Percent Mammographic Density and Dense Area as Risk Factors for Breast Cancer

Alcohol consumption and breast lesions: targets for risk-based screening in high-risk Italian women

BACKGROUND

Breast cancer in Italy is still the most frequent cancer among women, and alcohol consumption is recognized as a risk factor for its development. Overall, in 2020, approximately 10% of all breast cancer-related deaths were attributable to alcohol consumption. Despite advancements in diagnostics and therapeutic options reducing mortality trends, the incidence of breast cancer is projected to rise in Italy. This study aims to assess how alcohol consumption influences the timing of breast lesion diagnosis. Understanding these associations can enhance primary prevention strategies and support the adoption of a risk-based prevention approach, integrating lifestyle factors into personalized screening programs.

METHODS

P.I.N.K. (Prevention, Imaging, Network and Knowledge) study collected data on a prospective dynamic cohort of women who voluntarily underwent breast cancer screening at breast centers throughout Italy, between 2018 and 2023, outside the free national screening program. The occurrence of breast lesion diagnosis and baseline information were collected through clinical visits and an auto-administered questionnaire, including data on absent, moderate or high alcohol consumption during the last 12 months and smoking. 3774 women (mean age 58.9 ± 10.0, range 40-98 years) were included in the present analysis, encompassing women with a suspected or confirmed diagnosis of benign or malignant tumor and healthy women that contributed at least 4 years to the study. An Event History Analysis was carried out to evaluate the effect of alcohol consumption on the timing to event. The event was represented by the transition of the health status, from not diagnosed to diagnosed with breast lesion. The Accelerated Failure Time parameterization was used to directly interpret how the covariates influence the time to the event. The model was adjusted by familiality of breast/ovarian cancer, marital status, level of education, and type of access to health care.

RESULTS

High alcohol consumption exhibited an accelerating effect on the transition to the diagnosed state, indicating a significantly shortened time to event: β coefficient - 0.33 (p-value 0.010) in the adjusted model, indicating an anticipation of about 4 months. The effect of moderate alcohol consumption did not reach statistical significance, neither in the unadjusted model nor in the adjusted model. Adjustment for smoking status led to a further increase of the β coefficient for high alcohol consumption (- 0.40; p value 0.003) and brought moderate alcohol consumption closer to statistical significance (β - 0.15; p-value 0.087). Familiality of breast or ovarian cancer showed a statistically non-significant accelerating effect, while marital status different from maiden, high education, and private access to health care showed decelerating effects.

CONCLUSIONS

High alcohol consumption was confirmed as an accelerating factor in breast lesions diagnosis, while the effect of moderate consumption did not reach statistical significance. These results help identifying actionable targets for high-risk populations, emphasizing personalized risk-based screening programs and gender-sensitive interventions.

[Personalized profiling in the field of senology]

BACKGROUND

The concept of personalized medicine is becoming increasingly important. The possibilities of diagnostics include not only genetic and molecular tumor profiles, but also the use of precise and individual imaging techniques.

OBJECTIVES

The development and implementation of suitable diagnostic procedures with high sensitivity and specificity, which are at the same time tailored to the individual risk factors and biological characteristics of the patient, remain a challenge.

MATERIALS AND METHODS

To enable personalized profiling, comprehensive diagnostics must be established that take into account all parameters such as imaging, molecular and genetic markers as well as real-world data and the use of artificial intelligence. This article sheds light on different approaches to personalized diagnostics in breast cancer and highlights the current clinical standard, innovative areas of research and the resulting challenges.

CONCLUSION

The highest hurdles for newer imaging techniques are the standardization of image analysis and the validation of these techniques in large clinical trials. The use of artificial intelligence requires not only appropriate technical and medical expertise, but also a sensitive approach to issues such as data protection and patient privacy. Real-world registries offer insights into real world treatment situations and are therefore of great importance.

Correlation of RANK and RANKL with mammographic density in primary breast cancer patients

PURPOSE

The receptor activator of nuclear factor kappa B (RANK) and its ligand (RANKL) have been shown to promote proliferation of the breast and breast carcinogenesis. The objective of this analysis was to investigate whether tumor-specific RANK and RANKL expression in patients with primary breast cancer is associated with high percentage mammographic density (PMD), which is a known breast cancer risk factor.

