Title
Estimation of the Exposure-Response Relation between Benzene and Acute Myeloid Leukemia by Combining Epidemiologic, Human Biomarker, and Animal Data
Author
Scholten, B.
Portengen, L.
Pronk, A.
Stierum, R.
Downward, G.S.
Vlaanderen, J.
Vermeulen, R.
Publication year
2022
Abstract
Background: Chemical risk assessment can benefit from integrating data across multiple evidence bases, especially in exposure–response curve (ERC) modeling when data across the exposure range are sparse. Methods: We estimated the ERC for benzene and acute myeloid leukemia (AML), by fitting linear and spline-based Bayesian meta-regression models that included summary risk estimates from non-AML and nonhuman studies as prior information. Our complete dataset included six human AML studies, three human leukemia studies, 10 human biomarker studies, and four experimental animal studies. Results: A linear meta-regression model with intercept best predicted AML risks after cross-validation, both for the full dataset and AML studies only. Risk estimates in the low exposure range [
Subject
benzene
biological marker
acute myeloid leukemia
animal
Bayes theorem
human
occupational exposure
Animals
Bayes Theorem
Benzene
Biomarkers
Humans
Leukemia, Myeloid, Acute
Occupational Exposure
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http://resolver.tudelft.nl/uuid:3f103621-1d11-4d6d-a540-2584ea5fdaa5
DOI
https://doi.org/10.1158/1055-9965.epi-21-0287
TNO identifier
967464
ISSN
1538-7755
Source
Cancer Epidemiology, Biomarkers & Prevention, 31 (31), 751-757
Document type
article