Statistical Methods in Risk Science

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Advanced statistical methods are increasingly used in the quantitative characterization of risk, providing important evidence to support the development of risk decisions. The present research program focuses on six methodological issues of current interest, which will be addressed through the development and application of innovative statistical techniques. ***1. Environmental burden of disease (EBD). Estimation of the contribution of environmental agents to human disease is importing for establishing priorities for environmental health risk reduction. Statistical methods developed previously to characterize the EBD will be extended to incorporate reduction in quality of life, and illustrated using data from a recent meta-analysis of the risks of neurological disease associated with occupational exposure to lead.****2. Risks of radon in homes. Radon gas, an important cause of lung cancer, is naturally present in rocks and soils in the earth's crust, and enters homes through tiny cracks and fissures in the foundation. In order to guide further radon mitigation efforts, updated estimates of residential radon lung cancer risks will be developed based on new epidemiological and monitoring data from Canada and internationally.****3. Concordance between animal and human tumour sites. The International Agency for Research on Cancer (IARC) has recently completed a review an update of data on 109 cancer causing agents, including: pharmaceuticals; biological agents; arsenic, metals, fibres and dusts; radiation; personal habits and indoor combustions; and chemical agents and related occupations. These data will be used to evaluate the degree of concordance between tumour types seen in animals and humans that are caused by these agents****4. Biological mechanisms of cancer in animals and humans. The IARC data described in (3) above will also be used to compare the mechanisms by which carcinogenic agents operate in animals and humans.****5. Use of pharmacokinetic models for tissue dosimetry. The use of tissue concentrations predicted by pharmacokinetic models in dose-response modelling will be explored, with the expectation that tissue doses may lead to more accurate indicators of risk than dietary or ambient concentrations.****6. Optimal experimental designs for the Ames Salmonella assay. Because of the recent trend towards the use of in vitro data in toxicity testing, optimal experimental designs to estimate a point of departure on the dose-response curve (including both the traditional benchmark dose and the recently proposed signal-to-noise crossover dose) used in setting exposure guidelines for the Ames Salmonella assay will be developed.****Collectively, this work will expand the suite of techniques available for quantitative risk assessment, thereby contributing to better assessments of risk and sound risk-based decision making.******