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Cancer Epidemiol Biomarkers Prev. Author manuscript; available in PMC Jun 1, 2010.
Published in final edited form as:
PMCID: PMC2746957
NIHMSID: NIHMS130329
Pre-diagnosis reproductive factors and all-cause mortality for women with breast cancer in the Breast Cancer Family Registry
Kelly-Anne Phillips,*1,2,3 Roger L. Milne,*2,4 Dee W. West,5,6 Pamela J. Goodwin,7,8 Graham G. Giles,9 Ellen T. Chang,5,6 Jane C. Figueiredo,10 Michael L. Friedlander,11 Theresa H. M. Keegan,5,6 Gord Glendon,12 Carmel Apicella,2 Frances P O’Malley,13 Melissa C. Southey,14 Irene L. Andrulis,7,12,13,15 Esther M. John,5,6 and John L. Hopper2
1Division of Haematology and Medical Oncology, Peter MacCallum Cancer Centre, Victoria, Australia
2Centre for Molecular, Environmental, Genetic and Analytic Epidemiology, School of Population Health, The University of Melbourne, Victoria, Australia
3Dept of Medicine, St Vincent’s Hospital, The University of Melbourne, Victoria, Australia
4Genetic & Molecular Epidemiology Group, Human Cancer Genetics Program, Spanish National Cancer Research Center (CNIO), Madrid, Spain
5Northern California Cancer Center, Fremont, California, USA
6Division of Epidemiology, Department of Health Research and Policy, Stanford University School of Medicine, Stanford, California, USA
7Samuel Lunenfeld Research Institute, Mount Sinai Hospital, University of Toronto, Toronto, Ontario, Canada
8Departments of Medicine and Public Health Sciences, Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
9Cancer Epidemiology Centre, The Cancer Council Victoria, Carlton, Victoria, Australia
10Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, California, USA
11Prince of Wales Hospital, Randwick, New South Wales, Australia
12Ontario Cancer Genetics Network, Cancer Care Ontario, Toronto, Ontario, Canada
13Department of Pathology and Laboratory Medicine, Mount Sinai Hospital, University of Toronto, Toronto, Ontario, Canada
14Department of Pathology, The University of Melbourne, Victoria, Australia
15Department of Molecular Genetics, University of Toronto, Toronto, Ontario, Canada
*Contributed equally to this work.
Corresponding author: Professor John Hopper, Molecular, Environmental, Genetic and Analytic (MEGA), Epidemiology Centre, University of Melbourne, Level 2, 723 Swanston Street, Carlton, Victoria 3053, AUSTRALIA, Ph 61 3 8344 0697; Fax 61 3 9349-5815, Email: j.hopper/at/unimelb.edu.au
Studies have examined the prognostic relevance of reproductive factors prior to breast cancer (BC) diagnosis, but most have been small and overall their findings inconclusive. Associations between reproductive risk factors and all-cause mortality after BC diagnosis were assessed using a population-based cohort of 3,107 women of white European ancestry with invasive BC (1,130 from Melbourne and Sydney, Australia; 1,441 from Ontario, Canada; and 536 from Northern California, USA). During follow-up with a median of 8.5 years, 567 deaths occurred. At recruitment, questionnaire data were collected on oral contraceptive use, number of full-term pregnancies, age at first full-term pregnancy, time from last full-term pregnancy to BC diagnosis, breastfeeding, age at menarche and menopause and menopausal status at BC diagnosis. Hazard ratios (HR) for all-cause mortality were estimated using Cox proportional hazards models with and without adjustment for age at diagnosis, study center, education and body mass index. Compared with nulliparous women, those who had a child up to 2 years, or between 2 to 5 years, prior to their BC diagnosis were more likely to die. The unadjusted HR estimates were 2.75 (95%CI=1.98–3.83, p<0.001) and 2.20 (95%CI=1.65–2.94, p<0.001), respectively, and the adjusted estimates were 2.25 (95%CI=1.59–3.18, p<0.001) and 1.82 (95%CI=1.35–2.46, p<0.001), respectively). When evaluating the prognosis of women recently diagnosed with BC, the time since last full-term pregnancy should be routinely considered along with other established host and tumor prognostic factors, but consideration of other reproductive factors may not be warranted.
