Background: Evidence for an association of alcohol consumption with prognosis after a diagnosis of breast cancer has been inconsistent. We have reviewed and summarized the published evidence and evaluated the association using individual patient data from multiple case cohorts.

Methods: A MEDLINE search to identify studies published up to January 2013 was performed. We combined published estimates of survival time for “moderate drinkers” versus nondrinkers. An analysis of individual participant data using Cox regression was carried out using data from 11 case cohorts.

Results: We identified 11 published studies suitable for inclusion in the meta-analysis. Moderate postdiagnosis alcohol consumption was not associated with overall survival [HR, 0.95; 95% confidence interval (CI), 0.85–1.05], but there was some evidence of better survival associated with prediagnosis consumption (HR, 0.80; 95% CI, 0.73–0.88). Individual data on alcohol consumption for 29,239 cases with 4,839 deaths were available from the 11 case cohorts, all of which had data on estrogen receptor (ER) status. For women with ER-positive disease, there was little evidence that pre- or postdiagnosis alcohol consumption is associated with breast cancer–specific mortality, with some evidence of a negative association with all-cause mortality. On the basis of a single study, moderate postdiagnosis alcohol intake was associated with a small reduction in breast cancer–specific mortality for women with ER-negative disease. There was no association with prediagnosis intake for women with ER-negative disease.

Conclusion: There was little evidence that pre- or post-diagnosis alcohol consumption is associated with breast cancer–specific mortality for women with ER-positive disease. There was weak evidence that moderate post-diagnosis alcohol intake is associated with a small reduction in breast cancer–specific mortality in ER-negative disease.

Impact: Considering the totality of the evidence, moderate postdiagnosis alcohol consumption is unlikely to have a major adverse effect on the survival of women with breast cancer. Cancer Epidemiol Biomarkers Prev; 23(6); 934–45. ©2014 AACR.

This article is featured in Highlights of This Issue, p. 893

Many studies have investigated the association of alcohol consumption and prognosis in women diagnosed with breast cancer. However, the results of these studies have been inconsistent. Many studies have reported no significant association between pre- or postdiagnosis alcohol consumption and overall survival (OS; refs. 1–10), whereas other studies showed a protective effect (11–16) or an adverse effect (17). Fewer studies have examined the association of alcohol consumption with breast cancer-specific survival (BCSS; refs. 1, 2, 7, 12, 14, 18–22) and even fewer studies investigated disease-free survival (DFS; refs. 1, 2, 7, 9, 13, 19, 20). Two reviews have been published and concluded that alcohol intake was not associated with survival in patients with breast cancer (23, 24). More recently, Kwan and colleagues reported the results of a joint analysis of data from three large cohorts with information on postdiagnosis alcohol consumption (1). Overall they found no association between regular alcohol consumption and breast cancer mortality, but regular alcohol consumption was associated with an increased risk of recurrence in postmenopausal women.

There are several possible reasons for the heterogeneity of the published evidence: different studies used different endpoints, many studies had a small number of events and limited statistical power, the timing of the exposure varied and included both pre- and postdiagnosis alcohol intake, the range of alcohol consumption was limited in some studies, the classification of the exposure variable varied widely, and finally different studies adjusted for different covariates.

It is important to clarify the impact of alcohol intake on prognosis in women with breast cancer because alcohol is a well-established risk factor for breast cancer (25), and public health advice to women is to limit alcohol consumption. It is not clear, however, whether it is safe to continue with moderate alcohol consumption after breast cancer diagnosis. Thus, the key question relates to the influence of postdiagnosis alcohol consumption on outcome.

