Standardizing benchmark dose calculations to improve science-based decisions in human health assessments.
Environ Health Perspect
; 122(5): 499-505, 2014 May.
Article
em En
| MEDLINE
| ID: mdl-24569956
ABSTRACT
BACKGROUND:
Benchmark dose (BMD) modeling computes the dose associated with a prespecified response level. While offering advantages over traditional points of departure (PODs), such as no-observed-adverse-effect-levels (NOAELs), BMD methods have lacked consistency and transparency in application, interpretation, and reporting in human health assessments of chemicals.OBJECTIVES:
We aimed to apply a standardized process for conducting BMD modeling to reduce inconsistencies in model fitting and selection.METHODS:
We evaluated 880 dose-response data sets for 352 environmental chemicals with existing human health assessments. We calculated benchmark doses and their lower limits [10% extra risk, or change in the mean equal to 1 SD (BMD/L10/1SD)] for each chemical in a standardized way with prespecified criteria for model fit acceptance. We identified study design features associated with acceptable model fits.RESULTS:
We derived values for 255 (72%) of the chemicals. Batch-calculated BMD/L10/1SD values were significantly and highly correlated (R2 of 0.95 and 0.83, respectively, n = 42) with PODs previously used in human health assessments, with values similar to reported NOAELs. Specifically, the median ratio of BMDs10/1SDNOAELs was 1.96, and the median ratio of BMDLs10/1SDNOAELs was 0.89. We also observed a significant trend of increasing model viability with increasing number of dose groups.CONCLUSIONS:
BMD/L10/1SD values can be calculated in a standardized way for use in health assessments on a large number of chemicals and critical effects. This facilitates the exploration of health effects across multiple studies of a given chemical or, when chemicals need to be compared, providing greater transparency and efficiency than current approaches.
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Benchmarking
Tipo de estudo:
Etiology_studies
/
Prognostic_studies
/
Risk_factors_studies
Limite:
Humans
Idioma:
En
Ano de publicação:
2014
Tipo de documento:
Article