Literature DB >> 12969419

Benchmark calculations in risk assessment using continuous dose-response information: the influence of variance and the determination of a cut-off value.

Salomon J Sand1, Dietrich von Rosen, Agneta Falk Filipsson.   

Abstract

A benchmark dose (BMD) is the dose of a chemical that corresponds to a predetermined increase in the response (the benchmark response, BMR) of a health effect. In this article, a method (the hybrid approach) for benchmark calculations from continuous dose-response information is investigated. In the formulation of the methodology, a cut-off value for an adverse health effect has to be determined. It is shown that the influence of variance on the hybrid model depends on the choice of determination of the cut-off point. If the cut-off value is determined as corresponding to a specified tail proportion of the control distribution, P(0), the BMD becomes biased upward when the variance is biased upward. On the contrary, if the cut-off value is directly determined to some level of the continuous response variable, the BMD becomes biased upward when the variance is biased downward. A simulation study was also performed in which the accuracy and precision of the BMD was compared for the two ways of determining the cut-off value. In general, considering BMRs of 1, 5, and 10% (additional risk) the precision of the BMD became higher when the cut-off value was estimated by specifying P(0), relative to the case with a direct determination. Use of the square-root of the maximum-likelihood estimator of the variance in BMD estimation may provide a bias that is reflected by the cut-off formulation (downward bias if specifying P(0), and upward bias if specifying the cut-off, c, directly). This feature may be reduced if an unbiased estimator of the standard deviation is used in the calculations.

Mesh:

Substances:

Year:  2003        PMID: 12969419     DOI: 10.1111/1539-6924.00381

Source DB:  PubMed          Journal:  Risk Anal        ISSN: 0272-4332            Impact factor:   4.000


  4 in total

1.  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

2.  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

3.  Application of BMD approach to identify thresholds of cadmium-induced renal effect among 35 to 55 year-old women in two cadmium polluted counties in China.

Authors:  Qi Wang; Jia Hu; Tian-xu Han; Mei Li; Huan-hu Zhao; Jian-wei Chen; Lin-Xiang Ye; Yi-Kai Zhou
Journal:  PLoS One       Date:  2014-02-04       Impact factor: 3.240

4.  Dose-Related Severity Sequence, and Risk-Based Integration, of Chemically Induced Health Effects.

Authors:  Salomon Sand; Roland Lindqvist; Dietrich von Rosen; Nils-Gunnar Ilbäck
Journal:  Toxicol Sci       Date:  2018-09-01       Impact factor: 4.849

  4 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.