A new method for determining allowable daily intakes*1

Crump, Kenny S.

doi:10.1016/0272-0590(84)90107-6

Cited by 847 publications

(103 citation statements)

References 6 publications

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“…Traditional methods that apply the lowest‐observed‐adverse‐effect‐level or no‐observed‐adverse‐effects‐level, may be limited by the selection of doses, sample sizes required to detect subtle effects and by technical and biological variability that limits ability to detect significant changes (Crump, 1984). In contrast, benchmark dose (BMD) modeling fits experimental dose–response data with a statistical model to identify a defined level of response relative to a control group.…”

Section: Introductionmentioning

confidence: 99%

“…In contrast, benchmark dose (BMD) modeling fits experimental dose–response data with a statistical model to identify a defined level of response relative to a control group. BMD was developed to overcome the limitations of the lowest‐observed‐adverse‐effect‐level/no‐observed‐adverse‐effects‐level approach (Crump, 1984). Regulatory agencies have increasingly adopted BMD modeling for human health risk assessment (Budtz‐Jorgensen et al ., 2013; Health Canada, 2013).…”

Section: Introductionmentioning

confidence: 99%

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BMDExpress Data Viewer ‐ a visualization tool to analyze BMDExpress datasets

Kuo

Webster

Thomas

et al. 2015

J of Applied Toxicology

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Regulatory agencies increasingly apply benchmark dose (BMD) modeling to determine points of departure for risk assessment. BMDExpress applies BMD modeling to transcriptomic datasets to identify transcriptional BMDs. However, graphing and analytical capabilities within BMDExpress are limited, and the analysis of output files is challenging. We developed a web‐based application, BMDExpress Data Viewer (http://apps.sciome.com:8082/BMDX_Viewer/), for visualizing and graphing BMDExpress output files. The application consists of “Summary Visualization” and “Dataset Exploratory” tools. Through analysis of transcriptomic datasets of the toxicants furan and 4,4′‐methylenebis(N,N‐dimethyl)benzenamine, we demonstrate that the “Summary Visualization Tools” can be used to examine distributions of gene and pathway BMD values, and to derive a potential point of departure value based on summary statistics. By applying filters on enrichment P‐values and minimum number of significant genes, the “Functional Enrichment Analysis” tool enables the user to select biological processes or pathways that are selectively perturbed by chemical exposure and identify the related BMD. The “Multiple Dataset Comparison” tool enables comparison of gene and pathway BMD values across multiple experiments (e.g., across timepoints or tissues). The “BMDL‐BMD Range Plotter” tool facilitates the observation of BMD trends across biological processes or pathways. Through our case studies, we demonstrate that BMDExpress Data Viewer is a useful tool to visualize, explore and analyze BMDExpress output files. Visualizing the data in this manner enables rapid assessment of data quality, model fit, doses of peak activity, most sensitive pathway perturbations and other metrics that will be useful in applying toxicogenomics in risk assessment. © 2015 Her Majesty the Queen in Right of Canada. Journal of Applied Toxicology published by John Wiley & Sons, Ltd.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

BMDExpress Data Viewer ‐ a visualization tool to analyze BMDExpress datasets

Kuo

Webster

Thomas

et al. 2015

J of Applied Toxicology

View full text Add to dashboard Cite

show abstract

“…However, when one or more parameters (those of interest, or nuisance parameters, or both) lie on the boundary of the parameter space, the distribution of the likelihood ratio test statistic may not be limits of model parameters are often approximated by Wald intervals, which are known to be inaccurate (Bailer and Smith 1994, Moerbeek et al 2004, Nitcheva et al 2007). These problems were acknowledged long ago (Crump et al 1984), but have not been resolved clearly for the practitioners of dose-response modeling.…”

Section: Statistical Inferencementioning

confidence: 99%

“…A variety of models are in use (Krewski and The benchmark dose method (Crump 1984, Filipsson et al 2003, Parham and Portier 2005 consists of estimating a lower confidence limit for the dose associated with a specified increase  in adverse response (i.e., increased risk) above the background level. In practice, the specified increase is typically 1% to 10% for cancer quantal response models (Filipsson et al 2003, Parham andPortier 2005).…”

Section: Dose-response Models and Risk Estimatesmentioning

confidence: 99%

Some New Aspects of Statistical Inference for Multistage Dose-Response Models with Applications

Sinha

Kopylev

Fox

2012

Pak.j.stat.oper.res.

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“…This method uses conventional mathematical models to obtain dose–response curves; that is, it does not assume linearity in the low-dose region. The BMD approach has been developed particularly by Crump (1984, 1995) and the U.S. EPA (1995).…”

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confidence: 99%

Application of Benzo( a )pyrene and Coal Tar Tumor Dose–Response Data to a Modified Benchmark Dose Method of Guideline Development

Fitzgerald

Robinson

Pester

2004

Environ Health Perspect

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Assessment of cancer risk from exposure to polycyclic aromatic hydrocarbons (PAHs) has been traditionally conducted by applying the conservative linearized multistage (LMS) model to animal tumor data for benzo(a)pyrene (BaP), considered the most potent carcinogen in PAH mixtures. Because it has been argued that LMS use of 95% lower confidence limits on dose is unnecessarily conservative, that assumptions of low-dose linearity to zero in the dose response imply clear mechanistic understanding, and that “acceptable” cancer risk rests on a policy decision, an alternative cancer risk assessment approach has been developed. Based in part on the emerging benchmark dose (BMD) method, the modified BMD method we used involves applying a suite of conventional mathematical models to tumor dose–response data. This permits derivation of the average dose corresponding to 5% extra tumor incidence (BMD0.05) to which a number of modifying factors are applied to achieve a guideline dose, that is, a daily dose considered safe for human lifetime exposure. Application of the modified BMD method to recent forestomach tumor data from BaP ingestion studies in mice suggests a guideline dose of 0.08 μg/kg/day. Based on this and an understanding of dietary BaP, and considering that BaP is a common contaminant in soil and therefore poses human health risk via soil ingestion, we propose a BaP soil guideline value of 5 ppm (milligrams per kilogram). Mouse tumor data from ingestion of coal tar mixtures containing PAHs and BaP show that lung and not forestomach tumors are most prevalent and that BaP content cannot explain the lung tumors. This calls into question the common use of toxicity equivalence factors based on BaP for assessing risk from complex PAH mixtures. Emerging data point to another PAH compound—7H-benzo(c)fluorene—as the possible lung tumorigen.

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A new method for determining allowable daily intakes*1

Cited by 847 publications

References 6 publications

BMDExpress Data Viewer ‐ a visualization tool to analyze BMDExpress datasets

BMDExpress Data Viewer ‐ a visualization tool to analyze BMDExpress datasets

Some New Aspects of Statistical Inference for Multistage Dose-Response Models with Applications

Application of Benzo( a )pyrene and Coal Tar Tumor Dose–Response Data to a Modified Benchmark Dose Method of Guideline Development

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