Toxicological Review of Barium and Compounds
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- Bu səhifədəki naviqasiya:
- Scientific Comments from the Public Comment
- REFERENCES FOR APPENDIX A-2
- APPENDIX B - BENCHMARK DOSE (BMD) ANALYSIS
- Figure B–1. Third degree multistage model for increased incidence of nephropathy in male mice.
- Figure B–2. Model output.
- Figure B–2. Model output (continued)
- REFERENCES FOR APPENDIX B
a threefold UF. At the same time, this reviewer stated that a data base UF of 1 should be considered because of the low concentrations of barium in finished drinking water and because the chemical has a relatively short biological half-life. A third reviewer noted that there are significant deficiencies in the barium data base regarding the long-term effect of barium on the bone. The reviewer felt this was a significant concern since approximately 90% of the total body burden of barium is in the bone. Moreover, this reviewer stated that the potential for barium to adversely affect bone tissue in postmenopausal women might represent a susceptible subpopulation. A fourth reviewer stated that, because of limitations in the data base, this UF should not be lowered. The fifth reviewer stated that the choice of UFs was consistent with standard practice and that the data did not support the choice of different values for the UFs. Response: Uncertainty factors were selected in consideration of the available data and EPA standard practices. A 10-fold UF was used to account for uncertainty in extrapolating from laboratory animals to humans (i.e., interspecies variability). Insufficient information is available regarding the toxicity of chronic barium exposure in humans to quantify a dose-response relationship. A 10-fold UF was used to account for variation in susceptibility among members of the human population (i.e., interindividual variability). The available data from experimental animals suggest that gastrointestinal absorption may be higher in children than in adults (Taylor et al., 1962; Cuddihy and Griffith, 1972). A threefold UF was used to account for uncertainty associated with deficiencies in the data base. Neither a two-generation reproductive study nor an adequate investigation of developmental effects has been conducted. Moreover, there are no available data on the potential effect of barium deposition in bone tissue.
(2001) recommended using increased kidney weight as a critical effect. Response: Reference to Dallas and Williams (2001) in the discussion of previous assessments that considered increased kidney weight as an adverse effect was an error that has been corrected.
were selected as the critical effect rather than renal effects in rats as recommended by Dallas and Williams (2001) in their peer-reviewed approach. A-14
Response: Nephropathy in male mice has been chosen as the critical effect because it provided the best evidence of a dose-response relationship. Chemical-related nephropathy was not detected in the chronic rat study because of the prevalence of spontaneous degenerative nephropathy in both the control and treatment groups. Additional text has been added to Section 5.1 to augment the description of the choice of nephropathy in mice as the critical effect.
was appropriate and correctly applied in the derivation of the RfD. BMD analysis is not appropriate for establishing the point of departure because there is only a single dose showing a significant difference from controls. Response: Concerns about whether it was appropriate to use BMD modeling, or if the modeling was applied correctly, are based on the assumption that a trend must be statistical significant in order to be modeled. As noted above, the draft Benchmark Dose Technical Support Document (p. 17, U.S. EPA, 2000c) discusses the minimum data set for calculating a BMD and states “there must be at least a statistically or biologically significant [underline added for emphasis] dose-related trend in the selected endpoint.” In mice with chronic exposure to barium in drinking water, the trend of increasing incidences of nephropathy was not found to be statistically significant. This trend was determined to be biologically significant because of the increased severity and irreversibility of the lesions (see Section 5.1.2 of the Toxicological
Brenniman, GR; Levy, PS. (1984) Epidemiological study of barium in Illinois drinking water supplies. In: Advances in modern toxicology. Calabrese, EJ, ed. Princeton, NJ: Princeton Scientific Publications, pp. 231-240. Brenniman, GR; Kojola, WH; Levy, PS; et al. (1981) High barium levels in public drinking water and its association with elevated blood pressure. Arch Environ Health 36(1):28-32. Cuddihy, RG; Griffith, WC. (1972) A biological model describing tissue distribution and whole-body retention of barium and lanthanum in beagle dogs after inhalation and gavage. Health Phys 23:621-333. Dallas, CE; Williams, PL. (2001) Barium: rationale for a new oral reference dose. J. Toxicol Environ Health Part B 4:395-429. Dietz, DD; Elwell, MR; Davis Jr, WE; et al. (1992) Subchronic toxicity of barium chloride dihydrate administered to rats and mice in the drinking water. Fundam Appl Toxicol 19:527-537. A-15
National Toxicology Program (NTP), Public Health Service, U.S. Department of Health and Human Services. (1994) NTP technical report on the toxicology and carcinogenesis studies of barium chloride dihydrate (CAS no. 10326-27- 9) in F344/N rats and B6C3F1 mice (drinking water studies). NTP TR 432. Research Triangle Park, NC. NIH pub. no. 94-3163. NTIS pub PB94-214178. Taylor, DM; Bligh, PH; Duggan, MH. (1962) The absorption of calcium, strontium, barium and radium from the gastrointestinal tract of the rat. Biochem J 83:25-29. U.S. EPA.(2000c) Benchmark Dose Technical Guidance Document [external review draft]. EPA/630/R-00/001. Available from: U.S. EPA. (2002) A review of the reference dose and reference concentration processes. Risk Assessment Forum, Washington, DC; EPA/630/P-02/0002F. Available from: Wones, RG; Stadler, BL; Frohman, LA. (1990) Lack of effect of drinking water barium on cardiovascular risk factor. Environ Health Perspect 85:355-359. A-16