METHODS

Immunohistochemical staining of RANK and RANKL was performed in tissue microarrays (TMAs) from primary breast cancer samples of the Bavarian Breast Cancer Cases and Controls (BBCC) study. For RANK and RANKL expression, histochemical scores (H scores) with a cut-off value of > 0 vs 0 were established. PMD was measured in the contralateral, non-diseased breast. Linear regression models with PMD as outcome were calculated using common predictors of PMD (age at breast cancer diagnosis, body mass index (BMI) and parity) and RANK and RANKL H scores. Additionally, Spearman rank correlations (ρ) between PMD and RANK and RANKL H score were performed.

RESULTS

In the final cohort of 412 patients, breast cancer-specific RANK and RANKL expression was not associated with PMD (P = 0.68). There was no correlation between PMD and RANK H score (Spearman's ρ = 0.01, P = 0.87) or RANKL H score (Spearman's ρ = 0.04, P = 0.41). RANK expression was highest in triple-negative tumors, followed by HER2-positive, luminal B-like and luminal A-like tumors, while no subtype-specific expression of RANKL was found.

CONCLUSION

Results do not provide evidence for an association of RANK and RANKL expression in primary breast cancer with PMD.

The Relationship Between Breast Density and Breast Cancer Surgical Outcomes: A Systematic Review

This study aims to investigate the relationship between mammographic breast density and the surgical outcomes of breast cancer. PubMed, SCOPUS, Web of Science, Science Direct, and the Wiley Library were systematically searched for relevant literature. Rayyan QRCI was employed throughout this comprehensive process. Our results included ten studies with a total of 5017 women diagnosed with breast cancer. The follow-up duration ranged from 1 year to 15.1 years. Eight out of the twelve included studies reported that low mammographic breast density was significantly associated with no local recurrence, metachronous contralateral breast cancer, and fewer challenges in the preoperative and intraoperative phases. On the other hand, four studies reported that mammographic breast density is not linked to disease recurrence, survival, re-excision, or an incomplete clinical and pathological response. There is a significant association between low mammographic breast density and reduced challenges in the preoperative and intraoperative phases, as well as no local recurrence and fewer mastectomy cases. However, the link between mammographic breast density and disease recurrence, survival, re-excision, and incomplete clinical and pathological response is less clear, with some studies reporting no significant association. The findings suggest that mammographic breast density may play a role in certain aspects of breast cancer outcomes, but further research is needed to fully understand its impact.

RANK and RANKL Expression in Tumors of Patients with Early Breast Cancer

Introduction

The receptor activator of nuclear factor-κB (RANK) pathway was associated with the pathogenesis of breast cancer. Several studies attempted to link the RANK/RANKL pathway to prognosis; however, with inconsistent outcomes. We aimed to further contribute to the knowledge about RANK/RANKL as prognostic factors in breast cancer. Within this study, protein expression of RANK and its ligand, RANKL, in the tumor tissue was analyzed in association with disease-free survival (DFS) and overall survival (OS) in a study cohort of patients with early breast cancer.

Patients and Methods

607 samples of female primary and early breast cancer patients from the Bavarian Breast Cancer Cases and Controls Study were analyzed to correlate the RANK and RANKL expression with DFS and OS. Therefore, expression was quantified using immunohistochemical staining of a tissue microarray. H-scores were determined with the cut-off value of 8.5 for RANK and 0 for RANKL expression, respectively.

Results

RANK and RANKL immunohistochemistry were assessed by H-score. Both biomarkers did not correlate (ρ = -0.04). According to molecular subtypes, triple-negative tumors and HER2-positive tumors showed a higher number of RANK-positive tumors (H-score ≥ 8.5), however, no subtype-specific expression of RANKL could be detected. Higher RANKL expression tended to correlate with a better prognosis. However, RANK and RANKL expression could not be identified as statistically significant prognostic factors within the study cohort.

Conclusions

Tumor-specific RANK and RANKL expressions are not applicable as prognostic factors for DFS and OS, but might be associated with subtype-specific breast cancer progression.

