Quantitative estimates of the risk of lung cancer or mesothelioma in humans from asbestos exposure made by the U.S. Environmental Protection Agency (EPA) make use of estimates of potency factors based on phase-contrast microscopy (PCM) and obtained from cohorts exposed to asbestos in different occupational environments. These potency factors exhibit substantial variability. The most likely reasons for this variability appear to be differences among environments in fiber size and mineralogy not accounted for by PCM.In this article, the U.S. Environmental Protection Agency (EPA) models for asbestos-related lung cancer and mesothelioma are expanded to allow the potency of fibers to depend upon their mineralogical types and sizes. This is accomplished by positing exposure metrics composed of nonoverlapping fiber categories and assigning each category its own unique potency. These category-specific potencies are estimated in a meta-analysis that fits the expanded models to potencies for lung cancer (K L 's) or mesothelioma (K M 's) based on PCM that were calculated for multiple epidemiological studies in our previous paper (Berman and Crump, 2008). Epidemiological study-specific estimates of exposures to fibers in the different fiber size categories of an exposure metric are estimated using distributions for fiber size based on transmission electron microscopy (TEM) obtained from the literature and matched to the individual epidemiological studies. The fraction of total asbestos exposure in a given environment respectively represented by chrysotile and amphibole asbestos is also estimated from information in the literature for that environment. Adequate information was found to allow K L 's from 15 epidemiological studies and K M 's from 11 studies to be included in the meta-analysis.Since the range of exposure metrics that could be considered was severely restricted by limitations in the published TEM fiber size distributions, it was decided to focus attention on four exposure metrics distinguished by fiber width: "all widths," widths >0.2 µm, widths <0.4 µm, and widths <0.2 µm, each of which has historical relevance. Each such metric defined by width was composed of four categories of fibers: chrysotile or amphibole asbestos with lengths between 5 µm and 10 µm or longer than 10 µm. Using these metrics three parameters were estimated for lung cancer and, separately, for mesothelioma: K L A , the potency of longer (length >10 µm) amphibole fibers; rpc, the potency of pure chrysotile (uncontaminated by amphibole) relative to amphibole asbestos; and rps, the potency of shorter fibers (5 µm < length < 10 µm) relative to longer fibers.For mesothelioma, the hypothesis that chrysotile and amphibole asbestos are equally potent (rpc = 1) was strongly rejected by every metric and the hypothesis that (pure) chrysotile is nonpotent for mesothelioma was not rejected by any metric. Best estimates for the relative potency of chrysotile ranged from zero to about 1/200th that of amphibole asbestos (depending on metric). For lung can...

The most recent update of the U.S. Environmental Protection Agency (EPA) health assessment document for asbestos (Nicholson, 1986, referred to as "the EPA 1986 update") is now 20 years old. That document contains estimates of "potency factors" for asbestos in causing lung cancer (K L 's) and mesothelioma (K M 's) derived by fitting mathematical models to data from studies of occupational cohorts. The present paper provides a parallel analysis that incorporates data from studies published since the EPA 1986 update.The EPA lung cancer model assumes that the relative risk varies linearly with cumulative exposure lagged 10 years. This implies that the relative risk remains constant after 10 years from last exposure. The EPA mesothelioma model predicts that the mortality rate from mesothelioma increases linearly with the intensity of exposure and, for a given intensity, increases indefinitely after exposure ceases, approximately as the square of time since first exposure lagged 10 years. These assumptions were evaluated using raw data from cohorts where exposures were principally to chrysotile (South Carolina Although the linear EPA model generally provided a good description of exposure response for lung cancer, in some cases it did so only by estimating a large background risk relative to the comparison population. Some of these relative risks seem too large to be due to differences in smoking rates and are probably due at least in part to errors in exposure estimates. There was some equivocal evidence that the relative risk decreased with increasing time since last exposure in the Wittenoom cohort, but none either in the South Carolina cohort up to 50 years from last exposure or in the New Jersey cohort up to 35 years from last exposure.textileThe mesothelioma model provided good descriptions of the observed patterns of mortality after exposure ends, with no evidence that risk increases with long times since last exposure at rates that vary from that predicted by the model (i.e., with the square of time). In particular, the model adequately described the mortality rate in Quebec chrysotile miners and millers up through >50 years from last exposure. There was statistically significant evidence in both the Wittenoom and Quebec cohorts that the exposure intensity-response is supralinear 1 rather than linear. The best-fitting models predicted that the mortality rate varies as [intensity] 0.47 for Wittenoom and as [intensity] 0.19 for Quebec and, in both cases, the exponent was significantly less than 1 ( p < .0001).Using the EPA models, K L 's and K M 's were estimated from the three sets of raw data and also from published data covering a broader range of environments than those originally addressed in the EPA 1986 update. Uncertainty in these estimates was quantified using "uncertainty bounds" that reflect both statistical and nonstatistical uncertainties. Lung cancer potency factors (K L 's) were developed from 20 studies from 18 locations, compared to 13 locations covered in the EPA 1986 update. Mesothelioma p...

Data from inhalation studies in which AF/HAN rats were exposed to nine different types of asbestos dusts (in 13 separate experiments) are employed in a statistical analysis to determine if a measure of asbestos exposure (expressed as concentrations of structures with defined sizes, shapes and mineralogy) can be identified that satisfactorily predicts the observed lung tumor or mesothelioma incidence in the experiments. Due to limitations in the characterization of asbestos structures in the original studies, new exposure measures were developed from samples of the original dusts that were re-generated and analyzed by transmission electron microscopy using a direct transfer technique. This analysis provided detailed information on the mineralogy (i.e., chrysotile, amosite, crocidolite or tremolite), type (i.e., fiber, bundle, cluster, or matrix), size (length and width) and complexity (i.e., number of identifiable components of a cluster or matrix) of each individual structure. No univariate measure of exposure was found to provide an adequate description of the lung tumor responses observed among the inhalation studies, although the measure most highly correlated with tumor incidence is the concentration of structures > or = 20 microns in length. Multivariate measures of exposure were identified that do adequately describe the lung tumor responses. Structures contributing to lung tumor risk appear to be long (> or = 5 microns) thin (0.4 microns) fibers and bundles, with a possible contribution by long and very thick (> or = 5 microns) complex clusters and matrices. Potency appears to increase with increasing length, with structures longer than 40 microns being about 500 times more potent than structures between 5 and 40 microns in length. Structures < 5 microns in length do not appear to make any contribution to lung tumor risk. This analysis did not find a difference in the potency of chrysotile and amphibole toward the induction of lung tumors. However, mineralogy appears to be important in the induction of mesothelioma with chrysotile being less potent than amphibole.

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