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Journal of Clinical Oncology, Vol 26, No 20 (July 10), 2008: pp. 3310-3316 © 2008 American Society of Clinical Oncology. DOI: 10.1200/JCO.2006.10.3168 Risk Factors for the Incidence of Breast Cancer: Do They Affect Survival From the Disease?
From the Oncology Centre, Addenbrooke's Hospital; Departments of Oncology and Public Health and Primary Care, University of Cambridge; and Strangeways Research Laboratories, Cambridge, United Kingdom Corresponding author: Gillian C. Barnett, MD, Oncology Centre, Box 193, Addenbrooke's Hospital, Hills Rd, Cambridge, CB2 2QQ, United Kingdom; e-mail: gillbarnett{at}doctors.org.uk
Purpose Risk factors that influence the incidence of breast cancer may also affect survival after diagnosis. Methods Data from 4,560 women with invasive breast cancer who had taken part in the population-based Studies of Epidemiology and Risk Factors in Cancer Heredity (SEARCH) breast cancer study were used to investigate the influence on survival of variables related to pregnancy, menarche and menopause, prior use of exogenous hormones, height, weight, body mass index (BMI), smoking history, and alcohol intake. Results In univariate analyses, there was no association between prognosis and age at menarche and menopause, menopausal status at diagnosis, smoking history, or prior use of the oral contraceptive pill. Women whose most recent pregnancy was more than 30 years ago had a 35% reduced risk of dying (95% CI, 8% to 54%) compared with women who had a full-term pregnancy in the past 15 years, and the use of hormone replacement therapy for more than 4 years was associated with a similar risk reduction. BMI was associated with a 3% (95% CI, 1% to 4%) increase in mortality per unit increase. Improved prognosis was seen with increasing current alcohol consumption, with a 2% (95% CI, 1% to 3%) reduction in the risk of death per unit of alcohol consumed per week. Conclusion The apparent benefit of alcohol intake has not been described before, and our data need to be interpreted with some caution. However, our finding that an increase in BMI is associated with a poorer prognosis supports previously published data and suggests that advice on weight loss should be given to all obese patients with breast cancer.
Many lifestyle and environmental risk factors for breast cancer have been identified, including age at menarche, age at menopause, parity, age of first and subsequent pregnancies, breastfeeding, exogenous estrogen use, body mass index (BMI), height, and alcohol consumption. These risk factors may promote the development of specific types of breast cancer, and it is possible that the established environmental and lifestyle risk factors influence the course of the disease and have an effect on survival. Some studies have reported no association between parity and prognosis,1-4 others have shown a better prognosis among nulliparous women,5-10 and two studies have reported that nulliparity is an adverse prognostic factor.11,12 Early age at first full-term pregnancy has been found to be an adverse prognostic factor,1,2,13 and a poorer prognosis may be associated with decreasing time from last birth and the diagnosis of breast cancer.4,6,8,10,14-18 No effect of time since last pregnancy was found in one study.19 Similar uncertainty surrounds the relationship between exogenous estrogen use and survival from breast cancer. Several studies have reported no association,1,20 whereas others have shown an improved survival for users of the oral contraceptive pill (OCP).21-23 One study reported that early age of contraceptive use has an adverse prognostic effect.24 A randomized trial comparing hormone replacement therapy (HRT) users compared with nonusers found that larger tumors and more advanced disease were seen in HRT users.25 However, many observational studies, which include younger women, have suggested that breast cancers in HRT users show favorable prognostic characteristics.26-28 An inverse relationship between alcohol consumption and breast cancer survival has been reported,29 but the results of several other studies do not support this.30-33 Tobacco use has been associated with a less favorable prognosis.34,35 The association increased with increasing number of cigarettes per day and with total number of years smoked. A recent review36 examined 34 studies that related some measure of obesity to recurrence risk or survival in early-stage breast cancer. A statistically significant association between obesity and recurrence or survival or both was reported by 26 studies, and eight studies reported no association of obesity with prognosis. The aim of this study was to investigate the impact of established risk factors for breast cancer on overall survival after a diagnosis of breast cancer, using data from a large population-based breast cancer case series. This study differs from previously published studies in its large size and its consideration of multiple risk factors that may affect survival.
