Mammographic density, breast cancer risk and risk prediction

Circulating sex hormones and mammographic breast density among postmenopausal women

The use of breast density as an intermediate or predictive marker of breast cancer risk is limited by an incomplete understanding of the etiology of breast density. High blood levels of endogenous estrogens and androgens are associated with increased risk of breast cancer among postmenopausal women. We sought to examine whether these hormones are also associated with breast density. The Wisconsin Breast Density Study enrolled 257 postmenopausal women, ages 55-70 years, with no history of postmenopausal hormone use, from mammography clinics in Madison, Wisconsin. Subjects provided a blood sample for sex hormone analysis, and breast density was measured from subjects' screening mammograms using a computer-assisted thresholding method. Numerous sex hormones were associated with breast density in age-adjusted analyses. However, further adjustment for body mass index and other potentially confounding factors substantially attenuated or eliminated these associations. In the fully adjusted model, there remained a positive association between percent breast density and serum progesterone (P=0.03), with percent density rising from 11.9% (95% CI: 9.8, 14.1%) among women in the lowest quartile of serum progesterone to 15.4% (12.9, 18.2%) among women in the highest quartile. There was also a positive association between sex hormone binding globulin and percent breast density (P=0.06). In contrast, there were no independent associations between percent breast density and estradiol (total, free, or bioavailable), estrone, estrone sulfate, or testosterone (total, free, or bioavailable). These results suggest that breast density has a hormonal etiology; however, it may differ in important ways from that of breast cancer risk.

Mammographic density and breast cancer risk: the role of the fat surrounding the fibroglandular tissue

Introduction

Both the percent of mammographic density and absolute dense (fibroglandular) area are strong breast cancer risk factors. The role of non-dense (fat) breast tissue is not often investigated, but we hypothesize that this also influences risk. In this study we investigated the independent effects of dense and fat tissue, as well as their combined effect on postmenopausal breast cancer risk.

Methods

We performed a nested case-control study within the EPIC-NL cohort (358 postmenopausal breast cancer cases and 859 postmenopausal controls). We used multivariate logistic regression analyses to estimate breast cancer odds ratios adjusted for body mass index and other breast cancer risk factors.

Results

Large areas of dense (upper (Q5) vs lower quintile (Q1): OR 2.8 95% CI 1.7 to 4.8) and fat tissue (Q5 vs Q1: OR 2.4; 95% CI 1.3 to 4.2) were independently associated with higher breast cancer risk. The combined measure showed that the highest risk was found in women with both a large (above median) area of dense and fat tissue.

Conclusions

Fibroglandular and breast fat tissue have independent effects on breast cancer risk. The results indicate that the non-dense tissue, which represents the local breast fat, increases risk, even independent of body mass index (BMI). When studying dense breast tissue in relation to breast cancer risk, adjustment for non-dense tissue seems to change risk estimates to a larger extent than adjustment for BMI. This indicates that adjustment for non-dense tissue should be considered when studying associations between dense areas and breast cancer risk.

Less mammographic density after nasal versus oral administration of postmenopausal hormone therapy

OBJECTIVE

Nasal administration gives a more acute but shorter rise in serum hormone levels than oral administration and may therefore have less effect on the fibroglandular tissue in the breasts. We studied the change in mammographic breast density after nasal vs. oral administration of postmenopausal hormone therapy (PHT).

METHODS

We studied participants in a randomized, controlled trial on the impact of nasal vs. oral administration of PHT (combined 17β-estradiol plus norethisterone) for 1 year. Two radiologists classified mammographic density at baseline and after 1 year into four categories. Also, the percentage density was calculated by a computer-based method. The main outcome measure was the difference in the proportion of women with an increase in mammographic density category after 1 year between the nasal and oral groups. Also, the change in the percentage density was calculated.