APPENDIX B - BENCHMARK DOSE (BMD) ANALYSIS The incidence of nephropathy in mice chronically exposed to barium in drinking water was modeled using EPA’s Benchmark Dose Modeling Software Version 1.3.2 (U.S. EPA, BMDS). All of the available models for dichotomous endpoints were fit to the incidence data shown in Table 5–2. The best fitting model was selected by evaluating the goodness-of-fit for each model fit. For each model, the software performed residual and overall chi-squared goodness-of-fit tests and determined the Akaike Information Criterion (AIC). The chi-squared p-value is a measure of the closeness between the observed data and the predicted data (predicted using the model fit). Models with chi-square p-values $ 0.1 were considered adequate fits. The AIC is a measure of the model fit, adjusted for the number of parameters used. The model with the lowest AIC value among those with adequate chi-squared p-values is considered to be the best fitting model (U.S. EPA, 2000c). Based on these criteria, a third degree multistage model was selected for the male data and a fifth degree model was selected for the female data (Table 5–3). Table 5–3 shows a comparison of BMDs for 5% and 10% extra risk and the 95% lower confidence limits on these estimates (BMDLs). A benchmark response of 10% (BMR 10 ) has
historically been used as a point of comparison across studies containing quantal data, because this is near the limit of sensitivity found for most chronic animal studies (U.S. EPA, 2000c). For this assessment, a BMR 05 was selected because the critical effect was considered to be substantially adverse and because the data supported the use of a BMR lower than 10%. The data support the selection of a BMR 05 because a chemical-related response below 10% was observed in the intermediate dose group. In addition, there was a statistically significant increasing trend in incidence of chemical-related nephropathy with increasing exposure level, supporting the biological significance demonstrated by the increased severity of the lesions over that seen in control animals. For the male data set, the best-fitting model predicts a BMD 05 of 84 mg/kg-day with a lower 95% confidence limit (i.e., BMDL 05 ) of 63 mg/kg-day. For females, the best-fitting model predicts a BMD 05 of 93 mg/kg-day and a BMDL 05 of 58 mg/kg-day. Both of these fits are quite similar, and when rounded to one significant figure both are consistent with a point of departure of 60 mg/kg-day. Confidence in the model for the male data set is slightly greater because there is a smaller difference between the BMD and BMDL, therefore the male BMDL 05 was used for B-1 deriving the RfD. A graph of the data set and model fit used to derive the RfD is presented in Figure B–1 and the model output in Figure B–2. Figure B–1. Third degree multistage model for increased incidence of nephropathy in male mice. Multistage Model with 0.95 Confidence Level 0 0.1
0.2 0.3
0.4 BMD
BMDL Multistage Frac tion Affec ted 0 20 40 60
80 100
120 140
160 dose
14:20 05/23 2005 B-2
Figure B–2. Model output. ==================================================================== Multistage Model. $Revision: 2.1 $ $Date: 2000/08/21 03:38:21 $ Input Data File: C:\BMDS\DATA\BAMALEMICE.(d) Gnuplot Plotting File: C:\BMDS\DATA\BAMALEMICE.plt Tue Jan 18 16:24:21 2005 ==================================================================== BMDS MODEL RUN ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ The form of the probability function is: P[response] = background + (1-background)*[1-EXP( -beta1*dose^1-beta2*dose^2-beta3*dose^3)] The parameter betas are restricted to be positive Dependent variable = Incidence Independent variable = Dose Total number of observations = 4 Total number of records with missing values = 0 Total number of parameters in model = 4 Total number of specified parameters = 0 Degree of polynomial = 3 Maximum number of iterations = 250 Relative Function Convergence has been set to: 1e-008 Parameter Convergence has been set to: 1e-008 Default Initial Parameter Values Background = 0 Beta(1) = 0 Beta(2) = 0 Beta(3) = 9.40534e-008 Asymptotic Correlation Matrix of Parameter Estimates ( *** The model parameter(s) -Beta(1) -Beta(2) have been estimated at a boundary point, or have been specified by the user, and do not appear in the correlation matrix ) Background Beta(3)
Background 1 -0.49 B-3 Figure B–2. Model output (continued) Beta(3) -0.49 1
Variable Estimate Std. Err. Background 0.00770741 0.0775982 Beta(1) 0 NA Beta(2) 0 NA Beta(3) 8.802e-008 4.26319e-008 NA - Indicates that this parameter has hit a bound implied by some inequality constraint and thus has no standard error. Analysis of Deviance Table Model
Log(likelihood) Deviance Test DF P-value
Full model -51.2286 Fitted model -52.1568 1.8564 2
Reduced model -73.2401 44.0231 3
AIC: 108.314
Goodness of Fit Dose
Est._Prob. Expected Observed Size
Chi^2 Res. ----------------------------------------------------------------------- i: 1 0.0000
0.0077 0.455
1 59
1.208 i: 2
30.0000 0.0101
0.604 0 60 -1.010 i: 3
75.0000 0.0439
2.545 2 58 -0.224 i: 4
160.0000 0.3081
18.484 19
60 0.040
Chi-square = 1.41
DF = 2 P-value = 0.4937 Benchmark Dose Computation Specified effect = 0.05 Risk Type = Extra risk Confidence level = 0.95
BMD = 83.5269
BMDL = 63.4689
REFERENCES FOR APPENDIX B U.S.EPA (Environmental Protection Agency). (BMDS) Software and help files can be downloaded from: U.S.EPA (Environmental Protection Agency). (2000c) Benchmark dose technical guidance document [external review draft]. EPA/630/R-00/001. Available from: http://www.epa.gov/cgi-bin/claritgw?op-Display&document=clserv:ORD:0603;&rank=4&template=epa B-4 Document Outline
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