Quantitative risk assessment, effect

Exposure assessment, step three, allows a risk assessor to estimate the significance of the effects induced by high doses of a chemical in experimental animals in a human situation. Exposure assessment is, in fact, a prerequisite for quantitative risk assessment because it allows a comparison between effects induced by high dose with those induced by low doses, and also allows... 

Evaluating risk to process plant building occupants can be accomplished through detailed qualitative and/or quantitative risk assessment. However, because of the large numbers of buildings and varying plant situations involved, these types of studies could be costly and time-consuming if applied in all cases, and should be reserved for those situations for which cost-effective solutions cannot otherwise be identified. 

The purpose of this chapter is not to discuss the merits, or lack thereof, of using plasma cholinesterase inhibition as an adverse effect in quantitative risk assessments for chlorpyrifos or other organophosphate pesticides. A number of regulatory agencies consider the inhibition of plasma cholinesterase to be an indicator of exposure, not of toxicity. The U.S. Environmental Protection Agency, at this point, continues to use this effect as the basis for calculating the reference doses for chlorpyrifos, and it is thus used here for assessing risks. 

The dangerous properties of acute toxicity, irritation, corrosivity, sensitisation, repeated-dose toxicity and CMR are evaluated in terms of their potential toxic effects to workers, consumers and man exposed indirectly via the environment, based on the use for each stage in the lifecycle of the substance from which exposure can occur. Risk assessment is also required if there are reasonable grounds for concern for potential hazardous properties, e.g., from positive in vitro mutagenicity tests or structural alerts. The risk assessment involves comparing the estimated occupational or consumer exposure levels with the exposure levels at which no adverse effects are anticipated. This may be a quantitative risk assessment, based on the ratio between the two values, or a qualitative evaluation. The principles of human health risk assessment are covered in detail by Illing (a.30) and more briefly in Chapter 7 of (73). 

In this paper I have tried to show that measurement of health benefits attributable to TSCA is not feasible. I hope that in doing so I have not belabored the obvious. For new chemicals and for most existing chemicals, prospective evaluation of health benefits to be achieved by various exposure controls will have to be based on extrapolation from microbial and animal data. However, while such extrapolation may be useful in a qualitative sense, quantitative risk assessment techniques involve considerable uncertainty, and in any case have not been developed for chronic effects other than cancer. 

Gronlund (1992) has investigated methods used for quantitative risk assessment of non-genotoxic substances, with special regard to the selection of assessment factors. Gronlund found that humans, in most cases, seem to be more sensitive to the toxic effects of chemicals than experimental animals, and that the traditional 10-fold factor for interspecies differences apparently is too small in order to cover the real variation. It was also noted that a general interspecies factor to cover all types of chemicals and all types of experimental animals cannot be expected. It was concluded that a 10-fold factor for interspecies variability probably protects a majority, but not all of the population, provided that the dose correction for differences in body size between experimental animals and humans is performed by the body surface area approach (Section 5.3.2.2). If the dose correction is based on the body weight approach (Section 5.3.2.1), the 10-fold factor was considered to be too small in most cases. 

The most widely used of the many mathematical models proposed for extrapolation of carcinogenicity data from animal studies to low-dose human exposures (i.e., low-dose extrapolation) is the LMS model. This has, in effect, become the default approach for quantitative risk assessment and has been used by, e.g., the US-EPA for many years as well as by the WHO in relation to derivation of drinking-water guideline values for potential carcinogens (WHO 1996) (see Section 9.2.1.2 for drinking-water guideline values). 

Nesnow S. 1994. Mechanistic linkage between DNA adducts, mutations in oncogenes, and tumorigenicity of carcinogenic aromatic hydrocarbons in strain A/J mice. In Chemical mixtures and quantitative risk assessment. Abstract of the second annual HERL symposium, Nov. 7-10., Raleigh, North Carolina Health Effects Research Laboratory, U.S. Environmental Protection Agency. 