RESULTS

The study group comprised 112 healthy postmenopausal women (mean age 56 years), of whom 53 received oral and 59 intranasal PHT. An increase in mammographic density category after 1 year was seen in 20% of the women in the nasal group and in 34% of the oral group. This resulted in a non-significant difference in the proportion of women in whom mammographic breast density had increased by 214% (95% confidence interval (CI) 230% to 2.7%). The mean change in percentage density was 21.2% in the nasal group and + 1.2% in the oral group, yielding a 22.4% differential effect (95% CI 27.3% to 2.5%).

CONCLUSIONS

One year of nasal PHT gave a smaller, although not statistically significant, increase in mammographic density than oral PHT. Remaining issues are the relation between the route of administration of PHT and breast complaints and breast cancer risk.

Versican but not decorin accumulation is related to malignancy in mammographically detected high density and malignant-appearing microcalcifications in non-palpable breast carcinomas

Background

Mammographic density (MD) and malignant-appearing microcalcifications (MAMCs) represent the earliest mammographic findings of non-palpable breast carcinomas. Matrix proteoglycans versican and decorin are frequently over-expressed in various malignancies and are differently involved in the progression of cancer. In the present study, we have evaluated the expression of versican and decorin in non-palpable breast carcinomas and their association with high risk mammographic findings and tumor characteristics.

Methods

Three hundred and ten patients with non-palpable suspicious breast lesions, detected during screening mammography, were studied. Histological examination was carried out and the expression of decorin, versican, estrogen receptor α (ERα), progesterone receptor (PR) and c-erbB2 (HER-2/neu) was assessed by immunohistochemistry.

Results

Histological examination showed 83 out of 310 (26.8%) carcinomas of various subtypes. Immunohistochemistry was carried out in 62/83 carcinomas. Decorin was accumulated in breast tissues with MD and MAMCs independently of the presence of malignancy. In contrast, versican was significantly increased only in carcinomas with MAMCs (median ± SE: 42.0 ± 9.1) and MD (22.5 ± 10.1) as compared to normal breast tissue with MAMCs (14.0 ± 5.8), MD (11.0 ± 4.4) and normal breast tissue without mammographic findings (10.0 ± 2.0). Elevated levels of versican were correlated with higher tumor grade and invasiveness in carcinomas with MD and MAMCs, whereas increased amounts of decorin were associated with in situ carcinomas in MAMCs. Stromal deposition of both proteoglycans was related to higher expression of ERα and PR in tumor cells only in MAMCs.

Conclusions

The specific accumulation of versican in breast tissue with high MD and MAMCs only in the presence of malignant transformation and its association with the aggressiveness of the tumor suggests its possible use as molecular marker in non-palpable breast carcinomas.

Analysis of parenchymal texture with digital breast tomosynthesis: comparison with digital mammography and implications for cancer risk assessment

PURPOSE

To correlate the parenchymal texture features at digital breast tomosynthesis (DBT) and digital mammography with breast percent density (PD), an established breast cancer risk factor, in a screening population of women.

MATERIALS AND METHODS

This HIPAA-compliant study was approved by the institutional review board. Bilateral DBT images and digital mammograms from 71 women (mean age, 54 years; age range, 34-75 years) with negative or benign findings at screening mammography were retrospectively collected from a separate institutional review board-approved DBT screening trial (performed from July 2007 to March 2008) in which all women had given written informed consent. Parenchymal texture features of skewness, coarseness, contrast, energy, homogeneity, and fractal dimension were computed from the retroareolar region. Principal component analysis (PCA) was applied to obtain orthogonal texture components. Mammographic PD was estimated with software. Correlation analysis and multiple linear regression with generalized estimating equations were performed to determine the association between texture features and breast PD. Regression was adjusted for age to determine the independent association of texture to breast PD when age was also considered as a predictor variable.

