Objective-To use various exposureresponse models to estimate the risk of mortality from lung cancer due to occupational exposure to respirable crystalline silica dust. Methods-Data from a cohort mortality study of 2342 white male California diatomaceous earth mining and processing workers exposed to crystalline silica dust (mainly cristobalite) were reanalyzed with Poisson regression and Cox's proportional hazards models. Internal and external adjustments were used to control for potential confounding from the eVects of time since first observation, calendar time, age, and Hispanic ethnicity. Cubic smoothing spline models were used to assess the fit of the models. Exposures were lagged by 10 years. Evaluations of the fit of the models were performed by comparing their deviances. Lifetime risks of lung cancer were estimated up to age 85 with an actuarial approach that accounted for competing causes of death. Results-Exposure to respirable crystalline silica dust was a significant predictor (p<0.05) in nearly all of the models evaluated and the linear relative rate model with a 10 year exposure lag seemed to give the best fit in the Poisson regression analysis. For those who died of lung cancer the linear relative rate model predicted rate ratios for mortality from lung cancer of about 1.6 for the mean cumulative exposure to respirable silica compared with no exposure. The excess lifetime risk (to age 85) of mortality from lung cancer for white men exposed for 45 years and with a 10 year lag period at the current Occupational Safety and Health Administration (OSHA) standard of about 0.05 mg/m 3 for respirable cristobalite dust is 19/1000 (95% confidence interval (95% CI) 5/1000 to 46/1000). Conclusions-There was a significant risk of mortality from lung cancer that increased with cumulative exposure to respirable crystalline silica dust. The predicted number of deaths from lung cancer suggests that current occupational health standards may not be adequately protecting workers from the risk of lung cancer. (Occup Environ Med 2001;58:38-45)

Epidemiologic data is increasingly being used for dose-response analysis in risk assessment. The Environmental Protection Agency (EPA) and other U.S. agencies have expressed a preference for using epidemiologic data rather than toxicologic data when possible. However, there are a number of important sources of uncertainty in using epidemiologic data for this purpose that need to be clearly recognized and, when possible, quantified. This paper presents a critical review of the major sources of uncertainty in the use of epidemiologic data for cancer risk assessment. These may include: (1) study design issues such as potential confounding and other biases, inadequate sample size, and followup, (2) the choice of the data set, (3) specification of the dose-response model, (4) estimation of exposure and dose, and (5) unrecognized variability in susceptibility. Examples from risk assessments for cadmium, asbestos, and diesel exhaust are used to illustrate the potential magnitude of some of these sources of uncertainty. It is shown that the overall uncertainty from these various sources combined may often result in highly uncertain risk estimates from dose-response modeling of epidemiologic data. For this reason, we believe it is best to present a range of possible risk estimates, which, to the extent possible, reflects the variability and uncertainty inherent in the dose-response evaluation of epidemiologic data.

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Background-Silicosis, a lung disease caused by inhaling respirable crystalline silica dust, is an occupational illness affecting millions of workers worldwide.