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Channing Laboratory, Brigham and Women’s Hospital and Harvard Medical School, Boston, Massachusetts 02115 [C. B., G. A. C., W. C. W., F. E. S., S. E. H.]; Departments of Epidemiology [G. A. C., W. C. W., S. E. H.], Nutrition [W. C. W.], and Environmental Health [F. E. S.], Harvard School of Public Health, Boston, Massachusetts 02115; and Departments of Medicine and Oncology, Cancer Prevention Research Unit, Lady Davis Institute of the Jewish General Hospital and McGill University, Montreal, Quebec, Canada H3T 1E2 [M. P.]
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ABSTRACT |
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 Top ABSTRACT INTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONREFERENCES |
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INTRODUCTION |
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TopABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONREFERENCES |
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The percentage of the total breast area that appears mammographically dense (percentage of breast density) is another strong predictor of breast cancer risk (6) . Mammographic breast density reflects a combination of epithelial and/or stromal proliferation relative to fat within the breast (7) . Women with >74% breast density have about a 5-fold greater risk of developing breast cancer than women with 0% breast density (6) . In light of the possible role of IGF-I in breast stromal and epithelial proliferation and the associations-at least in premenopausal women-between IGF-I and breast cancer risk, we evaluated the association of circulating IGF-I and IGFBP-3 levels with the percentage of the breast that is mammographically dense among participants in the NHS.
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MATERIALS AND METHODS |
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TopABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONREFERENCES |
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In the study reported here, we compared the percentage of the total breast area appearing dense on mammography with the plasma concentrations of IGF-I and IGFBP-3 among selected NHS participants who had served as controls in the previous study of plasma IGF-I and IGFBP-3 with risk of breast cancer (2) . These participants had no history of cancer and were either premenopausal or postmenopausal and were not using postmenopausal hormones at the time of blood sample collection. Women using postmenopausal hormones within the last 3 months or whose menstrual periods were induced by hormones during the last year also were not included in this study because use of postmenopausal hormones has been reported to lower circulating IGF-I levels (9, 10) and increase the percentage of breast density (11–13) . For each eligible participant, we sought to assess breast density from a mammogram that had been taken as close as possible to the date of blood collection. Because mammographic density is associated with both menopausal status and use of postmenopausal hormones, we restricted our analyses to participants whose reported menopausal status and postmenopausal hormone use at the time of mammography was the same as that at the time of blood sampling. This study was approved by the Committee on the Use of Human Subjects in Research at the Brigham and Women’s Hospital.
Of the 99 eligible women with known IGF-I levels who were premenopausal at the time of blood sampling, 87 (88%) indicated that they had a mammogram and provided written consent for our evaluation. We obtained mammograms of 80 of these women (92%), 65 (81%) of whom were premenopausal at mammography. Of the 307 eligible women who were postmenopausal and were not using postmenopausal hormones at the time of blood sampling 263 (86%) indicated that they had a mammogram and provided written consent for our evaluation. We obtained a usable film screen mammogram for 221 (84%) of these women, 192 (87%) of whom were postmenopausal and had not been using postmenopausal hormones at mammography.
IGF-I and IGFBP-3 were assayed by ELISA with reagents from Diagnostic Systems Laboratory (Webster, TX). The correlations between IGF-I values obtained by ELISA and those obtained by RIA after acid chromatography were high [Pearson r = 0.97 (2) ]. Plasma concentrations of IGF-I and IGFBP-3 were not affected by the blood collection and storage procedures followed in the NHS (2) . Previous studies have indicated that a single IGF-I measurement accurately reflects longer-term circulating IGF-I concentrations; the correlation coefficient between samples drawn 6 weeks apart was 0.94 (14) . Masked split specimens were included in every batch assayed for assessment of within- and between-batch coefficients of variation. For IGF-I and IGFBP-3, the within-batch coefficients of variation were 8.7% and 9.3%, respectively (2) , and the between-batch coefficients of variation were 15.6% and 19.4%, respectively (2) . Laboratory batch was controlled for in all analyses.
