Literature DB >> 1700346

Risk assessment for neurotoxic effects.

D W Gaylor1, W Slikker.   

Abstract

Regulation of neurotoxicants is generally based on setting allowable doses (exposures) by dividing a no observed adverse effect level (NOAEL) by uncertainty factors that hopefully account for interspecies and intraspecies differences for extrapolations of experimental results obtained in animals to humans. This procedure makes no use of estimates of risk as a function of dose or does it acknowledge any risk at the NOAEL. The purpose of this paper is to illustrate how bioassay data can be used to estimate the risk of neurotoxic effects as a function of dose. In the absence of direct measurements of neurotoxic effects, biomarkers associated with neurotoxic effects can be used as measures of toxicity. In the absence of a definition of an adverse effect, an abnormal level for a measure of toxicity can be established which occurs only in a small fraction of a population which is not exposed to the substance under investigation. Risk is defined as the proportion of a population whose levels of a measure of toxicity equal or exceeds the abnormal level of the measure under study. The procedure is illustrated using data for neurochemical, neurohistological, and behavioral effects of methylenedioxymethamphetamine (MDMA) administered to rats or monkeys. This procedure is more versatile than the NOAEL/uncertainty factor approach since it provides estimates of risk as a function of dose of a potential neurotoxic substance.

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Year:  1990        PMID: 1700346

Source DB:  PubMed          Journal:  Neurotoxicology        ISSN: 0161-813X            Impact factor:   4.294


  10 in total

1.  On use of the multistage dose-response model for assessing laboratory animal carcinogenicity.

Authors:  Daniela K Nitcheva; Walter W Piegorsch; R Webster West
Journal:  Regul Toxicol Pharmacol       Date:  2007-03-25       Impact factor: 3.271

2.  Simultaneous Confidence Bands for Abbott-Adjusted Quantal Response Models.

Authors:  Brooke E Buckley; Walter W Piegorsch
Journal:  Stat Methodol       Date:  2008-05

3.  Bayesian Quantile Impairment Threshold Benchmark Dose Estimation for Continuous Endpoints.

Authors:  Matthew W Wheeler; A John Bailer; Tarah Cole; Robert M Park; Kan Shao
Journal:  Risk Anal       Date:  2017-05-29       Impact factor: 4.000

4.  Translational benchmark risk analysis.

Authors:  Walter W Piegorsch
Journal:  J Risk Res       Date:  2010-07

Review 5.  Risk assessment for neurobehavioral toxicity: SGOMSEC joint report.

Authors:  D Hattis; J Glowa; H Tilson; B Ulbrich
Journal:  Environ Health Perspect       Date:  1996-04       Impact factor: 9.031

6.  Benchmark dose for cadmium-induced renal effects in humans.

Authors:  Yasushi Suwazono; Salomon Sand; Marie Vahter; Agneta Falk Filipsson; Staffan Skerfving; Jonas Lidfeldt; Agneta Akesson
Journal:  Environ Health Perspect       Date:  2006-07       Impact factor: 9.031

7.  Benchmark concentrations for methylmercury obtained from the Seychelles Child Development Study.

Authors:  K S Crump; C Van Landingham; C Shamlaye; C Cox; P W Davidson; G J Myers; T W Clarkson
Journal:  Environ Health Perspect       Date:  2000-03       Impact factor: 9.031

8.  Estimating risk from ambient concentrations of acrolein across the United States.

Authors:  Tracey J Woodruff; Ellen M Wells; Elizabeth W Holt; Deborah E Burgin; Daniel A Axelrad
Journal:  Environ Health Perspect       Date:  2006-12-11       Impact factor: 9.031

9.  bmd: an R package for benchmark dose estimation.

Authors:  Signe M Jensen; Felix M Kluxen; Jens C Streibig; Nina Cedergreen; Christian Ritz
Journal:  PeerJ       Date:  2020-12-17       Impact factor: 2.984

10.  Benchmark calculations for perchlorate from three human cohorts.

Authors:  Kenny S Crump; John P Gibbs
Journal:  Environ Health Perspect       Date:  2005-08       Impact factor: 9.031

  10 in total

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