Dose response assessment uncertainty

The qualitative and, wherever possible, quantitative description of the inherent properties of an agent or situation having the potential to cause adverse effects. This should, where possible, include a dose-response assessment and its attendant uncertainties. 

It is recognized that the NOAEL derived by using this traditional approach for dose-response assessment is not very accurate with respect to the degree to which it corresponds with the (unknown) tme NAEL. Furthermore, in this traditional approach, only the data obtained at one dose (NOAEL) are used in the hazard assessment rather than the complete dose-response data set. In case sufficient data are available, the shape of the dose-response curve should be taken into account in the hazard assessment. In the case of a steep dose-response curve, the derived NOAEL can be considered as more reliable because the greater the slope, the greater the reduction in response to reduced doses. In the case of a shallow dose-response curve, the uncertainty in the derived NOAEL may be higher and this has to be taken into account in the hazard assessment (see Section 5.7). If a LOAEL has to be used in the hazard assessment, then this value can only be considered reliable in the case of a very steep dose-response curve. 

Probabilistic methods can be applied in dose-response assessment when there is an understanding of the important parameters and their relationships, such as identification of the key determinants of human variation (e.g., metabolic polymorphisms, hormone levels, and cell replication rates), observation of the distributions of these variables, and valid models for combining these variables. With appropriate data and expert judgment, formal approaches to probabilistic risk assessment can be applied to provide insight into the overall extent and dominant sources of human variation and uncertainty. 

Risk characterization is the qualitative and/or quantitative estimation, including attendant uncertainties, of the severity and probability of known and potential adverse effects of a substance in a given population it is based on hazard identification, dose-response assessment and exposure assessment (OECD/IPCS, 2001), as described above. 

There are two possible approaches to estimating the human safe dose for chemicals that cause deterministic effects the use of safety and uncertainty factors and mathematical modeling. The former constitutes the traditional approach to dose-response assessment for chemicals that induce deterministic effects. Biologically-based mathematical modeling approaches that more realistically predict the responses to such chemicals, while newer and not used as widely, hold promise to provide better extrapolations of the dose-response relationship below the lowest dose tested. 

Although dose-response assessments for deterministic and stochastic effects are discussed separately in this Report, it should be appreciated that many of the concepts discussed in Section 3.2.1.2 for substances that cause deterministic effects apply to substances that cause stochastic effects as well. The processes of hazard identification, including identification of the critical response, and development of data on dose-response based on studies in humans or animals are common to both types of substances. Based on the dose-response data, a NOAEL or a LOAEL can be established based on the limited ability of any study to detect statistically significant increases in responses in exposed populations compared with controls, even though the dose-response relationship is assumed not to have a threshold. Because of the assumed form of the dose-response relationship, however, NOAEL or LOAEL is not normally used as a point of departure to establish safe levels of exposure to substances causing stochastic effects. This is in contrast to the common practice for substances causing deterministic effects of establishing safe levels of exposure, such as RfDs, based on NOAEL or LOAEL (or the benchmark dose) and the use of safety and uncertainty factors. 

UCL takes into account measurement uncertainty in the study used to estimate the dose-response relationship, such as the statistical uncertainty in the number of tumors at each administered dose, but it does not take into account other uncertainties, such as the relevance of animal data to humans. It is important to emphasize that UCL gives an indication of how well the model fits the data at the high doses where data are available, but it does not indicate how well the model reflects the true response at low doses. The reason for this is that the bounding procedure used is highly conservative. Use of UCL has become a routine practice in dose-response assessments for chemicals that cause stochastic effects even though a best estimate (MLE) also is available (Crump, 1996 Crump et al., 1976). Occasionally, EPA will use MLE of the dose-response relationship obtained from the model if human epidemiologic data, rather than animal data, are used to estimate risks at low doses. MLEs have been used nearly universally in estimating stochastic responses due to radiation exposure. 

Although rarely presented in a dose-response assessment, in nearly all cases the lower bound on the incremental probability of a response will be zero or less (see Figure 3.7). That is, the statistical model that accounts for the uncertainty in the results of an animal study also accommodates the possibility that no response may occur at low doses and that, in fact, there may be fewer responses (e.g., cancers) than observed in the control population at some low doses. The possibility of reduced responses at low doses also is shown by the lower confidence limit of data on radiation-induced cancers in some organs of humans including, for example, the pancreas, prostate, and kidney (Thompson et al., 1994). 

