Abstract
Cruciferous vegetables are a major source of glucosinolate-derived bioactive compounds such as isothiocyanates, which have been shown in animal and in vitro studies to inhibit cancer growth and progression. Few studies have investigated cruciferous vegetable intake after diagnosis and breast cancer outcomes. Using data from the After Breast Cancer Pooling Project, which includes prospective data from US and Chinese breast cancer survivors, we evaluated the association of cruciferous vegetables with breast cancer outcomes. Analyses included 11,390 women diagnosed with stage I–III invasive breast cancer (1990–2006) from four cohorts. Cruciferous vegetable intake (g/day) was assessed using food frequency questionnaires (mean of 22 months post-diagnosis). Study heterogeneity was evaluated by the Q statistic; hazard ratios (HRs) and 95% confidence intervals (CIs) were estimated using delayed-entry Cox regression models stratified by study. After a median follow-up of 9.0 years, 1,725 deaths and 1,421 recurrences were documented. In pooled analyses using study-specific quartiles, cruciferous vegetable intake was not associated with breast cancer outcomes, adjusting for known clinical prognostic factors and selected lifestyle factors. HRs (95%CIs) by increasing quartiles (reference=lowest quartile) were 1.08 (0.93–1.25), 1.01 (0.87–1.18), and 1.10 (0.95–1.28) for recurrence (Ptrend=0.34) and 1.01 (0.88–1.15), 0.97 (0.84–1.11), and 0.99 (0.86–1.13) for total mortality (Ptrend=0.84). No associations were observed for subgroups defined by ER status, stage, or tamoxifen therapy. Cruciferous vegetable intake at approximately two years after diagnosis was not associated with recurrence or mortality. Our results do not support an association between post-diagnosis cruciferous vegetable intake and breast cancer outcomes.
Keywords: dietary factors, cruciferous vegetables, breast cancer, prognosis, survival
INTRODUCTION
Cruciferous vegetables, such as cauliflower, cabbage, bok choy, turnip greens, and broccoli, contain high amounts of glucosinolates, which are hydrolyzed to bioactive compounds such as isothiocyanates (ITCs) and indoles (1). ITCs are known to induce phase II enzymes, such as glutathione-S-transferases (GSTs), which are involved in the detoxification of carcinogens (1, 2). Animal and in vitro studies have shown that ITCs and indoles can induce apoptosis and cell cycle arrest, inhibit invasion and migration, and induce anti-angiogenesis in cancer cells (1, 2, 3–5). ITCs and indole-3-carbinol have been shown to reduce cell proliferation in human breast cancer cells and inhibit mammary tumor growth in vivo (3, 6–8). Some studies have reported an inverse association between higher intakes of cruciferous vegetables and risk of developing breast cancer; however, results are inconsistent (9–12).
To our knowledge, only two reports have prospectively evaluated the association between post-diagnosis cruciferous vegetable intake and breast cancer outcomes. One study, a secondary analysis of the Women’s Healthy Eating & Living (WHEL) Study, reported an inverse association between baseline higher cruciferous vegetable intake and recurrence among tamoxifen users, but not tamoxifen non-users (13). However, this study’s randomized dietary intervention, which was not stratified by tamoxifen use, and achieved a major increase in cruciferous vegetable consumption (14), observed no effect of the intervention on breast cancer recurrence or survival (15). A second cohort study, which did not stratify by tamoxifen use and did not have information on breast cancer recurrence, reported no association between cruciferous intake and breast cancer survival (16).
Given the limited research to date, we used data from the After Breast Cancer Pooling Project (ABCPP), an international collaboration of prospective studies of breast cancer survivors, to investigate the association of cruciferous vegetable intake after diagnosis with breast cancer outcomes.
