Application of two statistical approaches (Bayesian Kernel Machine Regression and Principal Component Regression) to assess breast cancer risk in association to exposure to mixtures of brominated flame retardants and per- and polyfluorinated alkylated substances in the E3N cohort

Application of two statistical approaches (Bayesian Kernel Machine Regression and Principal Component Regression) to assess breast cancer risk in association to exposure to mixtures of brominated flame retardants and per- and polyfluorinated alkylated substances in the E3N cohort

Abstract Background Brominated flame retardants (BFR) and per- and polyfluorinated alkylated substances (PFAS) are two groups of substances suspected to act as endocrine disruptors. Such substances could therefore be implicated in the occurrence of breast cancer, nevertheless, previous studies have...

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Main Authors: Pauline Frenoy (Author), Vittorio Perduca (Author), German Cano-Sancho (Author), Jean-Philippe Antignac (Author), Gianluca Severi (Author), Francesca Romana Mancini (Author)
Format: Book
Published: BMC, 2022-02-01T00:00:00Z.
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3rd Floor Main Library

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