Study Population The Studies of Epidemiology and Risk Factors in Cancer Heredity breast cancer study is an ongoing population-based study of breast cancer in the region covered by the East Anglian Cancer Registry. The study was set up to investigate genetic susceptibility to breast cancer. All patients diagnosed with invasive breast cancer at younger than 55 years of age since 1991 and still alive in 1996 (prevalent cases; median age, 48 years), together with all those diagnosed at younger than 70 years of age between 1996 and the present (incident cases; median age, 54 years), are eligible to take part. On August 1, 2005, there were 12,767 eligible patients; however, 2,284 patients were not contacted because their general practitioner did not respond or thought that it would be inappropriate to contact the patient. Of the 10,583 patients who were contacted, 67% returned a questionnaire and 64% provided a blood sample for DNA analysis. Eligible patients who did not take part in the study were similar to participants, except the proportion of patients with clinical stage III/IV disease was higher in nonparticipants (10% v 5%). The study was reviewed by the Eastern Multicenter Research Ethics Committee. This analysis is based on data from 4,560 participants (98% of whom were white British) with a diagnosis of invasive breast cancer who have been included in our studies of genetic susceptibility.
Data Collection
Statistical Methods 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, on December 31, 2005 (6 months before the start of analysis). All patients were censored at 10 years. Each risk factor was treated as a categoric, ordinal, or continuous variable, as appropriate, and relevant hazard ratios (HRs) with 95% CIs were estimated. For categoric 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.37 All tests were two-sided. The assumption of proportional hazards was assessed using standard log-log plots and tested using Schoenfeld residuals. Intercooled Stata version 9 (STATA statistical software, release 9; Stata Corporation, College Station, TX) was used for all analyses.
The characteristics of the 4,560 patients with breast cancer are listed in Table 1. There were 3,312 patients (73%) enrolled as incident cases and 1,248 patients (27%) enrolled as prevalent cases. No significant difference in survival hazard was found between the two groups (P = .90).
Data on histopathologic type, clinical stage, and histologic grade were available for 4,557 (99%), 4,495 (99%) and 3,680 patients (81%), respectively. As expected, high grade, advanced-stage disease, and estrogen receptor status was strongly predictive of outcome (P < .0001), but histopathologic subtype had little effect (P = .69; Table 2). There was a tendency for an improved survival in older women (P = .040).
Table 3 lists the results of the univariate analyses for the reproductive and hormonal risk factors. Survival was similar in parous and nulliparous women. However, among parous women, survival was significantly poorer in those with four or more full-term pregnancies (P = .030) and in women whose last pregnancy was more recent. Only the term for time since last pregnancy was significant in a model that included both parity and time since last pregnancy. Compared with women with a pregnancy in the past 15 years, women whose most recent pregnancy was more than 30 years ago had a 35% reduced risk of dying (95% CI, 8% to 54%). Age at menarche, age at menopause, and age at first full-term pregnancy were not associated with outcome. Risk of death was similar in women who had ever used the OCP compared with those who never used it; total time taking the OCP or time since OCP was last used were not significant. Any use of HRT was not associated with outcome, although prognosis was significantly improved for women who used HRT for more than 4 years compared with those who never used it (HR = 0.65; 95% CI, 0.51 to 0.84; P = .001). There was no association between recency of HRT use and outcome (P = .44).
There was a tendency for taller women to have a lower risk of death (P = .040) and women who were in the highest quartile of BMI (BMI  28.5) were 1.52 times more likely to die (95% CI, 1.21 to 1.92) than women in the lowest quartile of BMI (BMI  22.7; Table 4).
Smoking status was not associated with prognosis. An improved prognosis was seen with increasing current alcohol consumption, the HR for death being 0.98 per unit of alcohol consumed per week (95% CI, 0.97 to 0.99; P = .0045). A current intake of more than seven units of alcohol per week was associated with a 22% reduction in risk of dying (95% CI, 5% to 36%; P = .0097). Figure 1 shows the cumulative mortality curves according to current alcohol intake. The quantity of alcohol consumed varied by clinical stage at diagnosis, being higher for patients with stage I and lowest for patients with stage IV tumors, suggesting that the effect of alcohol intake on survival may simply reflect stage of disease at diagnosis. A similar trend was seen with higher alcohol intake associated with low-grade tumors. Self-reported alcohol intake at age 30 years was not associated with survival.
