Risk analysis for environmental health triage

Purpose-Driven Risk Assessment

Chemical exposures are routine; some are controlled, some are not. Whether an exposure should be controlled depends on the acceptability of the consequences of controlling or not controlling the exposure. The federal government has the responsibility to protect human health against the harmful effects of chemical exposure, and uses rather conservative policies and procedures to develop regulatory exposure standards. These protective risk values typically do not inform the likelihood of harm or the type of harm that should be anticipated if regulated exposure standards are exceeded. Exposure guideline values are not regulatory and not enforceable. Their purpose is to predict the types and severity of responses with respect to the exposure. These values may be called "predictive," perhaps primarily because of the decreased level of conservatism based directly on their need to provide information on the likelihood of harm and the type of harm that should be anticipated when exposures are uncontrolled. If an emergency response action is required, the intensity of that response should be aligned with the anticipated impact of the exposure on human health and safety. The applicability of risk values for specific exposure scenarios should be selected based on the purpose for which they were developed.

Reassessment of MTBE cancer potency considering modes of action for MTBE and its metabolites

A 1999 California state agency cancer potency (CP) evaluation of methyl tert-butyl ether (MTBE) assumed linear risk extrapolations from tumor data were plausible because of limited evidence that MTBE or its metabolites could damage DNA, and based such extrapolations on data from rat gavage and rat and mouse inhalation studies indicating elevated tumor rates in male rat kidney, male rat Leydig interstitial cells, and female rat leukemia/lymphomas. More recent data bearing on MTBE cancer potency include a rodent cancer bioassay of MTBE in drinking water; several new studies of MTBE genotoxicity; several similar evaluations of MTBE metabolites, formaldehyde, and tert-butyl alcohol or TBA; and updated evaluations of carcinogenic mode(s) of action (MOAs) of MTBE and MTBE metabolite's. The lymphoma/leukemia data used in the California assessment were recently declared unreliable by the U.S. Environmental Protection Agency (EPA). Updated characterizations of MTBE CP, and its uncertainty, are currently needed to address a variety of decision goals concerning historical and current MTBE contamination. To this end, an extensive review of data sets bearing on MTBE and metabolite genotoxicity, cytotoxicity, and tumorigenicity was applied to reassess MTBE CP and related uncertainty in view of MOA considerations. Adopting the traditional approach that cytotoxicity-driven cancer MOAs are inoperative at very low, non-cytotoxic dose levels, it was determined that MTBE most likely does not increase cancer risk unless chronic exposures induce target-tissue toxicity, including in sensitive individuals. However, the corresponding expected (or plausible upper bound) CP for MTBE conditional on a hypothetical linear (e.g., genotoxic) MOA was estimated to be ∼2 × 10(-5) (or 0.003) per mg MTBE per kg body weight per day for adults exposed chronically over a lifetime. Based on this conservative estimate of CP, if MTBE is carcinogenic to humans, it is among the weakest 10% of chemical carcinogens evaluated by EPA.

Unveiling variability and uncertainty for better science and decisions on cancer risks from environmental chemicals

The National Research Council 2009 "Silver Book" panel report included a recommendation that the U.S. Environmental Protection Agency (EPA) should increase all of its chemical carcinogen (CC) potency estimates by ∼7-fold to adjust for a purported median-vs.-mean bias that I recently argued does not exist (Bogen KT. "Does EPA underestimate cancer risks by ignoring susceptibility differences?," Risk Analysis, 2014; 34(10):1780-1784). In this issue of the journal, my argument is critiqued for having flaws concerning: (1) intent, bias, and conservatism of EPA estimates of CC potency; (2) bias in potency estimates derived from epidemiology; and (3) human-animal CC-potency correlation. However, my argument remains valid, for the following reasons. (1) EPA's default approach to estimating CC risks has correctly focused on bounding average (not median) individual risk under a genotoxic mode-of-action (MOA) assumption, although pragmatically the approach leaves both inter-individual variability in CC-susceptibility, and widely varying CC-specific magnitudes of fundamental MOA uncertainty, unquantified. (2) CC risk estimates based on large epidemiology studies are not systematically biased downward due to limited sampling from broad, lognormal susceptibility distributions. (3) A good, quantitative correlation is exhibited between upper-bounds on CC-specific potency estimated from human vs. animal studies (n = 24, r = 0.88, p = 2 × 10(-8)). It is concluded that protective upper-bound estimates of individual CC risk that account for heterogeneity in susceptibility, as well as risk comparisons informed by best predictions of average-individual and population risk that address CC-specific MOA uncertainty, should each be used as separate, complimentary tools to improve regulatory decisions concerning low-level, environmental CC exposures.

