Scandinavian Journal of Work Environment & Health · 2013 · 49 citations · 23 references
MedicineEndocrinologyOncologyBreast OncologyMolecular OncologyOncogenesBreast Cancer OncologyBreast Cancer Risk AssessmentShift WorkShift Work Health EffectsEstrogen Receptor ExpressionEstrogen Receptor StatusGene-environment Interaction In CancerHormone Receptor - Positive Breast CancerHormone Receptor-positive DiseaseImmunohistochemical BiomarkersMalignant Breast TumorsNight Shift Work
OBJECTIVES: The potential mechanisms that link night-shift work with breast cancer have been extensively discussed. Exposure to light at night (LAN) depletes melatonin that has oncostatic and anti-estrogenic properties and may lead to a modified expression of estrogen receptor (ER) α. Here, we explored the association between shift work and breast cancer in subgroups of patients with ER-positive and -negative tumors. METHODS: GENICA (Gene-ENvironment Interaction and breast CAncer) is a population-based case-control study on breast cancer with detailed information on shift work from 857 breast cancer cases and 892 controls. ER status was assessed by immunohistochemical staining. Associations between night-shift work and ER-positive and -negative breast cancer were analyzed with conditional logistic regression models, adjusted for potential confounders. RESULTS: ER status was assessed for 827 cases and was positive in 653 and negative in 174 breast tumors. Overall, 49 cases and 54 controls were "ever employed" in shift work including night shifts for ≥ 1 year. In total, "ever shift work" and "ever night work" were not associated with an elevated risk of ER-positive or -negative breast tumors. Night work for ≥ 20 years was associated with a significantly elevated risk of ER-negative breast cancer [odds ratio (OR) 4.73, 95% confidence interval (95% CI) 1.22-18.36]. CONCLUSIONS: Our case-control study suggests that long-term night-shift work is associated with an increased risk of ER-negative breast cancers. Further studies on histological subtypes and the analysis of other potentially relevant factors are crucial for discovering putative mechanisms.
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