Literature DB >> 31046141

A Review of Recent Advances in Benchmark Dose Methodology.

Signe M Jensen1, Felix M Kluxen2, Christian Ritz3.   

Abstract

In this review, recent methodological developments for the benchmark dose (BMD) methodology are summarized. Specifically, we introduce the advances for the main steps in BMD derivation: selecting the procedure for defining a BMD from a predefined benchmark response (BMR), setting a BMR, selecting a dose-response model, and estimating the corresponding BMD lower limit (BMDL). Although the last decade has shown major progress in the development of BMD methodology, there is still room for improvement. Remaining challenges are the implementation of new statistical methods in user-friendly software and the lack of consensus about how to derive the BMDL.
© 2019 Society for Risk Analysis.

Keywords:  BMDL; hybrid approach; model averaging; risk assessment; simultaneous inference

Year:  2019        PMID: 31046141     DOI: 10.1111/risa.13324

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


  4 in total

1.  Family Socioeconomic Position and Lung Cancer Risk: A Meta-Analysis and a Mendelian Randomization Study.

Authors:  Xusen Zou; Runchen Wang; Zhao Yang; Qixia Wang; Wenhai Fu; Zhenyu Huo; Fan Ge; Ran Zhong; Yu Jiang; Jiangfu Li; Shan Xiong; Wen Hong; Wenhua Liang
Journal:  Front Public Health       Date:  2022-06-06

2.  Benchmark dose risk analysis with mixed-factor quantal data in environmental risk assessment.

Authors:  Maria A Sans-Fuentes; Walter W Piegorsch
Journal:  Environmetrics       Date:  2021-03-09       Impact factor: 1.527

3.  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

4.  Comparison Of Observation-Based And Model-Based Identification Of Alert Concentrations From Concentration-Expression Data.

Authors:  Franziska Kappenberg; Marianna Grinberg; Xiaoqi Jiang; Annette Kopp-Schneider; Jan G Hengstler; Jörg Rahnenführer
Journal:  Bioinformatics       Date:  2021-01-30       Impact factor: 6.937

  4 in total

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