Carolin C. Hack

The Contributions of Breast Density and Common Genetic Variation to Breast Cancer Risk

We evaluated whether a 76-locus polygenic risk score (PRS) and Breast Imaging Reporting and Data System (BI-RADS) breast density were independent risk factors within three studies (1643 case patients, 2397 control patients) using logistic regression models. We incorporated the PRS odds ratio (OR) into the Breast Cancer Surveillance Consortium (BCSC) risk-prediction model while accounting for its attributable risk and compared five-year absolute risk predictions between models using area under the curve (AUC) statistics. All statistical tests were two-sided. BI-RADS density and PRS were independent risk factors across all three studies (P interaction = .23). Relative to those with scattered fibroglandular densities and average PRS (2(nd) quartile), women with extreme density and highest quartile PRS had 2.7-fold (95% confidence interval [CI] = 1.74 to 4.12) increased risk, while those with low density and PRS had reduced risk (OR = 0.30, 95% CI = 0.18 to 0.51). PRS added independent information (P < .001) to the BCSC model and improved discriminatory accuracy from AUC = 0.66 to AUC = 0.69. Although the BCSC-PRS model was well calibrated in case-control data, independent cohort data are needed to test calibration in the general population.

Characterizing mammographic images by using generic texture features

IntroductionAlthough mammographic density is an established risk factor for breast cancer, its use is limited in clinical practice because of a lack of automated and standardized measurement methods. The aims of this study were to evaluate a variety of automated texture features in mammograms as risk factors for breast cancer and to compare them with the percentage mammographic density (PMD) by using a case-control study design.MethodsA case-control study including 864 cases and 418 controls was analyzed automatically. Four hundred seventy features were explored as possible risk factors for breast cancer. These included statistical features, moment-based features, spectral-energy features, and form-based features. An elaborate variable selection process using logistic regression analyses was performed to identify those features that were associated with case-control status. In addition, PMD was assessed and included in the regression model.ResultsOf the 470 image-analysis features explored, 46 remained in the final logistic regression model. An area under the curve of 0.79, with an odds ratio per standard deviation change of 2.88 (95% CI, 2.28 to 3.65), was obtained with validation data. Adding the PMD did not improve the final model.ConclusionsUsing texture features to predict the risk of breast cancer appears feasible. PMD did not show any additional value in this study. With regard to the features assessed, most of the analysis tools appeared to reflect mammographic density, although some features did not correlate with PMD. It remains to be investigated in larger case-control studies whether these features can contribute to increased prediction accuracy.

Association of mammographic density with hormone receptors in invasive breast cancers: results from a case-only study.

For many breast cancer (BC) risk factors, there is growing evidence concerning molecular subtypes for which the risk factor is specific. With regard to mammographic density (MD), there are inconsistent data concerning its association with estrogen receptor (ER) and progesterone receptor (PR) expression. The aim of our study was to analyze the association between ER and PR expression and MD. In our case‐only study, data on BC risk factors, hormone receptor expression and MD were available for 2,410 patients with incident BC. MD was assessed as percent MD (PMD) using a semiautomated method by two readers for every patient. The association of ER/PR and PMD was studied with multifactorial analyses of covariance with PMD as the target variable and including well‐known factors that are also associated with MD, such as age, parity, use of hormone replacement therapy, and body mass index (BMI). In addition to the commonly known associations between PMD and age, parity, BMI and hormone replacement therapy, a significant inverse association was found between PMD and ER expression levels. Patients with ER‐negative tumors had an average PMD of 38%, whereas patients with high ER expression had a PMD of 35%. A statistical trend toward a positive association between PMD and PR expression was also seen. PMD appears to be inversely associated with ER expression and may correlate positively with PR expression. These effects were independent of other risk factors such as age, BMI, parity, and hormone replacement therapy, possibly suggesting other pathways that mediate this effect.

Mammographic density is the main correlate of tumors detected on ultrasound but not on mammography.

Although mammography screening programs do not include ultrasound examinations, some diagnostic units do provide women with both mammography and ultrasonography. This article is concerned with estimating the risk of a breast cancer patient diagnosed in a hospital‐based mammography unit having a tumor that is visible on ultrasound but not on mammography. A total of 1,399 women with invasive breast cancer from a hospital‐based diagnostic mammography unit were included in this retrospective study. For inclusion, mammograms from the time of the primary diagnosis had to be available for computer‐assisted assessment of percentage mammographic density (PMD), as well as Breast Imaging Reporting and Data System (BIRADS) assessment of mammography. In addition, ultrasound findings were available for the complete cohort as part of routine diagnostic procedures, regardless of any patient or imaging characteristics. Logistic regression analyses were conducted to identify predictors of mammography failure, defined as BIRADS assessment 1 or 2. The probability that the visibility of a tumor might be masked at diagnosis was estimated using a regression model with the identified predictors. Tumors were only visible on ultrasound in 107 cases (7.6%). PMD was the strongest predictor for mammography failure, but age, body mass index and previous breast surgery also influenced the risk, independently of the PMD. Risk probabilities ranged from 1% for a defined low‐risk group up to 40% for a high‐risk group. These findings might help identify women who should be offered ultrasound examinations in addition to mammography.

