DOI:10.1093/jnci/djs635 © The Author 2013. Published by Oxford University Press. All rights reserved. .For Permissions, please e-mail: [email protected]
Article
Fruit and Vegetable Intake and Risk of Breast Cancer by Hormone Receptor Status Seungyoun Jung, Donna Spiegelman, Laura Baglietto, Leslie Bernstein, Deborah A. Boggs, Piet A. van den Brandt, Julie E. Buring, James R. Cerhan, Mia M. Gaudet, Graham G. Giles, Gary Goodman, Niclas Hakansson, Susan E. Hankinson, Kathy Helzlsouer, Pamela L. Horn-Ross, Manami Inoue, Vittorio Krogh, Marie Lof, Marjorie L. McCullough, Anthony B. Miller, Marian L. Neuhouser, Julie R. Palmer, Yikyung Park, Kim Robien, Thomas E. Rohan, Stephanie Scarmo, Catherine Schairer, Leo J. Schouten, James M. Shikany, Sabina Sieri, Schoichiro Tsugane, Kala Visvanathan, Elisabete Weiderpass, Walter C. Willett, Alicja Wolk, Anne Zeleniuch-Jacquotte, Shumin M. Zhang, Xuehong Zhang, Regina G. Ziegler, Stephanie A. Smith-Warner
Manuscript received February 27, 2012; revised November 28, 2012; accepted November 29, 2012. Downloaded from
Correspondence to: Seungyoun Jung, ScD, Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Longwood Avenue, Boston, MA 02115 (e-mail: [email protected]). http://jnci.oxfordjournals.org/ Background Estrogen receptor–negative (ER−) breast cancer has few known or modifiable risk factors. Because ER− tumors account for only 15% to 20% of breast cancers, large pooled analyses are necessary to evaluate precisely the suspected inverse association between fruit and vegetable intake and risk of ER− breast cancer.
Methods Among 993 466 women followed for 11 to 20 years in 20 cohort studies, we documented 19 869 estrogen receptor positive (ER+) and 4821 ER− breast cancers. We calculated study-specific multivariable relative risks (RRs) and 95% confidence intervals (CIs) using Cox proportional hazards regression analyses and then combined them using a random-effects model. All statistical tests were two-sided. at University of Central Florida on September 29, 2013 Results Total fruit and vegetable intake was statistically significantly inversely associated with risk of ER− breast cancer but not with risk of breast cancer overall or of ER+ tumors. The inverse association for ER− tumors was observed primarily for vegetable consumption. The pooled relative risks comparing the highest vs lowest quintile of total vegetable consumption were 0.82 (95% CI = 0.74 to 0.90) for ER− breast cancer and 1.04 (95% CI = 0.97 to 1.11) for + ER breast cancer (Pcommon-effects by ER status < .001). Total fruit consumption was non-statistically significantly asso- ciated with risk of ER− breast cancer (pooled multivariable RR comparing the highest vs lowest quintile = 0.94, 95% CI = 0.85 to 1.04).
Conclusions We observed no association between total fruit and vegetable intake and risk of overall breast cancer. However, vegetable consumption was inversely associated with risk of ER− breast cancer in our large pooled analyses.
J Natl Cancer Inst 2013;105:219–236
Breast cancer is a heterogeneous disease. Expression of the estro- studies (5–7) have recently investigated the association between gen receptor (ER) can be used to explain, in part, some of the dif- fruit and vegetable intake and risk of breast cancer by receptor ferences in etiology, and clinical characteristics of breast cancer and status. All three studies found that women who consumed higher survival rates among breast cancer patients (1–3). Breast tumors levels of fruits and vegetables had a 32% to 50% lower risk of ER− that express the ER (ER+ tumors) are more strongly associated with breast cancer compared with women who consumed low levels of hormone-related factors than tumors that do not express the ER fruits and vegetables. In another cohort study that evaluated only (ER− tumors). Classic risk factors, such as late age at first birth and dietary patterns, women consuming a high fruit or salad pattern number of births, are more consistently associated with risk of ER+ were observed to have a 45% lower risk of ER− breast cancer (8). breast cancer than with risk of ER− breast cancer (1). In addition, Because the number of studies examining ER− breast cancer is few risk factors have been identified for ER− breast cancer. limited, more evidence is needed to examine the role of diet in Fruit and vegetable intake has been hypothesized to reduce ER− breast cancer. the risk of breast cancer, but the current evidence is inconclusive. One challenge in examining ER− breast cancer in epidemiologic A recent meta-analysis of 14 cohort studies reported a statistically studies is that ER− breast cancer accounts for only 15% to 20% of significant 11% reduced risk of breast cancer overall comparing breast cancers (9). Thus, in most studies, the number of ER− breast high vs low fruit and vegetable intake; results were not reported for cancer case patients is relatively low, which affects the power to breast cancer subtypes defined by receptor status (4). Three cohort detect modest associations with certainty. jnci.oxfordjournals.org JNCI | Articles 219 Therefore, with the advantage of a large number of case patients, education, physical activity, smoking history, and family history of we evaluated the relation between fruit and vegetable consumption breast cancer. and risk of breast cancer by ER status in a pooled analysis of 20 pro- spective cohorts. These analyses expand our prior analyses of fruit Case Ascertainment and vegetable consumption and breast cancer risk (10) by including Incident invasive breast cancer case patients in each study were 12 more prospective studies and increasing the follow-up time for identified by follow-up questionnaires and subsequent review most of the studies in the original analyses. In addition, only two of medical records (28–30), linkage to cancer registries (31–41), of the 20 studies in this pooled analysis have previously examined or both (42–45). Some studies also used linkage to mortality associations specifically with fruit and vegetable consumption and registries to identify case patients (16,28,30,33,34,39,43,45,46). We risk of ER− breast cancer (5, 6). In secondary analyses, we examined considered case patients with borderline hormone receptor status tumors classified by progesterone receptor (PR) status. as positive for that hormone receptor.
