@duke.edu

Abstract: Over the past several decades, various publications have established “reference” populations for background levels of asbestos exposure. Currently accepted background or reference range of asbestos fiber burden in non-exposed individuals for our laboratory is 0-20 asbestos bodies/gram (AB/g) based on an analysis of 84 individuals from two different states. Herein, we will review the various analytical methods for fiber analysis and review the methods employed by different authors to establish asbestos fiber and asbestos body counts in their control populations. Our control/reference values for fibers by electron microscopy are based on 20 cases with normal lungs, no asbestos related disease, and AB/gm within our previously determined background range. Further discussion will include recently published work illustrating the correlation of asbestos lung burden analysis and environmental exposure assessment, reaffirming the accepted background level of asbestos.

W4-D.5    4:50 pm Reconstruction of Takehome Exposure: Are the Risks Significant? Boelter Fred*; RHP Risk Management Inc.   fboelter@rhprisk.com

Abstract: The concept of “exposure” is not infrequently judged to be something bad. In fact, human exposure occurs constantly and usually without adverse effect not infrequently because the residual risk is deemed not unacceptable and thus safe. Remember that there are naturally occurring background exposure levels of contaminants. What health professionals work to avoid are “overexposures” where the probability of an adverse effect increases to an unacceptable level of risk. Household exposures can create challenges for health professionals, perhaps even more so than with occupational, workplace, or environmental exposures. Part of the challenges rests with the sanctity of the home and the castle doctrine. Namely, in their home or on their premises a person is allowed to do whatever they want, in whatever way they want, with whatever they want unless, of course, the activities run afoul of the law or regulations. A question thus arises regarding the significance of household exposure where take-home from occupational activities of the spouse, parent, relative or family friend or combination thereof is presumed to be the only potential source of exposure for other household members. We correlated exposure reconstruction estimates with biomarker pathology results and found that estimated household exposures was in the range of 0.2% to 4% of the estimated occupational exposure. Our findings provide support and a method for evaluating the plausibility that a diagnosed disease today could or could not be related to past practices though a household member’s occupation. Such techniques have broad application for understanding the significant or insignificance of hazard, exposure, and risk.



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