RESULTS

Texture feature correlations to breast PD were stronger with DBT than with digital mammography. Statistically significant correlations (P < .001) were observed for contrast (r = 0.48), energy (r = -0.47), and homogeneity (r = -0.56) at DBT and for contrast (r = 0.26), energy (r = -0.26), and homogeneity (r = -0.33) at digital mammography. Multiple linear regression analysis of PCA texture components as predictors of PD also demonstrated significantly stronger associations with DBT. The association was strongest when age was also considered as a predictor of PD (R² = 0.41 for DBT and 0.28 for digital mammography; P < .001).

CONCLUSION

Parenchymal texture features are more strongly correlated to breast PD in DBT than in digital mammography. The authors' long-term hypothesis is that parenchymal texture analysis with DBT will result in quantitative imaging biomarkers that can improve the estimation of breast cancer risk.

Mechanical phenotype is important for stromal aromatase expression

Evidence that aromatase expression in tumor-associated breast stroma is elevated, provides a rationale for use of aromatase inhibitors (AIs) in breast cancer treatment. However, regulation of local aromatase expression in cancer-free breast stroma is poorly understood. Recent clinical work indicates that stromal cells in dense breast tissue tend to express higher levels of aromatase than their counterpart from non-dense tissue. Consistent with the clinical observation, our cell culture-based study indicated that cell density, cell shape, and extracellular matrix (ECM) significantly induced stromal aromatase expression via a distinct signal transduction pathway. In addition, we identified a number of cell surface markers that are commonly associated with aromatase-expressing stromal cells. As mammographic density is one of the strongest and most prevalent risk factors for breast cancer, these findings provide a potential mechanistic link between alterations in tissue composition of dense breast tissue and increased stromal aromatase expression. Further exploration of the in vitro model system may advance understanding of an important problem in breast cancer biology.

Volume of mammographic density and risk of breast cancer

BACKGROUND

Assessing the volume of mammographic density might more accurately reflect the amount of breast volume at risk of malignant transformation and provide a stronger indication of risk of breast cancer than methods based on qualitative scores or dense breast area.

METHODS

We prospectively collected mammograms for women undergoing screening mammography. We determined the diagnosis of subsequent invasive or ductal carcinoma in situ for 275 cases, selected 825 controls matched for age, ethnicity, and mammography system, and assessed three measures of breast density: percent dense area, fibroglandular volume, and percent fibroglandular volume.

RESULTS

After adjustment for familial breast cancer history, body mass index, history of breast biopsy, and age at first live birth, the ORs for breast cancer risk in the highest versus lowest measurement quintiles were 2.5 (95% CI: 1.5-4.3) for percent dense area, 2.9 (95% CI: 1.7-4.9) for fibroglandular volume, and 4.1 (95% CI: 2.3-7.2) for percent fibroglandular volume. Net reclassification indexes for density measures plus risk factors versus risk factors alone were 9.6% (P = 0.07) for percent dense area, 21.1% (P = 0.0001) for fibroglandular volume, and 14.8% (P = 0.004) for percent fibroglandular volume. Fibroglandular volume improved the categorical risk classification of 1 in 5 women for both women with and without breast cancer.

CONCLUSION

Volumetric measures of breast density are more accurate predictors of breast cancer risk than risk factors alone and than percent dense area.

IMPACT

Risk models including dense fibroglandular volume may more accurately predict breast cancer risk than current risk models.

Comparison of radiation exposure and associated radiation-induced cancer risks from mammography and molecular imaging of the breast

PURPOSE

Recent studies have raised concerns about exposure to low-dose ionizing radiation from medical imaging procedures. Little has been published regarding the relative exposure and risks associated with breast imaging techniques such as breast specific gamma imaging (BSGI), molecular breast imaging (MBI), or positron emission mammography (PEM). The purpose of this article was to estimate and compare the risks of radiation-induced cancer from mammography and techniques such as PEM, BSGI, and MBI in a screening environment.