The aim of this study was to carry out a systematic review and meta-analysis of published data to provide more precise estimates of mortality risk after breast cancer diagnosis and, if possible, to identify the causes of heterogeneity across published studies. In addition, we evaluated the association between alcohol consumption and prognosis in large case cohorts: the Studies of Epidemiology and Risk Factors in Cancer Heredity breast cancer cohort (SEARCH), the European Prospective Investigation into Cancer and Nutrition (EPIC), and nine studies from the Breast Cancer Association Consortium (BCAC). The association between self-reported postdiagnosis alcohol consumption and all-cause mortality has been previously reported for SEARCH (11), but the sample size is now considerably larger, data on breast cancer-specific mortality are now available, and data on other variables such as tumor estrogen receptor (ER) status are more complete.

Systematic review and meta-analysis of the published studies

A MEDLINE search of the literature up to and including January 2013 was performed using the following search terms: [“survival” (Mesh) or “mortality” (Mesh) or “survival rate” (Mesh) or “DFS” (Mesh) or “recurrence” (Mesh)] or “prognosis” (Mesh) or “death” (Mesh) or survival or mortality or relapse or recurrence or outcome or prognosis or death) and [“ethanol” (Mesh) or “alcohols” (Mesh) or “alcohol drinking” (Mesh) or “alcoholic beverages” (Mesh) or alcohol or wine or spirits or beer] and [“breast neoplasms” (MeSH) or breast cancer or breast neoplasm]. Overall 1,096 hits were retrieved; of these 50 articles were relevant based on skimming the titles and the abstracts. Each article was reviewed and included in the analysis if the following criteria were met: (i) case cohort published as an original article and (ii) findings expressed as HRs. In addition, the bibliographies of all retrieved articles were reviewed for any relevant publications missed by the search. Overall 22 original studies were relevant and were systematically reviewed. Only the most recent and complete article of studies published more than once was included in the meta-analysis. From each article, we abstracted the HR and 95% confidence limits for different exposure categories of alcohol consumption associated with any of the following endpoints: BCSS, OS, and DFS. If adjusted HR estimates were reported, we used the maximally adjusted estimates.

Different studies used different units to measure alcohol consumption, including grams, milliliters, ounces, or drinks consumed per day, week, or month. We converted these to units per week as a standard measure of ethanol intake according to the following equivalencies: 1 mL = 0.8 g, 1 oz = 28 g, 1 drink = 12.5 g, and 1 U = 8 g. We defined patients who consumed not more than 2 U of alcohol per day (14 U per week) as moderate drinkers, and compared them with nondrinkers in the meta-analysis. However, some studies used different cutoff points; we excluded reported categories that included women with alcohol consumption of more than 2 U per day (Supplementary Fig. S1). Where a single study included more than one moderate drinker category, these estimates were pooled.

We performed fixed-effect meta-analysis using the inverse-variance weighting method (26). Statistical heterogeneity between studies was assessed using the among-study variance (τ2) and the I2 statistic (27). When two estimates were used from the same study, they were combined in the same way.

SEARCH, EPIC, and BCAC breast cancer cohorts

SEARCH cohort.

SEARCH is an ongoing, population-based study of breast cancer in the region covered by the Eastern Cancer Registration and Information Centre (ECRIC). A detailed description of the study has previously been published (11). The study was set up to investigate genetic susceptibility to breast cancer. All patients diagnosed with invasive breast cancer before the age of 55 years since 1991 and still alive at the start of the study in 1996 (prevalent cases; median age, 48 years) together with all those diagnosed under 70 years of age between 1996 and the present (incident cases; median age, 54 years), are eligible to take part. The study was approved by the Cambridgeshire Research Ethics Committee. The present analysis is based on data from 8,446 participants (98% of whom were White British) with a diagnosis of invasive breast cancer.

A self-administered questionnaire was used to collect information on lifestyle factors, including height, weight, smoking history, and current (postdiagnosis) alcohol intake. Reported weekly alcohol intake was converted into standard units. The local area Index of Multiple Deprivation was used as a proxy for socioeconomic status (SES; ref. 28). Age at diagnosis, vital status, and data on tumor characteristics were obtained through the ECRIC. The registry actively follows up individuals at 3 and 5 years after diagnosis and every 5 years afterwards with continuous passive follow-up through notifications of death received from the Office for National Statistics.