MATERIALS AND METHODS
The ABCPP includes pooled data on 18,314 breast cancer survivors from four prospective cohorts recruited from US sites and Shanghai, China (17). Three cohorts recruited only breast cancer patients: the Shanghai Breast Cancer Survival Study (SBCSS) (18), the Life After Cancer Epidemiology (LACE) Study (19), and the WHEL Study (20). The WHEL study was an intervention trial (1995–2006) designed to test adoption of a diet high in vegetables, fruit, and fiber and low in fat among breast cancer survivors. The fourth cohort consists of breast cancer patients diagnosed in the Nurses’ Health Study (NHS) (21). Institutional review board approval was obtained for each study, and informed consent was obtained.
Cruciferous vegetable intake was assessed via food frequency questionnaires (FFQ) validated for major nutrients and/or food groups or based on a validated questionnaire. Details on each FFQ have been described (18–22). Vegetable intake was based on FFQs at study enrollment for LACE and WHEL and first post-diagnosis survey for the NHS (Table 1). For the SBCSS, the first post-diagnosis interview was conducted when many patients were receiving chemotherapy/radiotherapy (about 6 months post-diagnosis); therefore the 18-month interview was used. The NHS and LACE study provided data on servings/week, which were converted to grams/day (23).
Table 1.
WHEL (n=1,435) | LACE (n=1,866) | NHS (n=3,902) | SBCSS (n=4,187) | |
---|---|---|---|---|
|
|
|
|
|
Age at diagnosis, mean (SD) | 51.1 (8.9) | 58.6 (10.8) | 64.5 (7.6) | 53.5 (10.0) |
Years of diagnosis, range | 1991–2000 | 1996–2000 | 1990–2004 | 2002–2006 |
Median follow-up, years | 11.5 | 11.8 | 12.0 | 5.3 |
Total deaths, n | 212 | 364 | 641 | 508 |
Recurrences, n | 270 | 342 | 402 | 407 |
Months between diagnosis and dietary assessment, mean, (range) | 23.4 (1.9–48.3) | 22.5 (11.0–38.8) | 23.8 (0.9–47.9) | 18.3 (11.7–34.7) |
Cruciferous (g/day) median (10th–90th ) | 23.8 (6.9–77.9) | 22.4 (4.4–74.0) | 25.4 (5.6–70.7) | 93.0 (39.4–188) |
Types of cruciferous vegetables assessed from food frequency questionnaire | broccoli greens (mustard, turnip, collard) cauliflower/Brussels sprouts watercress cabbage/coleslaw radishes turnips rutabaga | broccoli cooked greens (spinach, mustard greens, turnip greens, collards) cauliflower/cabbage/sauer-kraut/Brussels sprouts coleslaw | broccoli Kale/mustard greens/chard cauliflower cabbage/coleslaw Brussels sprouts | greens and Chinese greens, cabbage (Chinese cabbage, bok choy, green cabbage), cauliflower, and turnips |
Total number of separate items for cruciferous vegetables | 8 | 4 | 5 | 5 |
Outcome Ascertainment
Each cohort followed participants to ascertain breast cancer outcomes, including breast cancer recurrence (defined as recurrence/metastasis or development of new primary breast cancer) and mortality outcomes. New primary breast cancers were not available from the NHS. Detailed methods regarding outcome ascertainment and cohort follow-up have been published (17–21).
Statistical Analysis
Women were excluded for the following reasons: breast cancer diagnosis before 1990 (n=2,960), stage IV breast cancer or missing stage (n=420), death or loss to follow-up before dietary assessment (n=27), missing cruciferous vegetable intake (n=1,703), first post-diagnosis dietary measure >5 years after diagnosis (n=296), and WHEL study intervention group (n=1,537). The final sample size included 11,390 women. We present pooled results using both study-specific quartiles and common absolute cutpoints (based on estimated servings/day (e.g., ½ cup of cooked broccoli=78 grams) and adequate sample size).