Results of a probabilistic risk assessment indicate that neither occupational exposure nor environmental exposure to atrazine and simazine is likely to produce adverse health consequences in the US population. This conclusion is based on a quantitative risk assessment that potential human exposure to atrazine and simazine is much smaller than the intakes required to produce adverse health effects in animal experiments. 

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)... 

Because the literature describes several limitations in the use of NOAELs (Gaylor 1983 Crump 1984 Kimmel and Gaylor 1988), the evaluative process considers other methods for expressing quantitative dose-response evaluations. In particular, the BMD approach originally proposed by Crump (1984) is used to model data in the observed range. That approach was recently endorsed for use in quantitative risk assessment for developmental toxicity and other noncancer health effects (Barnes et al. 1995). The BMD can be useful for interpreting dose-response relationships because it accounts for all the data and, unlike the determination of the NOAEL or LOAEL, is not limited to the doses used in the experiment. The BMD approach is especially helpful when a NOAEL is not available because it makes the use of a default uncertainty factor for LOAEL to NOAEL extrapolation unnecessary. 

A different approach, called a quantitative risk assessment, is used for nonthreshold effects, such as cancer. Sophisticated statistical models are used to extrapolate the experimental animal data obtained at high doses to the low exposures predicted in humans. The linearized multistage (LMS) model is frequently... 

U.S. EPA (U.S. Environmental Protection Agency). 1991b. General Quantitative Risk Assessment Guidelines for Noncancer Health Effects. 

A primary directive of CERCLA is the protection of public health. Because the hazards that exist at Superfund sites tend to be quite variable, it has not been possible to establish specific cleanup criteria for the hazardous substances regulated under CERCLA potential human health effects must be evaluated by quantitative risk assessment on a site-by-site basis. Each Superfund site is assessed individually to determine how clean is clean. The rationale is that the hazard of a contaminant is a function of its potential to reach a receptor (e.g., groundwater, population) and the potential harm to the exposed receptor. The ability of a contaminant to migrate, its potential to degrade, and its distance to a receptor of concern (i.e., the risk), all are site-specific. Only on the basis of such individualized risk assessment is it possible to achieve efficient and cost-effective cleanup of the thousands of hazardous waste sites throughout the US. 

EPA recommends three approaches (1) if the toxicity data on mixture of concern are available, the quantitative risk assessment is done directly form these preferred data (2) when toxicity data are not available for the mixture of concern, data of a sufficiently similar mixture can be used to derive quantitative risk assessment for mixture of concern and (3) if the data are not available for both mixture of concern and the similar mixture, mixture effects can be evaluated from the toxicity data of components. According to EPA, the dose-additive models reasonably predict the systemic toxicity of mixtures composed of similar (dose addition) and dissimilar (response addition) compounds. Therefore, the potential health risk of a mixture can be estimated using a hazard index (HI) derived by summation of the ratios of the actual human exposure level to estimated maximum acceptable level of each toxicant. A HI near to unity is suggestive of concern for public health. This approach will hold true for the mixtures that do not deviate from additivity and do not consider the mode of action of chemicals. Modifications of the standard HI approach are being developed to take account of the data on interactions. 

Can Science Effectively Predict Risks Through Quantitative Risk Assessments - A Policy Perspective. Over the years, scientists have gained a great deal of experience, through the conduct of risk assessments, in how to perform each step in the risk assessment more efficiently and accurately. Improvements to risk assessment have been identified, significantly advancing the usefulness of risk assessment. 

As no adverse effects associated with vitamin K consumption from food or supplements have been reported in humans or animals, the U.S. Institute of Medicine has reported that a quantitative risk assessment cannot be performed, and thus a UL cannot be derived for vitamin... 