METHODS

The authors used a common scheme for all estimates of cancer incidence and mortality based on the excess absolute risk model from the BEIR VII report. The lifetime attributable risk model was used to estimate the lifetime risk of radiation-induced breast cancer incidence and mortality. All estimates of cancer incidence and mortality were based on a population of 100 000 females followed from birth to age 80 and adjusted for the fraction that survives to various ages between 0 and 80. Assuming annual screening from ages 40 to 80 and from ages 50 to 80, the cumulative cancer incidence and mortality attributed to digital mammography, screen-film mammography, MBI, BSGI, and PEM was calculated. The corresponding cancer incidence and mortality from natural background radiation was calculated as a useful reference. Assuming a 15%-32% reduction in mortality from screening, the benefit/risk ratio for the different imaging modalities was evaluated.

RESULTS

Using conventional doses of 925 MBq Tc-99m sestamibi for MBI and BSGI and 370 MBq F-18 FDG for PEM, the cumulative cancer incidence and mortality were found to be 15-30 times higher than digital mammography. The benefit/risk ratio for annual digital mammography was >50:1 for both the 40-80 and 50-80 screening groups, but dropped to 3:1 for the 40-49 age group. If the primary use of MBI, BSGI, and PEM is in women with dense breast tissue, then the administered doses need to be in the range 75-150 MBq for Tc-99m sestamibi and 35 MBq-70 MBq for F-18 FDG in order to obtain benefit/risk ratios comparable to those of mammography in these age groups. These dose ranges should be achievable with enhancements to current technology while maintaining a reasonable examination time.

CONCLUSIONS

The results of the dose estimates in this study clearly indicate that if molecular imaging techniques are to be of value in screening for breast cancer, then the administered doses need to be substantially reduced to better match the effective doses of mammography.

Assessment of mammographic density before and after first full-term pregnancy

Mammographic density (MD) has consistently been found as one of the strongest breast cancer risk factors. In our study, both qualitative and quantitative density measurements were performed in a hospital-based group of premenopausal women before and after first full-term pregnancy providing an opportunity for direct evaluation of the effects of one pregnancy on MD. Mammograms were obtained from 23 women before and after first full-term pregnancy and from 28 nulliparous controls. MD was determined by a standard qualitative assessment method using the Breast Imaging Reporting and Data System, and a quantitative computer-based threshold method (0-100%). The mean age at mammography before and after pregnancy was 31 and 34 years, respectively, with a mean difference of 40 months between mammographies. The quantitative density assessment showed a significant reduction in relative MD after pregnancy of 12 percentage points (8.6-15.4), compared with 3.1 (0.0-6.2) in the nulliparous control group (P<0.001). A reduction in MD of more than 10% was seen in 52% of the patients, compared with 18% of the controls. The qualitative density assessment confirmed a reduction in MD after pregnancy by one Breast Imaging Reporting and Data System category (P=0.02). This longitudinal study showed that MD can be influenced by one full-term pregnancy. This effect was seen with both quantitative and qualitative assessment methods. It may be hypothesized that breast cancer risk reduction associated with pregnancy is mediated through a direct reduction of MD, and MD assessment might be incorporated in individualizing risk assessment and prevention.

Effects of isoflavones on breast density in pre- and post-menopausal women: a systematic review and meta-analysis of randomized controlled trials

BACKGROUND

Isoflavones from soy and red clover exert modest hormonal effects in women, but the relevance to risk of breast cancer is unclear. The aim of this meta-analysis was to assess the effects of isoflavone-rich foods or supplements on a biomarker of breast cancer risk, women's mammographic density.

METHODS

Electronic searches were performed on The Cochrane Library, Medline and EMBASE (to June 2009), and reference lists and trial investigators were consulted to identify further studies. Randomized controlled trials (RCTs) of isoflavone-rich foods or supplements versus placebo with a duration of at least 6 months were included in our analysis. Inclusion/exclusion, data extraction and validity assessment were carried out independently in duplicate, and meta-analysis used to pool study results. Subgrouping, sensitivity analysis, assessment of heterogeneity and funnel plots were used to interpret the results.

