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Applications of multinomial dose-response models in developmental toxicity risk assessment.

Authors

  • Krewski, D, Krewski D, Health Protection Branch, Health and Welfare Canada, Ottawa, Ontario.

  • Zhu, Y, Zhu Y,

YEAR OF PUBLICATION: 1994
SOURCE: Risk Anal. 1994 Aug;14(4):613-27. doi: 10.1111/j.1539-6924.1994.tb00275.x.
JOURNAL TITLE ABBREVIATION: Risk Anal
JOURNAL TITLE: Risk analysis : an official publication of the Society for Risk Analysis
ISSN: 0272-4332 (Print) 0272-4332 (Linking)
VOLUME: 14
ISSUE: 4
PAGES: 613-27
PLACE OF PUBLICATION: United States
ABSTRACT:

Reproductive and developmental anomalies induced by toxic chemicals may be identified using laboratory experiments with small mammalian species such as rats, mice, and rabbits. In this paper, dose-response models for correlated multinomial data arising in studies of developmental toxicity are discussed. These models provide a joint characterization of dose-response relationships for both embryolethality and teratogenicity. Generalized estimating equations are used for model fitting, incorporating overdispersion relative to the multinomial variation due to correlation among littermates. The fitted dose-response models are used to estimate benchmark doses in a series of experiments conducted by the U.S. National Toxicology Program. Joint analysis of prenatal death and fetal malformation using an extended Dirichlet-trinomial covariance function to characterize overdispersion appears to have statistical and computational advantages over separate analysis of these two end points. Benchmark doses based on overall toxicity are below the minimum of those for prenatal death and fetal malformation and may, thus, be preferred for risk assessment purposes.

LANGUAGE: eng
DATE OF PUBLICATION: 1994 Aug
DATE COMPLETED: 19941201
DATE REVISED: 20191023
MESH DATE: 1994/08/01 00:01
EDAT: 1994/08/01 00:00
STATUS: MEDLINE
PUBLICATION STATUS: ppublish
OWNER: NLM

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Daniel Krewski

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Dr. Daniel Krewski is Chief Risk Scientist and co-founder of Risk Sciences International (RSI), a firm established in 2006 to bring evidence-based, multidisciplinary expertise to the challenge of understanding, managing, and communicating risk. As RSI’s inaugural CEO and long-time scientific...
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