Evaluating exposure-response relationship in 1,3-butadiene and leukemia studies

1,3-Butadiene (BD) exposure's link to leukemia is under regulatory scrutiny. The assessment methods for BD exposure risks have evolved from early animal and limited human studies to advanced exposure-response modelling with comprehensive quantitative data. The objec- tive of this study is to explore the nuances of exposure-response modelling, investigating how various statistical methods have influenced the quan- tification of exposure-response relationships.

Although this study was not conducted as a formal systematic review, a search was performed in Medline/Pubmed to identify all human studies on leukemia risk assessment for BD exposure. This search included articles written in English. The electronic search spanned from inception of records until July 23, 2023, using the search term: "butadiene AND (leukaemia OR leukemia OR myeloid OR lymphoid)" and was restricted to human species. Focusing on the synthetic styrene-butadiene rubber (SBR) industry cohort study conducted by the University of Alabama at Birmingham, USA, this review evaluates various statistical models and factors influenc- ing exposure-response modelling.

Peak exposures to BD may be more influential in the dose-response relationship than cumulative or long-term exposure. The authors recommend utilizing β-coefficients derived from the latest SBR study update, employing Cox proportional hazard modelling, non-lagged and non-transformed cumulative BD exposure, and adjusting for age and peak BD exposure. The study reveals that statistical model selection has a limited impact on the calculated dose-response effects. The significant variation in estimated cancer mortality values arises from additional assumptions needed for metrics like the excess leukemia risk or the occupational BD effective concentration.

In con- clusion, this study provides insights into exposure-response modelling for BD exposure and leukemia mortality, highlighting the importance of peak exposures. The recommended statistical approach offers a reliable basis for regulatory risk assessment and public health population metrics. Int J Occup Med Environ Health. 2024;37(3):300-10.