Statistical Analysis Methods After applying the exclusion criteria used by each study, we further Study Population excluded participants with a prior cancer diagnosis (except non- The Pooling Project of Prospective Studies of Diet and Cancer melanoma skin cancer) at baseline, with energy intakes beyond 3
(Pooling Project) is a long-standing international consortium of pro- standard deviations from the study-specific loge-transformed mean spective cohort studies (11). The analyses conducted here included energy intake, and with missing data for total fruit or total vegeta- 20 studies (Table 1) that met all of the following criteria: 1) at least ble intake. one publication on any diet and cancer association; 2) comprehen- Associations for total, ER−, ER+, PR−, and PR+ breast cancer sive assessment of usual dietary intake; 3) validation of the dietary were evaluated separately in each study by Cox proportional assessment method or a closely related instrument; and 4) at least 25 hazards regression analyses (47) using SAS PROC PHREG (48). incident breast cancer case patients of the specific hormone recep- The Netherlands Cohort Study was analyzed as a case–cohort tor subtype being evaluated in that analysis. Each study included in study (49). The Nurses’ Health Study was analyzed as two separate our analyses was reviewed and approved by the institutional review cohorts (1980–1986 Nurses’ Health Study[a]; 1986–2006 Nurses’ boards of the institution where the study was conducted. Health Study[b]) to take advantage of the more detailed dietary assessment in 1986. Because blocks of person-time in different time Assessment of Dietary and Nondietary Factors periods are asymptotically uncorrelated according to survival data Dietary intake was assessed by a validated food frequency ques- theory, pooling of estimates from these two time periods produces tionnaire (FFQ) at baseline in each study. Each FFQ listed three valid estimates (50). For all cohorts, person-years of follow-up to 15 fruit and six to 30 vegetable items. Due to the varying fre- were calculated from the date the baseline questionnaire was quency responses and portion sizes in the diet assessment methods returned or completed to the date of diagnosis of incident breast across studies, fruit and vegetable intake was expressed as grams cancer, death, loss to follow-up (if applicable), or end of follow-up, consumed per day (10). whichever came first. Breast cancer case patients without hormone We analyzed intakes of total fruit and vegetables, total fruit, and receptor status information or with a different subtype than the total vegetables. To examine the potential beneficial or adverse effect one being evaluated were censored at their date of diagnosis. Age of particular bioactive compounds (12), we also analyzed botanically at baseline and year of baseline questionnaire return were used as defined fruit and vegetable subgroups (13) and specific fruits and stratification variables so we could account for age, calendar time, vegetables that were assessed as separate items in more than half and time since entry into the study. In multivariable analyses, for the cohorts. Because of their high protein or starch content, mature studies with more than 200 case patients of the outcome evaluated, beans and potatoes were excluded from the total vegetable group we included the confounding variables (see Table 2 for a list of (14) but were included in their relevant botanical group. Pickled the confounding variables and their categorizations) directly in fruit and vegetables were also excluded from the fruit and vegeta- the model. Otherwise, we used propensity scores to adjust for ble groups because they contain potentially carcinogenic nitrates confounding (51–53). Missing indicator variables were created for and preservatives (15). In each study, nutrient intake estimates from missing responses for each measured confounding variable in a the FFQ used in that study or a closely related instrument were study, if applicable. compared with multiple 24-hour dietary recalls or dietary records. We pooled the study-specific rate ratios using a random-effects However, only five studies compared intakes between the FFQ and model (54) weighted by the sum of the inverse of the variance and comparison methods for intakes of total fruit and vegetables (16), the estimated between-studies variance components. Between- total vegetables (17–19), total fruit (17–19), or individual fruits or studies heterogeneity was evaluated using the Q statistic (54,55). vegetables (20); correlations that compared intake estimates from To test the assumption of proportional hazards, we added an inter- the FFQs and comparison methods for these fruit and vegetable action term between age and fruit and vegetable intake into the groups or items exceeded 0.35. Validity correlations for folate, vita- model and pooled the study-specific parameter estimates of the min C, and carotene intakes, which are closely related to fruit and interaction term using the random-effects model (54). We observed vegetable intake (21), ranged 0.3 to 0.65 (11,17,20,22–27). no violation of the proportional hazards assumption. At baseline, each study collected information on age, height, We modeled fruit and vegetable intake using study-specific and body weight. Most studies also measured reproductive factors, quintiles and categories defined by common absolute intake cut
220 Articles | JNCI Vol. 105, Issue 3 | February 6, 2013 Median 68 (20–196) 116 (40–255) 116 (10th–90th) 217 (100–392) 217 162 (86–287) 162 162 (59–389) 162 157 (66–233) 157 195 (91–383) 195 147 (61–302) 147 150 (61–305) 150 135 (51–288) 135 157 (68–325) 157 220 (102–432) 200 (75–424) 3 8 8 8 9 11 10 16 13 13 13 14 25 No. of No. Total Vegetables, g/day Vegetables, Total questions Median (10th–90th) 118 (32–193) 118 173 (33–388) 173 152 (25–390) 152 195 (52–396) 195 180 (52–380) 180 182 (34–511) 182 290 (94–595) 207 (80–393) 289 (77–696) 392 (136–835) 338 (130–625) 291 (97–537) 208 (46–500) Total Fruits, g/day Fruits, Total 4 7 7 6 5 7 11 11 12 13 19 15 15 No. of No. questions — § 17 19 14 PR 46 72 55 42 32 64 20 28 43 missing, % missing, − 82 78 48 PR 199 140 204 786 240 388 561 625 270 331 + 87 168 163 296 361 420 309 667 326 PR 1117 1917 1483 1544 ER 17 15 14 16 44 56 53 38 28 60 27 39 — § missing, % missing, No. of case patients‡ No. − 69 50 31 ER 171 121 125 166 183 464 238 323 343 254 + 111 ER 198 416 193 392 493 367 793 700 1329 1930 1835 2322 919 799 289 288 670 367 Total 2013 1240 1305 1849 5972 2999 2696 Age 18–93 31–70 54–70 50–71 31–75 40–59 52–71 40–87 40–59 40–93 21–69 49–71 22–104 range, y range, 8279 6000 size† 74 138 13 257 cohort cohort 62 573 22 456 21 609 34 580 42 061 51 890 48 900 Baseline 100 064 200 049 Years of Years Follow-up 1986–1999 1987–1999 1986–2003 1995–2003 1990–2006 1990–2004 1986–2004 1989–2007 1992–2003 1995–2003 1995–2008 1985–2005 1980–2000 Characteristics of the cohort studies included in the pooled analyses of fruit and vegetable intake and breast cancer risk by hormone receptor status* Characteristics of the cohort