EPIC cohort.

Data from incident breast cancer cases from EPIC were included in the analysis. EPIC is an ongoing multicenter prospective cohort study designed to investigate the associations between diet, lifestyle, genetic and environmental factors, and various types of cancer. A detailed description of the methods has previously been published (29). In summary, 521,448 participants from 10 European countries (∼70% women) mostly ages 35 years or above were recruited between 1992 and 2000. Written informed consent was provided by all study participants. Ethical approval for the EPIC study was provided from the Review Boards of the International Agency for Research on Cancer and local participating centers. Self-administered lifestyle questionnaires were used to obtain information on alcohol consumption, smoking status, and education, which was used as a proxy for SES. Height and weight were measured by trained research staff.

Incident cancer cases were identified through record linkages with regional cancer registries in all EPIC study centers except those in France, Germany, Greece, and Naples (Italy) where follow-up is conducted by review of health insurance records, contacts with cancer and pathology registries, and/or direct contact with cohort members. Vital status was ascertained through linkages with regional and national mortality registries and data collected by active follow-up (Germany and Greece). For the present study, the latest dates of complete follow-up for cancer incidence and vital status in the EPIC centers ranged from 2002 to 2006.

BCAC studies.

BCAC comprises multiple studies investigating inherited susceptibility to breast cancer susceptibility (30). Many of these have detailed pathologic data on the breast cancer cases linked to follow-up data. All BCAC studies that had collected data on alcohol intake, and had data available on survival time were eligible for inclusion in this analysis. In all the studies, the prediagnosis alcohol intake was estimated using a self-reported questionnaire that was filled in after diagnosis. A multistep data, harmonization procedure was used to reconcile differences in individual study questionnaires (31). In total, nine studies from Europe, North America, Japan, and Australia contributed unpublished data on 10,232 cases. A full description of all studies included is given in Supplementary Table S1.

Statistical analysis

Cox regression was used to assess the association of alcohol consumption and survival for the SEARCH, EPIC, and BCAC breast cancer case cohorts. Because cases were enrolled at variable times after diagnosis, analyses were conducted allowing for left-truncated data. Time to failure was considered from the date of diagnosis. Time at risk began on the date of receipt of the completed questionnaire and ended at the date of death from any cause or, if death did not occur, at date of last follow-up. Follow-up of all breast cancer cases was censored at 15 years. EPIC data were stratified by country and BCAC data were stratified by study. We modeled alcohol consumption both as a categorical and as an ordinal variable in four categories: nondrinkers, up to 7, >7 to 14, and >14 U per week. We also carried out multivariable analyses adjusting for body mass index (BMI; in quartiles), smoking status (never, former, and current), menopausal status at diagnosis (<45 years, premenopausal; 45–55 years, perimenopausal, ≥55 years, menopausal), and SES. SES was categorized into five groups (1 = least deprived in SEARCH and the most educated in EPIC). Tumor characteristics considered included clinical stage (I–IV), histopathological grade (well, moderately and poorly differentiated), and ER status (negative/positive). Stage and grade were modeled as ordinal variables in the multivariable analysis. ER-positive and ER-negative disease were analyzed separately. HRs with 95% confidence intervals (CI) were estimated. For categorical variables, a likelihood-ratio test for heterogeneity of risk between groups was carried out by comparing the fit of the full model with the intercept-only model. A similar procedure was used for a trend test for ordinal and continuous variables. All tests were two sided. The assumption of proportional hazards was assessed using standard log–log plots and tested using Schoenfeld residuals. ER status and stage were time dependent (in addition to grade in SEARCH) and were therefore treated as time-dependent variables in an extended Cox model. Intercooled Stata version 12 (STATA statistical software, release 12; Stata Corporation) was used for all analyses.

