Letters to the Editor pubs.acs.org/crt
Letter to the Editor Regarding the Article by Bailey et al., 2009
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estimates than the probit but illustrates the extreme model sensitivity of the extrapolations made by Bailey et al. The probit model is always exceptionally flat at low doses4 and consequently will show strong divergence at low doses from a linear model no matter what data the models are fit to. Thus, the “conclusion” Baily et al. reached, “The shapes of ... the fitted curves [e.g., probit] for liver... display increasingly steep slopes with decreasing dose and thus may be taken to suggest that a finite dose may be reached in which there would be no observable increase above background tumor rate (slope of infinity), that is, a threshold,” was guaranteed once the probit model was selected no matter how the data came out. Instead of comparing the predictions of the EPA linear model to highly uncertain extrapolated values, a much more definitive analysis would be to compare the predictions of the EPA approach to the actual data obtained by Bailey et al. Since the chief interest is in the low dose predictions, a valid comparison would be to compare the statistical upper bound on additional risk at the lowest experimental dose (risk at the lowest dose minus risk at zero dose) to the predictions of the EPA method at that dose. (Since Bailey et al.’s data would be considered consistent with the EPA approach if the prediction of the EPA approach was within the confidence bounds, a reasonable measure of the degree of inconsistency is the amount by which the risk predicted by the EPA approach lies outside of the confidence intervals.) Fitting the probit model to the data on liver tumors, I obtained an LED10 value of 15.1 ppm, compared to the 12.6 ppm obtained by Bailey et al. using the logit model. (Both analyses omitted the data at the highest dose.) Extrapolating down linearly from this point to the lowest experimental dose of 0.45 ppm yields a prediction for additional risk of (0.45/15.1)0.1 = 0.0030. By comparison, there were 12 of 8748 trout with liver tumors at this dose, compared to 10 among 8363 control trout, which gives an upper bound for a 95% statistical confidence interval for additional risk at 0.45 ppm of 0.0013. Thus, the estimate from the EPA approach does overestimate the observed risk at the lowest dose in the experiment, but by amount we can only say is ≥ a factor of 0.0030/0.0013 = 2.3 (2.7 using Bailey et al’s LED10). This amount of overestimation is small compared to the other uncertainties in using such calculations to set guidelines for human exposures (generally using rodent data rather than fish data). The prediction of the EPA approach is in even closer agreement with the low dose trout data on stomach tumors than with that on liver tumors. This can be easily seen from Bailey et al.’s1 Figure 4B, which shows the EPA linear extrapolated additional risk nearly equal to the statistical upper bound on additional risk computed at the lowest experimental dose. Bailey et al. summarized the results of their analysis by stating that their extrapolated predictions of the dose corresponding to 10−6 additional risk were 500−1500-fold higher than that
o the Editor: In an article published in this journal, Bailey et al.1 studied the response of liver and stomach tumors in rainbow trout to low doses of dibenzo[a,l]pyrene (DBP). The trout model offers a number of advantages over rodent models for studying low-dose effects, including lower costs and requiring a far less complex infrastructure than rodent models, advantages that facilitate testing larger numbers of animals. Utilizing these advantages, Bailey et al. conducted an experiment in which a total of 40,800 trout were fed 0−225 ppm dibenzo[a,l]pyrene (DBP) in food in eight graded dose levels for 4 weeks and observed for nine months subsequently. To enhance power to detect effects at lower doses, larger numbers of animals were included in the control group and in low dose groups. These group sizes far exceeded those in the largest rodent bioassays. The main conclusion of Bailey et al.1 involved the comparison of their results to the low dose risk predictions of the EPA LED10 linear extrapolation method.2 However, rather than comparing the predictions of the EPA method to their data, instead Bailey et al. compared the predictions of the EPA method to values obtained by extrapolating their data below their lowest experimental dose using models which they themselves claim (rightly) have no special biological significance. Bailey et al. present results using three such models, of which the probit model shows the greatest divergence from the predictions of the EPA method. It is well known that extrapolation to low doses using such models is extremely uncertain.3 For example, the dose response in Figure 1 labeled
Figure 1. The most that can be said is that EPA LED10 extrapolation only overestimates the trout liver cancer response at lowest dose tested by a factor of ≥2.3.
modified probit (probit with a small linear dose term added) fits the trout data about as well as the probit but predicts a dose corresponding to a risk of 1/1,000,000 of only 10 times greater than the EPA model compared to the 1480 times greater value obtained from the probit fit1 (their Table 2). This is not to suggest that the alternate model provides more accurate © XXXX American Chemical Society
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dx.doi.org/10.1021/tx400129r | Chem. Res. Toxicol. XXXX, XXX, XXX−XXX
Chemical Research in Toxicology
Letters to the Editor
predicted by the EPA linear approach. This claim is based on highly uncertain extrapolations and appears to suggest a much higher divergence between their data and the predictions of the EPA approach than is warranted. As noted above, the most that can be said is that data at the lowest dose Bailey et al. tested indicates that the EPA linear approach overestimated the additional risk at this dose only by a factor of ≥ between 2 and 3. Bailey et al.5 report on a similar trout experiment involving aflatoxin but analyzed the data using the same approach as that used in the DBP study.
Kenny Crump
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2220 South Vienna Ruston, Louisiana 71270, United States
REFERENCES
(1) Bailey, G. S., Reddy, A., Pereira, C. B., Harttig, U., Baird, W., et al. (2009) Nonlinear cancer response at ultralow dose: A 40,800-animal ED001 tumor and biomarker study. Chem. Res. Toxicol. 22, 1264−1276. (2) U. S. EPA (2005) Guidelines for Carcinogen Risk Assessment, EPA/ 630/P-03/001F, Risk Assessment Forum, U. S. Environmental Protection Agency, Washington, D.C. (3) NRC (National Research Council) (1982) Risk Assessment in the Federal Government: Managing the Process, National Academy Press, Washington, D.C. (4) Crump, K. S. (1977) Open query: Theoretical problems in the modified Mantel-Bryan procedure. Biometrics 33, 752−755. (5) Bailey, G., Williams, D., Orner, G., Hendricks, J., and Pereira, C. (2012) Cancer risk at ultra-low dose: Lessons learned from 40,000animal cancer dose-response studies. Genes Environ. 34, 156−164.
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dx.doi.org/10.1021/tx400129r | Chem. Res. Toxicol. XXXX, XXX, XXX−XXX