Women’s Health Study Health Study Women’s (United States) Study (Netherlands) Study Health–AARP Diet and (United Health Study States) Cohort Study (Australia) Cohort Study Center-Based Center-Based I Study Prospective (Japan) Study (United States) Study Against Cancer and Against Heart Disease (United States) II Nutrition Cohort (United States) Screening Study Screening Study (Canada) (United States) Demonstration Project Demonstration Project Study Follow-up (United States) Study (United States) Study Retinol Efficacy Trial Retinol Trial Efficacy (United States) (Table continues) (Table New York University York New Netherlands Cohort National Institutes of National Institutes Melbourne Collaborative Melbourne Collaborative Japan Public Health Public Japan Iowa Women’s Health Women’s Iowa CLUE II: Campaign Cancer Prevention Study Study Cancer Prevention Canadian National Breast California Teachers Study Teachers California Breast Cancer Detection Black Women’s Health Women’s Black Beta-Carotene and Table 1. (country) Study jnci.oxfordjournals.org JNCI | Articles 221 Median 61 (22–125) 77 (29–158) (10th–90th) 190 (94–348) 190 150 (68–292) 150 236 (112–452) 252 (120–493) 206 (95–399) 259 (129–470) 8 5 7 16 25 23 25 27 No. of No. Total Vegetables, g/day Vegetables, Total questions Median (10th–90th) 136 (37–297) 136 167 (46–374) 167 266 (86–539) 283 (97–616) 330 (174–541) 223 (68–508) 329 (115–642) 272 (73–560) Total Fruits, g/day Fruits, Total 5 4 6 6 15 16 15 21 No. of No. questions 6 4 10 14 15 16 PR 24 38 missing, % missing, − 92 PR 309 288 671 227 369 304 1276 breast cancer. − + 765 613 819 180 758 389 PR 1305 2475 5 9 4 ER 13 14 14 24 30 , and 7488 for PR for , and 7488 + missing, % missing, No. of case patients‡ No. − -transformed energy intake values beyond three standard deviations from the study-specific mean and previous cancer mean and previous three standardfrom the study-specific deviations beyond energy intake values -transformed 67 e ER 196 137 187 381 303 757 255 , 16 162 for PR for , 16 162 − + ER 737 937 858 206 846 528 1603 3075 , 4821 for ER , 4821 for + 283 Total 1175 1122 1072 1090 1331 2585 4462 Age 26–46 52–74 38–76 30–50 38–89 34–70 40–67 34–67 range, y range, 9 044 size† 28 276 93 765 47 514 cohort cohort 38 349 60 464 68 337 88 605 Baseline Years of Years Follow-up 1991–2003 1980–1986 1991–2006 1993–2004 1987–2005 1993–2007 1987–2002 1986–2006 diagnosis (other than nonmelanoma skin cancer). The Netherlands Cohort Study was analyzed as a case–cohort study, so its baseline cohort size does not reflect the above exclusions. Total cohort size was 993 466. was cohort size Total exclusions. does not reflect the above so its baseline cohort size as a case–cohort study, analyzed was Netherlands Cohort Study The diagnosis (other than nonmelanoma skin cancer). ER for 19 869 total 34 526 for breast cancer, number of patients was Total ER = estrogen receptor; PR = progesterone receptor with log women criteria and then excluding exclusion applying study-specific after Cohort size All case patients in these analyses from this study had information on estrogen and progesterone receptor status. had information from this study All case patients in these analyses (a). Health Study included in Nurses’ were not included as part of totalbecause the participants in this study (b) was cohort size Health Study Nurses’ Health Study (Sweden) Health Study (United States) Cohort (Sweden) Colorectal, and Ovarian Colorectal, and Ovarian Cancer Screening Trial (United States) Hormones, Diet and Breast Cancer (Italy) (United States) (United States) || (United States) Women’s Lifestyle and Lifestyle Women’s Women’s Health Study Health Study Women’s Swedish Mammography Mammography Swedish Prostate, Lung, Prospective Study on Study Prospective Nurses’ Health Study II Health Study Nurses’ Nurses’ Health Study (b) Health Study Nurses’ Nurses’ Health Study (a) Health Study Nurses’ ‡ Study (country) Study * † § || Table 1 (Continued). Table
222 Articles | JNCI Vol. 105, Issue 3 | February 6, 2013 by .12 .12 .36 .79 <.001 common effects for quintile 5§ for P receptor status status receptor for for .20 .25 .06 .04 .02 .08 .08 .65 .04 .16 .21 .15 .50 between-studies between-studies quintile 5‡ P heterogeneity † .36 .03 .91 .06 .57 .88 .30 .13 .60 .30 .77 .45 trend <.001 P Q5 917 958 964 6910 4217 1521 1529 7086 4052 3987 3296 3403 6981 1.04 (0.97 to 1.11) 1.04 1.02 (0.96 to 1.10) 1.02 1.00 (0.94 to 1.07) 1.00 0.90 (0.81 to 1.01) 0.99 (0.95 to 1.03) 0.99 (0.93 to 1.07) 0.99 (0.92 to 1.07) 0.94 (0.84 to 1.03) 0.94 (0.85 to 1.04) 0.97 (0.87 to 1.09) 0.98 (0.93 to 1.02) 0.99 (0.95 to 1.04) 0.82 (0.74 to 0.90) 0.82 (0.74 Q4 950 975 949 1514 7108 4103 4142 3313 1529 6909 3980 3348 7052 1.01 (0.95 to 1.08) 1.01 1.02 (0.97 to 1.07) 1.02 1.02 (0.95 to 1.08) 1.02 1.00 (0.95 to 1.06) 1.00 1.00 (0.95 to 1.05) 1.00 0.90 (0.80 to 1.01) 0.98 (0.94 to 1.03) 0.99 (0.93 to 1.05) 0.94 (0.85 to 1.04) 0.92 (0.81 to 1.05) 0.97 (0.88 to 1.07) 0.99 (0.94 to 1.04) 0.90 (0.81 to 1.00) 0.98) Q3 987 965 973 7143 4136 1496 1494 6943 3978 4026 3225 3298 6955 0.89 (0.82 to Quintile of intake 1.03 (0.96 to 1.11) 1.03 1.01 (0.98 to 1.05) 1.01 1.01 (0.96 to 1.05) 1.01 1.03 (0.97 to 1.08) 1.03 1.03 (0.97 to 1.09) 1.03 0.99 (0.94 to 1.05) 0.95 (0.86 to 1.03) 0.96 (0.87 to 1.06) 0.98 (0.93 to 1.03) 0.94 (0.86 to 1.03) 0.98 (0.89 to 1.07) 0.99 (0.94 to 1.03) Q2 965 968 967 1494 1483 3163 6915 6843 6887 3996 3852 3992 3265 1.01 (0.94 to 1.07) 1.01 1.02 (0.97 to 1.08) 1.02 (0.95 to 1.09) 1.02 1.02 (0.97 to 1.07) 1.02 1.00 (0.96 to 1.05) 1.00 1.00 (0.96 to 1.03) 1.00 1.00 (0.96 to 1.04) 1.00 0.92 (0.84 to 1.01) 0.96 (0.89 to 1.03) 0.95 (0.87 to 1.04) 0.99 (0.94 to 1.05) 0.96 (0.85 to 1.09) 0.99 (0.91 to 1.07) Q1 961 995 967 1. 0 0 3701 1440 1472 6555 6688 3662 3770 3028 2979 6643 1.00 (referent) 1.00 1.00 (referent) 1.00 1.00 (referent) 1.00 (referent) 1.00 (referent) 1.00 1.00 (referent) 1.00 (referent) 1.00 1.00 (referent) 1.00 (referent) 1.00 1.00 (referent) 1.00 (referent) 1.00 1.00 (referent) 1.00 No. of case patients No. of case patients No. of case patients No. of case patients No. of case patients No. of case patients No. of case patients No. of case patients No. of case patients No. of case patients RR (95% CI) (95% RR RR (95% CI) (95% RR CI) (95% RR CI) (95% RR RR (95% CI) (95% RR CI) (95% RR Pooled multivariable relativePooled risks* (95% confidence interval) of breast cancer by estrogen receptor/progesterone receptor subtype for quintiles fruit and vegetable intake
− + − + − + − + − + RR (95% CI) No. of case patients RR (95% CI) No. of case patients No. of case patients RR (95% CI) Total fruit and vegetables fruit Total Total vegetables Total fruits Total and vegetables fruit Total vegetables Total Total vegetables Total fruits Total Total fruit and vegetables|| fruit Total
By ER status ER ER PR ER ER ER By PR status PR PR PR
Table 2.
