An evaluation of benchmark dose methodology for non-cancer continuous-data health effects in animals due to exposures to dioxin (TCDD)

Does dioxin exert toxic effects in humans at or near current background body levels?: an evidence-based conclusion

Evidence-based toxicology like evidence-based medicine, provides scientifically grounded evidence-based conclusions as distinguished from authority-based opinions. As an example, we address a proposition from the US Environmental Protection Agency's (EPA) Draft Dioxin [2,3, 7,8-tetrachlorodibenzo-P-dioxin (TCDD)] reassessment that: ‘dioxin... can produce effects... at or near current background body burdens or intake levels’. Guided by a systematic, objective, and unbiased analysis of the available molecular, physiological, and clinical/epidemiologic data, in accordance with accepted principles of scientific logic, we reach the evidence-based conclusion that the proposition is rejected. When gaps in scientific knowledge necessitate formulation of opinions to meet preventive or precautionary goals, the reversion to authority should be explicitly acknowledged.

Current perspectives on the use of alternative species in human health and ecological hazard assessments

BACKGROUND

Traditional animal toxicity tests can be time and resource intensive, thereby limiting the number of chemicals that can be comprehensively tested for potential hazards to humans and/or to the environment.

OBJECTIVE

We compared several types of data to demonstrate how alternative models can be used to inform both human and ecological risk assessment.

METHODS

We reviewed and compared data derived from high throughput in vitro assays to fish reproductive tests for seven chemicals. We investigated whether human-focused assays can be predictive of chemical hazards in the environment. We examined how conserved pathways enable the use of nonmammalian models, such as fathead minnow, zebrafish, and Xenopus laevis, to understand modes of action and to screen for chemical risks to humans.

RESULTS

We examined how dose-dependent responses of zebrafish embryos exposed to flusilazole can be extrapolated, using pathway point of departure data and reverse toxicokinetics, to obtain human oral dose hazard values that are similar to published mammalian chronic toxicity values for the chemical. We also examined how development/safety data for human health can be used to help assess potential risks of pharmaceuticals to nontarget species in the environment.

DISCUSSION

Using several examples, we demonstrate that pathway-based analysis of chemical effects provides new opportunities to use alternative models (nonmammalian species, in vitro tests) to support decision making while reducing animal use and associated costs.

CONCLUSIONS

These analyses and examples demonstrate how alternative models can be used to reduce cost and animal use while being protective of both human and ecological health.

Accounting for Uncertainty in Heteroscedasticity in Nonlinear Regression

Toxicologists and pharmacologists often describe toxicity of a chemical using parameters of a nonlinear regression model. Thus estimation of parameters of a nonlinear regression model is an important problem. The estimates of the parameters and their uncertainty estimates depend upon the underlying error variance structure in the model. Typically, a priori the researcher would know if the error variances are homoscedastic (i.e., constant across dose) or if they are heteroscedastic (i.e., the variance is a function of dose). Motivated by this concern, in this article we introduce an estimation procedure based on preliminary test which selects an appropriate estimation procedure accounting for the underlying error variance structure. Since outliers and influential observations are common in toxicological data, the proposed methodology uses M-estimators. The asymptotic properties of the preliminary test estimator are investigated; in particular its asymptotic covariance matrix is derived. The performance of the proposed estimator is compared with several standard estimators using simulation studies. The proposed methodology is also illustrated using a data set obtained from the National Toxicology Program.