Interest in Integrative Medicine Among Postmenopausal Hormone Receptor–Positive Breast Cancer Patients in the EvAluate-TM Study

Background. Breast cancer patients often use complementary and alternative medicine, but few prospectively collected data on the topic are available specifically for postmenopausal breast cancer patients. A large prospective study was therefore conducted within a noninterventional study in order to identify the characteristics of patients interested in integrative medicine. Methods. The EvAluate-TM study is a prospective, multicenter noninterventional study in which treatment with the aromatase inhibitor letrozole was evaluated in postmenopausal women with hormone receptor–positive primary breast cancer. Between 2008 and 2009, 5045 postmenopausal patients were enrolled at 339 certified breast centers in Germany. As part of the data collection process, patients were asked at the baseline about their interest in and information needs relating to integrative medicine. Results. Of the 5045 patients recruited, 3411 responded to the questionnaire on integrative medicine and took part in the analysis, 1583 patients expressed an interest in integrative medicine, and 1828 patients declared no interest. Relevant predictors of interest in integrative medicine were age, body mass index, tumor size, previous chemotherapy, and use of concomitant medications for other medical conditions. Interest in integrative medicine declined highly significantly (P < .001) with age (<50 years, 74.1%; 50-60 years, 54.1%; >65 years, 38.0%). Patients in favor of integrative medicine were significantly less satisfied with the information received about individual treatments and antihormonal therapy. Patients with interest in integrative medicine were more often interested in rehabilitation and fitness, nutritional counseling, and additional support from self-help organizations. These women were mostly interested in receiving information about their disease and integrative medicine from a physician, rather than from other sources. Conclusions. This study shows that a considerable proportion of postmenopausal breast cancer patients are interested in integrative medicine. Information about integrative medicine should therefore be provided as part of patient care for this group. It was found that receiving concomitant medication for other medical conditions is one of the main predictors for women not being interested in integrative medicine. This group of patients may need special attention and individualized information about integrative medicine. Additionally, most patients were interested in obtaining the relevant information from their doctor.

Use of complementary and integrative medicine among German breast cancer patients: predictors and implications for patient care within the PRAEGNANT study network

PurposeThe present study aims to analyze a cohort of advanced breast cancer patients in Germany to assess their interest in complementary and alternative medicine (CAM) and patient’s use of most frequent CAM methods.Patients and methodsBased on the PREGNANT real-time breast cancer registry which is a multicenter study in Germany, questionnaires of 580 patients with advanced breast cancer were evaluated. The implemented questionnaire for CAM asked for general interest in CAM and for patient’s use of different CAM methods at present and in the past. The interest and application of CAM were analyzed for association with patients’ characteristics such as tumor, patient, and therapy characteristics.ResultsIn total, 436 out of 580 (75%) patients claimed to be interested in CAM. Further, interest in CAM is significantly correlated with younger age and absence of metastasis at the time of diagnosis. Multivariate analysis confirmed the patient’s age and distant disease status at the time of diagnosis as related to interest in CAM. A total of 56.4% of patients applied any CAM method in the past. Moreover, with increasing lines of therapies, the more frequent use of CAM was observed. Hereby, praying, vitamin supplements, and other food supplements were most frequently applied.ConclusionOur data demonstrate high overall interest and frequent use of CAM in advanced breast cancer patients supporting a strong demand of breast cancer patients for complementary counseling and treatments additional to the established cancer therapies. It is indispensable to implement counseling and evidence-based complementary treatments into clinical routine of cancer centers and to adapt postgraduate medical education, respectively.

Correlates of mammographic density in B-mode ultrasound and real time elastography.

The aim of our study involved the assessment of B-mode imaging and elastography with regard to their ability to predict mammographic density (MD) without X-rays. Women, who underwent routine mammography, were prospectively examined with additional B-mode ultrasound and elastography. MD was assessed quantitatively with a computer-assisted method (Madena). The B-mode and elastography images were assessed by histograms with equally sized gray-level intervals. Regression models were built and cross validated to examine the ability to predict MD. The results of this study showed that B-mode imaging and elastography were able to predict MD. B-mode seemed to give a more accurate prediction. R2 for B-mode image and elastography were 0.67 and 0.44, respectively. Areas in the B-mode images that correlated with mammographic dense areas were either dark gray or of intermediate gray levels. Concerning elastography only the gray levels that represent extremely stiff tissue correlated positively with MD. In conclusion, ultrasound seems to be able to predict MD. Easy and cheap utilization of regular breast ultrasound machines encourages the use of ultrasound in larger case–control studies to validate this method as a breast cancer risk predictor. Furthermore, the application of ultrasound for breast tissue characterization could enable comprehensive research concerning breast cancer risk and breast density in young and pregnant women.