We used delayed-entry Cox proportional hazards regression models to estimate study-specific hazard ratios (HRs) and 95% confidence intervals (CIs). Entry date was date of enrollment (LACE, WHEL), first post-diagnosis questionnaire (NHS), or 18-month interview (SBCSS). Exit date was date of death (or recurrence/metastasis for the recurrence analysis) or date of last contact (i.e., date of last follow-up survey or last registry linkage, whichever was most recent). The Q statistic was used to test for heterogeneity in risk estimates across studies (24). As p-values for the Q statistic were not statistically significant, we conducted a pooled analysis using combined data with Cox regression models stratified by study. Covariates, available for all four cohorts and selected a priori, included age at diagnosis, AJCC 6th edition tumor stage, estrogen receptor (ER)/progesterone receptor (PR) status, cancer treatment (surgery, chemotherapy, radiotherapy, hormonal therapy), education, race/ethnicity, menopausal status, recreational physical activity in metabolic equivalent (MET)-hours per week (25), smoking, and body mass index (BMI).
Potential effect modifiers included ER status and stage. To compare with the previous WHEL study report, we also evaluated tamoxifen use as a potential effect modifier (13). Multiplicative interactions were tested by using the −2 log likelihood ratio test statistic, comparing models with and without the interaction terms. Tests for linear trend were calculated using the median intakes for each quartile and modeling these as continuous variables. The proportional hazards assumption was evaluated by testing the statistical significance of interaction terms for each covariate and survival time. The assumption of proportional hazards was violated for two covariates (stage and ER/PR status); hence, the interaction terms for these covariates with survival time were included in final Cox models, as appropriate. All analyses were performed using SAS (version 9.3; SAS Institute, Cary, NC). Tests of statistical significance were two-sided and P-values <0.05 were considered statistically significant.
RESULTS
After a median follow-up of 9.0 years, 1,725 deaths and 1,421 recurrences were documented. Table 1 displays select cohort characteristics and amount and types of cruciferous vegetables by cohort. Chinese women consumed the highest amount of cruciferous vegetables (median=93.1 g/day); cruciferous vegetable intake was similar by US cohort.
US and Chinese breast cancer survivors who consumed higher amounts of cruciferous vegetables after diagnosis tended to be younger (data not shown). Adjusting for age, higher intake of cruciferous vegetables was associated with both higher education and recreational physical activity levels (among US and Chinese women), while current smoking was associated with lower intake of cruciferous vegetables (among US women only), and BMI and clinical characteristics were not associated with cruciferous vegetable intake (data not shown).
Table 2 presents multivariable HRs for the association of cruciferous vegetable intake and breast cancer outcomes. Adjusting for age at diagnosis, stage, ER/PR status, cancer treatment, socio-demographics, smoking, BMI, exercise, and menopausal status, cruciferous vegetable intake was not associated with breast cancer recurrence or total mortality. Additional adjustment for red meat intake (g/day) did not alter results (data not shown).
Table 2.
Recurrenceb | Total Mortality | ||||||
---|---|---|---|---|---|---|---|
Cruciferous vegetables | Cohort | Events | HR | (95% CI) | Events | HR | (95% CI) |
Study-specific quartiles (g/day)c | |||||||
Q1 | 2,833 | 336 | 1.00 | (reference) | 454 | 1.00 | (reference) |
Q2 | 2,810 | 357 | 1.08 | (0.93–1.25) | 427 | 1.01 | (0.88–1.15) |
Q3 | 2,905 | 347 | 1.01 | (0.87–1.18) | 419 | 0.97 | (0.84–1.11) |
Q4 | 2,842 | 381 | 1.10 | (0.95–1.28) | 425 | 0.99 | (0.86–1.13) |
Ptrend | 0.34 | 0.84 | |||||
Common Cutpoints (g/day)e | |||||||
<39 | 5,447 | 738 | 1.00 | (reference) | 934 | 1.00 | (reference) |
39–78 | 2,806 | 341 | 1.00 | (0.88–1.15) | 378 | 0.89 | (0.79–1.01) |
≥78 | 3,137 | 342 | 1.05 | (0.89–1.24) | 413 | 1.03 | (0.88–1.20) |
Ptrend | 0.60 | 0.82 |
HRs were from delayed-entry Cox proportional hazards regression models with study as a stratification variable and adjusted for age at diagnosis, ER/PR status, TNM stage, chemotherapy, surgery, radiotherapy, hormonal therapy, smoking, BMI, exercise, menopausal status, race/ethnicity, and education.
