Literature DB >> 9663933

Some implications for quantitative risk assessment if hormesis exists.

R L Sielken1, D E Stevenson.   

Abstract

The existence of hormesis should impact quantitative risk assessment in at least seven fundamental ways. (1) The dose-response models for bioassay and epidemiological data should have greater flexibility to fit the observed shape of the dose-response data and no longer be forced to always be linearly increasing at low doses. (2) Experimental designs should be altered to provide greater opportunity to identify the hormetic component of a dose-response relationship. (3) Rather than a lifetime average daily dose or its analog for shorter time periods, dose scales or metrics should be used that reflect the age or time dependence of the dose level. (4) Low-dose risk characterization should include the likelihood of beneficial effects and the likelihood that a dose level has reasonable certainty of no appreciable adverse health effects. (5) Exposure assessments should make greater efforts to characterize the distribution of actual doses from exposure rather than just upper bounds. (6) Uncertainty characterizations should be expanded to include both upper and lower bounds, and there should be an increased explicit use of expert judgement and weight-of-evidence based distributional analyses reflecting more of the available relevant dose-response information and alternative risk characterizations. (7) Risk should be characterized in terms of the net effect of a dose on health rather than a dose's effect on a single factor affecting health - for example, risk would be better expressed in terms of mortality from all causes combined rather than a specific type of fatal disease.

Mesh:

Year:  1998        PMID: 9663933     DOI: 10.1177/096032719801700508

Source DB:  PubMed          Journal:  Hum Exp Toxicol        ISSN: 0960-3271            Impact factor:   2.903


  3 in total

1.  Inference for the existence of hormetic dose-response relationships in toxicology studies.

Authors:  Steven B Kim; Scott M Bartell; Daniel L Gillen
Journal:  Biostatistics       Date:  2016-02-12       Impact factor: 5.899

2.  Summary of dose-response modeling for developmental toxicity studies.

Authors:  Daniel L Hunt; Shesh N Rai; Chin-Shang Li
Journal:  Dose Response       Date:  2008-10-16       Impact factor: 2.658

3.  Simulated climate change conditions unveil the toxic potential of the fungicide pyrimethanil on the midge Chironomus riparius: a multigeneration experiment.

Authors:  Ruth Müller; Anne Seeland; Lucas S Jagodzinski; Joao B Diogo; Carsten Nowak; Jörg Oehlmann
Journal:  Ecol Evol       Date:  2012-01       Impact factor: 2.912

  3 in total

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