RESULTS

Eight RCTs (1287 women) compared isoflavones with placebo for between 6 months and 3 years. Meta-analysis suggested no overall effect of dietary isoflavones on breast density in all women combined [mean difference (MD) 0.69%, 95% confidence interval (CI) -0.78 to 2.17] or post-menopausal women (MD -1.10%, 95% CI -3.22 to 1.03). However, there was a modest increase in mammographic density in premenopausal women (MD 1.83%, 95% CI 0.25-3.40) without heterogeneity but this effect was lost in one of three sensitivity analyses.

CONCLUSIONS

Isoflavone intake does not alter breast density in post-menopausal women, but may cause a small increase in breast density in premenopausal women. Larger, long-term trials are required to determine if these small effects are clinically relevant.

Independent association of lobular involution and mammographic breast density with breast cancer risk

Background

Lobular involution, or age-related atrophy of breast lobules, is inversely associated with breast cancer risk, and mammographic breast density (MBD) is positively associated with breast cancer risk.

Methods

To evaluate whether lobular involution and MBD are independently associated with breast cancer risk in women with benign breast disease, we performed a nested cohort study among women (n = 2666) with benign breast disease diagnosed at Mayo Clinic between January 1, 1985, and December 31, 1991 and a mammogram available within 6 months of the diagnosis. Women were followed up for an average of 13.3 years to document any breast cancer incidence. Lobular involution was categorized as none, partial, or complete; parenchymal pattern was classified using the Wolfe classification as N1 (nondense), P1, P2 (ductal prominence occupying <25%, or >25% of the breast, respectively), or DY (extremely dense). Hazard ratios (HRs) and 95% confidence intervals (CIs) to assess associations of lobular involution and MBD with breast cancer risk were estimated using adjusted Cox proportional hazards model. All tests of statistical significance were two-sided.

Results

After adjustment for MBD, having no or partial lobular involution was associated with a higher risk of breast cancer than having complete involution (none: HR of breast cancer incidence = 2.62, 95% CI = 1.39 to 4.94; partial: HR of breast cancer incidence = 1.61, 95% CI = 1.03 to 2.53; P_trend = .002). Similarly, after adjustment for involution, having dense breasts was associated with higher risk of breast cancer than having nondense breasts (for DY: HR of breast cancer incidence = 1.67, 95% CI = 1.03 to 2.73; for P2: HR of breast cancer incidence = 1.96, 95% CI = 1.20 to 3.21; for P1: HR of breast cancer incidence = 1.23, 95% CI = 0.67 to 2.26; P_trend = .02). Having a combination of no involution and dense breasts was associated with higher risk of breast cancer than having complete involution and nondense breasts (HR of breast cancer incidence = 4.08, 95% CI = 1.72 to 9.68; P = .006).

Conclusion

Lobular involution and MBD are independently associated with breast cancer incidence; combined, they are associated with an even greater risk for breast cancer.

Computational simulation of breast compression based on segmented breast and fibroglandular tissues on magnetic resonance images

This study presents a finite element-based computational model to simulate the three-dimensional deformation of a breast and fibroglandular tissues under compression. The simulation was based on 3D MR images of the breast, and craniocaudal and mediolateral oblique compression, as used in mammography, was applied. The geometry of the whole breast and the segmented fibroglandular tissues within the breast were reconstructed using triangular meshes by using the Avizo 6.0 software package. Due to the large deformation in breast compression, a finite element model was used to simulate the nonlinear elastic tissue deformation under compression, using the MSC.Marc software package. The model was tested in four cases. The results showed a higher displacement along the compression direction compared to the other two directions. The compressed breast thickness in these four cases at a compression ratio of 60% was in the range of 5-7 cm, which is a typical range of thickness in mammography. The projection of the fibroglandular tissue mesh at a compression ratio of 60% was compared to the corresponding mammograms of two women, and they demonstrated spatially matched distributions. However, since the compression was based on magnetic resonance imaging (MRI), which has much coarser spatial resolution than the in-plane resolution of mammography, this method is unlikely to generate a synthetic mammogram close to the clinical quality. Whether this model may be used to understand the technical factors that may impact the variations in breast density needs further investigation. Since this method can be applied to simulate compression of the breast at different views and different compression levels, another possible application is to provide a tool for comparing breast images acquired using different imaging modalities--such as MRI, mammography, whole breast ultrasound and molecular imaging--that are performed using different body positions and under different compression conditions.