As there are no reports of adverse effects from consumption of excess thiamine from food and supplements (supplements of 50 mg/day are widely available without prescription), and the data are inadequate for a quantitative risk assessment, no UL has been defined for thiamine. However, as stimulators of transketolase enzyme synthesis such as thiamine support a high rate of nucleic acid ribose synthesis necessary for tumor cell survival, chemotherapy resistance, and proliferation, some concern has been expressed that thiamine supplementation of common food products may contribute to increased cancer rates in the Western world. There is, however, littie evidence to support this assumption. Rarely, individuals given high-dose intravenous thiamine in treatment of beriberi have developed anaphylaxis, the frequency being about 1 100,000. 

A systems hazards analysis (SHA) is a systematic and comprehensive search for and evaluation of all significant failure modes of facility systems components that can be identified by an experienced team. The hazards assessment often includes failure modes and effects analysis, fault tree analysis, event tree analysis, and hazards and operability studies. Generally, the SHA does not include external factors (e.g., natural disasters) or an integrated assessment of systems interactions. However, the tools of SHA are valuable for examining the causes and the effects of chemical events. They provide the basis for the integrated analysis known as quantitative risk assessment. For an example SHA see the TOCDF Functional Analysis Workbook (U.S. Army, 1993-1995). 

The initial step in using key events in an MOA framework is a quahtative one, as described in Table 13.2, namely to match the key events for a particular chemical with those for a particular MOA (DNA-reactivity in Table 13.2). However, it is also possible to utilize key events to develop informative biomarkCTs of exposure and effect as well as bioindicators of disease outcome that can be utilized in a quantitative risk assessment process. 

Bukowski, J., Korn, L. R., and Wartenberg, D. (1995). Correlated inputs in quantitative risk assessment The effects of distributional shape. Risk Anal 15, 215-219. 

Quantitative risk assessment for noncancer effects is commonly based... 

Model choice is an important sonrce of nncertainty for the purpose of quantitative risk assessment. Changing the underlying modeling assumptions can have a dramatic effect on the estimated benchmark dose. The committee snggests that the K-power (K > 1) model results be used. 

Quantitative risk assessment depends on data that are reliable, sensitive and quantitative. It may well be that the numerical extrapolation from the current small scale (but manageable) laboratory tests can be substantially improved and moved downward to the effects of lower dose levels through the shrewd use of these isolated cell and biochemical test systems where the interplay of inactivation, activation and target molecule injury can be studied at concentrations well below those possible where one is looking at endpoints in relatively small groups of whole animals. 

Quantitative risk assessment requires extrapolation from results of experimental assays conducted at high dose levels to predicted effects at lower dose levels which correspond to human exposures. The meaning of this high to low dose extrapolation within an animal species will be discussed, along with its inherent limitations. A number of commonly used mathematical models of dose-response necessary for this extrapolation, will be discussed. Other limitations in their ability to provide precise quantitative low dose risk estimates will also be discussed. These include the existence of thresholds incorporation of background, or spontaneous responses modification of the dose-response by pharmacokinetic processes. 

In my mind, the problem of performing quantitative risk assessment translates to the problem of building good quantitative descriptions or models of the effects and exposure processes Involved In the particular risk problem of Interest. While very Important In the policy process of risk management, the human perception and valuation processes Illustrated on the right hand side of Figure 1 are not part of quantitative risk assessments as It Is usually defined and practiced. 

Of course, quantitative risk assessment is still necessary, even when ecological models are used, but in addition to specific, absolute quantifications, a main area of ecological models could be relative risk assessments Which application scheme is more efficient in terms of interest, for example, control efficiency, effects on nontarget organisms, and costs ... 

Extrapolating Rodent Cancer Test Results to Humans. It is prudent to assume that if a chemical is a carcinogen in rats and mice at the maximum tolerated dose (MTD), it is also likely to be a carcinogen in humans the MTD. However, until we understand more about mechanisms, we cannot reliably predict risk to humans at low doses, often hundreds of thousands of times below the dose where an effect is observed in rodents. Thus, quantitative risk assessment is currently not scientifically possible (1.17,20). 

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