BRCA mutations and their influence on pathological complete response and prognosis in a clinical cohort of neoadjuvantly treated breast cancer patients

PurposeBRCA1/2 mutations influence the molecular characteristics and the effects of systemic treatment of breast cancer. This study investigates the impact of germline BRCA1/2 mutations on pathological complete response and prognosis in patients receiving neoadjuvant systemic chemotherapy.MethodsBreast cancer patients were tested for a BRCA1/2 mutation in clinical routine work and were treated with anthracycline-based or platinum-based neoadjuvant chemotherapy between 1997 and 2015. These patients were identified in the tumor registry of the Breast Center of the University of Erlangen (Germany). Logistic regression and Cox regression analyses were performed to investigate the associations between BRCA1/2 mutation status, pathological complete response, disease-free survival, and overall survival.ResultsAmong 355 patients, 59 had a mutation in BRCA1 or in BRCA2 (16.6%), 43 in BRCA1 (12.1%), and 16 in BRCA2 (4.5%). Pathological complete response defined as “ypT0; ypN0” was observed in 54.3% of BRCA1/2 mutation carriers, but only in 22.6% of non-carriers. The adjusted odds ratio was 2.48 (95% CI 1.26–4.91) for BRCA1/2 carriers versus non-carriers. Patients who achieved a pathological complete response had better disease-free survival and overall survival rates compared with those who did not achieve a pathological complete response, regardless of BRCA1/2 mutation status.ConclusionsBRCA1/2 mutation status leads to better responses to neoadjuvant chemotherapy in breast cancer. Pathological complete response is the main predictor of disease-free survival and overall survival, independently of BRCA1/2 mutation status.

Correlation of mammographic density and serum calcium levels in patients with primary breast cancer

Percentage mammographic breast density (PMD) is one of the most important risk factors for breast cancer (BC). Calcium, vitamin D, bisphosphonates, and denosumab have been considered and partly confirmed as factors potentially influencing the risk of BC. This retrospective observational study investigated the association between serum calcium level and PMD. A total of 982 BC patients identified in the research database at the University Breast Center for Franconia with unilateral BC, calcium and albumin values, and mammogram at the time of first diagnosis were included. PMD was assessed, using a semiautomated method by two readers. Linear regression analyses were conducted to investigate the impact on PMD of the parameters of serum calcium level adjusted for albumin level, and well‐known clinical predictors such as age, body mass index (BMI), menopausal status and confounder for serum calcium like season in which the BC was diagnosed. Increased calcium levels were associated with reduced PMD (P = 0.024). Furthermore, PMD was inversely associated with BMI (P < 0.001) and age (P < 0.001). There was also an association between PMD and menopausal status (P < 0.001). The goodness‐of‐fit of the regression model was moderate. This is the first study assessing the association between serum calcium level and PMD. An inverse association with adjusted serum calcium levels was observed. These findings add to previously published data relating to vitamin D, bisphosphonates, denosumab, and the RANK/RANKL signaling pathway in breast cancer risk and prevention.

Risk, Prediction and Prevention of Hereditary Breast Cancer – Large-Scale Genomic Studies in Times of Big and Smart Data

Over the last two decades genetic testing for mutations in BRCA1 and BRCA2 has become standard of care for women and men who are at familial risk for breast or ovarian cancer. Currently, genetic testing more often also includes so-called panel genes, which are assumed to be moderate-risk genes for breast cancer. Recently, new large-scale studies provided more information about the risk estimation of those genes. The utilization of information on panel genes with regard to their association with the individual breast cancer risk might become part of future clinical practice. Furthermore, large efforts have been made to understand the influence of common genetic variants with a low impact on breast cancer risk. For this purpose, almost 450 000 individuals have been genotyped for almost 500 000 genetic variants in the OncoArray project. Based on first results it can be assumed that – together with previously identified common variants – more than 170 breast cancer risk single nucleotide polymorphisms can explain up to 18% of familial breast cancer risk. The knowledge about genetic and non-genetic risk factors and its implementation in clinical practice could especially be of use for individualized prevention. This includes an individualized risk prediction as well as the individualized selection of screening methods regarding imaging and possible lifestyle interventions. The aim of this review is to summarize the most recent developments in this area and to provide an overview on breast cancer risk genes, risk prediction models and their utilization for the individual patient.