4.5 Article

Key event-informed risk models for benzene-induced acute myeloid leukaemia

期刊

TOXICOLOGY LETTERS
卷 340, 期 -, 页码 141-152

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ELSEVIER IRELAND LTD
DOI: 10.1016/j.toxlet.2021.01.003

关键词

Benzene; Acute myeloid leukemia; Risk model; Occupational; Mortality; Key event; Hematotoxicity; Genotoxicity; Exposure response modelling; Dose response modelling

资金

  1. LOA REACH Consortia

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Occupational exposure to benzene at levels of 10 ppm or more is associated with increased risk of acute myeloid leukaemia (AML). Preventing early key events can lead to prevention of adverse outcomes caused by myelodysplastic syndromes (MDS) and AML, and modification approaches using sub-linear and segmented linear increases in risk have been suggested. Incorporating key event information into risk models provides greater flexibility in risk model development and selection.
Occupational exposure to benzene at levels of 10 ppm or more has been associated with increased risk of acute myeloid leukaemia (AML). The mode of action (MOA) for AML development leading to mortality is anticipated to include multiple earlier key events, which can be observed in hematotoxicity and genetic toxicity in peripheral blood of exposed workers. Prevention of these early events would lead to prevention of the apical, adverse outcomes, the morbidity and mortality caused by the myelodysplastic syndromes (MDS) and AML. Incorporation of key event information should modify the risk model, but few modification approaches have been suggested. To that end, two approaches to risk model modification are described that use sub-linear and segmented linear increases in risk below key events, while maintaining a linear increase in AML mortality risk beginning at 2 ppm, the lowest observed adverse effect concentration (LOAEC) identified for hemato- and geno- toxicity in high quality studies of human occupational exposure. Below 2 ppm two different modification approaches to quantitative risk models were applied: a continuously decreasing slope model and a segmented modification in slope. These two approaches provide greater flexibility to incorporate MOA information in risk model development and selection. (C) 2021 Published by Elsevier B.V.

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