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Cancer Research Center of Hawaii, Honolulu, HI
2To whom correspondence should be addressed. E-mail: gertraud{at}crch.hawaii.edu.
| ABSTRACT |
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KEY WORDS: soy intervention mammographic density breast cancer risk early life nutrition
For Commentary on this article see: J. Nutr. 134: 29112912, 2004.
Mammographic density is a strong predictor of breast cancer risk. Women with high densities are 46 times more likely to develop the disease (1). In addition to anthropometric, reproductive, and genetic determinants of mammographic density (1,2), a number of intervention studies indicated that dietary and hormonal factors may influence breast density. In a study of pre- and postmenopausal women, the size of the dense areas decreased by 6.1% in the intervention group compared with 2.1% in the control group after a 2-y low fat dietary modification (3). Hormone replacement therapy containing progesterone increased breast densities (4) after 1 y of medication, whereas suppression of ovarian function through a gonadotropin-releasing hormone agonist (5) and tamoxifen therapy (6) achieved substantial reduction in mammographic densities.
Soy consumption is traditionally high in Asian countries in which the incidence of breast cancer is lower than in Western countries (7). A number of well-conducted case-control studies support the hypothesis that soy consumption protects against breast cancer (811), and a large prospective cohort study from Japan (12) observed a protective effect of miso soup; however, several studies did not find an association (1315). Interestingly, the Shanghai Breast Cancer Study reported an inverse relation between adolescent soy intake and breast cancer risk (16) with an odds ratio (OR) of 0.51 (95% CI: 0.40.65) for the highest compared with the lowest quintile of soy intake. The importance of soy consumption in early life was also underscored by a study among Asian-Americans in California (10), showing that women who reported high soy intake during both adolescence and adulthood had the lowest risk (OR = 0.77, 95% CI: 0.511.1) of developing breast cancer. A considerable amount of evidence from animal research supports these epidemiologic findings. Animals that are given genistein perinatally or prepubertally experience greater protection against experimentally induced breast cancer than animals fed soy during adulthood (17,18).
Only a few studies have examined the relation between soy intake and mammographic density as a biomarker of breast cancer risk. In a cross-sectional design, mammographic density was positively associated with soy intake in a multiethnic population from Hawaii (19). Among Chinese women in Singapore, soy intake was negatively associated with high percentage density patterns (20). Two randomized trials with isoflavone supplements for 1 y showed no significant change in mammographic density by group (21,22). It is possible, however, that the effects of soy foods differ from those of isoflavone supplements. We conducted a large nutritional intervention study to examine the effects of a 2-y soy intervention on breast cancer risk among premenopausal women (23,24). This paper examines the mammographic changes during the trial and explores the relation of lifetime soy intake with the breast density percentage.
| SUBJECTS AND METHODS |
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25 mg of isoflavones and corresponded to 180 g soymilk, 126 g tofu, a 58 g soy protein bar, 31 g soy protein powder, or 23 g roasted soy nuts. The control women consumed their usual diet; they were asked not to increase their previous low soy intake. Individual counseling, frequent contacts with the study staff, group meetings, and newsletters were offered to help maintain adherence. Evidence from soy intake logs, 24-h recalls, and urinary isoflavone excretion by HPLC with diode-array detection (25) suggest that the women adhered closely to the study regimen (23). According to 7 unannounced 24-h recalls, the intervention women consumed a daily mean of 58 ± 15.8 mg isoflavones compared with 5.0 ± 6.0 mg in the control group. This was confirmed by mean urinary isoflavone excretions of 32.2 ± 34.9 and 64.1 ± 67.8 nmol/mg creatinine in the intervention group after y 1 and 2 and only 7.2 ± 19.4 and 10.0 ± 18.7 nmol/mg in the control group. The dropout rates of 15.6% (17/109) in the intervention and 12.6% (14/111) in the control group did not differ significantly. We observed no adverse effects related to the soy foods. Mammographic data collection. The goal was to obtain 1 mammogram at baseline and a second one after 2 y for each woman, but we also retrieved mammograms for the interim years, if available. None of the mammograms were performed for study purposes only; the subjects physicians ordered all mammograms. After scanning films from both breasts with a Kodak LS85 Film Digitizer and removing all personal identifiers from the image, one of the authors performed computer-assisted density assessment (21,26). All mammograms for 1 woman were assessed during the same session, but the reader was unaware of the group status or the time sequence of the mammograms. A recent report testing different reading conditions indicates that with one exception, all of the randomization and