CI) (95% RR CI) (95% RR continues) (Table CI) (95% RR CI) (95% RR Total breast cancer Total
ER jnci.oxfordjournals.org JNCI | Articles 223 points across studies. To test for trend across categories of intake, by the median value of the intake category for each participant was
.62 entered as a continuous term in the model. We also modeled fruit and vegetable intakes as continuous variables when nonparamet- common effects for quintile 5§ for P ric regression analyses showed that the associations were linear. To receptor status status receptor test for linearity, all studies were aggregated into a single dataset, participants within the top 1% of fruit and vegetable intake were excluded to prevent a spurious association due to the influence of for for extreme values, and participants were stratified by age at baseline,
.50 .004 year of baseline questionnaire return, and study. We tested for between-studies between-studies quintile 5‡ P heterogeneity linearity using the likelihood ratio test, comparing the model fit including the linear term and cubic spline terms selected by step- wise regression with that of a model including only the linear term
† (56,57). We examined whether the effects of fruit and vegetable .49 .97 trend
P intake varied by cancer subtype using a contrast test (58,59). To investigate whether associations between fruit and vegeta- ble consumption and breast cancer risk varied by factors that may influence estrogen levels or the bioactive functions of phytochemi- cals, we further evaluated the associations between total fruit and Q5
1524 vegetable, total fruit, and total vegetable consumption and risk of 3262 ER− and ER+ breast cancer by menopausal status at diagnosis using 1.01 (0.93 to 1.10) 1.01
0.98 (0.91 to 1.06) a previously created algorithm (60) (premenopausal, postmeno- pausal), postmenopausal hormone use (never, past, current user at baseline among postmenopausal women), alcohol consumption (nondrinker, <15 g/day, ≥15 g/day), body mass index (<25, ≥25 kg/ m2), multivitamin use (current user, nonuser), family history of Q4 1492 3226 breast cancer (yes, no), approximate median age at diagnosis (<64, ≥64 years), and smoking status (never, past, current smoker) using 0.99 (0.92 to 1.05) 0.95 (0.87 to 1.04) a mixed-effects meta-regression model (11,61). We also explored sources of heterogeneity by region, number of fruit and vegetable items on the FFQ, median follow-up time, median age at diagnosis, and the proportion of women who were postmenopausal at base- Q3 1524 3344 line. For all tests, two-sided 95% confidence intervals (CIs) were calculated, and P less than.05 was considered statistically significant. Quintile of intake 1.02 (0.97 to 1.08) 1.02 0.97 (0.90 to 1.04) ), height (<1.60, 1.60 to <1.65, 1.65 to <1.70, 1.70 to <1.75, ≥1.75 m), oral contraceptive use (never, ever), menopausal status menopausal status ever), use (never, m), oral contraceptive ≥1.75 to <1.75, 1.70 to <1.70, 1.65 to <1.65, 1.60 ), height (<1.60, 2
kg/m Results In the 20 prospective studies with maximum follow-up of 11 to Q2 1475 3261 20 years, 34 526 incident invasive breast cancer case patients were identified among a total of 993 466 women. Receptor status infor- 1.02 (0.96 to 1.09) 1.02 0.96 (0.88 to 1.06) mation was available for 24 673 breast cancers, among which there were 19 869 ER+, 4821 ER−, 16 162 PR+, and 7488 PR− breast can- cer case patients (Table 1). Fruit and vegetable consumption varied
g/day), smoking status (never, past, current), education ( consumption (Ptrend = .03). When intakes of fruits and vegetables were examined separately, inverse associations were observed for No. of case patients No. of case patients RR (95% CI) (95% RR RR (95% CI) (95% RR both total fruit (pooled multivariable relative risk [RR] comparing the highest vs lowest quintile = 0.94, 95% CI = 0.85 to 1.04) and − + total vegetable intake, with a stronger association observed for total vegetable intake (pooled multivariable RR = 0.82, 95% CI = 0.74 The relative risks were adjusted for ethnicity (White, African-American, Hispanic, Asian, others), family history others), family no), personal historyAsian, of breast cancer (yes, no), alcohol consumption African-American, Hispanic, of benign breast disease (yes, ethnicity adjusted for (White, risks were relative The to <30, ≥30 15 >0 to <5, 5 <15, (nondrinkers, (<23, 23 to <25, 25 <30, ≥30 body mass index years), ≥15 to 14, 13 to 12, (premenopausal women, never user of hormone replacement therapy among postmenopausal women, past user of hormone replacement therapy among postmenopausal women, and current user of hormone and current among postmenopausal women, past user of hormone replacement therapy among postmenopausal women, user of hormone replacement therapy never (premenopausal women, of questionnaire and year in years Age continuous), combination between parity (0, 1 to 2, ≥3) and age of first birth (≤25, >25 years). energy intake (kcal/day, among postmenopausal women), replacement therapy risk; CI = confidence interval; All statisticaltwo-sided. RR = relative ER = estrogen receptor; PR = progesterone receptor. tests were included as stratification variables. were return test statistic. Wald calculated using the trend was P , test for calculated using the Q statistic. heterogeneityquintile 5 was for between-studies P , test for calculated using a contrast test. quintile 5 was for receptor status by common effects P , test for of total whom dataincluded in the analyses participants for on totalmissing who were vegetables were missing and 11 whom data were breast cancer for on total fruits nine participants who developed were There and vegetables. fruit Total fruits Total Table 2 (Continued). Table * † ‡ § || PR PR to 0.90 comparing the highest vs lowest quintile; Pheterogeneity for 224 Articles | JNCI Vol. 105, Issue 3 | February 6, 2013 quintile 5 = .50) (Figure 1). The difference in the associations for further modeled total fruit and vegetable, total fruit, and total veg- ER− and ER+ breast cancer was statistically significant only for total etable consumption as deciles; the risk estimates for these three − + vegetable intake (Pcommon-effects for highest quintile < .001). groups for both ER and ER breast cancer (data not shown) were Intakes of total fruit and vegetables, total fruit, and total vegeta- consistent with those observed for the analyses of quintiles and cat- bles were not statistically significantly associated with the risk of egories based on common absolute intake cutpoints. breast cancer overall or ER+ breast cancer, with pooled multivari- The nonparametric regression analyses indicated that all associ- able relative risks ranging from 0.98 to 1.04 (Table 2). For exam- ations presented in Table 2 were linear (Pnonlinearity > .05). Therefore, ple, the pooled multivariable relative risk comparing the highest vs we conducted analyses in which fruit and vegetable intakes were lowest quintile of total vegetable consumption in relation to risk modeled as continuous variables. The pooled multivariable rela- of ER+ breast cancer was 1.04 (95% CI= 0.97 to 1.11) (Table 2). tive risks for ER− breast cancer for a 300 g/day increment (approxi- The results for total breast cancer did not change materially when mately three servings/day) in intake were 0.94 (95% CI = 0.91 to we limited the analyses to the 24 675 case patients with nonmiss- 0.98) for total fruits and vegetables, 0.88 (95% CI = 0.81 to 0.95) ing ER data (data not shown). In addition, when we analyzed the for total vegetables, and 0.96 (95% CI = 0.91 to 1.00) for total fruits 9856 case patients with missing ER data, the pooled multivariable (Pheterogeneity > .34 for each). These three groups were non-statistically relative risks for total fruit and vegetables, total fruit, and