Keywords: Breast cancer, survival, reproductive, outcome, pregnancy
Reproductive factors have a clear role in the etiology of breast cancer (1). It is therefore plausible that they might also influence the course of the disease. The time between last full-term pregnancy and subsequent breast cancer diagnosis has recently emerged as an independent predictor of survival (27). The influences of exposure to other reproductive factors prior to breast cancer diagnosis, such as oral contraceptive (OC) use, breastfeeding, parity (number of full-term pregnancies), age at menarche and menopause and menopausal status on breast cancer prognosis remain uncertain (6, 816). These factors are highly inter-related, and might be confounded with established prognostic factors such as age at diagnosis, body mass index (BMI), and education. The aim of the current study was to examine the potential impact of pre-diagnosis reproductive factors on all-cause mortality after breast cancer using a large, international, multi-centre, population-based cohort.
Subjects were from population-based samples of women recently diagnosed with invasive breast cancer recruited by the Australian (Melbourne and Sydney), Canadian (Ontario) and United States (Northern California) registries of the Breast Cancer Family Registry (Breast CFR) (17). The Breast CFR was established in 1995 with support from the National Cancer Institute (U.S.A.) and is a collaboration of six academic and research institutions. Details of sampling strategies and data and biospecimen collection relevant to this study have been described elsewhere (18). For the current study, women reporting ethnicity other than white European, as well as women who had been found to carry a germline mutation in BRCA1 or BRCA2 (19), were excluded.
A core epidemiology questionnaire was administered at enrolment in the Breast CFR to collect information on demographics, race/ethnicity, personal cancer history, reproductive history and other factors (18). Information on broad categories of treatment received (e.g. type of chemotherapy and hormonal therapy) within the first year after diagnosis was obtained using a validated self-reported treatment questionnaire (20). Detailed information on duration and dose of therapies was not available. Tumor pathology data were obtained by central review or abstracted from the diagnostic report. Vital status of cases was ascertained through various complementary follow-up activities. All three sites contacted treating physicians, reviewed hospital medical records and performed checks by linkage to their local cancer registry and death registry. Information was also obtained directly from the cases or their relatives. In Northern California, cases or their relatives were contacted on an annual basis by phone. In Ontario, information was collected on an annual basis via mailed, self-completed questionnaires. In Australia between 2005 and 2006, cases and their relatives were mailed and, if necessary, phoned, to complete an extensive follow-up epidemiologic and family history questionnaire. Approval from the appropriate institutional review board was obtained at each participating registry and all study participants provided written informed consent.
Statistical Methods
Pre-diagnosis reproductive variables considered as potential prognostic factors in this study were: OC use, defined as use for at least 12 months (ever, duration, years since last use, use before first pregnancy and use before age 20 years), parity (number of full-term pregnancies), age at first full-term pregnancy, time from last full-term pregnancy to breast cancer diagnosis, breastfeeding (ever and duration), age at menarche, age at menopause and menopausal status at breast cancer diagnosis. Reproductive factors were categorized as presented in Table 1. Hazard ratios (HR) and 95% confidence intervals for all-cause mortality associated with each reproductive factor were estimated using multivariate Cox proportional hazards models. Women were censored at the date they were last known to be alive. Time to death was measured from the date of diagnosis. Subjects’ person years were left-truncated at the date of interview. Fitted models initially included age at diagnosis (continuous), study center (Australia, Ontario, Northern California), education (university degree, high school certificate, lower), and BMI (continuous) as covariates. Further sensitivity analyses also included tumor characteristics (size, grade, number of involved axillary nodes, and hormone receptor status), each categorized as presented in Table 1, and hormonal therapy (yes, no), chemotherapy (yes, no) and radiation treatment (yes, no) within the first year after diagnosis as independent covariates. Additional sensitivity analyses were conducted, excluding subjects not known to be free of metastases at diagnosis and/or those with missing information on tumor characteristics.
Table 1
Table 1
Distribution of patients according to both established prognostic factors (personal and tumour characteristics) and pre-diagnosis reproductive factors considered in the current study
Schoenfeld residuals were used to test the proportional hazards assumption. There was evidence of deviation for age at diagnosis, tumour grade and chemotherapy treatment. The final multivariable models therefore included these factors as stratifying variables (age at diagnosis in the categories presented in Table 1) rather than covariates.
HR estimates with floating confidence intervals (21, 22) were generated by including eight dummy variables in Cox regression using "deviation from means coding" (23). The ln(HR) for nulliparity (and its corresponding standard error) was estimated as the negative sum of these eight ln(HR)s using the "lincom" command in Stata. These nine ln(HR)s were then rescaled by subtracting the ln(HR) for nulliparity from each, thereby setting the HR to 1.0 for nulliparity.
All statistical analyses were performed using STATA 10.0 (24) and all hypothesis tests and p-values were two-tailed.