viewing methods produced very similar overall results (27). The mammographic measures included the total breast area, the dense area of the breast, and the percentage density, calculated as the ratio of the dense area to the total area. We averaged the values for the right and the left breast except for 2 women for whom only one side was available at baseline. The readings for the 2 sides did not differ; the Pearson correlation coefficients varied between 0.92 and 0.97 for the mammographic measures of interest. A sample of 219 mammograms was read in duplicate to assess reproducibility. The intraclass correlation coefficients (ICC) (28) were ICC = 0.93 (95% CI: 0.910.95) for the size of the dense areas and ICC = 0.998 (95% CI: 0.9970.999) for the total breast area, resulting in an ICC of 0.95 for the percentage density (95% CI: 0.930.96). We had at least 2 mammograms for 98 intervention and 103 control women. Of these, final mammograms were obtained at 12 mo for 6 women from each group because they left the study before the end of the 2-y period. For 1 woman in each group, the mammograms could not be located. For 7 control and 10 intervention women, only baseline mammograms were available because they dropped out of the study before 1 y or did not have a follow-up mammogram. The change in mammographic measures was calculated as the difference between the final and the baseline measure. Because the time between baseline mammogram and randomization varied due to scheduling, we computed the change in mammographic density per year using the exact dates of the mammograms.
Lifetime soy questionnaire. To estimate soy exposure since birth, we designed a 1-page questionnaire modeled after a validated soy questionnaire assessing intake during the past year (29). It included 1 section for the following stages of life: infancy, childhood (19 y), adolescence (1019 y), early adulthood (2029 y), and late adulthood (30+ y). Participants marked the annual frequency of usual serving sizes for 4 categories of soy foods (tofu; soy beans and sprouts; soy milk and drinks; and other soy products). For infancy, soy-based formula was the only choice. To obtain a summary score for early life (019 y), adulthood (since age 20), and lifetime, we added the frequencies of intake by stage and computed the mean annual intake in number of servings. Then we created binary variables low vs. high soy intake using the median intake. The cutoff point for soy intake during early life was any vs. no soy intake; during adulthood it was 36 servings/y; and for the entire life it was 27 servings/y. Finally, we classified adult intake into 3 categories: none, <1 serving/wk, and 1+ serving/wk.
Statistical analysis.
All statistical analyses were performed with the SAS software package (SAS Institute) (30). Results were reported as means and SD; an
-level of 0.05 was considered significant. In the questionnaire, subjects marked all ethnic backgrounds that applied to themselves and to their parents. Because of the small sample size, ethnicity was collapsed into 3 categories: Caucasian, Asian (Chinese, Filipino, Japanese), and Mixed/Other (Native Hawaiians, mixed, and others). A woman was classified as Caucasian if both parents had some Caucasian ancestry and shared no other ethnic background. Subjects who reported <4 ethnic backgrounds were classified as Chinese, Japanese, or Filipino, if both parents were of Asian ancestry or if the mother was of the respective ethnic background and the parents shared no other ethnic background. The final category includes women with any Native Hawaiian background and all subjects who did not fit the Caucasian or Asian category. We used t tests and
2-tests to test for the equality of the 2 groups at baseline. After calculating the change in mammographic measures from baseline to the end of the study, we used 2-sample t tests to examine the differences between the 2 groups and paired t tests to evaluate the change over time. This procedure was repeated for the following subgroups; BMI > or < 25 kg/m2 at baseline, Asian ethnicity, place of birth (U.S. vs. other), and soy consumption (low vs. high) during early life, adulthood, and lifetime. Multiple linear regression using the procedure PROC GLM in SAS (30) was used to explore determinants of annual change in the breast density percentage. We included demographic, anthropometric, reproductive, and soy intake variables as covariates in the regression models.
| RESULTS |
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In an exploratory analysis with possible predictors of change in the percentage density, any soy consumption during early life was positively associated with change in the percentage density/y (P = 0.03), whereas soy intake during adulthood was negatively associated with change in the percentage density/y (P = 0.007). Women who reported no soy during adulthood experienced a mean decrease of 0.51%/y. The mean decrease was 0.65% for women reporting <1 weekly serving and 3.14%/y for women with at least 1 serving/wk. This model was adjusted for ethnicity, age, group status, place of birth, number of children, the percentage density at baseline, BMI at baseline, and change in BMI, but only the percentage density at baseline (P = 0.10) and change in BMI (P = 0.10) showed a weak nonsignificant relation with change in the percentage density.