total veg- significantly inversely associated with risk of PR− breast cancer, but etables were comparable with those for ER+ breast cancer, ranging no associations or non-statistically significant positive associations from 0.95 to 1.01 when comparing the highest vs lowest quintile of were observed for the risk of ER+ and PR+ breast cancer (data not intake. There was a suggestion that the study-specific results were shown). Further adjustment for intake of beta-carotene, lutein, and heterogeneous for intakes of these three fruit and vegetable groups fiber (which are concentrated in vegetables and could be driving the + and risk of ER breast cancer (for each group, Pheterogeneity for quintile association for total vegetable consumption) (62) did not substan- 5 ≤.06) (Table 2). For example, the study-specific multivariable rel- tially change the inverse association between total vegetable con- ative risks for quintile 5 compared with quintile 1 ranged from 0.55 sumption and ER− breast cancer risk. Analyses that only included to 1.39 for the association between total vegetable consumption case patients diagnosed after 5 years of study enrollment yielded and risk of ER+ breast cancer, with positive associations observed similar relative risks to those using all case patients (data not shown). in nine studies and inverse associations observed in 12 studies. In We further analyzed breast cancer subtypes classified by ER exploratory analyses to identify possible reasons for the heteroge- and PR status jointly (Table 3). For total vegetable intake, we neity, differences in the number of fruit and vegetable questions observed a statistically significant 16% lower risk of ER−PR− breast on the FFQs, median age at diagnosis, proportion of women who cancer (pooled multivariable RR comparing the highest vs lowest were postmenopausal at baseline, and length of follow-up did not quintiles of total vegetables = 0.84, 95% CI = 0.75 to 0.93), but a account for the heterogeneity observed. There was a suggestion non-statistically significant positive association for ER+PR+ breast that the associations for quintile 5 differed by region, with stronger cancer (pooled multivariable RR for same comparison = 1.04, 95% inverse associations observed among studies from continents other CI = 0.98 to 1.11) (Table 3). For total fruit and vegetable and total than North America compared with studies conducted in North fruit consumption, we observed weaker non-statistically signifi- − − America (Pdifference by region ≤.02; data not shown). cant inverse associations with risk of ER PR breast cancer than Intakes of total fruits and vegetables, total fruits, and total veg- observed for total vegetable intake. The risk estimates for ER+PR+ etables were not statistically significantly associated with risk of breast cancer ranged from 1.00 to 1.04 comparing the highest vs PR− or PR+ breast cancers. For total vegetable consumption, the lowest quintile for each of the three fruit and vegetable groups. pooled multivariable relative risk for PR− breast cancer was 0.94 When we examined fruit and vegetable intake grouped accord- (95% CI = 0.84 to 1.03) comparing the highest to the lowest quin- ing to botanical taxonomy (13) (Supplementary Table 2, available tile (Table 2). online), only intake of the Rosaceae family (eg, apples, peaches) was We also evaluated associations with fruit and vegetable intake statistically significantly inversely associated with the risk of ER− categorized using common absolute intake cut points across stud- breast cancer: the pooled multivariable relative risk for a 100 g/day ies (Supplementary Table 1, available online). Associations com- increment in intake (approximately 1 serving/day) was 0.91 (95% paring the highest vs lowest category were of similar magnitude CIs = 0.88 to 0.95) (Supplementary Table 2, available online) for to those observed in the quintile analyses. For example, for total Rosaceae. Non-statistically significant inverse associations were vegetable intake, the pooled multivariable relative risks comparing observed for intakes of the Cruciferae (eg, brococoli, cabbage), ≥ 400 g/day to 100 to <200 g/day were 0.85 (95% CI = 0.75 to 0.97) Cucurbitaceae (eg, melon, squash), and Leguminosae (eg, beans, for ER− tumors and 1.03 (95% CI = 0.97 to 1.10) for ER+ tumors peas) families and risk of ER− breast cancer. For these botanical (Supplementary Table 1, available online). The age-standardized groups, null associations with relative risks ranging from 0.99 to incidence rates of ER− tumors were 32 per 100 000 person-years 1.02 were observed with risk of ER+ breast cancer. Intakes of the among those who consumed ≥400 g/day of total vegetables and Rutaceae (eg, grapefruits, oranges) and Solanaceae (eg, potatoes, 36 per 100 000 person-years among those who consumed <100 g/ tomatoes) families were not associated with risk of ER− or ER+ day of total vegetables. In these analyses, statistically significant breast cancer. differences in the risk of ER− vs ER+ breast cancer were observed In the analyses of intakes of specific fruits and vegetables for both total fruit and vegetable intake and total vegetable intake (Table 4), we observed statistically significant inverse associations (Pcommon-effects by ER status for highest category ≤.02) (Supplementary for intakes of apples/pears, peaches/nectarines/apricots, and straw- Table 1, available online). To compare more extreme intakes, we berries, carrots, and lettuce/salad with risk of ER− breast cancer jnci.oxfordjournals.org JNCI | Articles 225 Figure 1. Study-specific and pooled multivariable-adjusted relative Teachers Study, CLUE2 = Campaign Against Cancer and Heart Disease; risks of estrogen receptor–negative (ER−) breast cancer and total veg- CNBSS = Canadian National Breast Screening Study; CPS2 = Cancer etable consumption, quintile 5 vs quintile1. The squares and horizontal Prevention Study II Nutrition Cohort; IWHS = Iowa Women’s Health lines correspond to the study-specific relative risks and 95% confidence Study; JPHCI = Japan Public Health Center-Based Prospective Study I; intervals, respectively, for the comparison of quintile 5 (Q5) to quintile MCCS = Melbourne Collaborative Cohort Study; NHSa = Nurses’ 1 (Q1) of total vegetable consumption. The size of the squares reflects Health Study(a); NHSb = Nurses’ Helath Study(b); NHS2 = Nurses’ the study-specific weight (inverse of the variance). The diamond repre- Health Study II; NLCS = Netherlands Cohort Study; NYU = New York sents the pooled relative risk and 95% confidence interval. All statisti- University Women’s Health Study; ORDET = Prospective Study on cal tests were two-sided. AARP = National Institutes of Health–AARP Hormones, Diet and Breast Cancer; PLCO = Prostate, Lung, Colorectal, Diet and Health Study; CARET =Beta-Carotene and Retinol Efficacy and Ovarian Cancer Screening Trial; SMC = Swedish Mammography Trial; BWHS = Black Women’s Health Study; BCDDP = Breast Cancer Cohort; WHS =Women’s Health Study; WLHS = Women’s Lifestyle and Detection Demonstration Project Follow-up Study; CTS = California Health Study. but non-statistically significant associations with risk of ER+ breast with risk of ER− breast cancer. These results, which included only cancer. For ER− breast cancer, when we included intakes of straw- three previously published reports (5,7,68), were not statistically berries, apples/pears, and peaches/nectarines/apricots or intakes of significantly heterogenous across studies and were not modified by lettuce/salad and carrots simultaneously in the model, the associa- other breast cancer risk factors, including menopausal status and tion for each food did not change substantially and remained statis- age. Total fruit and vegetable, total fruit, and total vegetable intakes