4.5.1 Pulmonary Inflammation
As discussed above, the evidence in rats sug-gests that the lung tumor mechanism asso-ciated with PSLT particles such as TiO2 is a secondary genotoxic mechanism involving chronic inflammation and cell proliferation.
One plausible approach to developing risk esti-mates for TiO2 is to estimate exposure concen-trations that would not be expected to produce an inflammatory response, thus preventing the development of responses that are secondary to inflammation, including cancer. A bench-mark dose analysis for pulmonary inflamma-tion in the rat was described in Secinflamma-tion 4.3.1, and the results of extrapolating the rat BMDs to humans are presented in Table 4–3. Since two of the three studies available yielded 95%
BMDLs of 0.78 and 1.03 mg/m3, a concentra-tion of approximately 0.9 mg/m3 is reasonable as the starting point for development of rec-ommendations for human exposures for fine TiO2. Similarly, a concentration of approxi-mately 0.11 mg/m3 is appropriate as the start-ing point for developstart-ing recommended expo-sures to ultrafine TiO2.
As noted in Section 4.3.1.3, the human pulmo-nary inflammation BMDs in Table 4–3 are es-timates of frank-effect levels and should be ad-justed by the application of uncertainty factors to allow for uncertainty in animal-to-human ex-trapolation and interindividual variability. These uncertainty factors are commonly assumed to be ten-fold for animal-to-human extrapola-tion and another ten-fold for interindividual
variability; the animal-to-human uncertainty may be subdivided into a factor of 4 for toxi-cokinetics and 2.5 for toxicodynamics (WHO 1994). Since the rat BMDs were extrapo-lated to humans using a deposition/clear-ance model, it is reasonable to assume that the animal-to-human toxicokinetic subfactor of 4 has already been accounted for; therefore, a total uncertainty factor of 25 (2.5 for animal-to-human toxicodynamics times 10 for inter-individual variability) should be applied. This results in estimated exposure concentrations designed to prevent pulmonary inflammation of 0.04 mg/m3 for fine TiO2 and 0.004 mg/m3 for ultrafine TiO2.
4.5.2 Lung Tumors
Rather than estimating an exposure concentra-tion designed to avoid secondary toxicity by preventing pulmonary inflammation, another possible basis for developing a REL is to model the risk of lung tumors directly. In the absence of mechanistic data in humans, the tumorigenic mechanism operative in rats cannot be ruled out. Therefore, one approach for estimation of recommended levels of occupational exposure to TiO2 is to estimate the pulmonary particle surface area dose associated with a 1/1000 in-crease in rat lung tumors and to extrapolate that dose to humans on the basis of particle surface area per unit of lung surface area. This approach was used to assess the excess risk of lung cancer at various working lifetime expo-sure concentrations of fine or ultrafine TiO2 (Table 4–6). Selection of the model for esti-mating risks has a significant impact on the risk estimates. As shown in Table 4–6, the 95%
LCL working lifetime mean concentration of fine TiO2 associated with a 1/1000 excess risk of lung cancer is 0.3 to 4.4 mg/m3, depending on the model used to fit the rat lung tumor
data. For ultrafine TiO2, the 95% LCL working lifetime mean concentration associated with a 1/1000 excess risk of lung cancer is 0.04 to 0.54 mg/m3, depending on the model.
Although any of the models evaluated in Table 4–6 could conceivably be used to develop rec-ommendations for occupational exposures to TiO2, the model averaging procedure is attrac-tive since it incorporates both statistical vari-ability and model uncertainty into confidence limit estimation. However, an argument could also be made for basing recommendations on the multistage model, due to its long his-tory of use for carcinogen risk assessment or the quantal-linear model, on the grounds that it generates the lowest BMD and BMDL and is thus arguably the most health-protective.
The BMD and BMDL derived via each of these models are shown in Table 4–6 for both fine and ultrafine TiO2.
Since the various models produce different risk estimates and there is no clear mechanistically based preference for one model over another, it is appropriate to summarize the results by using a MA technique. MA, as implemented here, uses all the information from the various dose-response models, weighting each model by the Akaike information criterion for model fit and constructing an average dose-response model with lower bounds computed by boot-strapping. This method was described by Wheeler and Bailer [2007], who demonstrated via simulation studies that the MA method has superior statistical properties to a strategy of simply picking the best-fitting model from the BMDS suite. As shown in Table 4–6, the model average estimate of the working lifetime mean concentration of fine TiO2 associated with a 1/1000 excess risk of lung cancer is 13.2 mg/m3, with a 95% LCL of 2.4 mg/m3. The correspond-ing estimates for ultrafine TiO2 are 1.6 mg/m3,
with a 95% LCL of 0.3 mg/m3. NIOSH believes that it is reasonable and prudent to use the 95% LCL model-averaged estimates as the ba-sis for RELs, as opposed to the MLEs, in order to allow for model uncertainty and statistical variability in the estimates.