To assess mammographic density, the cranio-caudal views of both breasts were digitized at 261 microns/pixel with a Lumysis 85 laser film scanner, which covers a range of 0–4.0 optical density. The software for computer-assisted thresholding was developed at the University of Toronto [Toronto, Canada (15, 16) ]. Details regarding the software used to determine the total breast area and the area of dense mammographic appearance, based on variations in gray scale, have been published previously (15–17) . In brief, the film screen images are digitized and viewed on the computer screen. For each image, the observer sets the appropriate threshold level that defines the edge of the breast. Next, within this region of interest determined by the edge of the breast threshold, the observer sets a second threshold level delineating the dense area of the image viewed on the screen. The computer calculates the total number of pixels within the entire region of interest and that within the region identified as dense; from these values, the percentage of the breast area that appears dense is estimated. This measure of mammographic breast density has been shown to predict breast cancer risk (17) and was highly reproducible as measured within this study [within-person intraclass correlation coefficient = 0.93 (18) ].
The average density for both breasts was evaluated as the measure of interest. Additional analyses evaluated the associations when either a random side was selected for breast density determination or the greater breast density (right or left side) was used; results were essentially the same. Due to the symmetry between breast density for the right and left sides (mean difference, 0.47%), similar conclusions would be drawn no matter which measure was selected.
Information on menopausal status and use of postmenopausal hormones was obtained from either the biennial NHS questionnaire or by a supplemental questionnaire at the time of blood collection. From the supplemental questionnaire, women were defined as premenopausal if they reported having a menstrual period that was not induced by hormone medication within the last 12 months before blood collection or having had a hysterectomy with at least one ovary retained and were <49 years of age (nonsmokers) or <47 years (smokers). Women were defined as postmenopausal if they reported no menstrual period within the last 12 months before blood collection with natural menopause, radiation-induced menopause, bilateral oophorectomy, or surgical menopause with one or more ovaries retained and were >54 years (smokers) and >56 years (nonsmokers). These are the ages at which 90% of the participants in NHS who had a natural menopause were premenopausal or postmenopausal, respectively. Menopause status at the time of the mammogram was based on responses from the biennial questionnaire before the date of the mammogram. Women were asked whether their menstrual periods had ceased permanently. If they reported that their periods had not ceased and did not report use of postmenopausal hormones in the last 24 months, they were considered premenopausal. If they reported that their periods had ceased permanently, then the information regarding the reason their periods ceased and their age and smoking status determined whether they were postmenopausal as described above. All other covariates were assessed on the basis of the questionnaire preceding blood collection and, if different, on the basis of the questionnaire preceding mammography.
Age at mammography, BMI (kg/m2), history of
benign breast disease (yes or no), amount of usual alcohol consumption
(none, <5 g/day, 5–14.9 g/day, 15+ g/day), smoking status (never,
past, or current), parity (continuous), age at first birth
(continuous), family history of breast cancer (yes/no), type of
menopause (natural, surgical with ovaries removed, surgical with
retained ovaries, or surgical with unknown ovarian status), age at
menopause (continuous), and history of use of postmenopausal hormones
(never, past for <5 years, past for 5+ years) were all evaluated as
potential confounding variables because of their known associations
with breast density (6, 19)
or with IGF-I and IGFBP-3
levels (14, 20, 21) . Generalized linear models evaluated
the impact of each covariate as a predictor of percentage of breast
density (F test) and the test of heterogeneity (t test) of
the mean percentage of breast density across categories of each
covariate adjusted for age and BMI. Partial Spearman correlation
coefficients, adjusting for age and BMI, were calculated between the
percentage of breast density and each covariate. A covariate was
included as a potential confounder in the models if there was a
priori evidence of an association between the covariate and both
percentage of breast density and IGF levels, if there was evidence of a
trend in mean percentage of breast density across categories of the
covariate, if including the covariate in the models changed the
measures of association by 
10%, or if any of the Ps for
the tests (F test, t test, or correlation) were 
0.10. Due
to the small size of this study and the limited prevalence of some
covariates in this population, the associations that could be evaluated
were limited. For example, although smoking may be associated with
reduced IGF-1 levels, only 14% (9)
of premenopausal women and 13%
(22)
of postmenopausal women were current smokers in this population,
and smoking was not measurably associated with percentage of breast
density in this study.