To explore possible causal pathways for the factors found to be associated with prognosis, we investigated the effect of adjusting for stage, grade, and age at diagnosis on the HR estimates (Table 5). BMI, alcohol intake, and recency of pregnancy may all be associated with changes in hormonal milieu; so we also carried out multivariate analyses adjusting for estrogen receptor (ER) status in a multivariate model. ER status was available for 2,549 patients. The HRs for both BMI and years since last pregnancy were reduced, but not completely attenuated, by stage, grade, and age, with little change on inclusion of ER status in the model. However, the sample size was considerably reduced and the HRs were no longer significant. The effect of current alcohol consumption was also reduced, but less markedly.
We also carried out separate analyses by ER status. BMI was only associated with a poorer prognosis in ER-positive cases, with an HR per unit increase of 1.05 (95% CI,1.03 to 1.08) compared with 0.99 (95% CI, 0.96 to 1.03) in ER-negative cases: this difference was not statistically significant (P = .12). The effects of years since last pregnancy and current alcohol intake were similar in ER-positive and ER-negative cases (Appendix Table A1, online only).
We have investigated the influence of a variety of lifestyle factors on survival after a diagnosis of breast cancer and found several factors significant at the conventional level of .05. However, it is possible that some or all of the observed effects occurred as a result of chance (ie, they are type I statistical errors). We have estimated the effects of many variables (32 P values are presented in Tables 3 and 4), and the reported P values have not been adjusted for multiple hypothesis testing. Using a Bonferroni correction for 32 independent tests, a P value of .0016 would be required to be equivalent to a conventional significance of .05. However, this is conservative, because the 32 tests are not independent. For example, the tests for heterogeneity for BMI will not be independent of the test for trend.
As with other published data, we found that prognosis was similar in parous and nonparous women. We found some evidence that survival was worse in women with four or more full-term pregnancies (P = .03). However, this effect was explained by the recency of the last pregnancy in multiparous women, as a more recent pregnancy was associated with poorer prognosis (P = .0015). This remains significant after a conservative adjustment for 32 tests (Padj = .048). An effect of recent pregnancy has been reported by several other studies.4,6,8,10,14-18 Three previous studies have reported first pregnancy before age 20 years to be associated with a poorer prognosis. However, early age at first pregnancy was not associated in our study with outcome (age at first full-term pregnancy > 26 years v Previous reports of the prognostic influence of the combined OCP have been contradictory,1,20-24 but we found little evidence that OCP use is important. We did find that prolonged use of HRT was associated with an improved prognosis (P = .0019); however, this is no longer significant after adjusting for multiple testing (Padj = .061). Our findings are supported by previous findings that HRT-associated breast cancer tends to have favorable prognostic features.26-28 Our finding that increasing BMI is associated with a poorer prognosis (P = .00094; Padj = .03) is supported by other published data.36 Several mechanisms have been proposed to explain this; in particular, obesity is associated with hormonal profiles that favor tumor growth. Adipose tissue is an important extragonadal source of estrogens in postmenopausal women, and obesity is also associated with decreased levels of sex hormone-binding globulin.38,39 In healthy obese premenopausal women, a high BMI is associated with hyperinsulinemia, hyperandrogenism, lower sex hormone–binding globulin levels, but relatively unchanged or decreased estrogens. The adverse effect of increased BMI may be related to insulin and insulin-like growth factor 1, which stimulate cell proliferation and inhibit apoptosis.40 In addition, both insulin and insulin-like growth factor 1 stimulate the synthesis of sex steroids and inhibit the synthesis of sex hormone–binding globulin.41 Furthermore, higher fasting insulin levels have been correlated with an increased recurrence risk and decreased survival in early breast cancer.42