Clinical outcome of veterans with acute coronary syndrome who had been exposed to agent orange

2,3,7,8-Tetrachlorodibenzo-p-dioxin (TCDD), one of the components of Agent Orange, has been reported to be a deadly poison despite its presence at extremely small doses. TCDD is reported to cause various kinds of cancers and other harmful effects on humans. However, a correlation between exposure to TCDD and acute coronary syndrome (ACS) is not yet proven. Thus, we examined the correlation between exposure to TCDD and ACS through an analysis of coronary angiograms from veterans of the Vietnam War. Two hundred fifty-one consecutive men undergoing coronary angiograms owing to ACS between April 2004 and May 2009 at Gwangju Veterans Hospital were analyzed. Included subjects were between 50 and 70 years of age. The patients were divided into two groups: 121 patients who had been exposed to TCDD (Group I) and 130 patients who had not been exposed to TCDD (Group II). Clinical and coronary angiographic findings were evaluated. Baseline clinical characteristics, inflammatory markers, and echocardiographic parameters were not significantly different between the two groups. The incidence of hypertension (71.1% vs. 60.0%, p=0.039) and hyperlipidemia (27.3% vs. 16.9%, p=0.038) was higher in Group I than in Group II. Total occlusion, stent length, stent use, and coronary lesion characteristics were not significantly different between the two groups. The rate of major adverse cardiovascular events (MACE) had no relationship with exposure to TCDD. Exposure to TCDD might not affect severity or the rate of MACE in persons with ACS.

Human and rat primary hepatocyte CYP1A1 and 1A2 induction with 2,3,7,8-tetrachlorodibenzo-p-dioxin, 2,3,7,8-tetrachlorodibenzofuran, and 2,3,4,7,8-pentachlorodibenzofuran

The concentration dose response for aryl hydrocarbon receptor (AHR)-mediated CYP1A1 and CYP1A2 messenger RNA (mRNA) induction and enzyme activity was determined in primary cultures of rat and human hepatocytes for 2,3,7,8-tetrachlorodibenzo-p-dioxin, 2,3,4,7,8-pentachlorodibenzofuran, and 2,3,7,8-tetrachlorodibenzofuran. Eleven different congener concentrations from 0.00001 to 100 nM were used, thus spanning seven orders of magnitude. The Hill model was used to obtain values of EC(x) and maximal response from the individual data sets. No-observed effect concentration values were derived using several statistical methods including Dunnett's test, the Welch-Aspin test, and step-down bilinear regression. Thresholds were estimated using baseline projection methods and a "hockey stick" fitting method. Human hepatocytes were less responsive and less sensitive with respect to CYP1A1 activity and mRNA induction than rats. On the other hand, the human CYP1A2 response was more robust than the response in rats but generally less sensitive. These data allow an evaluation of relative species sensitivities for developing interspecies toxicodynamic adjustment factors, for assessing AHR activation thresholds, and for evaluating relative congener potencies. Overall, these data support the position that humans are less sensitive than rats to these AHR-dependent end points and support the use of a data-derived adjustment factor of 1.0 or less for extrapolating between rats and humans.

A margin-of-exposure approach to assessment of noncancer risks of dioxins based on human exposure and response data

BACKGROUND

Risk assessment of human environmental exposure to polychlorinated dibenzo-p-dioxins and dibenzofurans (PCDD/PCDFs) and other dioxin-like compounds is complicated by several factors, including limitations in measuring intakes because of the low concentrations of these compounds in foods and the environment and interspecies differences in pharmacokinetics and responses.

OBJECTIVES

We examined the feasibility of relying directly on human studies of exposure and potential responses to PCDD/PCDFs and related compounds in terms of measured lipid-adjusted concentrations to assess margin of exposure (MOE) in a quantitative, benchmark dose (BMD)-based framework using representative exposure and selected response data sets.

METHODS

We characterize estimated central tendency and upper-bound general U.S. population lipid-adjusted concentrations of PCDD/PCDFs from the 1970s and early 2000s based on available data sets. Estimates of benchmark concentrations for three example responses of interest (induction of cytochrome P4501A2 activity, dental anomalies, and neonatal thyroid hormone alterations) were derived based on selected human studies.

RESULTS

The exposure data sets indicate that current serum lipid concentrations in young adults are approximately 6- to 7-fold lower than 1970s-era concentrations. Estimated MOEs for each end point based on current serum lipid concentrations range from < 10 for neonatal thyroid hormone concentrations to > 100 for dental anomalies-approximately 6-fold greater than would have existed during the 1970s.