tically significant except that the association for apple/pear intake were observed to have non-statistically significant associations with was attenuated and became non-statistically significant (data not risk of ER+ breast cancer. shown). Although some studies have reported potentially adverse We observed null associations between total fruit and vegeta- effects of bioactive compounds present in fruits and vegetables ble, total vegetable, and total fruit intakes and risk of overall breast (12,63–67), no statistically significant positive associations were cancer. A recent meta-analysis of 14 cohort studies (4) found that observed for any of the specific fruit and vegetables or botanically high vs low fruit and vegetable intake was inversely associated with defined fruit and vegetable subgroups examined in our analyses. a statistically significant 11% lower risk of overall breast cancer. We observed an inverse association between total fruit and veg- Based on more than 15 cohort and 40 case–control studies pub- etable, total fruit, and total vegetable intakes and risk of ER− breast lished through 2007, the World Cancer Research Fund/American cancer in most of the population subgroups evaluated. These asso- Institute for Cancer Research concluded that the evidence for an ciations, as well as those for ER+ breast cancer, were not modified association between fruit and vegetable consumption and breast by several breast cancer risk factors (all P values, test for interaction cancer risk was limited (69). However, our analyses have demon- ≥ 0.09) (Table 5). strated that examining associations with only total breast cancer may mask specific relationships for less common subtypes such as ER− breast cancer. Discussion We observed a statistically significant inverse association for In this pooled analysis of 993 466 women from 20 prospective stud- total vegetable consumption with risk of ER− breast cancer. To our ies, we observed modest statistically significant inverse associations knowledge, among the few cohort studies (5,7,68) that have previ- between total fruit and vegetable and total vegetable consump- ously examined associations between fruit and vegetable consump- tion and risk of ER− breast cancer. For total fruit consumption, tion and risk of breast cancer by hormone receptor status, only the we found a weaker, non-statistically significant inverse association Danish Diet, Cancer and Health Study (7) was not included in our 226 Articles | JNCI Vol. 105, Issue 3 | February 6, 2013 by .14 .83 <.001 common effects for quintile 5|| for P receptor status status receptor for .01 .10 .10 .17 .12 .75 .83 .30 .06 .69 .53 .32 between-studies between-studies quintile 5§ P heterogeneity ‡ .04 .49 .21 .87 .83 .29 .41 .001 .27 .13 .75 .41 trend P Q5 113 113 7 74 74 5 103 713 727 750 782 3139 3096 3259 1.01 (0.93 to 1.10) 1.01 1.04 (0.98 to 1.11) 1.04 1.02 (0.90 to 1.14) 1.02 1.04 (0.89 to 1.20) 1.04 1.00 (0.93 to 1.08) 1.00 0.99 (0.88 to 1.10) 0.93 (0.80 to 1.08) 0.97 (0.86 to 1.09) 0.86 (0.58 to 1.27) 0.68 (0.51 to 0.90) 0.70 (0.51 to 0.96) 0.84 (0.75 to 0.93) 98 92 Q4 676 106 771 736 789 706 785 3198 3166 3096 1.01 (0.96 to 1.07) 1.01 1.03 (0.92 to 1.15) 1.03 1.02 (0.96 to 1.09) 1.02 1.00 (0.93 to 1.07) 1.00 0.97 (0.85 to 1.11) 0.97 (0.84 to 1.12) 0.92 (0.83 to 1.03) 0.92 (0.82 to 1.03) 0.91 (0.80 to 1.04) 0.72 (0.52 to 1.00) 0.63 (0.48 to 0.84) 0.71 (0.53 to 0.97) Q3 111 105 105 725 793 675 772 688 778 3191 3139 3079 Quintile of intake 1.03 (0.96 to 1.11) 1.03 1.00 (0.90 to 1.11) 1.00 1.03 (0.97 to 1.09) 1.03 0.76 (0.58 to 1.00) 0.76 0.87 (0.66 to 1.14) 0.99 (0.94 to 1.05) 0.97 (0.87 to 1.09) 0.95 (0.85 to 1.06) 0.97 (0.87 to 1.09) 0.95 (0.85 to 1.05) 0.89 (0.80 to 1.00) 0.72 (0.53 to 0.97) ), height (<1.60, 1.60 to <1.65, 1.65 to <1.70, 1.70 to <1.75, ≥1.75 m), oral contraceptive use (never, ever), menopausal status (premenopausal menopausal status ever), use (never, m), oral contraceptive ≥1.75 to <1.75, 1.70 to <1.70, 1.65 to <1.65, 1.60 ), height (<1.60, 2 Q2 112 102 108 676 793 671 793 664 781 3115 3107 3008 1.03 (0.96 to 1.10) 1.03 1.01 (0.95 to 1.08) 1.01 1.03 (0.98 to 1.08) 1.03 0.97 (0.84 to 1.11) 0.84 (0.61 to 1.15) 0.98 (0.88 to 1.09) 0.98 (0.89 to 1.08) 0.94 (0.85 to 1.04) 0.97 (0.87 to 1.08) 0.96 (0.85 to 1.09) 0.93 (0.71 to 1.22) 0.74 (0.57 to 0.97) 0.74 Q1 114 124 120 773 648 804 646 778 665 2867 2820 2906 1.00 (referent) 1.00 1.00 (referent) 1.00 (referent) 1.00 1.00 (referent) 1.00 1.00 (referent) 1.00 1.00 (referent) 1.00 (referent) 1.00 (referent) 1.00 1.00 (referent) 1.00 (referent) 1.00 (referent) 1.00 1.00 (referent) 1.00 No. of case patients No. of case patients No. of case patients No. of case patients No. of case patients No. of case patients No. of case patients No. of case patients No. of case patients No. of case patients No. of case patients No. of case patients RR (95% CI) (95% RR CI) (95% RR RR (95% CI) (95% RR − + − + − + − + − + − + Pooled multivariable relativePooled risks (95% confidence interval) of breast cancer by joint estrogen receptor/progesterone receptor subtype for quintiles fruit and vegetable intake*,† PR PR PR PR PR PR PR PR PR PR PR PR − − + + − − + + − − + + The relative risks were adjusted for ethnicity (White, African-American, Hispanic, Asian, others), family history others), family no), personal historyAsian, of breast cancer (yes, no), alcohol consumption (non- African-American, Hispanic, of benign breast disease (yes, ethnicity adjusted for (White, risks were relative The 13 to 12, 11 (<11, medium, high), age at menarche activity (low, physical >high school), high school, education ( .01 .12 .98 .62 .02 .89 .33 .22 .07 .02 .22 status§ common effects <.001 P by receptor receptor by ‡ .11 .19 .50 .08 .60 .21 .05 .66 .35 .30 .50 .30 .47 .60 .43 .20 .86 .91 .86 .79 .89 .54 .63 .002 between-studies between-studies heterogeneity P RR (95% CI), RR (95% CI), 1.01 (0.98 to 1.04) 1.01 1.01 (0.91 to 1.13) 1.01 1.01 (0.97 to 1.05) 1.01 (0.97 to 1.05) 1.01 1.01 (0.95 to 1.06) 1.01 1.04 (0.87 to 1.24) 1.04 1.06 (0.98 to 1.16) 1.06 1.06 (1.00 to 1.12) (1.00 1.06 (0.99 to 1.08) 1.03 1.10 (0.93 to 1.29) 1.10 1.00 (0.95 to 1.05) 1.00 1.00 (0.92 to 1.09) 1.00 0.56 (0.41 to 0.76) 0.91 (0.84 to 0.98) 0.98 (0.88 to 1.08) 0.93 (0.83 to 1.04) 0.93 (0.82 to 1.06) 0.92 (0.84 to 1.00) 0.81 (0.70 to 0.94) 0.92 (0.85 to 0.99) 0.98 (0.94 to 1.02) 0.99 (0.91 to 1.08) 0.97 (0.92 to 1.02) to 1.15) 0.92 (0.74 unit: 1 serving/day unit: 75 68 56 78 57 87 114 190 120 131 138 134 (g/day) 1 Serving 1 1 6 oz 1 cup 1/2 cup 1/2 cup 1/2 cup 1/2 cup 1/2 fruit 1/4 melon Reference Reference 1 or 1/2 cup 1 or 1/2 cup serving size 3113 4740 4103 2912 3913 4657 4777 4271 3828 3505 3635 3649 case 15 474 No. of No. 13 162 12 956 19 408 19 708 16 081 16 505 15 942 15 936 16 449 19 678 18 509 patients 11 11 11 11 17 17 17 17 15 15 14 14 15 15 15 15 15 15 19 19 18 18 20 20 No. of No. studies† Pooled multivariable relativePooled risks (95% confidence interval) of breast cancer by estrogen receptor subtype for specific fruits and vegetables* − + − + − + − + − + − + − + − + − + − + − + − + Fruit juice Fruit Peaches, nectarines, apricots||,¶,#,**,††,§§,||||,##,††† Peaches, salad||,¶¶,##,‡‡‡ Lettuce, Apples, pears, applesauce||,¶ ER Vegetables Broccoli||,¶,§§,||||,## ER ER ER ER ER ER ER ER ER ER Table 4. item Food ER Grapefruit||,‡‡,§§,¶¶,##,*** ER Strawberries||,¶,#,**,††,‡‡,§§,||||,##,††† ER ER Bananas||,¶,#,**,†† ER Fruits ER ER Carrots|| ER Cantaloupe||,¶,‡‡,§§,||||,¶¶,## ER Oranges||,‡‡,§§,¶¶,##,*** ER ER Cabbage||,¶,‡‡,¶¶ ER ER (Table continues) (Table 228 Articles | JNCI Vol. 105, Issue 3 | February 6, 2013 .10 .31 .45 .33 status§ common effects P by receptor receptor by ‡ .15 .58 .70 .46 .66 .04 .04 .85 between-studies between-studies heterogeneity P RR (95% CI), RR (95% CI), 1.01 (0.94 to 