Statistical Modeling of Animal Bioassay Data with Variable Dosing Regimens: Example—Vinyl Chloride

Brown, Kenneth G.; Hoel, David G.

doi:10.1111/j.1539-6924.1986.tb00203.x

Cited by 8 publications

(4 citation statements)

References 18 publications

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“…Considerable past work has emphasized the potential for age-related differences in long-term risks from carcinogenic exposures that could result from early- versus late-life exposure to carcinogens that tend to cause mutations at a single stage that is either early or late in the multistage molecular pathologic sequence of genetic changes (Brown and Hoel 1986; Day and Brown 1980; Whittemore 1977). In general, carcinogenic risks will tend to be greater for early-life exposure to a carcinogen that causes relevant early-stage transitions but will tend to be greater for late-life exposure to a carcinogen that causes relevant late-stage transitions.…”

Section: Mapping Rodent Life Stages To Human Periods: Implications Fomentioning

confidence: 99%

Age-Related Differences in Susceptibility to Carcinogenesis. II. Approaches for Application and Uncertainty Analyses for Individual Genetically Acting Carcinogens

Hattis

Goble

Chu

2005

Environ Health Perspect

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In an earlier report we developed a quantitative likelihood-based analysis of the differences in sensitivity of rodents to mutagenic carcinogens across three life stages (fetal, birth to weaning, and weaning to 60 days) relative to exposures in adult life. Here we draw implications for assessing human risks for full lifetime exposures, taking into account three types of uncertainties in making projections from the rodent data: uncertainty in the central estimates of the life-stage–specific sensitivity factors estimated earlier, uncertainty from chemical-to-chemical differences in life-stage–specific sensitivities for carcinogenesis, and uncertainty in the mapping of rodent life stages to human ages/exposure periods. Among the uncertainties analyzed, the mapping of rodent life stages to human ages/exposure periods is most important quantitatively (a range of several-fold in estimates of the duration of the human equivalent of the highest sensitivity “birth to weaning” period in rodents). The combined effects of these uncertainties are estimated with Monte Carlo analyses. Overall, the estimated population arithmetic mean risk from lifetime exposures at a constant milligrams per kilogram body weight level to a generic mutagenic carcinogen is about 2.8-fold larger than expected from adult-only exposure with 5–95% confidence limits of 1.5-to 6-fold. The mean estimates for the 0- to 2-year and 2- to 15-year periods are about 35–55% larger than the 10- and 3-fold sensitivity factor adjustments recently proposed by the U.S. Environmental Protection Agency. The present results are based on data for only nine chemicals, including five mutagens. Risk inferences will be altered as data become available for other chemicals.

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Section: Mapping Rodent Life Stages To Human Periods: Implications Fomentioning

confidence: 99%

Age-Related Differences in Susceptibility to Carcinogenesis. II. Approaches for Application and Uncertainty Analyses for Individual Genetically Acting Carcinogens

Hattis

Goble

Chu

2005

Environ Health Perspect

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“…Both angiosarcomas and carcinomas in liver were observed. These data have been used to show that VC affects the first stage of a five-stage carcinogenesis by Brown and Hoel (1986). This information, along with the carcinogenic potency estimate calculated on the basis of the Maltoni et al study, are used to predict the tumor incidence rates observed in the study.…”

Section: Tumor Incidence and The Corresponding Metabolized Dose For Amentioning

confidence: 99%

“…In their analysis of data on angiosarcoma incidence from the drew et al (1983) study, Brown and Hoel (1986) concluded that VC appears to affect the first stage of a multistage (five-stage) carcinogenesis. This conclusion is consistent with the observation from an epidemiologic study prepared by Wong and Wharton (1986) for the Chemical Manufacturers Association (CMA).…”

Section: Evaluation Of Risk Estimate From Lifetime Bioassay Data Agaimentioning

confidence: 99%

Incorporation of biological information in cancer risk assessment: Example ? Vinyl chloride

Chen

Blancato

1989

Cell Biol Toxicol

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Vinyl chloride (VC) is used as an example to demonstrate how biological information can be incorporated into quantitative risk assessment. The information included is the pharmacokinetics of VC in animals and humans and the data-generated hypothesis that VC primarily affects the initiation stage of the multistage carcinogenesis. The emphasis in this paper is on the improvement of risk assessment methodology rather than the risk assessment of VC per se. Sufficient data are available to construct physiologically-based pharmacokinetic models for both animals and humans. These models are used to calculate the metabolized dose corresponding to exposure scenarios in animals and in humans. On the basis of the data on liver angiosarcomas and carcinomas in rats, the cancer risk per unit of metabolized dose is comparable, irrespective of routes (oral or inhalation) of exposure. The tumor response from an intermittent/partial lifetime exposure is shown to be consistent with that from a lifetime exposure when VC is assumed to affect the first (initiation) stage of the multistage carcinogenic process. Furthermore, the risk estimates calculated on the basis of animal data are shown to be consistent with the human experience.