566 women were excluded where disease-free follow-up time was ≤ date of exposure/enrollment.
Study-specific quartiles were as follows: <10.7, 10.7–22.4, 22.4–43.5, ≥ 43.5 (LACE); <13.0, 13.0-<23.8, 23.8–44.6, ≥ 44.6 (WHEL); <15.4, 15.4–25.4, 25.4–43.2, ≥ 43.2 (NHS); <61.5, 61.5–93, 93–138.0, ≥ 138.0 (SBCSS).
P-values for heterogeneity by study were 0.98 and 0.69 for recurrence and total mortality, respectively (using study-specific quartiles). P-values for heterogeneity by study were 0.89 and 0.91 for recurrence and total mortality, respectively (using common cutpoints).
78 grams/day is approximately equivalent to ½ cup/day of broccoli.
We also investigated cruciferous vegetable intake with breast-cancer specific and non-breast cancer mortality. Compared with quartile 1, HRs (95%CIs) by increasing quartiles were 1.15 (0.97–1.37), 1.01 (0.85–1.20), and 1.09 (0.92–1.30) for breast cancer specific-mortality (Ptrend=0.72), and 0.83 (0.66–1.02), 0.94 (0.76–1.16), and 0.86 (0.69–1.08) for non-breast cancer mortality (Ptrend=0.77). Differences in dietary assessments precluded our ability to assess associations between specific types of cruciferous vegetables and breast cancer outcomes across all cohorts, with the exception of broccoli across the US cohorts. Compared with quartile 1, HRs (95% CIs) by increasing tertiles of broccoli intake (g/day) were 1.00 (0.86–1.17) and 1.04 (0.89–1.20) for recurrence and 0.95 (0.83–1.10) and 0.94 (0.82–1.08) for mortality).
The association of cruciferous vegetables and breast cancer outcomes did not vary by ER status or stage (Table 3). We also examined the association of cruciferous vegetables and breast cancer outcomes by tamoxifen therapy (13), and none of the associations varied by tamoxifen use (Table 3).
Table 3.
Cruciferous Vegetable intake | Recurrence
|
Total Mortality
|
||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|
ER+ | ER− | ER+ | ER− | |||||||||
|
|
|||||||||||
Events | HR | (95% CI) | Events | HR | (95% CI) | Events | HR | (95% CI) | Events | HR | (95% CI) | |
|
|
|||||||||||
Study-specific quartiles (g/day)b | ||||||||||||
Q1 | 252 | 1.00 | (reference) | 76 | 1.00 | (reference) | 332 | 1.00 | (reference) | 111 | 1.00 | (reference) |
Q2 | 254 | 0.99 | (0.83–1.18) | 93 | 1.28 | (0.94–1.74) | 311 | 0.98 | (0.84–1.15) | 106 | 1.00 | (0.76–1.31) |
Q3 | 248 | 0.95 | (0.80–1.13) | 89 | 1.15 | (0.84–1.57) | 305 | 0.96 | (0.82–1.12) | 99 | 0.89 | (0.67–1.17) |
Q4 | 281 | 1.05 | (0.88–1.25) | 90 | 1.26 | (0.92–1.72) | 299 | 0.93 | (0.79–1.09) | 112 | 1.11 | (0.84–1.45) |
Ptrend | 0.65 | 0.27 | 0.35 | 0.13 | ||||||||
Pinteraction | 0.77 | 0.53 | ||||||||||
Stage I–II | Stage III | Stage I–II | Stage III | |||||||||
|
||||||||||||
Study-specific quartiles (g/day) | ||||||||||||
Q1 | 234 | 1.00 | (reference) | 102 | 1.00 | (reference) | 331 | 1.00 | (reference) | 123 | 1.00 | (reference) |
Q2 | 259 | 1.11 | (0.93–1.33) | 98 | 1.02 | (0.77–1.36) | 316 | 1.05 | (0.89–1.22) | 111 | 0.95 | (0.73–1.23) |
Q3 | 252 | 1.02 | (0.85–1.22) | 95 | 0.99 | (0.75–1.33) | 289 | 0.92 | (0.79–1.08) | 130 | 1.10 | (0.85–1.41) |
Q4 | 274 | 1.14 | (0.95–1.36) | 107 | 1.05 | (0.79–1.39) | 304 | 1.02 | (0.87–1.20) | 121 | 0.94 | (0.73–1.22) |
Ptrend | 0.28 | 0.82 | 0.60 | 0.72 | ||||||||
Pinteraction | 0.44 | 0.76 | ||||||||||
