Exposure to Polybrominated Diphenyl Ethers and a Polybrominated Biphenyl and Risk of Thyroid Cancer in Women: Single and Multi-Pollutant Approaches
Menée à l'aide d'échantillons sanguins prélevés sur 250 femmes atteintes d'un cancer papillaire de la thyroïde et sur 250 témoins (âge moyen : 51 ans), cette étude analyse l'association entre une exposition à certains polluants (polybromodiphényléthers ou biphényles polybromés) et le risque de développer la maladie
Background : Thyroid cancer incidence is the most rapidly increasing malignancy; rates are three times higher in women than men. Thyroid-hormone disrupting flame-retardant chemicals, including polybrominated diphenyl ethers (PBDE) and polybrominated biphenyls (PBB), may contribute to this trend. Methods : We investigated the relationship between PBDE/PBB exposure and papillary thyroid cancer (PTC) in 250 incident female papillary thyroid cancer cases and 250 female controls frequency-matched on age. Interviews and post-diagnostic serum samples were collected from 2010-2013. Serum samples were analyzed for 11 congeners. We calculated odds ratios (OR) and 95% confidence intervals (95%CI) using single-pollutant logistic regression models for continuous and categorical lipid-adjusted serum concentrations of PBDE/PBB, adjusted for age, alcohol consumption, and education. We applied three multi-pollutant approaches (standard multi-pollutant regression models, hierarchical Bayesian modeling [HBM], principal components analysis [PCA]) to investigate associations with PBDE/PBB mixtures. Results : In single pollutant models, a decreased risk was observed at the highest (>90th percentile) versus lowest (<median) category of BDE-209 concentrations (OR: 0.47; 95%CI: 0.23-0.98); an elevated PTC risk was observed at the highest versus lowest category of BB-153 concentrations (OR: 1.81; 95%CI: 0.96-3.39). In standard multi-pollutant models, an interquartile range increase in BDE-100 concentrations was associated with increased PTC risk (OR: 1.18; 95%CI: 1.01-1.38). HBM and PCA yielded no statistically significant results. Conclusions : Our results using single and multi-pollutant modeling do not generally support a positive association with PBDE/PBB and PTC risk. Impact : Prospective studies with more advanced statistical approaches to analyze mixtures and populations with higher exposures could reveal new insights.