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“…(1)(2)(3) The multistage model, proposed by Armitage and Doll" to explain the observation that the age-specific incidence rates of many cancers increase with a power of age, views the process of carcinogenesis as the progressive deterioration of a normal cell through a sequence of intermediate stages to malignancy. When a couple of crucial approximations are made, the Armitage-Doll model generates an incidence function that increases with a power of age.…”

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confidence: 99%

Biologically Based Models for Cancer Risk Assessment: A Cautionary Note¹

Moolgavkar

Dewanji

1988

Risk Analysis

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Biologically based models of carcinogenesis are becoming increasingly popular for risk assessment.(1-3) The multistage model, proposed by Armitage and Doll" to explain the observation that the age-specific incidence rates of many cancers increase with a power of age, views the process of carcinogenesis as the progressive deterioration of a normal cell through a sequence of intermediate stages to malignancy. When a couple of crucial approximations are made, the Armitage-Doll model generates an incidence function that increases with a power of age. These approximations have been examined in detail in a previous publicatiod5) and will not be reviewed here. Suffice it to say that the approximations are unlikely to hold in animal experiments in which, typically, a large proportion of animals develops tumors. For risk assessment the multistage model is often used in the form P ( d , t ) =1-exp[-g ( d ) H ( t ) ]where P(d,t) is the probability of a carcinogenic response by time r, g ( d ) is a polynomial in dose, and H ( r ) is a power of time. This formulation depends crucially on the adequacy of the approximations alluded to above, and may, thus, be inappropriate in precisely those situations in which it is most widely used, viz., in the analysis of animal experimental data.More recently Thorslund et ~l . (~) have proposed that risk assessment be based on a two-stage model for carcinogenesis developed by Moolgavkar and 'Research supported by USPHS grant CA-39949 from NIH. Venzod6) and shown to be consistent with a large body of epidemiologic and experimental data by Moolgavkar and budson.(') In the original mathematical development of the model@) the parameters of the model were assumed to be independent of time. Thorslund et present an expression for the incidence function generated by the model when the parameters are made time dependent. This allows the use of the model for the analysis of carcinogenesis experiments with time-dependent dosing patterns. Thorslund etdo not present a derivation of the expression for the incidence function. We would like to point out that the derivation depends upon the adequacy of an approximation. As in the case of the Armitage-Doll model, this approximation is unlikely to be adequate when dealing with animal experiments in which the probability of tumor is high. Specifically, let Y( t) and Z ( t ) represent the number of intermediate (premalignant) and malignant cells at time r, and let p 2 ( r ) represent the second event (mutation) rate. Then the incidence function predicted by the model is where E is the expectation. When the probability of tumor is small, it is reasonable to make the approximation E [ Y ( t ) l Z ( t ) =o] = E [ Y (~) ]That is, the conditional expectation may be replaced to a good approximation by the unconditional expectation of the random variable Y ( t ) . This approximation is essential for the expression presented by 5 0272-4332/SS/0300-05$06.CCl/101988 Society tor Risk Analysis

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Statistical Modeling of Animal Bioassay Data with Variable Dosing Regimens: Example—Vinyl Chloride

Cited by 8 publications

References 18 publications

Age-Related Differences in Susceptibility to Carcinogenesis. II. Approaches for Application and Uncertainty Analyses for Individual Genetically Acting Carcinogens

Age-Related Differences in Susceptibility to Carcinogenesis. II. Approaches for Application and Uncertainty Analyses for Individual Genetically Acting Carcinogens

Incorporation of biological information in cancer risk assessment: Example ? Vinyl chloride

Biologically Based Models for Cancer Risk Assessment: A Cautionary Note¹

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Statistical Modeling of Animal Bioassay Data with Variable Dosing Regimens: Example—Vinyl Chloride

Cited by 8 publications

References 18 publications

Age-Related Differences in Susceptibility to Carcinogenesis. II. Approaches for Application and Uncertainty Analyses for Individual Genetically Acting Carcinogens

Age-Related Differences in Susceptibility to Carcinogenesis. II. Approaches for Application and Uncertainty Analyses for Individual Genetically Acting Carcinogens

Incorporation of biological information in cancer risk assessment: Example ? Vinyl chloride

Biologically Based Models for Cancer Risk Assessment: A Cautionary Note1

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Biologically Based Models for Cancer Risk Assessment: A Cautionary Note¹