Climate change - An uncertainty factor in risk analysis of contaminated land

Metals frequently occur at contaminated sites, where their potential toxicity and persistence require risk assessments that consider possible long-term changes. Changes in climate are likely to affect the speciation, mobility, and risks associated with metals. This paper provides an example of how the climate effect can be inserted in a commonly used exposure model, and how the exposure then changes compared to present conditions. The comparison was made for cadmium (Cd) exposure to 4-year-old children at a highly contaminated iron and steel works site in southeastern Sweden. Both deterministic and probabilistic approaches (through probability bounds analysis, PBA) were used in the exposure assessment. Potential climate-sensitive variables were determined by a literature review. Although only six of the total 39 model variables were assumed to be sensitive to a change in climate (groundwater infiltration, hydraulic conductivity, soil moisture, soil:water distribution, and two bioconcentration factors), the total exposure was clearly affected. For example, by altering the climate-sensitive variables in the order of 15% to 20%, the deterministic estimate of exposure increased by 27%. Similarly, the PBA estimate of the reasonable maximum exposure (RME, defined as the upper bound of the 95th percentile) increased by almost 20%. This means that sites where the exposure in present conditions is determined to be slightly below guideline values may in the future exceed these guidelines, and risk management decisions could thus be affected. The PBA, however, showed that there is also a possibility of lower exposure levels, which means that the changes assumed for the climate-sensitive variables increase the total uncertainty in the probabilistic calculations. This highlights the importance of considering climate as a factor in the characterization of input data to exposure assessments at contaminated sites. The variable with the strongest influence on the result was the soil:water distribution coefficient (Kd).

Generic Hockey-Stick Model for Estimating Benchmark Dose and Potency: Performance Relative to BMDS and Application to Anthraquinone

Benchmark Dose Model software (BMDS), developed by the U.S. Environmental Protection Agency, involves a growing suite of models and decision rules now widely applied to assess noncancer and cancer risk, yet its statistical performance has never been examined systematically. As typically applied, BMDS also ignores the possibility of reduced risk at low doses ("hormesis"). A simpler, proposed Generic Hockey-Stick (GHS) model also estimates benchmark dose and potency, and additionally characterizes and tests objectively for hormetic trend. Using 100 simulated dichotomous-data sets (5 dose groups, 50 animals/group), sampled from each of seven risk functions, GHS estimators performed about as well or better than BMDS estimators, and a surprising observation was that BMDS mis-specified all of six non-hormetic sampled risk functions most or all of the time. When applied to data on rodent tumors induced by the genotoxic chemical carcinogen anthraquinone (AQ), the GHS model yielded significantly negative estimates of net potency exhibited by the combined rodent data, suggesting that-consistent with the anti-leukemogenic properties of AQ and structurally similar quinones-environmental AQ exposures do not likely increase net cancer risk. In addition to its simplicity and flexibility, the GHS approach offers a unified, consistent approach to quantifying environmental chemical risk.

Probabilistic exposure analysis for chemical risk characterization

This paper summarizes the state of the science of probabilistic exposure assessment (PEA) as applied to chemical risk characterization. Current probabilistic risk analysis methods applied to PEA are reviewed. PEA within the context of risk-based decision making is discussed, including probabilistic treatment of related uncertainty, interindividual heterogeneity, and other sources of variability. Key examples of recent experience gained in assessing human exposures to chemicals in the environment, and other applications to chemical risk characterization and assessment, are presented. It is concluded that, although improvements continue to be made, existing methods suffice for effective application of PEA to support quantitative analyses of the risk of chemically induced toxicity that play an increasing role in key decision-making objectives involving health protection, triage, civil justice, and criminal justice. Different types of information required to apply PEA to these different decision contexts are identified, and specific PEA methods are highlighted that are best suited to exposure assessment in these separate contexts.