OBJECTIVE: To give an up-to-date assessment of the association of alcohol with female breast cancer, addressing methodological issues and shortfalls in previous overviews. METHODS: Meta-analysis of studies (any language) providing original data on incidence of first primary breast cancer and alcohol. Two reviewers independently extracted data. Study quality assessed by objective criteria including degree of control for confounding; funnel plots examined for publication bias; meta-regression techniques to explore heterogeneity. Risks associated with drinking versus not drinking and dose-response not constrained through the origin estimated using random effects methods. RESULTS: Ninety-eight unique studies were included, involving 75,728 and 60,653 cases in drinker versus non-drinker and dose-response analyses, respectively. Findings were robust to study design and analytic approaches in the meta-analyses. For studies judged high quality, controlled for appropriate confounders, excess risk associated with alcohol drinking was 22% (95% CI: 9-37%); each additional 10 g ethanol/day was associated with risk higher by 10% (95% CI: 5-15%). There was no evidence of publication bias. Risk did not differ significantly by beverage type or menopausal status. Estimated population attributable risks were 1.6 and 6.0% in USA and UK, respectively. CONCLUSIONS: Taking account of shortcomings in the study base and methodological concerns, we confirm the alcohol-breast cancer association. We compared our results to those of an individual patient data analysis, with similar findings. We conclude that the association between alcohol and breast cancer may be causal.
OBJECTIVE: To give an up-to-date assessment of the association of alcohol with female breast cancer, addressing methodological issues and shortfalls in previous overviews. METHODS: Meta-analysis of studies (any language) providing original data on incidence of first primary breast cancer and alcohol. Two reviewers independently extracted data. Study quality assessed by objective criteria including degree of control for confounding; funnel plots examined for publication bias; meta-regression techniques to explore heterogeneity. Risks associated with drinking versus not drinking and dose-response not constrained through the origin estimated using random effects methods. RESULTS: Ninety-eight unique studies were included, involving 75,728 and 60,653 cases in drinker versus non-drinker and dose-response analyses, respectively. Findings were robust to study design and analytic approaches in the meta-analyses. For studies judged high quality, controlled for appropriate confounders, excess risk associated with alcohol drinking was 22% (95% CI: 9-37%); each additional 10 g ethanol/day was associated with risk higher by 10% (95% CI: 5-15%). There was no evidence of publication bias. Risk did not differ significantly by beverage type or menopausal status. Estimated population attributable risks were 1.6 and 6.0% in USA and UK, respectively. CONCLUSIONS: Taking account of shortcomings in the study base and methodological concerns, we confirm the alcohol-breast cancer association. We compared our results to those of an individual patient data analysis, with similar findings. We conclude that the association between alcohol and breast cancer may be causal.
Authors: Siying Wang; Mei Xu; Feifei Li; Xin Wang; Kimberly A Bower; Jacqueline A Frank; Yanmin Lu; Gang Chen; Zhuo Zhang; Zunji Ke; Xianglin Shi; Jia Luo Journal: Breast Cancer Res Treat Date: 2011-12-09 Impact factor: 4.872
Authors: Jürgen Rehm; Dolly Baliunas; Guilherme L G Borges; Kathryn Graham; Hyacinth Irving; Tara Kehoe; Charles D Parry; Jayadeep Patra; Svetlana Popova; Vladimir Poznyak; Michael Roerecke; Robin Room; Andriy V Samokhvalov; Benjamin Taylor Journal: Addiction Date: 2010-03-15 Impact factor: 6.526
Authors: Rosa Sanchez-Alvarez; Ubaldo E Martinez-Outschoorn; Zhao Lin; Rebecca Lamb; James Hulit; Anthony Howell; Federica Sotgia; Emanuel Rubin; Michael P Lisanti Journal: Cell Cycle Date: 2012-01-15 Impact factor: 4.534
Authors: Jue Wang; Amy Trentham-Dietz; Jocelyn D C Hemming; Curtis J Hedman; Brian L Sprague Journal: Cancer Epidemiol Biomarkers Prev Date: 2013-04-15 Impact factor: 4.254
Authors: Kerryn W Reding; Janet R Daling; David R Doody; Cecilia A O'Brien; Peggy L Porter; Kathleen E Malone Journal: Cancer Epidemiol Biomarkers Prev Date: 2008-07-29 Impact factor: 4.254