Procedures for calculating benchmark doses for health risk assessment.

Safety assessment for noncancer health effects generally has been based upon dividing a no observed adverse effect (NOAEL) by uncertainty (safety) factors to provide an acceptable daily intake (ADI) or reference dose (RfD). Since the NOAEL does not utilize all of the available dose-response data, allows higher ADI from poorer experiments, and may have an unknown, unacceptable level of risk, the benchmark dose (BD) with a specified, controlled low level of risk has become popular as an adjunct to the NOAEL or the low observed adverse effect level (LOAEL) in the safety assessment process. The purpose of this paper is to summarize statistical procedures available for calculating BDs and their confidence limits for noncancer endpoints. Procedures are presented and illustrated for quantal (binary), quasicontinuous (proportion), and continuous data. Quasicontinuous data arise in developmental studies where the measure of an effect for a fetus is quantal (normal or abnormal) but the experimental unit is the mother (litter) so that results can be expressed as the proportion of abnormal fetuses per litter. However, the correlation of effects among fetuses within a litter poses some additional statistical problems. Also, developmental studies usually include some continuous measures, such as fetal body weight or length. With continuous data there generally is not a clear demarcation between normal and adverse measurements. In such cases, extremely high and/or low measurements at some designated percentile(s) can be considered abnormal. Then the probability (risk) of abnormal individuals can be estimated as a function of dose. The procedure for estimating a BD with continuous data is illustrated using neurotoxicity data. When multiple measures of adverse effects are available, a BD can be estimated based on a selected endpoint or the appearance of any combination of endpoints. Multivariate procedures are illustrated using developmental and reproductive toxicity data.

[1]  C. Portier,et al.  An evaluation of the Rai and Van Ryzin dose-response model in teratology. , 1991, Risk analysis : an official publication of the Society for Risk Analysis.

[2]  Developmental toxicity of 2,4,5-trichlorophenoxyacetic acid (2,4,5-T). I. Multireplicated dose-response studies in four inbred strains and one outbred stock of mice. , 1992 .

[3]  R J Kavlock,et al.  Benchmark Dose Workshop: criteria for use of a benchmark dose to estimate a reference dose. , 1995, Regulatory toxicology and pharmacology : RTP.

[4]  L. Ryan,et al.  A semiparametric approach to risk assessment for quantitative outcomes. , 1996, Risk analysis : an official publication of the Society for Risk Analysis.

[5]  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.

[6]  Williams Da,et al.  The analysis of binary responses from toxicological experiments involving reproduction and teratogenicity. , 1975 .

[7]  C J Price,et al.  The developmental toxicity of diethylene glycol dimethyl ether in mice. , 1987, Fundamental and applied toxicology : official journal of the Society of Toxicology.

[8]  S. Zeger,et al.  Longitudinal data analysis using generalized linear models , 1986 .

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

[10]  V. Moser,et al.  A multidisciplinary approach to toxicological screening: III. Neurobehavioral toxicity. , 1995, Journal of toxicology and environmental health.

[11]  D. A. Williams.  Dose-response models for teratological experiments. , 1987, Biometrics.

[12]  G L Kimmel,et al.  Relationship between fetal weight and malformation in developmental toxicity studies. , 1991, Teratology.

[13]  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.

[14]  Ralph L. Kodell,et al.  Statistical methods of risk assessment for continuous variables , 1993 .

[15]  W. Slikker,et al.  Behavioral and neurochemical effects of orally administered MDMA in the rodent and nonhuman primate. , 1989, Neurotoxicology.

[16]  R L Kodell,et al.  Upper confidence limits on excess risk for quantitative responses. , 1993, Risk analysis : an official publication of the Society for Risk Analysis.

[17]  W Slikker,et al.  Risk assessment for neurotoxic effects. , 1990, Neurotoxicology.

[18]  M Lefkopoulou,et al.  Global tests for multiple binary outcomes. , 1993, Biometrics.

[19]  A. Scott,et al.  Tests for trend in developmental toxicity experiments with correlated binary data. , 1994, Risk analysis : an official publication of the Society for Risk Analysis.

[20]  L. Ryan,et al.  Modeling fetal death and malformation in developmental toxicity studies. , 1994, Risk analysis : an official publication of the Society for Risk Analysis.

[21]  N. Breslow,et al.  Approximate inference in generalized linear mixed models , 1993 .

[22]  D. Krewski,et al.  Applications of multinomial dose-response models in developmental toxicity risk assessment. , 1994, Risk analysis : an official publication of the Society for Risk Analysis.