CONCLUSIONS

Human studies of dioxin exposure and outcomes can be used in a BMD framework for quantitative assessments of MOE. Incomplete exposure characterization can complicate the use of such studies in a BMD framework.

Simultaneous Confidence Bands for Abbott-Adjusted Quantal Response Models

We study use of a Scheffé-style simultaneous confidence band as applied to low-dose risk estimation with quantal response data. We consider two formulations for the dose-response risk function, an Abbott-adjusted Weibull model and an Abbott-adjusted log-logistic model. Using the simultaneous construction, we derive methods for estimating upper confidence limits on predicted extra risk and, by inverting the upper bands on risk, lower bounds on the benchmark dose, or BMD, at which a specific level of 'benchmark risk' is attained. Monte Carlo evaluations explore the operating characteristics of the simultaneous limits.

Benchmark analysis for quantifying urban vulnerability to terrorist incidents

We describe a quantitative methodology to characterize the vulnerability of U.S. urban centers to terrorist attack, using a place-based vulnerability index and a database of terrorist incidents and related human casualties. Via generalized linear statistical models, we study the relationships between vulnerability and terrorist events, and find that our place-based vulnerability metric significantly describes both terrorist incidence and occurrence of human casualties from terrorist events in these urban centers. We also introduce benchmark analytic technologies from applications in toxicological risk assessment to this social risk/vulnerability paradigm, and use these to distinguish levels of high and low urban vulnerability to terrorism. It is seen that the benchmark approach translates quite flexibly from its biological roots to this social scientific archetype.

Assessment factors--applications in health risk assessment of chemicals

We review the scientific basis for default assessment factors used in risk assessment of nongenotoxic chemicals including the use of chemical- and pathways specific assessment factors, and extrapolation approaches relevant to species differences, age and gender. One main conclusion is that the conventionally used default factor of 100 does not cover all inter-species and inter-individual differences. We suggest that a species-specific default factor based on allometric scaling should be used for inter-species extrapolation (basal metabolic rate). Regarding toxicodynamic and remaining toxicokinetic differences we suggest that a percentile from a probabilistic distribution is chosen to derive the assessment factor. Based on the scarce information concerning the human-to-human variability it is more difficult to suggest a specific assessment factor. However, extra emphasis should be put on sensitive populations such as neonates and genetically sensitive subgroups, and also fetuses and children which may be particularly vulnerable during development and maturation. Factors that also need to be allowed for are possible gender differences in sensitivity, deficiencies in the databases, nature of the effect, duration of exposure, and route-to-route extrapolation. Since assessment factors are used to compensate for lack of knowledge we feel that it is prudent to adopt a "conservative" approach, erring on the side of protectiveness.

Comparing experimental designs for benchmark dose calculations for continuous endpoints

The BMD (benchmark dose) method that is used in risk assessment of chemical compounds was introduced by Crump (1984) and is based on dose-response modeling. To take uncertainty in the data and model fitting into account, the lower confidence bound of the BMD estimate (BMDL) is suggested to be used as a point of departure in health risk assessments. In this article, we study how to design optimum experiments for applying the BMD method for continuous data. We exemplify our approach by considering the class of Hill models. The main aim is to study whether an increased number of dose groups and at the same time a decreased number of animals in each dose group improves conditions for estimating the benchmark dose. Since Hill models are nonlinear, the optimum design depends on the values of the unknown parameters. That is why we consider Bayesian designs and assume that the parameter vector has a prior distribution. A natural design criterion is to minimize the expected variance of the BMD estimator. We present an example where we calculate the value of the design criterion for several designs and try to find out how the number of dose groups, the number of animals in the dose groups, and the choice of doses affects this value for different Hill curves. It follows from our calculations that to avoid the risk of unfavorable dose placements, it is good to use designs with more than four dose groups. We can also conclude that any additional information about the expected dose-response curve, e.g., information obtained from studies made in the past, should be taken into account when planning a study because it can improve the design.

