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.

Cancer risk assessment, indicators, and guidelines for polycyclic aromatic hydrocarbons in the ambient air.

Polycyclic aromatic hydrocarbons (PAHs) are formed during incomplete combustion. Domestic wood burning and road traffic are the major sources of PAHs in Sweden. In Stockholm, the sum of 14 different PAHs is 100-200 ng/m(3) at the street-level site, the most abundant being phenanthrene. Benzo[a]pyrene (B[a]P) varies between 1 and 2 ng/m(3). Exposure to PAH-containing substances increases the risk of cancer in humans. The carcinogenicity of PAHs is associated with the complexity of the molecule, i.e., increasing number of benzenoid rings, and with metabolic activation to reactive diol epoxide intermediates and their subsequent covalent binding to critical targets in DNA. B[a]P is the main indicator of carcinogenic PAHs. Fluoranthene is an important volatile PAH because it occurs at high concentrations in ambient air and because it is an experimental carcinogen in certain test systems. Thus, fluoranthene is suggested as a complementary indicator to B[a]P. The most carcinogenic PAH identified, dibenzo[a,l]pyrene, is also suggested as an indicator, although it occurs at very low concentrations. Quantitative cancer risk estimates of PAHs as air pollutants are very uncertain because of the lack of useful, good-quality data. According to the World Health Organization Air Quality Guidelines for Europe, the unit risk is 9 X 10(-5) per ng/m(3) of B[a]P as indicator of the total PAH content, namely, lifetime exposure to 0.1 ng/m(3) would theoretically lead to one extra cancer case in 100,000 exposed individuals. This concentration of 0.1 ng/m(3) of B[a]P is suggested as a health-based guideline. Because the carcinogenic potency of fluoranthene has been estimated to be approximately 20 times less than that of B[a]P, a tentative guideline value of 2 ng/m(3) is suggested for fluoranthene. Other significant PAHs are phenanthrene, methylated phenanthrenes/anthracenes and pyrene (high air concentrations), and large-molecule PAHs such as dibenz[a,h]anthracene, benzo[b]fluoranthene, benzo[k]fluoranthene, and indeno[1,2,3-cd]pyrene (high carcinogenicity). Additional source-specific indicators are benzo[ghi]perylene for gasoline vehicles, retene for wood combustion, and dibenzothiophene and benzonaphthothiophene for sulfur-containing fuels.

Dose-response modeling and benchmark calculations from spontaneous behavior data on mice neonatally exposed to 2,2',4,4',5-pentabromodiphenyl ether.

In this paper the benchmark dose (BMD) method was introduced for spontaneous behavior data observed in 2-, 5-, and 8-month-old male and female C57Bl mice exposed orally on postnatal day 10 to different doses of 2,2',4,4',5-pentabromodiphenyl ether (PBDE 99). Spontaneous behavior (locomotion, rearing, and total activity) was in the present work quantified in terms of a fractional response defined as the cumulative response after 20 min divided by the cumulative response produced over the whole 1-h test period. The fractional response contains information about the time-response profile (which differs between the treatment groups) and has appropriate statistical characteristics. In the analysis, male and female mice could be characterized by a common dose-response model (i.e., they responded equally to the exposure to PBDE 99). As a primary approach, the BMD was defined as the dose producing a 5 or 10% change in the mean fractional response. According to the Hill model, considering a 10% change the lower bound of the BMD for rearing, locomotion, and total activity was 1.2, 0.85, and 0.31 mg PBDE 99/kg body weight, respectively. A probability-based procedure for BMD modeling was also considered. Using this methodology, the BMD was defined as corresponding to an excess risk of 5 or 10% of falling below cutoff points representing adverse levels of fractional response.

The current state of knowledge on the use of the benchmark dose concept in risk assessment.

This review deals with the current state of knowledge on the use of the benchmark dose (BMD) concept in health risk assessment of chemicals. The BMD method is an alternative to the traditional no-observed-adverse-effect level (NOAEL) and has been presented as a methodological improvement in the field of risk assessment. The BMD method has mostly been employed in the USA but is presently given higher attention also in Europe. The review presents a number of arguments in favor of the BMD, relative to the NOAEL. In addition, it gives a detailed overview of the several procedures that have been suggested and applied for BMD analysis, for quantal as well as continuous data. For quantal data the BMD is generally defined as corresponding to an additional or extra risk of 5% or 10%. For continuous endpoints it is suggested that the BMD is defined as corresponding to a percentage change in response relative to background or relative to the dynamic range of response. Under such definitions, a 5% or 10% change can be considered as default. Besides how to define the BMD and its lower bound, the BMDL, the question of how to select the dose-response model to be used in the BMD and BMDL determination is highlighted. Issues of study design and comparison of dose-response curves and BMDs are also covered.