Association between mammographic density and age-related lobular involution of the breast

PURPOSE

Mammographic density and lobular involution are both significant risk factors for breast cancer, but whether these reflect the same biology is unknown. We examined the involution and density association in a large benign breast disease (BBD) cohort.

PATIENTS AND METHODS

Women in the Mayo Clinic BBD cohort who had a mammogram within 6 months of BBD diagnosis were eligible. The proportion of normal lobules that were involuted was categorized by an expert pathologist as no (0%), partial (1% to 74%), or complete involution (>or= 75%). Mammographic density was estimated as the four-category parenchymal pattern. Statistical analyses adjusted for potential confounders and evaluated modification by parity and age. We corroborated findings in a sample of women with BBD from the Mayo Mammography Health Study (MMHS) with quantitative percent density (PD) and absolute dense and nondense area estimates.

RESULTS

Women in the Mayo BBD cohort (n = 2,667) with no (odds ratio, 1.7; 95% CI, 1.2 to 2.3) or partial (odds ratio, 1.3; 95% CI, 1.0 to 1.6) involution had greater odds of high density (DY pattern) than those with complete involution (P trend < .01). There was no evidence for effect modification by age or parity. Among 317 women with BBD in the MMHS study, there was an inverse association between involution and PD (mean PD, 22.4%, 21.6%, 17.2%, for no, partial, and complete, respectively; P trend = .04) and a strong positive association of involution with nondense area (P trend < .01). No association was seen between involution and dense area (P trend = .56).

CONCLUSION

We present evidence of an inverse association between involution and mammographic density.

Genetic variation in the estrogen metabolic pathway and mammographic density as an intermediate phenotype of breast cancer

Introduction

Several studies have examined the effect of genetic variants in genes involved in the estrogen metabolic pathway on mammographic density, but the number of loci studied and the sample sizes evaluated have been small and pathways have not been evaluated comprehensively. In this study, we evaluate the association between mammographic density and genetic variants of the estrogen metabolic pathway.

Methods

A total of 239 SNPs in 34 estrogen metabolic genes were studied in 1,731 Swedish women who participated in a breast cancer case-control study, of which 891 were cases and 840 were controls. Film mammograms of the medio-lateral oblique view were digitalized and the software Cumulus was used for computer-assisted semi-automated thresholding of mammographic density. Generalized linear models controlling for possible confounders were used to evaluate the effects of SNPs on mammographic density. Results found to be nominally significant were examined in two independent populations. The admixture maximum likelihood-based global test was performed to evaluate the cumulative effect from multiple SNPs within the whole metabolic pathway and three subpathways for androgen synthesis, androgen-to-estrogen conversion and estrogen removal.

Results

Genetic variants of genes involved in estrogen metabolism exhibited no appreciable effect on mammographic density. None of the nominally significant findings were validated. In addition, global analyses on the overall estrogen metabolic pathway and its subpathways did not yield statistically significant results.

Conclusions

Overall, there is no conclusive evidence that genetic variants in genes involved in the estrogen metabolic pathway are associated with mammographic density in postmenopausal women.

Single x-ray absorptiometry method for the quantitative mammographic measure of fibroglandular tissue volume

PURPOSE

This study describes the design and characteristics of a highly accurate, precise, and automated single-energy method to quantify percent fibroglandular tissue volume (%FGV) and fibroglandular tissue volume (FGV) using digital screening mammography.