1.08) 1.01 1.13 (0.75 to 1.69) 1.13 (0.99 to 1.26) 1.12 1.04 (0.96 to 1.13) 1.04 1.00 (0.90 to 1.11) 1.00 0.92 (0.83 to 1.01) 0.91 (0.80 to 1.04) 0.94 (0.76 to 1.17) 0.94 (0.76 unit: 1 serving/day unit: 73 122 128 202 (g/day) 1 Serving 1 1 1/2 cup 1/2 cup Reference Reference serving size 4749 3610 4273 4344 case 19 743 No. of No. 17 332 15 532 18 341 ), height (<1.60, 1.60 to <1.65, 1.65 to <1.70, 1.70 to <1.75, ≥1.75 m), oral contraceptive use (never, ever), menopausal status menopausal status ever), use (never, m), oral contraceptive ≥1.75 to <1.75, 1.70 to <1.70, 1.65 to <1.65, 1.60 ), height (<1.60, 2 patients kg/m 17 17 13 13 19 19 18 18 No. of No. studies† g/day), smoking status (never, past, current), education ( − + − + − + − + − + − Ye s Yes¶¶ Multivitamin use§§ Oral contraceptive use ‡‡ Oral contraceptive Menopausal status Postmenopausal hormone use¶ Postmenopausal Smoking status|||||| Alcohol consumption Ever ER ER Postmenopausal|| Ever** Ever†† Ever ER drink/day‡‡‡ <1 Past¶¶¶ Current### continues) (Table Table 5. modifiers Effect Premenopausal‡,§ Premenopausal‡,§ Never# Never# Never Never No|||| No ER Never Never Never ER Postmenopausal ER ER drink/day*** <1 Subgroup results ER ≥1drink/day§§§ ER ≥1drink/day††† ER ER 230 Articles | JNCI Vol. 105, Issue 3 | February 6, 2013 † .30 .38 .99 .59 .59 .68 .23 .92 .32 interaction P fruits Total RR (95% CI) 1.01 (0.97 to 1.04) 1.01 1.00 (0.99 to 1.01) 1.00 (0.99 to 1.01) 1.00 1.00 (0.98 to 1.01) 1.00 1.00 (0.98 to 1.01) 1.00 1.00 (0.98 to 1.02) 1.00 1.00 (0.98 to 1.03) 1.00 1.00 (0.99 to 1.02) 1.00 0.97 (0.84 to 1.11) 0.97 (0.85 to 1.11) 0.96 (0.91 to 1.01) 0.95 (0.89 to 1.01) 0.97 (0.81 to 1.16) 0.99 (0.83 to 1.18) 0.99 (0.96 to 1.02) 0.95 (0.86 to 1.05) 0.99 (0.93 to 1.06) 0.98 (0.93 to 1.03) 0.97 (0.89 to 1.06) 0.94 (0.89 to 1.00) 0.99 (0.98 to 1.00) † .14 .18 .52 .22 .99 .20 .97 .40 .73 interaction P RR (95% CI) vegetables Total 1.01 (0.97 to 1.04) 1.01 0.81 (0.58 to 1.14) 1.09 (0.88 to 1.35) 1.09 0.99 (0.86 to 1.15) 1.02 (0.99 to 1.04) 1.02 0.91 (0.78 to 1.06) 1.02 (1.00 to 1.04) (1.00 1.02 0.87 (0.80 to 0.95) (0.73 to 1.69) 1.11 1.01 (1.00 to 1.03) (1.00 1.01 0.87 (0.78 to 0.97) (0.99 to 1.02) 1.00 0.92 (0.83 to 1.02) (0.99 to 1.02) 1.01 0.75 (0.56 to 1.01) 0.88 (0.79 to 0.99) 1.01 (0.99 to 1.02) 1.01 (0.98 to 1.07) 1.03 0.89 (0.77 to 1.02) 0.98 (0.95 to 1.01) 1.01 (0.99 to 1.03) 1.01 † .71 .89 .22 .86 .23 .45 .58 .24 .47 interaction P vegetables vegetables RR (95% CI) ), height (<1.60, 1.60 to <1.65, 1.65 to <1.70, 1.70 to <1.75, ≥1.75 m), oral contraceptive use (never, ever), menopausal status (premenopausal women, (premenopausal women, menopausal status ever), use (never, m), oral contraceptive ≥1.75 to <1.75, 1.70 to <1.70, 1.65 to <1.65, 1.60 ), height (<1.60, 2 Total fruits and fruits Total 1.01 (0.84 to 1.21) 1.01 1.01 (0.99 to 1.03) 1.01 1.00 (0.99 to 1.01) 1.00 1.00 (0.99 to 1.01) 1.00 (0.98 to 1.01) 1.00 (0.99 to 1.01) 1.00 (0.99 to 1.01) 1.00 1.00 (0.99 to 1.01) 1.00 1.03 (0.88 to 1.20) 1.03 1.00 (0.97 to 1.02) 1.00 1.00 (0.99 to 1.02) 1.00 1.00 (0.99 to 1.00) 1.00 0.95 (0.84 to 1.07) 0.96 (0.89 to 1.04) 0.97 (0.92 to 1.03) 0.96 (0.89 to 1.04) 0.96 (0.93 to 1.00) 0.90 (0.81 to 1.00) 0.94 (0.91 to 0.98) 0.93 (0.88 to 0.98) 0.94 (0.89 to 0.98) kg/m 276 359 666 961 583 2107 2163 1803 2732 6069 3875 9228 2981 9323 3783 2572 9289 case No. of No. 10 080 10 380 17 439 15 759 patients g/day), smoking status (never, past, current), education ( 232 Articles | JNCI Vol. 105, Issue 3 | February 6, 2013 analyses. That study reported that women with total fruit and veg- ER− breast cancer. For example, intakes of alpha-carotene, beta- etable intake greater than 570 g/day had half the risk of ER− breast carotene, and lutein/zeaxanthin, which are especially abundant in cancer as women with intakes less than 255 g/day (7), although the vegetables (86), were each inversely associated with risk of ER− separate associations for fruit intake and vegetable intake were not breast cancer in a large pooled analysis that used the same cohorts statistically significant. No statistically significant associations were as the current pooled analysis. However, only a non-statistically observed for risk of ER+ breast cancer, which is consistent with our significant association was observed for beta-cryptoxanthin, which findings (7). On the other hand, case–control studies that evaluated is abundant in fruits. fruit and vegetable consumption in relation to breast cancer risk The main strength of this pooled analysis is that the large sam- by hormone receptor status (70–72) have found non-statistically ple size enabled us to examine associations separately with rela- significant inverse associations for risk of ER− breast cancer and tively high precision for breast cancer subtypes defined by hormone statistically significant inverse associations between intakes of total receptor status and investigate further whether these associations fruit and vegetables (71), total fruit (70), and specific vegetables were modified by menopausal status, age at diagnosis, or other (72) and risk of ER+ breast cancer, with 31% to 35% reduced risks accepted breast cancer risk factors. In addition, median fruit and of ER+ breast cancer observed when comparing the highest vs low- vegetable intake varied threefold to fourfold across the 20 cohorts, est intakes. In contrast, in the Women’s Healthy Eating and Living which provided ample variation in the exposure, thereby minimiz- randomized trial (73), the risk of breast cancer recurrence was not ing the potential to miss an association due to homogenous dietary statistically significantly different between the intervention group, habits. With ample heterogeneity in the types of vegetables and whose goal was to increase intake of fruit, vegetables, and fiber and fruits consumed across studies, we were able to analyze a variety of reduce intake of total fat, and the control group, even when strati- fruit and vegetable groups, ranging from comprehensive groupings fied by hormone receptor status of the initial tumor. However, the to specific foods. Further, exposures and covariables were coded in results of that study (73) might not be directly comparable with the same manner, enabling more equal comparisons across studies ours because it focused on breast cancer recurrence and not breast than possible in a meta-analysis (11). cancer incidence. Limitations of our study include the between-studies variation High vegetable consumption may be associated with risk of ER− in the dietary assessment methods, assessment of confounding fac- breast cancer but not with ER+ breast cancer, although the biologi- tors, and measurement of hormone receptor status. To minimize cal mechanism is not clear yet. There is substantial evidence that the the influence of the differences in dietary assessment methods, we etiology of breast cancer varies by ER status (1,3,74,75). The inci- categorized intake using both study-specific quintiles, which rank dence curves increase continuously with age for ER+ breast tumors individuals according to their relative intake within a study, and but plateau after menopause for ER− breast cancer (2). Compared absolute intake cut points, which take advantage of the variation with ER+ tumors, ER− breast cancers are more frequently diag- in intake levels across studies. The interpretation of the results was nosed as larger and more rapidly proliferating tumors than ER+ the same in both analyses, adding confidence in these findings. tumors (76), have lower 5-year survival rates (77), and are more Although the way confounders were measured varied across stud- common in African American and Asian women (78). Most of all, ies, the age-adjusted results were not materially different from the ER− tumors are less dependent on