BENCHMARK DOSE EVALUATIONS
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BENCHMARK DOSE EVALUATIONS FOR ACUTE INHALATION EXPOSURES TO HUMAN TOXICANTS. G. V. Alexeeff, K. K. Deng, R. L. Broadwin, A. G. Salmon Office of Environmental Health Hazard Assessment, California Environmental Protection Agency, Oakland, CA. Purpose.

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BENCHMARK DOSE EVALUATIONS

FOR

ACUTE INHALATION EXPOSURES

TO HUMAN TOXICANTS

G. V. Alexeeff, K. K. Deng, R. L. Broadwin, A. G. Salmon

Office of Environmental Health Hazard Assessment, California Environmental Protection Agency, Oakland, CA


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Purpose

To evaluate the application of the USEPA benchmark dose (BMD) methodology to acute inhalation exposure risk assessment using human data.

  • To refine BMD methodology.

  • To inform the standard method: no observed adverse effect level (NOAEL) divided by uncertainty factor (UF)s


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Background

  • Approaches to describe human risks and/or reference levels from acute inhalation exposures have been developed by:

    • American Conference of Governmental Industrial Hygienists Inc. (ACGIH) short-term exposure limits (STELs) and Ceiling values (ACGIH Worldwide, 2006).

    • National Research Council /USEPA acute emergency guidance levels (AEGLs) (NRC, 2000).

    • USEPA acute reference exposures (Strickland et al., 2002).

    • California acute reference exposure levels (Collins et al., 2004).


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Background (cont.)

  • Traditional NOAEL or LOAEL approach

    • empirically analyzes effects at discrete concentrations

    • does not infer about the exposure group response rates.

    • Usually is described as follows (Collins et al., 2004):

      Reference value = NOAEL (or LOAEL) / (UFA x UFH x UFother)

      • LOAEL refers to lowest observed adverse effect level

      • UF refers to uncertainty factor and may or may not be explicit

    • Remains the predominant methodology due to data available.


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Background (cont.)

  • BMD methodology is generally seen as an improvement of the NOAEL/LOAEL approach since:

    • reflects the shape of the dose-response curve

    • is not an artifact of the choice of experimental concentration.

    • takes into account some variability in the test population.

      • e.g., the choice of a 95% lower confidence limit (LCL).

    • increases the minimum quality of an acceptable study.


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Background (cont.)

  • BMD methodology

    • considers data consistency over a range of exposures

    • estimates a concentration at a defined response level

    • provides an estimate of toxicological response that could replace the NOAEL as the point of departure (POD) in health risk assessments.

    • described as follows (Collins et al., 2004):

      Reference value = POD/ (UFA x UFH x UFother)

      • POD (point of departure) could be BMD, NOAEL, or LOAEL

      • UF refers to uncertainty factor and may or may not be explicit


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Background (cont.)

  • BMD methodology requires the user to input the desired response rate. Usually the response rate chosen is 1, 5 or 10 %.

  • In 1999 we published a paper evaluating 100 acute inhalation lethality datasets using a BMD approach (Fowles et al.). From this analysis we decided on some preferred approaches for use in BMD evaluation.

    • Use of the probit model

    • Use of a 5% response rate

    • Equate the 5% response rate with the NOAEL

  • While we may deviate from these approaches, they generally represent our starting point.


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Background (cont.)

  • Caveat:

    • The Fowles et al. analysis is based on acute inhalation animal lethality evaluations.

    • There is little acute inhalation exposure information regarding

      • human endpoints or

      • non-lethal animal endpoints

  • The USEPA BMD software has a wide range of models to consider.

  • We considered whether other models may be superior to the probit model for a default approach.


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Approach

  • Literature search of all hazardous air pollutants to identify data sets reporting

    • mild acute effects (Alexeeff et al., 2002)

    • NOAEL

    • LOAEL

    • sufficient information to conduct a BMD analysis

  • Relevant NOAEL and LOAEL information was identified for 70 chemicals.


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Table 1. Studies Identified from the Literature Search for Evaluation

*Other refers to animal studies consisting of: baboon (N= 2), dog (N= 4), guinea pig (N= 19),

hamster (N= 4), monkey (N= 1), prairie dog (N=2), and rabbit (N= 6), and rock dove (N=1).


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Table 2. Studies Identified Sorted by Endpoint Category Evaluation

*Other refers to ratios based on endpoints of: cardiovascular (N= 4), hematologic (N=18), immune (N= 12), and reproductive (N=1).

Total N> 279 because some studies showed multiple effects.


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Human Studies Identified Evaluation

  • 60 human studies contained data which met the criteria of mild acute effects and reported NOAEL and LOAEL values.

    • 15 studies reported multiple doses.

  • For this BMD analysis, we focused on those studies based on dichotomous (quantal or effect/no effect) responses.

  • Eight data sets, for seven chemicals, met the additional criteria: dichotomous with at least three dose levels for BMD analysis.