METHODS

The method uses a breast tissue-equivalent phantom in the unused portion of the mammogram as a reference to estimate breast composition. The phantom is used to calculate breast thickness and composition for each image regardless of x-ray technique or the presence of paddle tilt. The phantom adheres to the top of the mammographic compression paddle and stays in place for both craniocaudal and mediolateral oblique screening views. We describe the automated method to identify the phantom and paddle orientation with a three-dimensional reconstruction least-squares technique. A series of test phantoms, with a breast thickness range of 0.5-8 cm and a %FGV of 0%-100%, were made to test the accuracy and precision of the technique.

RESULTS

Using test phantoms, the estimated repeatability standard deviation equaled 2%, with a +/-2% accuracy for the entire thickness and density ranges. Without correction, paddle tilt was found to create large errors in the measured density values of up to 7%/mm difference from actual breast thickness. This new density measurement is stable over time, with no significant drifts in calibration noted during a four-month period. Comparisons of %FGV to mammographic percent density and left to right breast %FGV were highly correlated (r=0.83 and 0.94, respectively).

CONCLUSIONS

An automated method for quantifying fibroglandular tissue volume has been developed. It exhibited good accuracy and precision for a broad range of breast thicknesses, paddle tilt angles, and %FGV values. Clinical testing showed high correlation to mammographic density and between left and right breasts.

Reduced DNA repair capacity for removing tobacco carcinogen-induced DNA adducts contributes to risk of head and neck cancer but not tumor characteristics

PURPOSE

Although cigarette smoking and alcohol use are known risk factors for squamous cell carcinoma of head and neck (SCCHN), only a few exposed individuals develop this disease, suggesting an individual susceptibility. In this study, we investigated the associations between genetically determined DNA repair capacity (DRC) for removing tobacco-induced DNA adducts and risk of SCCHN and tumor characteristics.

EXPERIMENTAL DESIGN

We measured DRC in cultured T lymphocytes using the host-cell reactivation assay in a hospital-based case-control study of 744 SCCHN patients and 753 age-, sex-, and ethnicity-matched cancer-free controls recruited from The University of Texas M.D. Anderson Cancer Center.

RESULTS

Patients with SCCHN had significantly lower mean DRC (8.84% +/- 2.68%) than controls (9.97% +/- 2.61%; P < 0.0001), and the difference accounted for approximately 2-fold increased risk of SCCHN [adjusted odds ratio (OR), 1.91; 95% confidence interval (CI), 1.52-2.40] after adjustment for other covariates. Compared with the highest DRC quartile of controls, this increased risk was dose dependent (second highest quartile: OR, 1.40; 95% CI, 0.99-1.98; third quartile: OR, 1.87; 95% CI, 1.34-2.62; and fourth quartile: OR, 2.76; 95% CI, 1.98-3.84, respectively; P(trend) < 0.0001). We also assessed the performance of DRC in risk prediction models by calculating the area of under the receiver operating characteristic curve. The addition of DRC to the model significantly improved the sensitivity of the expanded model. However, we did not find the association between DRC and tumor sites and stages.

CONCLUSION

DRC is an independent susceptibility biomarker for SCCHN risk but not a tumor marker.

Parenchymal texture analysis in digital breast tomosynthesis for breast cancer risk estimation: a preliminary study

RATIONALE AND OBJECTIVES

Studies have demonstrated a relationship between mammographic parenchymal texture and breast cancer risk. Although promising, texture analysis in mammograms is limited by tissue superposition. Digital breast tomosynthesis (DBT) is a novel tomographic x-ray breast imaging modality that alleviates the effect of tissue superposition, offering superior parenchymal texture visualization compared to mammography. The aim of this study was to investigate the potential advantages of DBT parenchymal texture analysis for breast cancer risk estimation.

MATERIALS AND METHODS

DBT and digital mammographic (DM) images of 39 women were analyzed. Texture features, shown in previous studies with mammograms to correlate with cancer risk, were computed from the retroareolar breast region. The relative performances of the DBT and DM texture features were compared in correlating with two measures of breast cancer risk: (1) the Gail and Claus risk estimates and (2) mammographic breast density. Linear regression was performed to model the association between texture features and increasing levels of risk.