Identifying soil cleanup criteria for dioxins in urban residential soils: how have 20 years of research and risk assessment experience affected the analysis?

This article reviews the scientific evidence and methodologies that have been used to assess the risks posed by 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) and presents a probabilistic analysis for identifying virtually safe concentrations of TCDD toxicity equivalents (TEQ) in residential soils. Updated data distributions that consider state-of-the-science cancer and noncancer toxicity criteria, child soil ingestion and dermal uptake, bioavailability in soil, and residential exposure duration are incorporated. The probabilistic analysis shows that the most sensitive determinants of dose and risk are childhood soil ingestion, exposure duration, and the selected TCDD cancer potency factor. It also shows that the cancer risk at 1 per 100,000 predicted more conservative (lower) soil criteria values than did the noncancer hazard (e.g., developmental and reproductive effects). In this analysis, acceptable or tolerable soil dioxin concentrations (TCDD TEQ) ranged from 0.4 to 5.5 ppb at the 95th percentile for cancer potency factors from 9600 to 156,000 (mg/kg/d)(-1) with site-specific adjustments not included. Various possible soil guidelines based on cancer and noncancer risks are presented and discussed. In the main, the current toxicology, epidemiology, and exposure assessment data indicate that the historical 1 ppb TEQ soil guidance value remains a reasonable screening value for most residential sites. This analysis provides risk managers with a thorough and transparent methodology, as well as a comprehensive information base, for making informed decisions about selecting soil cleanup values for PCDD/Fs in urban residential settings.

Identification of a Critical Dose Level for Risk Assessment: Developments in Benchmark Dose Analysis of Continuous Endpoints

The benchmark dose (BMD) method has been recommended to replace the no-observed-adverse-effect-level (NOAEL) approach in health risk assessment of chemical substances. In the present article, developments in BMD analysis from continuous experimental data are proposed. The suggested approach defines the BMD as the dose at which the slope of the S-shaped dose-response relationship changes the most in the low-dose region. This dose resides in a region where the sensitivity to chemical exposure may start to change noticeably. It is shown that the response (defined as a percent change relative to the magnitude, or size, of response) corresponding to the dose where the slope changes the most depends on the geometrical shape of the dose-response curve; the response becomes lower as the curve becomes more asymmetrical and threshold-like in the low-dose region. Given a symmetrical case, described by the Hill function, the response associated with the critical dose level becomes 21% (defined as a percent change relative to the magnitude, or size, of response). According to a limiting case of asymmetry and threshold-like characteristics, reflected by a Gompertz curve, the response corresponding to the dose of interest becomes as low as 7.3% (defined as a percent change relative to the magnitude, or size, of response). Use of a response in the range of 5-10% when estimating the BMD conservatively accounts for uncertainties associated with the proposed strategy, and may be appropriate in a risk assessment point of view. The present investigation also indicated that a BMD defined according to the suggested procedure may be estimated more precisely relative to BMDs defined under other approaches for continuous data.

Probabilistic risk characterization: An example with di(2-ethylhexyl) phthalate

While probabilistic methods gain attention in hazard characterization and are increasingly used in exposure assessment, full use of the available probabilistic information in risk characterization is still uncommon. Usually, after probabilistic hazard characterization and/or exposure assessment, percentiles from the obtained distributions are used as point estimates in risk characterization. In this way, all information on variability and uncertainty is lost, while these aspects are crucial in any risk assessment. In this paper, we present a method to integrate the entire distributions from probabilistic hazard characterization and exposure assessment into one risk characterization plot. This method is illustrated using di(2-ethylhexyl) phthalate as an example. The final result of this probabilistic risk assessment is summarized in a single plot, containing two pieces of information: the confidence we may have in concluding there is no risk, and the fraction of the population this conclusion applies to. This information leads to a better informed conclusion on the risk of a substance, and may be very useful to define the necessary measures for risk reduction.