Review of EPA's Integrated Risk Information System (IRIS) Process (2014) / Chapter Skim
Currently Skimming:
7 Derivation of Toxicity Values
7 Derivation of Toxicity Values
Pages 110-134
The Chapter Skim interface presents what we've algorithmically identified as the most significant single chunk of text within every page in the chapter.
Select key terms on the right to highlight them within pages of the chapter.
From page 110... ...
The next phase in an IRIS assessment is to quantify the hazards through the computation of toxicity values -- reference doses (RfDs) , reference concentrations (RfCs)
|
From page 111... ...
A POD is used as the starting point for later extrapolations and analyses. Unit risk or slope factor The increase in the probability of cancer incidence or related risk per unit dose exposure as determined from a POD (effective dose or its lower confidence limit)
|
From page 112... ...
Uncertainty Integration Evaluate studies, end points, or datasets for dose-response assessment Derive appropriate POD Data adequate for modeling: BMD Inadequate data: NOAEL or LOAEL Apply uncertainty factors Derive toxicity values FIGURE 7-2 Derivation of toxicity values. Data integration and uncertainty analysis must be considered in the process.
|
From page 113... ...
In particular, the committee focused on EPA's response to the major issues noted in the formaldehyde report, which included the need to establish clear guidelines for study selection and to describe, justify, and assess the assumptions and models used in deriving toxicity values. EPA has made a number of responsive changes in the IRIS program since the publication of the NRC formaldehyde report, including (a)
|
From page 114... ...
-- to assess the changes that EPA has made regarding this and related recommendations in the NRC formaldehyde report. The detailed presentation of dose-response modeling output and derivation of toxicity values is helpful.
|
From page 115... ...
can be fitted to a given dataset and how to use statistical criteria to select a best model and later a toxicity value. Although that approach might remain acceptable under some circumstances, the NRC formaldehyde committee encouraged EPA to move away from that old paradigm and to develop approaches for integrating multiple toxicity values rather than selecting one value or study that appears to be the "best." Example 6 also shows how EPA uses goodness-of-fit or information criteria in conjunction with the spread of the lower confidence limits on the BMD (BMDLs)
|
From page 116... ...
Thus, multiple criteria should be used simultaneously, and all details regarding assumptions and justifications of dose-response modeling should be included in the IRIS assessments. It should be noted that most of the dose-response models implemented in EPA's BMD software do not accommodate for adjustment for covariates that are independent risk factors or confounders, whereas most epidemiologic studies adjust for multiple covariates.
|
From page 117... ...
Provide Adequate Documentation for Conclusions and Estimation of Toxicity Values Recent EPA IRIS assessments have included extensive detail on published studies, evaluation of the evidence base regarding toxicity, and pharmacokinetic and dose-response modeling. Elements in dose-response analysis for which additional documentation is needed include the decision processes used by EPA to select studies for derivation of an RfC, RfD, or unit risk; the process used to select a particular value for the RfC, RfD, or unit risk from a range of values determined by using separate studies; and the process used to select a response level (typically 1, 5, or 10%)
|
From page 118... ...
However, the process that EPA uses to select the final values is still not sufficiently transparent and appears somewhat subjective, and documentation varies among draft IRIS assessments. Formal statistical methods are widely available for combining estimates from multiple studies and might be useful for this step in the IRIS process.
|
From page 119... ...
addresses that issue in two sections: "Considerations for Combining Data for Dose-Response Modeling" and "Considerations for Selecting Organ/System-Specific or Overall Toxicity Values." The first section describes criteria for pooling data at the individual level, and the second section indicates that either using a single study or combining aggregate estimates from different studies to produce a composite toxicity value might be acceptable if the methods are documented. In the first section, on pooled data analysis, EPA includes the following reasons for not combining data sets: heterogeneity in datasets because of differences in laboratory procedures, subject demographics, or route of exposure; and biologic or study-design limitations.
|
From page 120... ...