Data were analyzed with SAS software (22) . Because log transformations of IGF-I, IGFBP-3, and mean percentage of breast density produced a distribution more skewed than obtained from the natural scale and because the measure of interest was mean percentage of breast density across categories of IGF-I and IGFBP-3, all analyses were conducted with the natural scaled variables. Statistical differences in the associations between the IGF-I:IGFBP-3 ratio and mammographic density by menopausal status were evaluated with an interaction term in a linear regression model. Generalized linear model analyses of variance provided estimates of the mean percentage of breast density for each quartile of IGF-I, IGFBP-3, or IGF-I:IGFBP-3 ratio, adjusted for potential confounders. Spearman’s partial correlation coefficients were estimated for comparisons of the continuous measure of percentage of breast density with the continuous values for IGF-I, IGFBP-3, and the IGF-I:IGFBP-3 ratio. Two-sided Ps are reported for the Spearman’s partial correlation coefficients.
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RESULTS |
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TopABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONREFERENCES |
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).
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In premenopausal women, breast density was positively correlated with
IGF-I and inversely correlated with IGFBP-3 (Table 2
). Adjustment for IGFBP-3 in the models clarified the association
between IGF-I and breast density; likewise, adjustment for IGF-I levels
further strengthened the association between IGFBP-3 and breast
density. The strongest associations between premenopausal IGF-I and
breast density were seen with comparisons adjusted for age, IGFBP-3,
alcohol intake, batch, and BMI. The mean breast density was 30% for
women in the lowest quartile of IGF-I and 44% for women in the highest
quartile of IGF-I. The multivariate-adjusted correlation for the
continuous measures of IGF-I and percentage of breast density was 0.36
(P = 0.007). In contrast, the mean percentage
of breast density was 43% for women in the lowest quartile of IGFBP-3
and 36% for those in the highest quartile of IGFBP-3. The
multivariate-adjusted correlation for IGFBP-3 was -0.24
(P = 0.07). Models that evaluated breast
density across quartiles of the molar ratio of IGF-I:IGFBP-3 among
premenopausal women showed a strong positive association in all
analyses. Adjustment for BMI further strengthened this association. The
multivariate adjusted mean breast density values were 30%, 33%, 38%,
and 48% for the ascending quartiles of the IGF-I:IGFBP-3 ratio. The
partial Spearman correlation for the continuous measure of the
IGF-I:IGFBP-3 ratio was 0.39 (P = 0.004).
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)]. Likewise, there was no indication of an association between the
IGF-I:IGFBP-3 ratio and breast density in postmenopausal women. There
was no association noted with breast density and IGF-I or IGFBP-3 in
analyses that excluded women who had used postmenopausal hormones in
the past.
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DISCUSSION |
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TopABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONREFERENCES |
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Previous studies showed that breast cancer risk rose steadily with increased percentage of the breast area with a dense appearance on a prediagnostic mammogram, and this association was not explained by other breast cancer risk factors such as age, weight, age at first child’s birth, family history of breast cancer, alcohol use, prior benign breast disease, age at menarche, and age at menopause (6, 23) . The computer-assisted technique developed at the University of Toronto for the quantification of percentage of breast density based on gray scale thresholding is more highly reproducible than previous visual estimates of breast density and has been shown to be useful in identifying high-risk women (16–18) . Although techniques such as those applied in this study now exist to assess breast density more uniformly than methods used in the past, and the high risk of breast cancer associated with a greater proportion of breast density has been recognized for some time, it is still not known by what mechanism breast density is related to risk.
Current breast density, reflecting the proportion of stromal and epithelial proliferation, may simply indicate the area of susceptible tissue (number of epithelial cells) or may represent the interaction between stromal and epithelial proliferation influenced by local growth factors, including epidermal growth factor, transforming growth factors, IGF-I, and IGF-II (24) . Growing evidence indicates that breast development and involution are influenced by IGFs (which increase proliferation) and IGFBPs (which reduce proliferation; Ref. 25 ). IGFBPs inhibit proliferation of breast cancer cells in vitro (26) and are associated with postlactational involution of the mammary gland in animal models (27) . Thus, greater breast density may be a consequence of higher IGF levels and an associated increase in proliferation and/or of decreased IGFBP levels with a resulting reduction in the involution process.