estrogen levels (1). The known multivariable-adjusted results presented, suggesting that misclas- risk factors for breast cancer overall, such as nulliparity, delayed sification in the assessment of confounding variables may not have childbearing, early menarche, and postmenopausal obesity, have had a strong influence on the observed associations. The informa- been found to be more strongly associated with risk of ER+ than tion on hormone receptor status was not available for 4% to 60% ER- tumors (1,3). The beneficial effect of bioactive compounds in of case patients across studies. However, the distribution of the vegetables may be more detectable in preventing the less hormo- confounding variables and fruit and vegetable intake were similar nally dependent ER− tumors than ER+ breast cancer. Epidermal between case patients with and without hormone receptor status growth factor receptor tends to be overexpressed in ER− breast information. Further, the results for total fruit and vegetable, total tumors compared with ER+ breast tumors. This overexpression fruit, and total vegetable intakes and risk of overall breast cancer triggers nuclear factor-kappaB, which controls the transcription were similar when all case patients were analyzed or when we lim- of DNA that is involved in immune responses (79). Furthermore, ited our case definition to those case patients with ER data. the cell cycle regulators that are overexpressed differ between ER− Another limitation was having only a single measurement of and ER+ breast cancers. Cyclin E is overexpressed in ER− breast fruit and vegetable consumption at baseline. Furthermore, breast cancer, but cyclin D is overexpressed in ER+ breast cancer (80,81). cancer epidemiology suggests that the natural history of breast Phytochemicals found in vegetables have been suggested to reduce cancer has a long duration (87). Therefore, collecting dietary the level of epidermal growth factor receptor (82), nuclear factor- information only at baseline may have attenuated our observed kappaB (83,84), and cyclin E (85), which may, in turn, reduce the results, particularly if diet earlier in life is most important. In risk of developing ER− breast cancer. addition, we cannot rule out misclassification in estimated fruit We only observed a non-statistically significant inverse associa- and vegetable intake, which may have attenuated the associa- tion between total fruit intake and risk of ER− breast cancer. The tions observed. Finally, because we evaluated associations with 15 reason why the association for vegetable consumption is stronger specific fruit and vegetable items, differences observed between than that observed for fruit consumption is unclear. It may be that breast cancer subtypes for specific fruit and vegetable items could bioactive constituents that are more concentrated in commonly be because of chance, and these results should be interpreted with consumed vegetables than in fruits are more effective in preventing caution. jnci.oxfordjournals.org JNCI | Articles 233 In conclusion, this large pooled analysis of prospectively col- 15. International Agency for Research on, Cancer Iarc Working Group on the lected data provides compelling support for an association between Evaluation of Carcinogenic Risks to Humans. Some Naturally Occurring Substances: Food Items and Constituents, Heterocyclic Aromatic Amines and high vegetable and fruit consumption, especially vegetable con- Mycotoxins. Lyon, France: Distributed for the International Agency for − sumption, and reduced risk of ER breast cancer. 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J Am Diet Assoc. 2004;104(6):921–930. 2nd ed. New York: Oxford University Press; 2008. 63. Kilfoy BA, Zhang Y, Park Y, et al. Dietary nitrate and nitrite and the risk of thyroid cancer in the NIH-AARP Diet and Health Study. Int J Cancer. 2011;129(1):160–172. Funding 64. Higdon JV, Delage B, Williams DE, et al. Cruciferous vegetables and This work was supported by grants from National Institute of Health (CA55075 human cancer risk: epidemiologic evidence and mechanistic basis. to WCW) and the Breast Cancer Research Foundation (to WCW) and the Pharmacol Res. 2007;55(3):224–236. fellowship from Samsung Scholarship (to SJ). jnci.oxfordjournals.org JNCI | Articles 235 Notes Program, American Cancer Society, Atlanta, GA (MMG, MLM); Division of All authors contributed to these pooled analyses and read and approved the final Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA manuscript. (GG, MLN); Division of Nutritional Epidemiology, Institute of Environmental The sponsor had no role in the design, data collection, data analyses, interpre- Medicine (NH, AW) and Department of Medical Epidemiology and Biostatistics tation of the results, preparation of the manuscript or the decision to submit the (EW), Karolinska Institutet, Stockholm, Sweden; The Prevention and Research manuscript for publication. Center, The Weinberg Center for Women’s Health & Medicine, Mercy Medical We thank Shiaw-Shyuan Yaun, Tao Hou, and Ruifeng Li for their invaluable Center, Baltimore, MD (KH); Department of Epidemiology, The Johns Hopkins contributions for data management and statistical support. Bloomberg School of Public Health, Baltimore, MD (KH, KV); Cancer Prevention Affiliations of authors: Department of Nutrition (SJ, WCW, SAS-W), Institute of California, Fremont, California (PLH-R); Epidemiology and Prevention Department of Epidemiology (SJ, DS, JEB, SEH, WCW, SAS-W), and Division, Research Center for Cancer Prevention and Screening, National Department of Biostatistics (DS), Harvard School of Public Health, Boston, Cancer Center, Tokyo, Japan (MI, ST); Nutritional Epidemiology Unit, Fondazione MA; Cancer Epidemiology Centre, The Cancer Council Victoria, Carlton, IRCCS Istituto Nazionale Tumori Milano, Italy (VK, SSi); Department of Clinical Victoria, Australia (LBa, GGG); Centre for Molecular, Environmental, Genetic and Experimental Medicine, University of Linköping, Sweden (ML); Dalla Lana and Analytic Epidemiology, University of Melbourne, Melbourne, Australia School of Public Health, University of Toronto, Toronto, Ontario, Canada (ABM); (LBa, GGG); Division of Cancer Etiology, Department of Population Science, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Beckman Research Institute and City of Hope National Medical Center, Duarte, Rockville, MD (YP, CS, RGZ); Division of Epidemiology and Community Health, California (LBe); Slone Epidemiology Center at Boston University, Boston, MA School of Public Health, and Masonic Cancer Center, University of Minnesota, (DAB, JRP); Department of Epidemiology, GROW-School for Oncology and Minneapolis, MN (KR); Department of Epidemiology and Population Health, Developmental Biology, Maastricht University, Maastricht, the Netherlands Albert Einstein College of Medicine, Bronx, New York (TER); Department of (PAvdB, LJS); Division of Preventive Medicine (JEB, SMZ) and Channing Environmental Medicine, New York University School of Medicine, New York, Division of Network Medicine (SEH, WCW, XZ), Department of Medicine, NY (SSc, AZJ); Division of Preventive Medicine, School of Medicine, University Brigham and Women’s Hospital and Harvard Medical School, Boston, MA; of Alabama, Birmingham (JMS); Institute of Community Medicine, University Division of Biostatistics and Epidemiology, University of Massachussetts, of Tromsø, Tromsø, Norway (EW); Department of Etiological Research, Cancer Amherst, MA (SEH); Department of Health Sciences Research, College Registry of Norway, Oslo, Norway (EW); Department of Genetic Epidemiology, of Medicine, Mayo Clinic, Rochester, MN (JRC); Epidemiology Research Folkhälsan Research Center, Helsinki, Finland (EW). 236 Articles | JNCI Vol. 105, Issue 3 | February 6, 2013