Predicting mammographic density with linear ultrasound transducers

BACKGROUND

High mammographic density (MD) is a risk factor for the development of breast cancer (BC). Changes in MD are influenced by multiple factors such as age, BMI, number of full-term pregnancies and lactating periods. To learn more about MD, it is important to establish non-radiation-based, alternative examination methods to mammography such as ultrasound assessments.

METHODS

We analyzed data from 168 patients who underwent standard-of-care mammography and performed additional ultrasound assessment of the breast using a high-frequency (12 MHz) linear probe of the VOLUSON® 730 Expert system (GE Medical Systems Kretztechnik GmbH & Co OHG, Austria). Gray level bins were calculated from ultrasound images to characterize mammographic density. Percentage mammographic density (PMD) was predicted by gray level bins using various regression models.

RESULTS

Gray level bins and PMD correlated to a certain extent. Spearman's ρ ranged from - 0.18 to 0.32. The random forest model turned out to be the most accurate prediction model (cross-validated R2, 0.255). Overall, ultrasound images from the VOLUSON® 730 Expert device in this study showed limited predictive power for PMD when correlated with the corresponding mammograms.

CONCLUSIONS

In our present work, no reliable prediction of PMD using ultrasound imaging could be observed. As previous studies showed a reasonable correlation, predictive power seems to be highly dependent on the device used. Identifying feasible non-radiation imaging methods of the breast and their predictive power remains an important topic and warrants further evaluation. Trial registration 325-19 B (Ethics Committee of the medical faculty at Friedrich Alexander University of Erlangen-Nuremberg, Erlangen, Germany).

Understanding the contribution of lifestyle in breast cancer risk prediction: a systematic review of models applicable to Europe

BACKGROUND

Breast cancer (BC) is a significant health concern among European women, with the highest prevalence rates among all cancers. Existing BC prediction models account for major risks such as hereditary, hormonal and reproductive factors, but research suggests that adherence to a healthy lifestyle can reduce the risk of developing BC to some extent. Understanding the influence and predictive role of lifestyle variables in current risk prediction models could help identify actionable, modifiable, targets among high-risk population groups.

PURPOSE

To systematically review population-based BC risk prediction models applicable to European populations and identify lifestyle predictors and their corresponding parameter values for a better understanding of their relative contribution to the prediction of incident BC.

METHODS

A systematic review was conducted in PubMed, Embase and Web of Science from January 2000 to August 2021. Risk prediction models were included if (i) developed and/or validated in adult cancer-free women in Europe, (ii) based on easily ascertained information, and (iii) reported models' final predictors. To investigate further the comparability of lifestyle predictors across models, estimates were standardised into risk ratios and visualised using forest plots.

RESULTS

From a total of 49 studies, 33 models were developed and 22 different existing models, mostly from Gail (22 studies) and Tyrer-Cuzick and co-workers (12 studies) were validated or modified for European populations. Family history of BC was the most frequently included predictor (31 models), while body mass index (BMI) and alcohol consumption (26 and 21 models, respectively) were the lifestyle predictors most often included, followed by smoking and physical activity (7 and 6 models respectively). Overall, for lifestyle predictors, their modest predictive contribution was greater for riskier lifestyle levels, though highly variable model estimates across different models.

CONCLUSIONS

Given the increasing BC incidence rates in Europe, risk models utilising readily available risk factors could greatly aid in widening the population coverage of screening efforts, while the addition of lifestyle factors could help improving model performance and serve as intervention targets of prevention programmes.

Use of Nonsteroidal Anti-Inflammatory Drugs and Risk of Breast Cancer: Evidence from a General Female Population and a Mammographic Screening Cohort in Sweden