Paradoxically, breast density declines gradually with age, whereas breast cancer risk increases (6) . Because circulating levels of IGF-I and IGFBP-3 also decrease with age (21) , the relation between breast density and circulating IGF-I and IGFBP-3 is of great interest. The findings of this analysis are consistent with those of the previous NHS analysis of plasma IGF-I and breast cancer risk, which indicated a strong association of risk with premenopausal IGF-I levels adjusted for IGFBP-3 levels and no association of risk with postmenopausal levels (2) . A higher proportion of breast density has been associated with a 3–4-fold increase in the risk of breast cancer among premenopausal women and a 5–6-fold increase in the risk of breast cancer among postmenopausal women (6) . Although the lack of association between IGF-I and breast density in postmenopausal women seems inconsistent with the strong association observed between breast density and breast cancer risk in both premenopausal and postmenopausal women, it is possible that local expression of IGF-I and IGFBP-3 in breast tissue is the biologically relevant determinant of risk. Under this hypothesis, breast density may serve as a better proxy for local tissue IGF-I and IGFBP-3 levels than circulating plasma levels among postmenopausal women. Alternatively, high IGF-I and/or low IGFBP-3 levels that were correlated to breast density when premenopausal may determine both premenopausal and postmenopausal breast cancer risk. Under this hypothesis, risk of postmenopausal breast cancer would be largely determined before menopause, when circulating IGF-I was high, and IGFBP-3 was low. Postmenopausal breast density would continue to reflect breast cancer risk because low levels of IGFBP-3 would be associated with a reduced involution process. Interestingly, with the use of the antiestrogen tamoxifen, which has been shown to reduce IGF-1 levels (28) , mammographic parenchymal patterns became more lucent in postmenopausal women (29) . Further research is needed to test these hypotheses and evaluate the association between tissue levels and circulating levels of IGF-I and IGFBP-3 in both pre- and postmenopausal women. Studies are also needed to quantitate the intraindividual variation and changes in both IGF-1 and IGFBP-3 and percentage of breast density as a woman goes from being premenopausal to postmenopausal.
The blood collection in the NHS was not timed to the menstrual cycle among premenopausal women and is thus another potential source of variability in the assessment of an association of premenopausal plasma IGF-I and IGFBP-3 levels with breast density. However, in previous studies (30–33) , little variation in IGF levels has been observed over the menstrual cycle. Another potential limitation of this study is the time elapsed between the mammogram and the blood draw. However, analyses restricted to mammograms obtained within 6 months of the blood draw showed patterns of association similar to those reported herein. Furthermore, mammographic breast density has been shown to predict risk for 10 or more years. Therefore, given that the mammogram used in this study does not exactly reflect levels at the time of the blood draw, one would expect that the true associations between plasma levels and breast density measured concurrently would be even stronger than those demonstrated in this analysis. Likewise, to the degree that menopause status was misclassified and postmenopausal women were included among premenopausal women, there is likely to be a stronger association between IGF level and percentage of breast density in premenopausal women and a greater difference in the true associations between pre- and postmenopausal women than detected in this study. Because IGF-I is partially regulated by the levels of other endogenous hormones such as estradiol (34) , additional studies that incorporate information on other hormones as well as IGFs may more clearly elucidate the biology underlying the association between breast density and breast cancer risk.
To our knowledge, this is the first report of a direct comparison of plasma IGF-I and IGFBP-3 levels with breast density. The strong positive correlation between the IGF-I:IGFBP-3 ratio and breast density among premenopausal women and the lack of such an association in postmenopausal women provide further support for earlier reports of an increased risk of breast cancer associated with premenopausal levels of IGF-I adjusted for IGFBP-3 (2, 3, 5) .
Future studies will determine to what extent breast density and the IGF-I:IGFBP-3 ratio are independent breast cancer risk factors.