[23]  C. Kimmel,et al.  Dose-response assessment for developmental toxicity. II. Comparison of generic benchmark dose estimates with no observed adverse effect levels. , 1994, Fundamental and applied toxicology : official journal of the Society of Toxicology.

[24]  Martin Crowder,et al.  Beta-binomial Anova for Proportions , 1978 .

[25]  David W. Gaylor,et al.  Dose-response modeling of quantitative response data for risk assessment , 1992 .

[26]  C. Kimmel,et al.  Characterization of a developmental toxicity dose-response model. , 1989, Environmental health perspectives.

[27]  Williams Da,et al.  Estimation bias using the beta-binomial distribution in teratology. , 1988 .

[28]  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.

[29]  D. Gaylor,et al.  Analysis of trinomial responses from reproductive and developmental toxicity experiments. , 1991, Biometrics.

[30]  D W Gaylor,et al.  Quantitative risk analysis for quantal reproductive and developmental effects. , 1989, Environmental health perspectives.

[31]  L. Ryan,et al.  Statistical model for fetal death, fetal weight, and malformation in developmental toxicity studies. , 1993, Teratology.

[32]  L. Ryan.  The use of generalized estimating equations for risk assessment in developmental toxicity. , 1992, Risk analysis : an official publication of the Society for Risk Analysis.

[33]  W. Slikker,et al.  Neurochemical and neurohistological alterations in the rat and monkey produced by orally administered methylenedioxymethamphetamine (MDMA). , 1988, Toxicology and applied pharmacology.

[34]  D. Gaylor,et al.  Modeling for risk assessment of neurotoxic effects. , 1994, Risk Analysis.

[35]  L Ryan,et al.  Quantitative risk assessment for developmental toxicity. , 1992, Biometrics.

[36]  Kenny S. Crump,et al.  Calculation of Benchmark Doses from Continuous Data , 1995 .

[37]  D W Gaylor,et al.  Incidence of developmental defects at the no observed adverse effect level (NOAEL). , 1992, Regulatory toxicology and pharmacology : RTP.

[38]  Ralph L. Kodell,et al.  Quantitative Risk Assessment for Teratological Effects , 1989 .

[39]  Haseman Jk,et al.  Analysis of dichotomous response data from certain toxicological experiments. , 1979 .

[40]  D. A. Williams,et al.  Extra‐Binomial Variation in Logistic Linear Models , 1982 .

[41]  W. Piegorsch.  Biometrical methods for testing dose effects of environmental stimuli in laboratory studies , 1993 .

[42]  L L Kupper,et al.  The use of a correlated binomial model for the analysis of certain toxicological experiments. , 1978, Biometrics.

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

[44]  C J Price,et al.  The developmental toxicity of ethylene glycol in rats and mice. , 1985, Toxicology and applied pharmacology.

[45]  L. Haws,et al.  Two approaches for assessing human safety of disperse blue 1. , 1994, Regulatory toxicology and pharmacology : RTP.

[46]  D. Barnes,et al.  Reference dose (RfD): description and use in health risk assessments. , 1988, Regulatory toxicology and pharmacology : RTP.

[47]  P. McCullagh,et al.  Generalized Linear Models , 1992 .

[48]  D. Bowman,et al.  A full likelihood procedure for analysing exchangeable binary data. , 1995, Biometrics.

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

[50]  Louise Ryan,et al.  Bivariate Latent Variable Models for Clustered Discrete and Continuous Outcomes , 1992 .

[51]  Byron J. T. Morgan.  Analysis of Quantal Response Data , 1992 .

[52]  N. E. Breslow.  Statistical Methods in Cancer Research , 1986 .

[53]  K Y Liang,et al.  Longitudinal data analysis for discrete and continuous outcomes. , 1986, Biometrics.

[54]  D. Krewski,et al.  A simple data transformation for estimating benchmark doses in developmental toxicity experiments. , 1995, Risk analysis : an official publication of the Society for Risk Analysis.

[55]  Daniel Krewski,et al.  Dose-Response Models for Correlated Multinomial Data from Developmental Toxicity Studies , 1994 .

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

[57]  J. Chen.  A malformation incidence dose-response model incorporating fetal weight and/or litter size as covariates. , 1993, Risk analysis : an official publication of the Society for Risk Analysis.

[58]  C J Portier,et al.  An evaluation of some methods for fitting dose-response models to quantal-response developmental toxicology data. , 1993, Biometrics.

[59]  S. Raul.  On the beta-correlated binomial (bcb) distribution - a three parameter generalization of the binomial distribution , 1987 .