Literature DB >> 26873961

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

Steven B Kim1, Scott M Bartell2, Daniel L Gillen2.   

Abstract

In toxicology studies hormesis refers to a dose-response relationship with a stimulatory response at low doses and an inhibitory response at high doses. In this manuscript, we particularly focus on a J-shaped dose-response relationship for binary cancer responses. We propose and examine two new flexible models for testing the hypothesis of hormesis in a Bayesian framework. The first model is parametric and enhances the flexibility of modeling a hormetic zone by using a non-linear predictor in a multistage model. The second model is non-parametric and allows multiple model specifications, weighting the contribution of each model via Bayesian model averaging (BMA). Simulation studies show that the non-parametric modeling approach with BMA provides robust sensitivity and specificity for detecting hormesis relative to the parametric approach, regardless of the shape of a hormetic zone.
© The Author 2016. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Entities:  

Keywords:  Bayesian model averaging; Hormesis; Hypothesis testing; Multistage models; Non-parametric models

Mesh:

Year:  2016        PMID: 26873961      PMCID: PMC4915611          DOI: 10.1093/biostatistics/kxw004

Source DB:  PubMed          Journal:  Biostatistics        ISSN: 1465-4644            Impact factor:   5.899


  20 in total

1.  The hormetic dose-response model is more common than the threshold model in toxicology.

Authors:  Edward J Calabrese; Linda A Baldwin
Journal:  Toxicol Sci       Date:  2003-02       Impact factor: 4.849

2.  A parametric model for detecting hormetic effects in developmental toxicity studies.

Authors:  Daniel L Hunt; Dale Bowman
Journal:  Risk Anal       Date:  2004-02       Impact factor: 4.000

3.  Testing threshold and hormesis in a random effects dose-response model applied to developmental toxicity data.

Authors:  D Hunt; S N Rai
Journal:  Biom J       Date:  2005-06       Impact factor: 2.207

4.  Low-dose risk, hormesis, analogical and logical thinking.

Authors:  Giovanni A Zapponi; Ida Marcello
Journal:  Ann N Y Acad Sci       Date:  2006-09       Impact factor: 5.691

Review 5.  Hormesis defined.

Authors:  Mark P Mattson
Journal:  Ageing Res Rev       Date:  2007-12-05       Impact factor: 10.895

Review 6.  The linearized multistage model and the future of quantitative risk assessment.

Authors:  K S Crump
Journal:  Hum Exp Toxicol       Date:  1996-10       Impact factor: 2.903

Review 7.  Some implications for quantitative risk assessment if hormesis exists.

Authors:  R L Sielken; D E Stevenson
Journal:  Hum Exp Toxicol       Date:  1998-05       Impact factor: 2.903

8.  Estimation of a benchmark dose in the presence or absence of hormesis using posterior averaging.

Authors:  Steven B Kim; Scott M Bartell; Daniel L Gillen
Journal:  Risk Anal       Date:  2014-11-10       Impact factor: 4.000

9.  Modeling effective dosages in hormetic dose-response studies.

Authors:  Regina G Belz; Hans-Peter Piepho
Journal:  PLoS One       Date:  2012-03-16       Impact factor: 3.240

Review 10.  Multistage models of carcinogenesis.

Authors:  P Armitage
Journal:  Environ Health Perspect       Date:  1985-11       Impact factor: 9.031

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  1 in total

1.  Model Averaging with AIC Weights for Hypothesis Testing of Hormesis at Low Doses.

Authors:  Steven B Kim; Nathan Sanders
Journal:  Dose Response       Date:  2017-06-29       Impact factor: 2.658

  1 in total

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