Follow-up subsequent to the date of initial interview and covariate data (age at diagnosis, study center, education level, BMI and months since last full-term pregnancy) were available for 3,107 (98%) of 3,159 eligible women, and of these 567 (18%) had died. Median follow-up was 8.5 years. Subject and tumor characteristics are described in Table 1. Table 2 presents estimated hazard ratios and 95% confidence intervals for the associations between pre-diagnosis reproductive variables and all-cause mortality from both unadjusted and adjusted analyses.
Table 2
Table 2
Hazard ratio (HR) estimates and 95% confidence intervals (CI) for death (all causes) following breast cancer diagnosis associated with reproductive factors prior to diagnosis in unadjusted and adjusted analyses.
Based on unadjusted analyses, having had a recent full-term pregnancy prior to breast cancer diagnosis was associated with poorer survival. Compared with nulliparous women, those who had had a full-term pregnancy within 2 years prior to their breast cancer diagnosis, or within 2 to 5 yrs prior, were more likely to die (HR=2.75, 95%CI=1.98–3.83, p<0.001 and HR=2.20, 95%CI=1.65–2.94, p<0.001, respectively). Mortality was also associated with shorter time since last OC use (HR=0.71 per decade, 95%CI=0.62–0.80, p<0.001) and OC use before age 20 years (HR=1.27, 95%CI=1.02–1.58, p=0.03).
From adjusted analyses, poorer survival was associated only with time from last full-term pregnancy to diagnosis (Table 2). Compared with nulliparous women, those who had had a child within 2 years prior to their breast cancer diagnosis, or within 2 to 5 years prior, were more likely to die (HR=2.25, 95%CI=1.59–3.18, p<0.001 and HR=1.82, 95%CI=1.35–2.46, p<0.001, respectively). This association was further examined by plotting HR estimates and their floating 95% confidence intervals in smaller categories of time from last full-term pregnancy to diagnosis (Figure 1). This confirmed that most of the excess mortality above that for nulliparous women was for parous women who developed breast cancer within 6 years of their last full-term pregnancy, with the highest risk seen for those who developed breast cancer within 2 years of their last full-term pregnancy, and there was virtually no excess risk beyond 6 years.
Figure 1
Figure 1
HR estimates, with floating 95% confidence intervals, relative to nulliparous women, by categories of time between last full-term pregnancy and breast cancer diagnosis. Categories considered are defined by the values labeled on the x-axis, with lower (more ...)
Sensitivity analyses showed that the association between all-cause mortality and time between last full-term pregnancy and breast cancer diagnosis became slightly stronger when restricted to the 2,404 women who tested negative for metastases at diagnosis, with adjusted HR estimates of 2.39 (p<0.001) and 2.11 (p<0.001) for <2 years and 2 to 5 years since last full-term pregnancy, respectively). The same pattern of risk was also observed after including tumor characteristics and treatment within the first year after diagnosis in the adjusted analyses, based on the 1,826 women with complete data (HR=1.97, p=0.04 and HR=2.55, p=0.001, respectively).
The statistically significant unadjusted associations between OC use variables and mortality were no longer evident after adjustment for established determinants of mortality. The apparent association appeared to be due to confounding of OC use with age and time since last full-term pregnancy. After adjustment, the HR per decade for time since last OC use became 0.91, 95% CI=0.74–1.11, p=0.3, and the HR for OC use before age 20 years became 1.04, 95% CI=0.81–1.33, p=0.7. There were no statistically significant associations between all-cause mortality and any of the other pre-diagnosis reproductive factors from either the unadjusted or adjusted analyses, although for menopausal status there was a nominally significant association, but only after adjustment for age, and this disappeared once an additional adjustment was made for treatment, in particular chemotherapy. This may therefore represent a false positive association.
From this large, international, population-based study, we confirmed the previous observation - by us based on a subset of the current study (5), and by others (24, 6, 7, 25) - that recent childbirth prior to diagnosis with breast cancer was associated with increased all-cause mortality, and this association was highly statistically significant. Furthermore, by using floating confidence intervals, we were able to show graphically (see Figure 1) that this association steadily decreases with time since childbirth to become negligible after about 6 years. After adjusting for the known prognostic factors that we had measured, there was no compelling evidence of any prognostic associations with other measured reproductive factors.
The present study has a number of strengths, including the relatively large sample size, long follow-up period and population-based sampling. In particular, our deliberate over-sampling of women with an early age at diagnosis resulted in increased power to study the prognostic associations of pregnancies within a few years prior to diagnosis. Details on pre-diagnosis exposures to reproductive factors were collected uniformly across the three study centers by using a standard questionnaire. Previous studies have shown that self-reports of reproductive history have high validity (26, 27). We also adjusted for potentially important prognostic factors, including tumor characteristics, treatment and host factors (such as age at diagnosis and BMI (28)).