Published data meta-analysis

We identified 22 studies that investigated the relationship between alcohol consumption and survival (Table 1). Half of these studies had been conducted in the United States. Sample size varied considerably (range: 125–9,325 cases), with 12 studies including more than 1,000 cases. Median follow-up ranged from 3 to 13 years. Ten studies reported findings based on alcohol intake before breast cancer diagnosis and 12 studies measured alcohol intake after diagnosis.

Table 1.

Summary of studies that investigated the relationship between alcohol consumption and survival after breast cancer diagnosis

StudyYearNYear of diagnosisCountryAge at diagnosis range (mean)Exposure time (pre/postdiagnosis)StageFollow-up (mean/median)All-cause deathsBreast deathsRelapsesAdjusted for
Barnett et al. (11) 2008 4,560 1991–2005 UK 23–69 Post All 6.8 564   Age, stage, grade, ER status 
Beasley et al. (12) 2011 4,441 1988–2001 USA 20–79 Post Local and regional 5.5 525 137  BMI, physical activity, energy intake, age, state of residence, menopausal status, smoking, stage, HRT and treatment 
Dal et al. (37) 2008 1,453 1991–1994 Italy 23–74 Post All 12.6 503 398  Region of residence, age, year of diagnosis, TNM stage and ER/PR status 
Ewertz et al. (8) 1991 1,744 1983–1984 Denmark <70 Post All Up to 7 805   Tumor size, skin invasion, number of positive LNs and grade 
Flatt et al. (13) 2010 3,088 1991–2000 USA 18–70 Post Early 7.3 315  518 Stage, grade, years between diagnosis and study entry, physical activity, smoking, education, parity, body weight, and ethnicity. 
Franceschi et al. (5) 2009 1,453 1991–1994 Italy 23–74 Post  12.6 503   Region of residence, age at diagnosis, year of diagnosis, tumor, node and metastasis stage, estrogen and progesterone receptor status, BMI, and smoking habit. 
Goodwin et al. (18) 2003 477 1989–1996 Canada 26–74 (50) Post Early 6.1  52  BMI, age, stage, nodal status, adjuvant hormone and chemotherapy, and total energy. 
Hebert et al. (19) 1998 472 1982–1984 USA 20–80 Post Early Up to 10  73 109 Stage, ER status, age, BMI, menopausal status, meat and fat intake 
Holmes et al. (10) 1999 1,982 1976–1990 USA (54) Post All 18 378 326  Age, diet interval, diagnosis year, BMI, OCP, menopausal status, postmenopausal hormone use, smoking, age at first birth and parity, number of metastatic LNs. 
Kwan et al. (7) 2010 1,897 1997–2002 USA 18–70 Post Early 7.4 273 154 293 Age, BMI, folate intake, stage, hormone receptor status, tamoxifen use, treatment, and positive LN 
Kwan et al. (1) 2012 9,325 1990–2006 USA 58.8 Post I, II, III 10.3 1,542 911 1,487 Age, stage, race, education, menopausal status, hormone status, treatment, smoking, physical activity, BMI, and comorbidity 
McDonald et al. (21) 2002 125 1989–1994 USA (64.2) Post All 5.4 45 33  Stage, radiotherapy, cigarette smoking 
Rohan et al. (22) 1993 412 1982–1984 Australia  Post  5.5 123 112  BMI and energy intake 
Allemani et al. (17) 2011 264 1987–2001 Italy 35–70 Pre All 7.6 43   BMI and non-alcoholic energy intake 
Harris et al. (14) 2012 3,146 1987–2008 Sweden N/R Pre All up to 21 860 385  Age, energy intake, education level, marital status, menopausal status, BMI, calendar year of diagnosis, stage, grade and treatment 
Hellmann et al. (6) 2010 528 1976–2003 Denmark 33.1–95.4 Pre All 7.8 323   Smoking, physical activity, BMI, HRT, age, stage, menopausal status, parity, education, adjuvant treatment 
Holm et al. (20) 2012 1,028 1993–2006 Denmark 53–71 Pre Early 6.3 178 106 110 Tumor size, LN status, hormone receptor status, grade. BMI, smoking, menopausal status, HRT use, education level, physical activity, folate intake 
McEligot et al. (3) 2006 516 1994–1995 USA (65) Pre All 6.7 96 41  Not reported 
Pierce et al. (15) 2007 1,490 1991–2000 USA ≤70 Pre Early 8.7 135 118 236 Age, stage, adjuvant treatment, menopausal state, parity, smoking, physical activity, BMI, and HRT 
Reding et al. (16) 2008 1,286 1983–1992 USA ≤45 Pre All 10+ 364   Age, diagnosis year, mammography 
Saxe et al. (9) 1999 149 1989–1991 USA 26–95 (57.8) Pre All 5+ 26  28 Energy intake 