These findings may have therapeutic implications. In a study of postmenopausal women with advanced breast cancer, those with BMI Although we did show a significant association between increased alcohol consumption and improved survival (P = .0045), the association is no longer significant after a conservative Bonferroni correction (Padj = 0.144). The improved prognosis seen with increased current alcohol intake has not been described before. Furthermore, other studies have either shown no effect or have reported a poorer outcome in heavy drinkers. Our finding may be the result of bias. For example, underreporting of alcohol consumption may occur in those who delay presentation to their general practitioner with symptoms of recurrence or those who are less compliant with adjuvant therapies such as tamoxifen. Comorbidity in such patients may also be increased. Furthermore, alcohol consumption was ascertained at time of enrollment, which occurred at a variable time after diagnosis. It is therefore possible that higher alcohol consumption is a consequence, rather than a cause, of well-being. If this were true, it might be expected that the effect would be attenuated by adjusting for other variables likely to be associated with well being, such as clinical stage. However, the effect of current alcohol intake was largely independent of other prognostic markers. The patients were also asked about alcohol intake at age 30 years, which was not found to be associated with prognosis. However, the accuracy of these data may be limited, and more recent intake is likely to be more relevant biologically. Prospective studies with follow-up of incident cases and repeat measures of alcohol intake, before and after diagnosis, may offer the best approach for resolving the issue. The possibility of a true biologic effect cannot be discounted. Alcohol dehydrogenase catalyzes the oxidation of ethanol to acetaldehyde and plays a rate-limiting role in the metabolic pathway for most human ethanol oxidation. Class I alcohol dehydrogenase has been found to be highly expressed in normal mammary epithelium, but its expression is dramatically reduced in invasive breast cancers.44 The enzyme may thus have some tumor suppressor function in mammary epithelium. If class I alcohol dehydrogenase was increased with a moderate alcohol consumption, this could explain the observed improved survival of patients in this group. Alcohol can also affect the pharmacokinetics of drugs by altering gastric emptying or liver metabolism and may therefore affect survival by an effect on systemic treatment. Pregnancy, increased BMI, alcohol consumption, and hormone therapy are all thought to influence the incidence of breast cancer through hormonal mechanisms. They may therefore have a differential influence on risk of ER-positive (good prognosis) and ER-negative (poor prognosis) cancer, and their association with prognosis may simply reflect their association with ER status. Indeed, both alcohol intake and time since last pregnancy were associated with ER status (P = .031 and .026, respectively), and their effects were attenuated by adjusting for ER status. BMI was not associated with ER status (P = .88). An alternative explanation for the prognostic effects is that these factors promote tumor growth by altering serum hormone levels. Under this model, their effects would be expected to be different in ER-positive and ER-negative cases. This is supported by our finding of a difference in effects of BMI by ER status. Similar effects have been reported by others.45 In summary, we have found strong evidence that a recent pregnancy and high BMI are associated with a poorer prognosis after a diagnosis of breast cancer. Our data suggest that advice on weight loss should be given to all obese patients with breast cancer, although definitive clinical weight loss intervention trials in breast cancer populations are required to further clarify the relationship between breast cancer mortality and BMI. Further work to identify interactions between BMI and therapy is also warranted. Prolonged use of HRT and a moderate level of current alcohol intake seem to confer a good prognosis, but these associations are of borderline significance after adjustment for multiple testing and need to be interpreted with some caution. However, patients frequently ask about alcohol consumption during their follow-up. Our data suggest that moderate alcohol consumption after treatment for breast cancer, even if not beneficial, is unlikely to cause harm.
The author(s) indicated no potential conflicts of interest.
Conception and design: Gillian C. Barnett, Paul D.P. Pharoah Administrative support: Mitul Shah, Karen Redman Provision of study materials or patients: Karen Redman, Douglas F. Easton, Bruce A.J. Ponder, Paul D.P. Pharoah Collection and assembly of data: Gillian C. Barnett, Mitul Shah, Karen Redman, Douglas F. Easton, Paul D.P. Pharoah Data analysis and interpretation: Gillian C. Barnett, Paul D.P. Pharoah Manuscript writing: Gillian C. Barnett, Paul D.P. Pharoah Final approval of manuscript: Bruce A.J. Ponder, Paul D.P. Pharoah
Authors’ disclosures of potential conflicts of interest and author contributions are found at the end of this article.
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Copyright © 2008 by the American Society of Clinical Oncology, Online ISSN: 1527-7755. Print ISSN: 0732-183X
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ABSTRACT
INTRODUCTION