There have been several other large studies of the influence of pre-diagnosis reproductive factors on survival after a breast cancer diagnosis (610, 12, 13, 25). Most studies found associations with some reproductive factors, but the findings have not been consistent.
A population-based study of more than 1,000 women with breast cancer found that women who had four or more children had worse survival, only partly accounted for by confounding due to an association with having given birth within 5 years prior to diagnosis (6). In the current study, there was no evidence for an association between high parity and all-cause mortality. As the other published large studies of parity and survival have not adjusted, as we have, for recency of last birth (8, 10, 13), further examination of this issue is warranted.
Another study of more than 10,000 women with breast cancer found that women who had their first child when aged 20 to 24 years, or 25 to 29 years, had a marginally significantly reduced risk of death compared with those who had their first child before the age of 20 years, after adjustment for age at diagnosis, tumor size, nodal status, tumor grade, treatment, year of diagnosis and parity (RR=0.88; 95%CI=0.78–0.99 and RR=0.80; 95%CI=0.70–0.91 respectively) (12). The current study did not confirm that finding. Like other studies (6, 7), ours did not confirm the finding of Lees and colleagues that women who had breastfed had worse survival after a breast cancer diagnosis than those who had never breastfed (13).
Most recently, Barnett et al (25) showed that there was an association between survival after breast cancer diagnosis and proximity of last full-term pregnancy to study entry, but no association with other reproductive factors such as age at menarche, age at menopause, menopausal status at diagnosis or prior OC use. Although a large study (n=4560), their results are difficult to compare with ours given that it included both prevalent and incident breast cancers, and did not analyze time between last full-term pregnancy and breast cancer diagnosis. Other large recent studies have also found no association between survival and menopausal status, age at menarche, parity, age at first birth (9) or OC use (9, 16); recency of last childbirth prior to breast cancer diagnosis was not examined in these studies .
Our study provides further confirmation that having had a full-term pregnancy within 5 years prior to a breast cancer diagnosis is associated with an adverse prognosis which is not explained by other measured prognostic factors. Unmeasured factors that might be mediating this association include effects of the hormonal milieu of pregnancy such as relative insulin resistance, hyperprolactinaemia, or reduced melatonin levels in the postnatal period (5). These issues need further research. In the meantime, clinicians should be aware that women diagnosed with breast cancer within 5 years following childbirth tend to have a worse outcome than might be suggested just by assessing the standard histopathological and host prognostic factors. Whether more intensive adjuvant treatment would improve their prognosis is not known. The present and other studies suggest that, when evaluating the prognosis of women recently diagnosed with breast cancer, the poorer survival of women who have recently be given birth should be considered, in addition to their tumor and other established prognostic factors. Consideration of other reproductive factors does not appear to be warranted.
ACKNOWLEDGMENTS
The authors would like to thank the thousands of women and their families who participated in this research. We also thank Elaine Maloney and Nayana Weerasooriya from Cancer Care Ontario, Enid Satariano and Jocelyn Koo from the Northern California Cancer Center and Maggie Angelakos, Judi Maskiell and Gillian Dite from the Australian Breast Cancer Family Registry.
Research Support: This study was supported by the National Health and Medical Research Council (NHMRC) of Australia (#145604), the U.S. National Institutes of Health (RO1 CA102740-01A2) and by the National Cancer Institute, National Institutes of Health under RFA # CA-95-011 and through cooperative agreements with members of the Breast Cancer Family Registry (Breast CFR) and Principal Investigators, including Cancer Care Ontario (UO1 CA69467), Columbia University (U01 CA69398), Fox Chase Cancer Center (U01 CA69631), Huntsman Cancer Institute (U01 CA69446), Northern California Cancer Center (U01 CA69417) and the University of Melbourne (U01 CA69638). The content of this manuscript does not necessarily reflect the views or policies of the National Cancer Institute or any of collaborating centers in the Breast CFR, nor does mention of trade names, commercial products, or organizations imply endorsement by the US Government or the Breast CFR. The Australian Breast Cancer Family Study was also supported by the National Health and Medical Research Council of Australia, the New South Wales Cancer Council, the Victorian Health Promotion Foundation. Kelly-Anne Phillips is supported by the Cancer Council Victoria, John Colebatch Clinical Research Fellowship. John Hopper is an Australia Fellow of the NHMRC and Victorian Breast Cancer Research Consortium Group Leader.
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