4.5.3 Comparison of Possible Bases for an REL
As discussed above, occupational exposure concentrations designed to prevent pulmo-nary inflammation, and thus prevent the de-velopment of secondary toxicity (including lung tumors), are 0.04 mg/m3 for fine TiO2 and 0.004 mg/m3 for ultrafine TiO2. In comparison, modeling of the dose-response relationship for lung tumors indicates that occupational expo-sure concentrations of 2.4 mg/m3 for fine TiO2 and 0.3 mg/m3 for ultrafine TiO2 would be suf-ficient to reduce the risk of lung tumors to a 1/1000 lifetime excess risk level. The discrep-ancy between the occupational exposure con-centrations estimated from modeling either pulmonary inflammation or lung tumors raises serious questions concerning the optimal basis for a TiO2 REL. However, it must be acknowl-edged that the two sets of possible RELs are not based on entirely comparable endpoints.
The pulmonary inflammation-based exposure concentrations are expected to entirely prevent the development of toxicity secondary to pul-monary inflammation, resulting in zero excess risk of lung tumors due to exposure to TiO2. In contrast, the lung tumor-based exposure con-centrations are designed to allow a small, but nonzero, excess risk of lung tumors due to oc-cupational exposure to TiO2.
As discussed in Section 3.4.1, particle-induced pulmonary inflammation may act as a precur-sor for lung tumor development; however,
pulmonary inflammation itself is not a specific biomarker for lung cancer. As noted in Sec-tion 3.5.2.2, the precise level of sustained inflammation necessary to initiate a tumori-genic response is currently unknown. It is pos-sible that the 4% PMN response used in this analysis as the benchmark response level for pulmonary inflammation is overly protective and that a somewhat greater inflammatory re-sponse is required for tumor initiation.
It is also possible that the 25-fold uncer-tainty factor applied to the critical dose es-timate for pulmonary inflammation may be overly conservative, since pulmonary in-flammation is an early event in the sequence of events leading to lung tumors. However,
NIOSH has not previously used early events or secondary toxicity as a rationale for apply-ing smaller than normal uncertainty factors.
Given that in this case the primary objective of preventing pulmonary inflammation is to prevent the development of lung tumors, and given that lung tumors can be adequately con-trolled by exposures many-fold higher than the inflammation-based exposure concentrations, NIOSH has concluded that it is appropriate to base RELs for TiO2 on lung tumors rather than pulmonary inflammation. However, NIOSH notes that extremely low-level exposures to TiO2—i.e., at concentrations less than the pul-monary inflammation-based RELs—may pose no excess risk of lung tumors.
5 Hazard Classification and Recommended Exposure Limits
NIOSH initiated the evaluation of titanium dioxide by considering it as a single substance with no distinction regarding particle size.
However, a review of all the relevant scien-tific literature indicated that there could be a greater occupational health risk with smaller size (ultrafine) particles and therefore NIOSH provides separate recommendations for the ul-trafine and fine categories.
NIOSH has reviewed the relevant animal and human data to assess the carcinogenicity of titanium dioxide (TiO2) and has reached the following conclusions. First, the weight of evi-dence suggests that the tumor response ob-served in rats exposed to ultrafine TiO2 resulted from a secondary genotoxic mechanism involv-ing chronic inflammation and cell proliferation, rather than via direct genotoxicity of TiO2. This effect appears to be related to the physical form of the inhaled particle (i.e., particle surface area) rather than to the chemical compound itself.
Second, based on the weight of the scientific data (including increase in adenocarcinoma tu-mor incidence in a chronic inhalation study in rats of 10 mg/m3), NIOSH determined that in-haled ultrafine TiO2 is a potential occupational carcinogen and is recommending exposure lim-its to minimize the cancer risk from exposure to ultrafine TiO2. Finally, because the tumorigenic dose of fine TiO2 (250 mg/m3) in the Lee et al.
studies [1985, 1986a] was substantially higher than current inhalation toxicology practice—
and because there was no significant increase in tumors at 10 or 50 mg/m3—NIOSH did not use
the highest dose in its hazard identification and concluded that there is insufficient evidence to classify fine TiO2 as a potential occupational carcinogen. Although NIOSH has determined that the data are insufficient for cancer hazard classification of fine TiO2, the particle surface area dose and tumor response relationship is consistent with that observed for ultrafine TiO2 and warrants that precautionary mea-sures be taken to protect the health of workers exposed to fine TiO2. Therefore, NIOSH used all of the animal tumor response data to con-duct the dose-response modeling, and devel-oped separate mass-based RELs for ultrafine and fine TiO2.