RESULTS

No significant correlation was detected between parenchymal texture and the Gail and Claus risk estimates. Significant correlations were observed between texture features and breast density. Overall, the DBT texture features demonstrated stronger correlations with breast percent density than DM features (P < or = .05). When dividing the study population into groups of increasing breast percent density, the DBT texture features appeared to be more discriminative, having regression lines with overall lower P values, steeper slopes, and higher R(2) estimates.

CONCLUSION

Although preliminary, the results of this study suggest that DBT parenchymal texture analysis could provide more accurate characterization of breast density patterns, which could ultimately improve breast cancer risk estimation.

Exogenous and endogenous hormones, mammographic density and breast cancer risk: can mammographic density be considered an intermediate marker of risk?

Elevated mammographic density measures are a well-established, relatively strong risk factor for breast cancer development. A systematic review of prospective cohort studies and cross-sectional studies strikingly establishes parallels between the associations of combined postmenopausal estrogen and progestin replacement therapy with, on the one hand, mammographic densities and, on the other hand, breast cancer risk. Other parallel observations were the inverse associations of both mammographic density and breast cancer risk with the selective estrogen receptor modulator tamoxifen, and direct associations with prolactin. Paradoxically, however, high mammographic density has been found associated with higher risks of both estrogen- and progesterone-receptor positive (ER+/ PR+) and negative (ER-/PR-) breast cancers, while hormone replacement therapy (HRT) use, but also circulating (blood) levels of androgens, estrogens, and prolactin appear to be associated more specifically to the risk of ER+ tumors. The effects of aromatase inhibitors and gonadotropin-releasing hormone agonists on breast density, as well as on breast cancer risk, still require further investigation. Regarding circulating levels of insulin-like growth factor (IGF)-I or IGFBP-3, studies did not show fully consistent relationships with mammographic density measures and breast cancer risk. In view of these various findings, it is impossible, at present, to propose mammographic density measures as an intermediate risk-related phenotype, integrating the effects of exogenous and/or endogenous hormones on the risk of developing breast cancer.

Variation in breast cancer risk in BRCA1 and BRCA2 mutation carriers

Genetic testing for BRCA1 and BRCA2 (BRCA1/2) mutations can provide important information for women who are concerned about their breast and ovarian cancer risks and need to make relevant prevention and medical management decisions. However, lifetime risks of breast cancer in individual BRCA1/2 mutation carriers have been confusing to apply in clinical decision-making. Published risk estimates vary significantly and are very dependent on the characteristics of the population under study. Recently, Begg and colleagues estimated cancer risks in a population-based study of BRCA1/2 mutation carriers. Here, we discuss the clinical decision-making implications of this research in the context of risk factors that may influence risk estimates in BRCA1/2 mutation carriers.

Differences and similarities in breast cancer risk assessment models in clinical practice: which model to choose?

To show differences and similarities between risk estimation models for breast cancer in healthy women from BRCA1/2-negative or untested families. After a systematic literature search seven models were selected: Gail-2, Claus Model, Claus Tables, BOADICEA, Jonker Model, Claus-Extended Formula, and Tyrer-Cuzick. Life-time risks (LTRs) for developing breast cancer were estimated for two healthy counsellees, aged 40, with a variety in family histories and personal risk factors. Comparisons were made with guideline thresholds for individual screening. Without a clinically significant family history LTRs varied from 6.7% (Gail-2 Model) to 12.8% (Tyrer-Cuzick Model). Adding more information on personal risk factors increased the LTRs and yearly mammography will be advised in most situations. Older models (i.e. Gail-2 and Claus) are likely to underestimate the LTR for developing breast cancer as their baseline risk for women is too low. When models include personal risk factors, surveillance thresholds have to be reformulated. For current clinical practice, the Tyrer-Cuzick Model and the BOADICEA Model seem good choices.