Tamoxifen | No Tamoxifen | Tamoxifen | No Tamoxifen | |||||||||
|
|
|||||||||||
Study-specific quartiles (g/day)c | ||||||||||||
Q1 | 203 | 1.00 | (reference) | 47 | 1.00 | (reference) | 256 | 1.00 | (reference) | 69 | 1.00 | (reference) |
Q2 | 192 | 0.93 | (0.76–1.13) | 59 | 1.24 | (0.84–1.83) | 241 | 0.97 | (0.81–1.15) | 62 | 0.95 | (0.67–1.35) |
Q3 | 197 | 0.94 | (0.77–1.15) | 50 | 1.01 | (0.68–1.52) | 228 | 0.92 | (0.77–1.11) | 71 | 1.10 | (0.78–1.53) |
Q4 | 213 | 1.02 | (0.84–1.24) | 67 | 1.19 | (0.80–1.75) | 225 | 0.91 | (0.76–1.10) | 73 | 1.04 | (0.74–1.47) |
Ptrend | 0.76 | 0.78 | 0.30 | 0.87 | ||||||||
Pinteraction | 0.53 | 0.28 |
HRs were from delayed entry Cox proportional hazards regression models adjusted for age at diagnosis, ER/PR status (when applicable), TNM stage (when applicable), surgery, chemotherapy, radiotherapy, hormonal therapy (when applicable), smoking, BMI, exercise, menopausal status, race/ethnicity, and education. Study was included as a stratification variable.
Analyses stratified by ER status exclude 320 women missing ER status.
Among women with ER+ cancer (n=8,257), exclude women missing tamoxifen therapy information (n=38).
DISCUSSION
In this prospective pooled analysis of 11,390 breast cancer survivors from the U.S. and China, cruciferous vegetable intake assessed via FFQ at approximately 2 years after diagnosis was not associated with breast cancer recurrence or total mortality, overall or among subgroups defined by ER status, stage, and tamoxifen therapy. Our findings, from the largest study to date, do not support an association between intake of cruciferous vegetables after diagnosis and breast cancer outcomes.
In 2007, the WHEL Study reported that a major increase in vegetable (including cruciferous), fruit, and fiber intake, and a decrease in dietary fat intake was not associated with breast cancer outcomes (15). Cruciferous vegetable intake in the intervention group increased from 0.46 to 0.70 servings/day at year 1, and about half this increase was maintained through year 4 (14). In 2011, a secondary cohort analysis of the WHEL study reported a statistically significant inverse association for higher cruciferous vegetable intake at baseline and recurrence among tamoxifen users, but not among tamoxifen non-users (13). In our analysis, which included WHEL participants from the control group only, cruciferous vegetable intake was not associated with breast cancer outcomes either among tamoxifen users or non-users. We also conducted an analysis including the intervention group, and results were similar to presented findings (data not shown). Our overall findings are consistent with a report by Beasley and colleagues (n=4,441), which reported no association of cruciferous vegetable intake with breast cancer survival, however, findings were not reported by tamoxifen therapy (16).
Strengths of the present study include the large sample size and the inclusion of well-designed prospective cohort studies from the US and Shanghai, China with information on known clinical prognostic factors and post-diagnosis lifestyle factors. By conducting a pooled analysis with individual study data, we were able to use standardized statistical methods and definitions of covariates, thereby minimizing heterogeneity.