FIGURE 7-3 Simple Bayesian framework for estimating human toxicity from results of an animal study. TABLE 7-2 Conversion of Traditional EPA Uncertainty Factors to Bayesian Prior Standard Deviations on a Natural Log Scale Using 1-Sided or 2-Sided Confidence Intervals 95% One-Sided 97.5% One-Sided 99.5% One-Sided Uncertainty Factor 90% Two-Sided 95% Two-Sided 99% Two-Sided 3 0.668 0.561 0.427 5 0.978 0.821 0.625 10 1.400 1.175 0.894 100 2.800 2.350 1.788 300 3.468 2.910 2.214 1,000 4.200 3.524 2.682
|
From page 121... ...
For example, rat and mouse studies that used different strains might be considered exchangeable with each other for the purpose of estimating human-toxicity values but deemed more relevant than the in vitro and nonmammalian studies; a separate meta-analysis of humanequivalent dose-response estimates would then be determined for the rodent studies. Finally, epidemiologic studies with sufficient exposure characterization and adequate confounding control (if any such studies are available)
|
From page 122... ...
) /1.96 = 0.184, assuming that the LED10 is the lower bound of the twosided 95% confidence interval, and the induced prior standard deviation for the ln(ED10)
|
From page 123... ...
In this example, the Bayesian lower bound ED10 is slightly higher than the traditional RfD based on the human study alone because the animal and high-throughput studies suggest that the chemical is less toxic than the human study suggests and because standard error is smaller in the posterior distribution. In situations in which the central estimate of the ED10 is lower for the animal studies than for the human studies, the Bayesian lower bound could be less than the traditional RfD that is based on the human studies alone.
|
From page 124... ...
Analysis and Communication of Uncertainty As discussed earlier, estimation of toxicity values is the culminating step of the IRIS process. The reference values and unit risks draw on data from heterogeneous and dynamic systems that underpin hazard identification, exposure assessment (for epidemiologic studies)
|
From page 125... ...
Omission of one source of uncertainty in a given stage can result in an inaccurate or even distorted characterization of the overall uncertainty. Although it is critical for understanding the uncertainties and their overall effect on a final toxicity estimate, such a vertical integration of uncertainties is rarely done in IRIS assessments (NRC 2009, pp.100-101)
|
From page 126... ...
Grouping the toxicity estimates appropriately requires that the systems underpinning the individual toxicity values be comparable or homogeneous regarding such elements as study design, exposure regimen, and health effects. For example, when health end points are plausible for a common mechanism, there is good support for using the variation range of the corresponding toxicity values as the horizontal integration of the overarching uncertainty (NRC 2011)
|
From page 127... ...
are examples of approaches that support vertical integration of multistage uncertainties. An improved uncertainty analysis within an individual IRIS assessment does not necessarily dictate a complex level of sophistication in mathematical, statistical, or computational methods.
|
From page 128... ...
The guidelines should also establish an inventory of standard methods for uncertainty analysis according to the stage of an assessment and the nature or source of the uncertainty and should offer insights into method choice (van der Sluijs et al.
|
From page 129... ...
Good planning and documentation of uncertainty analysis facilitate better communication and will probably improve stakeholders' confidence in the IRIS process. FINDINGS AND RECOMMENDATIONS Finding: EPA develops toxicity values for health effects for which there is "credible evidence of hazard" after chemical exposure and of an adverse outcome.
|
From page 130... ...
Finding: Advanced analytic methods, such as Bayesian methods, for integrating data for doseresponse assessments and deriving toxicity estimates are underused by the IRIS program. Recommendation: As the IRIS program evolves, EPA should develop and expand its use of Bayesian or other formal quantitative methods in data integration for dose-response assessment and derivation of toxicity values.
|
From page 131... ...
Materials Submitted to the National Research Council, by Integrated Risk Information System Program, U.S. Environmental Protection Agency, January 30, 2013 [online]
|
From page 132... ...
Petersen, J.P. van der Sluijs, J.S.
|
From page 133... ...
EPA's Integrated Risk Information System (IRIS)
|
From page 134... ...
van der Sluijs, M.B.A. van Asselt, P
|
Key Terms
This material may be derived from roughly machine-read images, and so is provided only to facilitate research.
More
information on Chapter Skim is available.