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.

Comparison of available benchmark dose softwares and models using trichloroethylene as a model substance.

By using trichloroethylene as a model substance the U.S. EPA benchmark dose software was compared to the software by Crump and the software by Kalliomaa. Dose-response and dose-effect data on the liver, kidneys, central nervous system (CNS), and tumours were selected for the evaluation. Based on the present study the U.S. EPA software is preferable to the other softwares for dichotomous data. A wider range in benchmark doses was often observed for dichotomous data when the numbers of dose levels were limited. The log-logistic model in most cases gave the best fit when ranking the dichotomous models. In addition, the log-logistic model often implied a more conservative benchmark dose. For continuous data it was more difficult to find a model describing the data. The softwares by Kalliomaa and by the U.S. EPA offered the best opportunities for benchmark dose modelling of continuous data. Flexible models, like the Hill- and the Mult model, are needed for S-shaped continuous data but these models demand more dose levels in order to describe the data. Since the number of dose levels are important for model selection study design is important and should be further evaluated.

Evaluation of the benchmark dose method for dichotomous data: model dependence and model selection.

The benchmark dose (BMD) method was evaluated using the USEPA BMD software. Dose-response data on cleft palate and hydronephrosis for a number of related polyhalogenated aromatic compounds were obtained from the literature. According to chi(2) test statistics, each dichotomous USEPA model failed to adequately describe only 1 of 12 cleft palate data sets. For hydronephrosis, the models were discriminated to a higher extent according to global goodness-of-fit. NOAELs for cleft palate corresponded to BMDLs (the approximate lower confidence limit on the BMD) for extra risks in the range of 5% or below. Model dependence of the BMDL estimate was more pronounced at lower levels of benchmark response (BMR). A BMR of 5% (extra risk) is recommended for cleft palate since model differences at this level were limited for all data. In addition, at BMRs of 5-10% the BMDL for all models was little affected by the specified confidence limit size (in the 90-99% range). For BMDL determination a conservative model selection approach was applied. At the suggested level of BMR (5%) this procedure resulted in use of the same model (multistage model) for the cleft palate endpoint in general. Akaike's information criterion (AIC) was considered for comparison between models. Determination of appropriateness of use of such methods in dose-response applications requires further analysis.

The benchmark dose method--review of available models, and recommendations for application in health risk assessment.

The benchmark dose method has been proposed as an alternative to the no-observed-adverse-effect level (NOAEL) approach for assessing noncancer risks associated with hazardous compounds. The benchmark dose method is a more powerful statistical tool than the traditional NOAEL approach and represents a step in the right direction for a more accurate risk assessment. The benchmark dose method involves fitting a mathematical model to all the dose-response data within a study, and thus more biological information is incorporated in the resulting estimates of guidance values (e.g., acceptable daily intakes, ADIs). Although there is an increasing interest in the benchmark dose approach, it has not yet found its way into the regulatory toxicology in Europe, while in the United States the U.S. Environmental Protection Agency (EPA) already uses the benchmark dose in health risk assessment. Several software packages are today available for benchmark dose calculations. The availability of software to facilitate the analysis can make modeling appear simple, but often the interpretation of the results is not trivial, and it is recommended that benchmark dose modeling be performed in collaboration with a toxicologist and someone familiar with this type of statistical analysis. The procedure does not replace expert judgments of toxicologists and others addressing the hazard characterization issues in risk assessment. The aim of this article is to make risk assessors familiar with the concept, to show how the method can be used, and to describe some possibilities, limitations, and extensions of the benchmark dose approach. In this article the benchmark dose approach is presented in detail and compared to the traditional NOAEL approach. Statistical methods essential for the benchmark dose method are presented in Appendix A, and different mathematical models used in the U.S. EPA's BMD software, the Crump software, and the Kalliomaa software are described in the text and in Appendix B. For replacement of NOAEL in health risk assessment it is considered important that consensus is reached on the crucial parts of the benchmark dose method, that is, selection of risk types and the determination of a response level corresponding to the BMD, especially for continuous data. It is suggested that the BMD method is used as a first choice and that in cases where it is not possible to fit a model to the data the traditional NOAEL approach should be used instead. The possibilities to make benchmark dose calculations on continuous data need to be further investigated. In addition, it is of importance to study whether it would be appropriate to increase the number of dose levels by decreasing the number of animals in each dose group.