| DISCUSSION |
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Our results were consistent with our previous 1-y isoflavone supplement (100 mg/d) intervention (21). The percentage density in the control (P = 0.78) and intervention (P = 0.19) group showed a nonsignificant increase (0.4 and 2.5%, respectively). A 1-y intervention among primarily postmenopausal women in a study similar in size to this study found a decrease of 4% in breast density over 1 y without a difference between red-clover and placebo treatment (22). This larger decrease in density is probably due to the fact that only women with mammographic patterns that predict a relatively high risk to develop breast cancer were eligible to enter the trial. In a 2-y intervention with a low-fat, high-carbohydrate diet (3), the size of the dense areas also declined over time, i.e., 3.7 cm2 in the intervention and 1.3 cm2 in the control group. However, in that intervention, the overall breast size became smaller only in the intervention group (2.3 cm2) and remained more or less constant in the control group (+0.3 cm2) (22). In our study, soy intake during early life and adulthood was positively associated with the percentage density at baseline, which contradicts previous studies (10,16) showing that high adolescent soy intake was protective against breast cancer risk in later life.
In contrast to a previous cross-sectional study (31), we did not find differences in mammographic measures among women of different ethnic backgrounds. This is not a surprise given the younger age of these study subjects. A younger age makes it more likely that the women are third or fourth generation descendants of immigrants who have adopted the breast cancer risk of Caucasian women as reported from a large multiethnic cohort (32). The high percentage of women with a family history of breast cancer, the reproductive characteristics, the high educational level, and the strong motivation to participate in a prevention trial suggest that out study population carried an above average risk for breast cancer.
The major strengths of this trial are the excellent compliance with the study regimen (23), its relatively long duration, and the low dropout rates. To our knowledge, this is the first intervention with soy foods studying quantitative measures of mammographic density. Our study population included women from different ethnic groups who had experienced different levels of soy exposure during their lives. Despite the fact that only 18% of subjects switched mammographic clinics, some concerns about the comparability of mammograms are warranted. Minimal changes in positioning of the breast, the amount of pressure exerted during imaging, and the level of radiation exposure affect the appearance of the image. Different technicians use different approaches during the procedure. Slightly higher densities during the luteal phase may have added some error to the study (33) because we did not control the scheduling of mammograms and did not collect information on the timing of the mammogram during the menstrual cycle. We applied the newly developed lifetime soy frequency questionnaire for the first time. Although we think that it may correctly distinguish low from high soy exposure in women, it will require validation in the future. The distinct nature of tofu and other traditional soy foods makes it easy to recall their consumption, but assessment of soy intake will become more difficult in the future as more soy protein is introduced into Western foods (34). The association of early life and adult soy intake with breast density may be due to chance or due to unmeasured confounders, i.e., dietary or behavioral factors closely related to soy consumption.
In summary, we did not observe a difference in changes in the percentage of mammographic densities over 2 y of a soy intervention among premenopausal women. This indicates that soy foods do not appear to lead to increased proliferation during a 2-y period as proposed by 2 preliminary reports (35,36) that raised concerns about possible adverse effects of soy. Given the relation between soy intake before the intervention and the percentage density change over time, it appears that soy consumption during early life and adulthood may have more effect on mammographic density than foods during the intervention. This also raises the possibility that the effects of the intervention soy foods on breast density may be seen in later life even though we did not observe a significant change in mammographic density during the study period. Our findings of differing directions of association between early life and adult soy exposure with the percentage density change are puzzling. Other, unmeasured, confounding variables may have influenced the association. It remains to be determined whether soy consumption in early life can influence mammographic characteristics in later life. Future studies are warranted to investigate associations between soy intake during childhood and adolescence and subsequent breast cancer risk. Innovative research that assesses the association of declining percentage density with the increasing risk for breast cancer as age increases may also be necessary to understand the effect of the changes in percentage density over time.
| FOOTNOTES |
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Manuscript received 17 June 2004. Initial review completed 19 July 2004. Revision accepted 2 August 2004.
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