Vrieling et al. (2) 2012 2,522 2001–2005 Germany 50–74 Pre All 5.5 316 235 247 Age, study centre, tumor size, nodal status, metastases, tumor grade, ER/PR status, radiotherapy, HRT use at diagnosis, mode of detection 
Zhang et al. (4) 1995 698 1986–1991 USA 55–56 Pre All 56   Age 
StudyYearNYear of diagnosisCountryAge at diagnosis range (mean)Exposure time (pre/postdiagnosis)StageFollow-up (mean/median)All-cause deathsBreast deathsRelapsesAdjusted for
Barnett et al. (11) 2008 4,560 1991–2005 UK 23–69 Post All 6.8 564   Age, stage, grade, ER status 
Beasley et al. (12) 2011 4,441 1988–2001 USA 20–79 Post Local and regional 5.5 525 137  BMI, physical activity, energy intake, age, state of residence, menopausal status, smoking, stage, HRT and treatment 
Dal et al. (37) 2008 1,453 1991–1994 Italy 23–74 Post All 12.6 503 398  Region of residence, age, year of diagnosis, TNM stage and ER/PR status 
Ewertz et al. (8) 1991 1,744 1983–1984 Denmark <70 Post All Up to 7 805   Tumor size, skin invasion, number of positive LNs and grade 
Flatt et al. (13) 2010 3,088 1991–2000 USA 18–70 Post Early 7.3 315  518 Stage, grade, years between diagnosis and study entry, physical activity, smoking, education, parity, body weight, and ethnicity. 
Franceschi et al. (5) 2009 1,453 1991–1994 Italy 23–74 Post  12.6 503   Region of residence, age at diagnosis, year of diagnosis, tumor, node and metastasis stage, estrogen and progesterone receptor status, BMI, and smoking habit. 
Goodwin et al. (18) 2003 477 1989–1996 Canada 26–74 (50) Post Early 6.1  52  BMI, age, stage, nodal status, adjuvant hormone and chemotherapy, and total energy. 
Hebert et al. (19) 1998 472 1982–1984 USA 20–80 Post Early Up to 10  73 109 Stage, ER status, age, BMI, menopausal status, meat and fat intake 
Holmes et al. (10) 1999 1,982 1976–1990 USA (54) Post All 18 378 326  Age, diet interval, diagnosis year, BMI, OCP, menopausal status, postmenopausal hormone use, smoking, age at first birth and parity, number of metastatic LNs. 
Kwan et al. (7) 2010 1,897 1997–2002 USA 18–70 Post Early 7.4 273 154 293 Age, BMI, folate intake, stage, hormone receptor status, tamoxifen use, treatment, and positive LN 
Kwan et al. (1) 2012 9,325 1990–2006 USA 58.8 Post I, II, III 10.3 1,542 911 1,487 Age, stage, race, education, menopausal status, hormone status, treatment, smoking, physical activity, BMI, and comorbidity 
McDonald et al. (21) 2002 125 1989–1994 USA (64.2) Post All 5.4 45 33  Stage, radiotherapy, cigarette smoking 
Rohan et al. (22) 1993 412 1982–1984 Australia  Post  5.5 123 112  BMI and energy intake 
Allemani et al. (17) 2011 264 1987–2001 Italy 35–70 Pre All 7.6 43   BMI and non-alcoholic energy intake 
Harris et al. (14) 2012 3,146 1987–2008 Sweden N/R Pre All up to 21 860 385  Age, energy intake, education level, marital status, menopausal status, BMI, calendar year of diagnosis, stage, grade and treatment 
Hellmann et al. (6) 2010 528 1976–2003 Denmark 33.1–95.4 Pre All 7.8 323   Smoking, physical activity, BMI, HRT, age, stage, menopausal status, parity, education, adjuvant treatment 
Holm et al. (20) 2012 1,028 1993–2006 Denmark 53–71 Pre Early 6.3 178 106 110 Tumor size, LN status, hormone receptor status, grade. BMI, smoking, menopausal status, HRT use, education level, physical activity, folate intake 
McEligot et al. (3) 2006 516 1994–1995 USA (65) Pre All 6.7 96 41  Not reported 
Pierce et al. (15) 2007 1,490 1991–2000 USA ≤70 Pre Early 8.7 135 118 236 Age, stage, adjuvant treatment, menopausal state, parity, smoking, physical activity, BMI, and HRT 
Reding et al. (16) 2008 1,286 1983–1992 USA ≤45 Pre All 10+ 364   Age, diagnosis year, mammography 
Saxe et al. (9) 1999 149 1989–1991 USA 26–95 (57.8) Pre All 5+ 26  28 Energy intake 
Vrieling et al. (2) 2012 2,522 2001–2005 Germany 50–74 Pre All 5.5 316 235 247 Age, study centre, tumor size, nodal status, metastases, tumor grade, ER/PR status, radiotherapy, HRT use at diagnosis, mode of detection 
Zhang et al. (4) 1995 698 1986–1991 USA 55–56 Pre All 56   Age 