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ACKNOWLEDGMENTS |
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FOOTNOTES |
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1 Supported in part by a Massachusetts Department
of Public Health Breast Cancer Research grant; NIH Grants CA-75016,
CA-40356, and CA-49449; and a grant from the Canadian Breast Cancer
Research Initiative (to M. P.). 
2 To whom requests for reprints should be
addressed, at Channing Laboratory, 181 Longwood Avenue, Boston, MA
02115.
3 The abbreviations used are: IGF, insulin-like
growth factor; IGFBP, IGF-binding protein; NHS, Nurses’ Health Study;
BMI, body mass index.
Received 1/ 6/00. Accepted 5/17/00.
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D. Heng, F. Gao, R. Jong, E. Fishell, M. Yaffe, L. Martin, T. Li, J. Stone, L. Sun, J. Hopper, et al. Risk Factors for Breast Cancer Associated with Mammographic Features in Singaporean Chinese Women Cancer Epidemiol. Biomarkers Prev., November 1, 2004; 13(11): 1751 - 1758. [Abstract] [Full Text] [PDF]
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 R. G. Richards, D. M. Klotz, M. P. Walker, and R. P. DiAugustine Mammary Gland Branching Morphogenesis Is Diminished in Mice with a Deficiency of Insulin-like Growth Factor-I (IGF-I), But Not in Mice with a Liver-Specific Deletion of IGF-I Endocrinology, July 1, 2004; 145(7): 3106 - 3110. [Abstract] [Full Text] [PDF]
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 A. Decensi, B. Bonanni, L. Baglietto, A. Guerrieri-Gonzaga, F. Ramazzotto, H. Johansson, C. Robertson, I. Marinucci, F. Mariette, M. T. Sandri, et al. A Two-by-Two Factorial Trial Comparing Oral with Transdermal Estrogen Therapy and Fenretinide with Placebo on Breast Cancer Biomarkers Clin. Cancer Res., July 1, 2004; 10(13): 4389 - 4397. [Abstract] [Full Text] [PDF]
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J. H. Lai, D. Vesprini, W. Zhang, M. J. Yaffe, M. Pollak, and S. A. Narod A Polymorphic Locus in the Promoter Region of the IGFBP3 Gene Is Related to Mammographic Breast Density Cancer Epidemiol. Biomarkers Prev., April 1, 2004; 13(4): 573 - 582. [Abstract] [Full Text] [PDF]
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S. E. Oliver, B. Barrass, D. J. Gunnell, J. L. Donovan, T. J. Peters, R. A. Persad, D. Gillatt, D. E. Neal, F. C. Hamdy, and J. M. P. Holly Serum Insulin-Like Growth Factor-I Is Positively Associated with Serum Prostate-Specific Antigen in Middle-Aged Men without Evidence of Prostate Cancer Cancer Epidemiol. Biomarkers Prev., January 1, 2004; 13(1): 163 - 165. [Abstract] [Full Text] [PDF]
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 J. A. Harvey and V. E. Bovbjerg Quantitative Assessment of Mammographic Breast Density: Relationship with Breast Cancer Risk Radiology, January 1, 2004; 230(1): 29 - 41. [Abstract] [Full Text] [PDF]
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H. Yu, X.-O. Shu, B. D. L. Li, Q. Dai, Y.-T. Gao, F. Jin, and W. Zheng Joint Effect of Insulin-like Growth Factors and Sex Steroids on Breast Cancer Risk Cancer Epidemiol. Biomarkers Prev., October 1, 2003; 12(10): 1067 - 1073. [Abstract] [Full Text] [PDF]
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C.-C. Hong, H. J. Thompson, C. Jiang, G. L. Hammond, D. Tritchler, M. Yaffe, and N. F. Boyd Val158Met Polymorphism in Catechol-O-methyltransferase Gene Associated with Risk Factors for Breast Cancer Cancer Epidemiol. Biomarkers Prev., September 1, 2003; 12(9): 838 - 847. [Abstract] [Full Text] [PDF]