One limitation was that we were unable to examine individual types of cruciferous vegetables across cohorts due to differences in cruciferous vegetable questions on the FFQs by cohorts (see Table 1). The amount and type of bioactive compounds metabolized from cruciferous vegetables, such as ITCs, differ by type of cruciferous vegetable (1), and some studies have reported no association for total cruciferous vegetables and risk of developing breast cancer, but observed associations for specific types (e.g., broccoli, turnips) (10, 11). However, a recent pooled analysis of 20 studies reported no association of cruciferous vegetables (any type) or specific types with risk of developing breast cancer (12). Further, we found no association between broccoli and outcomes among ABCPP US participants. Finally, despite using different questionnaires, intake of total cruciferous vegetables across the US cohorts was comparable, suggesting similar dietary components were assessed.
Total energy intake, fruit intake, and non-cruciferous vegetable intake were not available across all studies to consider as potential confounders, as the SBCSS used a 29-item abbreviated FFQ focused on habitual consumption of major food groups of interest (i.e., cruciferous vegetables, soy foods, meat, and fish). However, the US studies had total energy intake available, and results among US women were unaltered after adjustment for this factor (data not shown). We also lacked data on measured ITCs, one of the major biological compounds in cruciferous vegetables thought to play a role in cancer preventative mechanisms (1, 2, 5, 7, 8). One study reported an inverse association between risk of developing breast cancer and urinary ITC levels, but no association for cruciferous vegetable intake based on an FFQ and breast cancer (9). The amount of ITCs varies by type of cruciferous vegetable, geographical region, and cooking method (e.g., boiling, steaming, or raw consumption); therefore, intake based on FFQs may not be sensitive enough to adequately reflect internal exposure to ITCs (1, 9). Inter-individual differences in metabolism of ITCs, and consumption of other types of vegetables, may also influence internal exposure (4). Future studies that directly measure urinary ITCs may be informative.
In conclusion, our results from a pooled prospective analysis of 11,390 US and Chinese breast cancer survivors, do not provide evidence for an association between post-diagnosis cruciferous vegetable consumption and breast cancer prognosis, overall or by ER status, stage, or tamoxifen therapy. However, direct measurement of urinary ITCs may be more informative, and future studies should consider measurement of both cruciferous vegetable intake and biomarkers of ITC exposure.
Acknowledgments
Financial support: This work was supported by the National Cancer Institute at the National Institutes of Health (Grant number 3R01 CA118229-03S1). SN was partly supported by grant 5K12ES015855 from the National Institute of Environmental Health Sciences. EMP was supported by grant T32 CA009001 from the National Cancer Institute. The parent grants for each individual cohort included are as follows: Women’s Healthy Eating & Living Study (Susan G. Komen Foundation, #KG100988), Life After Cancer Epidemiology Study (National Cancer Institute, R01 CA129059), Nurses’ Health Study (P01 CA87969), Shanghai Breast Cancer Survival Study (Department of Defense Breast Cancer Research Program (DAMD 17-02-1-0607) and the National Cancer Institute (R01 CA118229)).
The authors wish to thank the participants and research staff of the Shanghai Breast Cancer Survival Study, the Life After Cancer Epidemiology Study, the Nurses’ Health Study, and the Women’s Healthy Eating & Living Study.
Abbreviations
- ABCPP
After Breast Cancer Pooling Project
- BMI
Body mass index
- CIs
Confidence intervals
- ER
Estrogen receptor
- HRs
Hazard ratios
- LACE
Life After Cancer Epidemiology
- FFQ
Study Food frequency questionnaire
- MET
Metabolic equivalent
- NHS
Nurses’ Health Study
- PR
Progesterone receptor
- SBCSS
Shanghai Breast Cancer Survival Study
- WHEL
Women’s Healthy Eating & Living Study
Footnotes
Conflicts of interest: The authors have no conflicts of interest to disclose.
