Background:Several studies have reported discordant results regarding the impact of the CYP2D6 phenotype on both the effectiveness and the degree of endocrine symptoms associated with tamoxifen. Other studies have suggested that menopausal symptoms may be a predictive factor to tamoxifen response.Methods:We investigated the relationship between the CYP2D6-predicted phenotype and tamoxifen response in a nested case–control study among women from the International Breast cancer Intervention Study (IBIS-I), which evaluated tamoxifen in the preventive setting.Results:In this retrospective analysis of the tamoxifen-treated women in the IBIS-I study, 9 women (16.6%) who developed oestrogen receptor-positive invasive breast cancer had a 2D6 poor or intermediate metaboliser phenotype compared with 45 (20.6%) controls. Adjusted matched logistic regression revealed no significant difference between cases and controls for extensive vs intermediate metaboliser phenotype (OR=0.81 (0.30–2.23), P=0.7) or extensive vs poor metaboliser phenotype (OR=1.02 (0.31–3.32), P=0.9). Controls in the tamoxifen group with a poor metaboliser phenotype developed nonsignificantly fewer hot flushes compared with those with an extensive metaboliser phenotype (OR=0.40 (0.12–1.31)), but those with the intermediate phenotype developed nonsignificantly more hot flushes (OR=1.38 (0.58–3.29)) in an unadjusted analysis.Conclusion:Data from the preventive IBIS-I study did not support an association between the CYP2D6 phenotype and breast cancer outcome or the development of endocrine symptoms in tamoxifen-treated women.
Relationships between CYP2D6 phenotype, breast cancer and hot flushes in women at high risk of breast cancer receiving prophylactic tamoxifen: results from the IBIS-I trial
I. Šestak,Roseann Kealy,D. Nikoloff,M. Fontecha,J. Forbes,A. Howell,J. Cuzick
Published 2012 in British Journal of Cancer
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- Publication year
2012
- Venue
British Journal of Cancer
- Publication date
2012-06-26
- Fields of study
Medicine
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- External record
- Source metadata
Semantic Scholar, PubMed
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