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Data Analysis Identified

  • We analyzed and compared each data set using seven different BMD models for dichotomous data:

    • Probit

    • Quantal linear

    • Multistage

    • Weibull

    • Logistic

    • Quantal quadratic

    • Gamma


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Data Analysis (cont.) Identified

  • For each data set, comparisons among the BMDL and BMD values made at 1%, 5%, and 10% response rates are shown on the following slides.




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Table 4. Comparing BMD Response Rate01(Top Line) and BMDL01(Bottom Line) for Various BMD Models


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Table 4a. Comparing BMD Response Rate01 (Top Line) and BMDL01 (Bottom Line) for Various BMD Models


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Table 5. Comparing BMD Response Rate05(Top Line) and BMDL05(Bottom Line) for Various BMD Models


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Table 6. Comparing BMD Response Rate10(Top Line) and BMDL10(Bottom Line) for Various BMD Models


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Reviewing Model Results Response Rate

  • Data analyses via Weibull and Gamma dichotomous models were eliminated due to calculation failure for one or more chemicals.

  • For each data set, we considered whether the Chi-square p-value indicated that the fitted model adequately described the data, using a 0.05 rejection criterion. The quantal linear, multistage, and quantal quadratic models did not fit the data sets in all cases.


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Reviewing Model Results (cont.) Response Rate

  • Remaining models (probit and logistic) were compared using the goodness-of-fit statistics presented in the analsyis of deviance table. In almost all cases, there was little difference in the parameters evaluated.

  • The probit model yielded an adequate fit overall for all the data sets, particularly in the low dose region. We concluded that it served as useful default approach, particularly in light of extensive experience with the model in acute toxicology.

  • The remaining evaluations use the probit model.


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Table 7. Comparison of BMD to BMDL at 1%, 5%, and 10% Response Rates using the Probit Model

Note: * = Human irritants

MIBK = Methyl Isobutyl Ketone


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Relationship of BMC 95% Confidence Limits to Maximum Likelihood Estimates (Fowles et al., 1999)


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Table 8. NOAEL and LOAEL Values, Compared to BMDL-BMD Concentrations, for 1%, 5% & 10% Response Rates, Using the Probit Model

Note: Numbers in % response columns read as BMDL-BMD concentrations.

1: Anderson & Molhave, 1983; 2: Kulle et al., 1987


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NOAEL and LOAEL Values Concentrations, for 1%, 5% & 10% Response Rates, Using the Probit Model Compared to BMDL-BMD Concentrations

  • The relationship among the NOAEL, LOAEL, BMDL and BMD values were evaluated at the 1%, 5% and 10% response rates.

  • The 1% and 5% BMDL-BMD range is more closely associated with the NOAEL than the 10% range.

  • The 10% BMDL-BMD range may be associated with the LOAEL.


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Relationship of NOAEL and LOAEL to BMDL Concentrations, for 1%, 5% & 10% Response Rates, Using the Probit Model



Table 9 noael and loael values and bmdl response rates l.jpg
Table 9. NOAEL and LOAEL Values and BMDL Response Rates Data – Probit (Fowles

1: Anderson & Molhave, 1983

2: Kulle et al, 1987


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Estimating a Reference Level from the BMDL Data – Probit (Fowles

  • Assuming that the BMDL05 represented the identified POD, we estimated a reference exposure level using a default 10-fold interindividual uncertainty factor (UFH) for each of the data sets.

  • BMDL response rates were calculated at the estimated reference exposure level.


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Table 10. Estimated REL and BMDL Response Rate Using the Probit Model

CA REL = Reference 1-hour exposure level; NA= not available; Note: * = Human irritants

1: Anderson & Molhave, 1983; 2: Kulle et al, 1987 MIBK = Methyl Isobutyl Ketone


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Estimating a Reference Level from the BMDL Results Probit Model

  • All of the estimated risk levels were at or below 4 x 10-5.


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Estimating the BMDL Response Rate at the AEGL Probit Model

  • We identified relevant AEGL-1 levels for four of the seven substances from: http://www.epa.gov/oppt/aegl

  • AEGL-1 is the airborne concentration (expressed as ppm or mg/m3) of a substance above which it is predicted that the general population, including susceptible individuals, could experience notable discomfort, irritation, or certain asymptomatic nonsensory effects. However, the effects are not disabling and are transient and reversible upon cessation of exposure.

  • We calculated the BMDL response rate at the AEGL-1.


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Table 11. BMDL Reported Rates for Acute Emergency Guideline Levels (AEGLs)

Note: * = Human irritants

1: Anderson & Molhave, 1983

2: Kulle et al, 1987


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Estimating the BMDL Response Rate at the AEGL Results Levels (AEGLs)

  • Expected risk levels from the AEGL-1 values appear to be significant for the irritants vinyl acetate and formaldehyde.


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Discussion and Conclusion Levels (AEGLs)

  • The probit model consistently provides an adequate fit for these dichotomous acute human exposure data; this is consistent with the results for acute inhalation lethality animal data (Fowles et al., 1999).

