Evaluation of the benchmark dose method for dichotomous data: model dependence and model selection.

The benchmark dose (BMD) method was evaluated using the USEPA BMD software. Dose-response data on cleft palate and hydronephrosis for a number of related polyhalogenated aromatic compounds were obtained from the literature. According to chi(2) test statistics, each dichotomous USEPA model failed to adequately describe only 1 of 12 cleft palate data sets. For hydronephrosis, the models were discriminated to a higher extent according to global goodness-of-fit. NOAELs for cleft palate corresponded to BMDLs (the approximate lower confidence limit on the BMD) for extra risks in the range of 5% or below. Model dependence of the BMDL estimate was more pronounced at lower levels of benchmark response (BMR). A BMR of 5% (extra risk) is recommended for cleft palate since model differences at this level were limited for all data. In addition, at BMRs of 5-10% the BMDL for all models was little affected by the specified confidence limit size (in the 90-99% range). For BMDL determination a conservative model selection approach was applied. At the suggested level of BMR (5%) this procedure resulted in use of the same model (multistage model) for the cleft palate endpoint in general. Akaike's information criterion (AIC) was considered for comparison between models. Determination of appropriateness of use of such methods in dose-response applications requires further analysis.

[1]  B C Allen,et al.  Dose-response assessment for developmental toxicity. III. Statistical models. , 1994, Fundamental and applied toxicology : official journal of the Society of Toxicology.

[2]  M. Forster,et al.  Key Concepts in Model Selection: Performance and Generalizability. , 2000, Journal of mathematical psychology.

[3]  I. J. Myung,et al.  The Importance of Complexity in Model Selection. , 2000, Journal of mathematical psychology.

[4]  L. Birnbaum,et al.  Teratogenicity of three polychlorinated dibenzofurans in C57BL/6N mice. , 1987, Toxicology and applied pharmacology.

[5]  W Leisenring,et al.  Statistical properties of the NOAEL. , 1992, Regulatory toxicology and pharmacology : RTP.

[6]  L. Birnbaum,et al.  Retinoic acid and 2,3,7,8-tetrachlorodibenzo-p-dioxin selectively enhance teratogenesis in C57BL/6N mice. , 1989, Toxicology and applied pharmacology.

[7]  B. Allen,et al.  Calculation of benchmark doses for reproductive and developmental toxicity observed after exposure to isopropanol. , 1998, Regulatory toxicology and pharmacology : RTP.

[8]  D W Gaylor,et al.  Issues in qualitative and quantitative risk analysis for developmental toxicology. , 1988, Risk analysis : an official publication of the Society for Risk Analysis.

[9]  R J Kavlock,et al.  A simulation study of the influence of study design on the estimation of benchmark doses for developmental toxicity. , 1995, Risk analysis : an official publication of the Society for Risk Analysis.

[10]  David R. Anderson,et al.  Model selection and inference : a practical information-theoretic approach , 2000 .

[11]  A. Mantovani,et al.  Developmental toxicity of carbendazim: comparison of no-observed-adverse-effect level and benchmark dose approach. , 1998, Food and chemical toxicology : an international journal published for the British Industrial Biological Research Association.

[12]  H. Bozdogan,et al.  Akaike's Information Criterion and Recent Developments in Information Complexity. , 2000, Journal of mathematical psychology.

[13]  David R. Anderson,et al.  Model selection and multimodel inference : a practical information-theoretic approach , 2003 .

[14]  L. Birnbaum,et al.  Teratogenic effects of polychlorinated dibenzofurans in combination in mice , 1987 .

[15]  D Krewski,et al.  Procedures for calculating benchmark doses for health risk assessment. , 1998, Regulatory toxicology and pharmacology : RTP.

[16]  L Edler,et al.  Statistical models for low dose exposure. , 1998, Mutation research.

[17]  J. Busemeyer,et al.  Model Comparisons and Model Selections Based on Generalization Criterion Methodology. , 2000, Journal of mathematical psychology.

[18]  Wayne W. Daniel,et al.  Biostatistics: A Foundation for Analysis in the Health Sciences , 1974 .

[19]  M. D. Hogan,et al.  The impact of litter effects on dose-response modeling in teratology. , 1986, Biometrics.

[20]  K S Crump,et al.  A new method for determining allowable daily intakes. , 1984, Fundamental and applied toxicology : official journal of the Society of Toxicology.

[21]  Zucchini,et al.  An Introduction to Model Selection. , 2000, Journal of mathematical psychology.

[22]  T. Auton Calculation of benchmark doses from teratology data. , 1994, Regulatory toxicology and pharmacology : RTP.

[23]  Teratogenicity and immunotoxicity of 3,3',4,4',5-pentachlorobiphenyl in C57BL/6 mice. , 1993, Toxicology.

[24]  K. Rai,et al.  A dose-response model for teratological experiments involving quantal responses. , 1985, Biometrics.

[25]  L. Birnbaum,et al.  Teratogenic effects of 2,3,7,8-tetrabromodibenzo-p-dioxin and three polybrominated dibenzofurans in C57BL/6N mice. , 1991, Toxicology and applied pharmacology.

[26]  J. Haseman,et al.  Teratogenic potency of TCDD, TCDF and TCDD-TCDF combinations in C57BL/6N mice. , 1985, Toxicology letters.

[27]  Curtis D. Klaassen,et al.  Casarett and Doull's Toxicology. The Basic Science of Poisons , 1981 .

[28]  Golden,et al.  Statistical Tests for Comparing Possibly Misspecified and Nonnested Models. , 2000, Journal of mathematical psychology.

[29]  C. Kimmel,et al.  Evaluation of biologically based dose-response modeling for developmental toxicity: a workshop report. , 2000, Regulatory toxicology and pharmacology : RTP.

[30]  H. Akaike,et al.  Information Theory and an Extension of the Maximum Likelihood Principle , 1973 .

[31]  J. Lindsey,et al.  Choosing among generalized linear models applied to medical data. , 1998, Statistics in medicine.