References
- 1.International Agency for Research on Cancer, World Health Organization. IARC Handbooks of Cancer Prevention: Cruciferous Vegetables, Isothiocyanates and Indoles. Vol. 9. Lyon, France: IARC Press; 2004. [Google Scholar]
- 2.Navarro SL, Li F, Lampe JW. Mechanisms of action of isothiocyanates in cancer chemoprevention: an update. Food Funct. 2011;2(10):579–87. doi: 10.1039/c1fo10114e. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3.Aggarwal BB, Ichikawa H. Molecular targets and anticancer potential of indole-3-carbinol and its derivatives. Cell Cycle. 2005;4(9):1201–15. doi: 10.4161/cc.4.9.1993. [DOI] [PubMed] [Google Scholar]
- 4.Higdon JV, Delage B, Williams DE, Dashwood RH. Cruciferous vegetables and human cancer risk: epidemiologic evidence and mechanistic basis. Pharmacological Research. 2007;55(3):224–36. doi: 10.1016/j.phrs.2007.01.009. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.Zhang Y, Yao S, Li J. Vegetable-derived isothiocyanates: anti-proliferative activity and mechanism of action. Proc Nutr Soc. 2006;65(1):68–75. doi: 10.1079/pns2005475. [DOI] [PubMed] [Google Scholar]
- 6.Rahman KM, Aranha O, Sarkar FH. Indole-3-carbinol (I3C) induces apoptosis in tumorigenic but not in nontumorigenic breast epithelial cells. Nutr Cancer. 2003;45(1):101–12. doi: 10.1207/S15327914NC4501_12. [DOI] [PubMed] [Google Scholar]
- 7.Tseng E, Scott-Ramsay EA, Morris ME. Dietary organic isothiocyanates are cytotoxic in human breast cancer MCF-7 and mammary epithelial MCF-12A cell lines. Exp Biol Med (Maywood) 2004;229(8):835–42. doi: 10.1177/153537020422900817. [DOI] [PubMed] [Google Scholar]
- 8.Singh SV, Kim SH, Sehrawat A, Arlotti JA, Hahm ER, Sakao K, et al. Biomarkers of phenethyl isothiocyanate-mediated mammary cancer chemoprevention in a clinically relevant mouse model. J Natl Cancer Inst. 2012;104(16):1228–39. doi: 10.1093/jnci/djs321. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Fowke JH, Chung FL, Jin F, Qi D, Cai Q, Conaway C, et al. Urinary isothiocyanate levels, brassica, and human breast cancer. Cancer Res. 2003;63(14):3980–6. [PubMed] [Google Scholar]
- 10.Ambrosone CB, McCann SE, Freudenheim JL, Marshall JR, Zhang YS, Shields PG. Breast cancer risk in premenopausal women is inversely associated with consumption of broccoli, a source of isothiocyanates, but is not modified by GST genotype. Journal of Nutrition. 2004;134(5):1134–1138. doi: 10.1093/jn/134.5.1134. [DOI] [PubMed] [Google Scholar]
- 11.Lee SA, Fowke JH, Lu W, Ye C, Zheng Y, Cai Q, et al. Cruciferous vegetables, the GSTP1 Ile105Val genetic polymorphism, and breast cancer risk. Am J Clin Nutr. 2008;87(3):753–60. doi: 10.1093/ajcn/87.3.753. [DOI] [PubMed] [Google Scholar]
- 12.Jung S, Spiegelman D, Baglietto L, Bernstein L, Boggs DA, van den Brandt PA, et al. Fruit and vegetable intake and risk of breast cancer by hormone receptor status. J Natl Cancer Inst. 2013;105(3):219–36. doi: 10.1093/jnci/djs635. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.Thomson CA, Rock CL, Thompson PA, Caan BJ, Cussler E, Flatt SW, et al. Vegetable intake is associated with reduced breast cancer recurrence in tamoxifen users: a secondary analysis from the Women’s Healthy Eating and Living Study. Breast Cancer Research and Treatment. 2011;125(2):519–527. doi: 10.1007/s10549-010-1014-9. [DOI] [PubMed] [Google Scholar]