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K. H. Schmitz, R. L. Ahmed, and D. Yee Effects of a 9-Month Strength Training Intervention on Insulin, Insulin-like Growth Factor (IGF)-I, IGF-binding Protein (IGFBP)-1, and IGFBP-3 in 30-50-Year-Old Women Cancer Epidemiol. Biomarkers Prev., December 1, 2002; 11(12): 1597 - 1604. [Abstract] [Full Text] [PDF]
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D. B. Willis and N. H. Colburn Molecular Targets for Cancer Prevention: A Meeting Review of the Third American Cancer Society-Schilling Research Conference Cancer Epidemiol. Biomarkers Prev., October 1, 2002; 11(10): 972 - 978. [Abstract] [Full Text] [PDF]
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N. Boyd, L. Martin, J. Stone, L. Little, S. Minkin, and M. Yaffe A Longitudinal Study of the Effects of Menopause on Mammographic Features Cancer Epidemiol. Biomarkers Prev., October 1, 2002; 11(10): 1048 - 1053. [Abstract] [Full Text] [PDF]
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C. J. Fabian, B. F. Kimler, D. A. Brady, M. S. Mayo, C. H. J. Chang, J. A. Ferraro, C. M. Zalles, A. L. Stanton, S. Masood, W. E. Grizzle, et al. A Phase II Breast Cancer Chemoprevention Trial of Oral {alpha}-Difluoromethylornithine: Breast Tissue, Imaging, and Serum and Urine Biomarkers Clin. Cancer Res., October 1, 2002; 8(10): 3105 - 3117. [Abstract] [Full Text] [PDF]
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 N. F. Boyd, G. S. Dite, J. Stone, A. Gunasekara, D. R. English, M. R.E. McCredie, G. G. Giles, D. Tritchler, A. Chiarelli, M. J. Yaffe, et al. Heritability of Mammographic Density, a Risk Factor for Breast Cancer N. Engl. J. Med., September 19, 2002; 347(12): 886 - 894. [Abstract] [Full Text] [PDF]
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H. Yu, F. Jin, X.-O. Shu, B. D. L. Li, Q. Dai, J.-R. Cheng, H. J. Berkel, and W. Zheng Insulin-like Growth Factors and Breast Cancer Risk in Chinese Women Cancer Epidemiol. Biomarkers Prev., August 1, 2002; 11(8): 705 - 712. [Abstract] [Full Text] [PDF]
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S. J. London, J.-M. Yuan, G. S. Travlos, Y.-T. Gao, R. E. Wilson, R. K. Ross, and M. C. Yu Insulin-Like Growth Factor I, IGF-Binding Protein 3, and Lung Cancer Risk in a Prospective Study of Men in China J Natl Cancer Inst, May 15, 2002; 94(10): 749 - 754. [Abstract] [Full Text] [PDF]
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 K. W. Singletary and S. M. Gapstur Alcohol and Breast Cancer: Review of Epidemiologic and Experimental Evidence and Potential Mechanisms JAMA, November 7, 2001; 286(17): 2143 - 2151. [Abstract] [Full Text] [PDF]
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A. Decensi, H. Johansson, R. Miceli, L. Mariani, T. Camerini, E. Cavadini, M. G. Di Mauro, A. Barreca, A. G. Gonzaga, S. Diani, et al. Long-Term Effects of Fenretinide, a Retinoic Acid Derivative, on the Insulin-like Growth Factor System in Women with Early Breast Cancer Cancer Epidemiol. Biomarkers Prev., October 1, 2001; 10(10): 1047 - 1053. [Abstract] [Full Text] [PDF]
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Y.-P. Guo, L. J. Martin, W. Hanna, D. Banerjee, N. Miller, E. Fishell, R. Khokha, and N. F. Boyd Growth Factors and Stromal Matrix Proteins Associated with Mammographic Densities Cancer Epidemiol. Biomarkers Prev., March 1, 2001; 10(3): 243 - 248. [Abstract] [Full Text]
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J. Brisson, B. Brisson, G. Coté, E. Maunsell, S. Bérubé, and J. Robert Tamoxifen and Mammographic Breast Densities Cancer Epidemiol. Biomarkers Prev., September 1, 2000; 9(9): 911 - 915. [Abstract] [Full Text]
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