NOTE: Dal et al. and Franceschi et al. reported the results of the same study, but the latter reported more details (5, 37).

Seventeen studies reported the relationship between alcohol consumption and OS. Most studies reported no significant association between pre- or postdiagnosis alcohol consumption and OS (1–10). However, some studies found a protective effect of alcohol (11–16) and one showed an adverse effect (28). We excluded six of these studies from the meta-analysis as follows. One study reported a protective effect of alcohol but provided HRs without 95% CIs and an overall P value across multiple levels of exposure (15). Another study reported no association for a comparison of drinkers with nondrinkers (3). Two studies (9, 11) modeled alcohol intake as a continuous variable, one of which used data from SEARCH that we have updated in the new analysis reported in this paper (11). The other study reported no association between alcohol intake and prognosis (9). One study was excluded because there were large overlaps with the data reported in other publications (7). Finally one study was excluded because of lack of details about levels of exposure, although a trend toward lower risk of death from any cause with higher alcohol consumption was reported (Ptrend = 0.01; ref. 12).

Thus, 11 studies were included in the meta-analysis. For the purposes of this meta-analysis, we pooled the results for the reported comparison that we considered most closely approximating moderate alcohol consumption (up to 14 U per week) compared with nondrinkers. Six studies reported the association between prediagnosis alcohol intake and OS. Moderate alcohol consumption was associated with better survival (Fig. 1; HR, 0.80; 95% CI, 0.73–0.88). Five studies reported the association with postdiagnosis alcohol intake which was not associated with all-cause mortality (Fig. 2; HR, 0.95; 95% CI, 0.85–1.05).

Figure 1.

HRs for prediagnosis alcohol consumption and overall mortality (moderate drinkers vs. nondrinkers); Pheterogeneity = 0.36.

Figure 1.

HRs for prediagnosis alcohol consumption and overall mortality (moderate drinkers vs. nondrinkers); Pheterogeneity = 0.36.

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Figure 2.