  • Among 1%, 5% and 10% response rates, 5% overall is more closely associated with the NOAEL; therefore, human inhalation data sets at BMDL05 are considered to be similar to a NOAEL in estimating a concentration associated with a low level of risk. This is consistent with the results for acute inhalation lethality animal data (Fowles et al., 1999).


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Discussion and Conclusion (cont.) Levels (AEGLs)

  • The BMD 10% response rate may be associated with the LOAEL. This may require consideration of an additional uncertainty factor if the 10% response level is assumed.

  • The average ratio of the BMD to the BMDL was fairly constant across chemicals. This indicates that no significant divergence between the BMD and BMDL for most chemicals in the 1% to 10% range. This is consistent with the results for acute inhalation lethality animal data (Fowles et al., 1999).


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Discussion and Conclusion (cont.) Levels (AEGLs)

  • BMD approach provides a more consistent basis for estimating a point of departure. The estimated response rates at the NOAEL and LOAEL can vary substantially.

  • At the LOAEL, response rates above 25% can occur.

  • At the NOAEL, response rates are generally very low, although several in the 1% to 10% range were calculated.


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Discussion and Conclusion (cont.) Levels (AEGLs)

  • Using the BMD approach to estimate of the response rate of a guidance level may provide useful insight to the level of protection of the guidance level.


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Contributors Levels (AEGLs)

OEHHA Staff

George V. Alexeeff

Rachel Broadwin

James F. Collins

Melanie A. Marty

Andrew Salmon

Support Staff

Laurie Bliss

  • Students

  • Kitty K. Deng

  • Dora Wang

  • Melisa Masuda

  • Other Contributors

  • Jefferson R. Fowles


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References Levels (AEGLs)

  • ACGIH Worldwide. 2006. 2006 TLVs and BEIs, Based on the Documentation of the Threshold Limit Values for Chemical Substances and Physical Agents & Biological Exposure Indices. Cincinnati, OH: ACGIH Worldwide.

  • Acute Emergency Guidelines Levels (AEGLs). (2005). U.S. Environmental Protection Agency (EPA). http://www.epa.gov/oppt/aegl/chemlist.htm

  • Alexeeff, G.V., Broadwin, R., Liaw, J., and Dawson, S.V. (2002) Characterization of the LOAEL-NOAEL Uncertainty Factor for Mild Adverse Effects from Acute Inhalation Exposure. Reg. Toxicol. Pharmacol. 36:96-105.

  • Anderson, I., Molhave, L. (1983). Controlled human studies with formaldehyde. Formaldehyde Toxicity. Chapter 14, 154-164.

  • Carpenter, C. P., Kinkead, E. R., Geary, Jr., D. L., Sullivan, L. J., King, J. M. (1975). Petroleum hydrocarbon toxicity studies. V. Animal and human response to vapors of mixed xylenes. Toxicology Applied Pharmacology. 33, 543-558.


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References (cont.) Levels (AEGLs)

  • Collins, JF Et Al. (2004). Development of Acute Inhalation Reference Exposure Levels (RELs) to Protect the Public from Predictable Excursions of Airborne Toxicants. Journal of Appl Toxicol. 24, 155-166.

  • Fowles, JR Et Al. (1999). The Use of Benchmark Dose Methodology with Acute Inhalation Lethality Data. Regul Toxicol Pharmacol 29, 262-278.

  • Hjelm, E.W, Hagberg, M., Iregren, A., and Lof, A. (1990) Exposure to methyl isobutyl ketone: toxicokinetics and occurrence of irritative and CNS symptoms in man. Int Arch Occup Environ Health 62:19-26.

  • Imasheva, N.B. (1963) The Substantiation of the Maximal Permissible Concentration of Acetophenon in the Atmospheric Air. Hyg Sanit 28:57-63

  • Kulle, J. T., Sauder, L. R., Hebel, J. R., Green, D., and Chatham, M. D. (1987). Formaldehyde dose-response in healthy nonsmokers. J. Air Pollution Control Assoc. 37, 919-924.


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References (cont.) Levels (AEGLs)

  • Lester, D., Greenberg, L. A., and Adams, W. R. (1963). Effects of single and repeated exposures of humans and rats to vinyl chloride. Am. Ind. Hyg. Assoc. J. 3, 265-275.

  • NRC. 2000. Acute Exposure Guideline Levels for SElected Airborne Chemicals. Washington, DC: National Academy Press.

  • Smyth, H.F. and Carpenter, C.P. (1973) Vinyl Acetate Single Animal Inhalation and Human Sensory Response. Special Report 36-72. Union Carbide Corp. Danbury, CT.

  • Strickland, J.A. Et. Al. (2002). US EPA’s Acute Reference Exposure Methodology for Acute Inhalation Exposures. The Science of the Total Environment. 288, 51-63.

  • Ubaydullayev, R. (1968). A study of hygienic proper ties of methanol as an atmospheric air pollutant. USSR Lit. Air Pollut. Relat. Occup. Dis. – A Survey. 17, 39-45.