- 14.Pierce JP, Newman VA, Natarajan L, Flatt SW, Al-Delaimy WK, Caan BJ, et al. Telephone counseling helps maintain long-term adherence to a high-vegetable dietary pattern. Journal of Nutrition. 2007;137(10):2291–6. doi: 10.1093/jn/137.10.2291. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.Pierce JP, Natarajan L, Caan BJ, Parker BA, Greenberg ER, Flatt SW, et al. Influence of a diet very high in vegetables, fruit, and fiber and low in fat on prognosis following treatment for breast cancer: the Women’s Healthy Eating and Living (WHEL) randomized trial. Jama. 2007;298(3):289–98. doi: 10.1001/jama.298.3.289. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.Beasley JM, Newcomb PA, Trentham-Dietz A, Hampton JM, Bersch AJ, Passarelli MN, et al. Post-diagnosis dietary factors and survival after invasive breast cancer. Breast Cancer Res Treat. 2011;128(1):229–36. doi: 10.1007/s10549-010-1323-z. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Nechuta SJ, Caan BJ, Chen WY, Flatt SW, Lu W, Patterson RE, et al. The After Breast Cancer Pooling Project: rationale, methodology, and breast cancer survivor characteristics. Cancer Causes Control. 2011;22(9):1319–31. doi: 10.1007/s10552-011-9805-9. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Shu XO, Zheng Y, Cai H, Gu K, Chen Z, Zheng W, et al. Soy food intake and breast cancer survival. JAMA. 2009;302(22):2437–43. doi: 10.1001/jama.2009.1783. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19.Caan B, Sternfeld B, Gunderson E, Coates A, Quesenberry C, Slattery ML. Life After Cancer Epidemiology (LACE) study: A cohort of early stage breast cancer survivors (United states) Cancer Causes & Control. 2005;16(5):545–556. doi: 10.1007/s10552-004-8340-3. [DOI] [PubMed] [Google Scholar]
- 20.Pierce JP, Faerber S, Wright FA, Rock CL, Newman V, Flatt SW, et al. A randomized trial of the effect of a plant-based dietary pattern on additional breast cancer events and survival: the Women’s Healthy Eating and Living (WHEL) Study. Control Clin Trials. 2002;23(6):728–56. doi: 10.1016/s0197-2456(02)00241-6. [DOI] [PubMed] [Google Scholar]
- 21.Colditz GA, Hankinson SE. The Nurses’ Health Study: Lifestyle and health among women. Nature Reviews Cancer. 2005;5(5):388–396. doi: 10.1038/nrc1608. [DOI] [PubMed] [Google Scholar]
- 22.Martinez ME, Marshall JR, Graver E, Whitacre RC, Woolf K, Ritenbaugh C, et al. Reliability and validity of a self-administered food frequency questionnaire in a chemoprevention trial of adenoma recurrence. Cancer Epidemiol Biomarkers Prev. 1999;8(10):941–6. [PubMed] [Google Scholar]
- 23.U.S. Department of Agriculture, Agricultural Research Service. USDA National Nutrient Database for Standard Reference, Release 25. [last acessed 05-17-13];Nutrient Data Laboratory Home Page. 2012 http://www.ars.usda.gov/ba/bhnrc/ndl.
- 24.DerSimonian R, Laird N. Meta-analysis in clinical trials. Control Clin Trials. 1986;7(3):177–88. doi: 10.1016/0197-2456(86)90046-2. [DOI] [PubMed] [Google Scholar]
- 25.Ainsworth BE, Haskell WL, Leon AS, Jacobs DR, Jr, Montoye HJ, Sallis JF, et al. Compendium of physical activities: classification of energy costs of human physical activities. Med Sci Sports Exerc. 1993;25(1):71–80. doi: 10.1249/00005768-199301000-00011. [DOI] [PubMed] [Google Scholar]