Uncertainties and Deficiencies in Dose-Response Assessment. Any approach to determining the dose-response relationship for hazardous chemicals involves many attendant uncertainties that limit its accuracy. In addition, many dose-response assessments suffer from deficiencies in the way they are conducted, which further decreases accuracy. These two aspects of dose-response assessment, which in some ways have led to adoption of such conservative approaches as large safety factors and UCLs in applying the results to health protection of the public, are discussed in the following two sections. 

Uncertainties in dose-response assessment. Several aspects of dose-response assessment result in significant uncertainties in the accuracy of the resulting relationship. 

Deficiencies in dose-response assessment. In addition to the sources of uncertainty in dose-response assessment described above, there are several important deficiencies in the way that the... 

For food allergens, validated animal models for dose-response assessment are not available and human studies (double-blind placebo-controlled food challenges [DBPCFCs]) are the standard way to establish thresholds. It is practically impossible to establish the real population thresholds this way. Such population threshold can be estimated, but this is associated with major statistical and other uncertainties of low dose-extrapolation and patient recruitment and selection. As a matter of fact, uncertainties are of such order of magnitude that a reliable estimate of population thresholds is currently not possible. The result of the dose-response assessment can also be described as a threshold distribution rather than a single population threshold. Such distribution can effectively be used in probabilistic modeling as a tool in quantitative risk assessment (see Section 15.2.5)... 

Health organizations throughout the world utilize a safe dose concept in the dose-response assessment of noncancer toxicity. This safe dose has often been referred to by different names, such as acceptable daily intake (ADI), tolerable daily intake (TDI) or tolerable concentration (TC), minimal risk level (MRL), reference dose (RfD), and reference concentration (RfC). The approaches used by various health organizations share many of the same underlying assumptions, judgments on critical effect, and choices of uncertainty (or safety) factors. 

During the risk characterization step, most often risk for a hypothetical sensitive subgroup is reported historically, no average or central tendency and population risks have been estimated, although recent work also includes such values. Furthermore, risk or hazard from individual chemicals is often added to produce aggregate risk or hazard. These biases provide potential sources of uncertainty during this phase of the risk assessment process. In part because of these biases, new methods for conducting dose-response assessment have been developed, as discussed in the next section. 

Benchmark Dose (BMD) modeling is an alternative method to the NOAEL/ LOAEL approach (Cmmp, 1984 Dourson et al., 1985 Barnes et al., 1995 U.S. EPA, 2000a). The method fits flexible mathematical models to the dose-response data and then determines the dose associated with a specified incidence of the adverse effects. Once this dose is estimated, then an RfD is estimated with the use of one or more uncertainty factors or Chemical Specific Adjustment Factors (CSAF) as described above. Advantages over the NOAEL/LOAEL approach include (1) the BMD is not limited to the tested doses (2) a BMD can be calculated even when the study does not identify a NOAEL and (3) unlike the NOAEL approach, the BMD approach accounts for the statistical power of the study. Numerous examples of BMD use in the dose-response assessment part of the risk assessment process are available on the U.S. EPA s Integrated Risk Information System (IRIS) (2004b). 

As shown previously, PBPK models allow the conversion of potential dose or exposure concentration to tissue dose, which can then be used for risk characterization purposes. The choice of an internal dose metric is based principally on an understanding of the mode of action of the chemical species of concern. The internal dose metric (sometimes called the biologically effective dose) is often used in place of the applied dose in quantitative dose-response assessments, in order to reduce the uncertainty inherent in using the applied dose to derive risk values. 

An evaluation of human health hazards posed by dioxin-contaminated soil in certain areas of Missouri illustrates specific uncertainties in dioxin risk assessment. These uncertainties include the relationship of studies in animals to effects in humans, the level and extent of contamination in the soil, the level of exposure to humans, and the character of the dose-response curve. Uncertainties in assessing risks posed by toxic substances in general are viewed from the standpoint of a 1985 report prepared by the Task Force on Risk Assessment and Risk Management for the Secretary, Department of Health and Human Services. The Task Force listed nine commonly used assumptions—which may also be called uncertainties. 

What are some of the uncertainties with dose response assessments ... 

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