A link has been proposed between the use of nonsteroidal anti-inflammatory drugs (NSAIDs) and the risk of breast cancer. There is, however, insufficient data regarding the subtype and stage of breast cancer, and few studies have assessed the interaction between the use of NSAIDs and breast density or previous breast disorders. There is also a lack of data from population-based studies. We first conducted a nested case-control study within the general female population of Sweden, including 56,480 women with newly diagnosed breast cancer during 2006-2015 and five breast cancer-free women per case as controls, to assess the association of NSAID use with the risk of incident breast cancer, focusing on subtype and stage of breast cancer as well as the interaction between NSAID use and previous breast disorders. We then used the Karolinska Mammography Project for Risk Prediction of Breast Cancer (Karma) cohort to assess the interaction between NSAID use and breast density in relation to the risk of breast cancer. Conditional logistic regression was used to estimate the hazard ratio (HR) and a 95% confidence interval (CI) was used for breast cancer in relation to the use of aspirin and non-aspirin NSAIDs. In the nested case-control study of the general population, exclusive use of aspirin was not associated with the risk of breast cancer, whereas exclusive use of non-aspirin NSAIDs was associated with a modestly higher risk of stage 0-2 breast cancer (HR: 1.05; 95% CI: 1.02-1.08) but a lower risk of stage 3-4 breast cancer (HR 0.80; 95% CI: 0.73-0.88). There was also a statistically significant interaction between the exclusive use of NSAIDs and previous breast disorders (p for interaction: <0.001). In the analysis of Karma participants, the exclusive use of non-aspirin NSAIDs was associated with a lower risk of breast cancer among women with a breast dense area of >40 cm² (HR: 0.72; 95% CI: 0.59-0.89). However, the possibility of finding this by chance cannot be ruled out. Overall, we did not find strong evidence to support an association between the use of NSAIDs and the risk of breast cancer.

The Potential of Natural Products in the Treatment of Triple-Negative Breast Cancer

Triple-negative breast cancer (TNBC) is a subtype of breast cancer that lacks receptors for targeted therapy. Consequently, chemotherapy is currently the mainstay of systemic treatment options. However, the enrichment of cancer stem cells (CSC, a subpopulation with stem-cell characteristics and tumor-initiating propensity) promotes chemo-resistance and tumorigenesis, resulting in cancer recurrence and relapse. Furthermore, toxic side effects of chemotherapeutics reduce patient wellbeing. Natural products, specifically compounds derived from plants, have the potential to treat TNBC and target CSCs by inhibiting CSC signaling pathways. Literature evidence from six promising compounds were reviewed, including sulforaphane, curcumin, genistein, resveratrol, lycopene, and epigallocatechin-3-gallate. These compounds have been shown to promote cell cycle arrest and apoptosis in TNBC cells. They also could inhibit the epithelial-mesenchymal transition (EMT) that plays an important role in metastasis. In addition, those natural compounds have been found to inhibit pathways important for CSCs, such as NF-κB, PI3K/Akt/mTOR, Notch 1, Wnt/β-catenin, and YAP. Clinicals trials conducted on these compounds have shown varying degrees of effectiveness. Epidemiological case-control studies for the compounds commonly consumed in certain human populations have also been summarized. While in vivo and in vitro data are promising, further basic and clinical investigations are required. Likely, natural products in combination with other drugs may hold great potential to improve TNBC treatment efficacy and patient outcomes.

Mammographic microcalcifications and risk of breast cancer

BACKGROUND

Mammographic microcalcifications are considered early signs of breast cancer (BC). We examined the association between microcalcification clusters and the risk of overall and subtype-specific BC. Furthermore, we studied how mammographic density (MD) influences the association between microcalcification clusters and BC risk.

METHODS

We used a prospective cohort (n = 53,273) of Swedish women with comprehensive information on BC risk factors and mammograms. The total number of microcalcification clusters and MD were measured using a computer-aided detection system and the STRATUS method, respectively. Cox regressions and logistic regressions were used to analyse the data.

RESULTS

Overall, 676 women were diagnosed with BC. Women with ≥3 microcalcification clusters had a hazard ratio [HR] of 2.17 (95% confidence interval [CI] = 1.57-3.01) compared to women with no clusters. The estimated risk was more pronounced in premenopausal women (HR = 2.93; 95% CI = 1.67-5.16). For postmenopausal women, microcalcification clusters and MD had a similar influence on BC risk. No interaction was observed between microcalcification clusters and MD. Microcalcification clusters were significantly associated with in situ breast cancer (odds ratio: 2.03; 95% CI = 1.13-3.63).

CONCLUSIONS

Microcalcification clusters are an independent risk factor for BC, with a higher estimated risk in premenopausal women. In postmenopausal women, microcalcification clusters have a similar association with BC as baseline MD.

Mammographic Density Change and Risk of Breast Cancer

BACKGROUND

We examined the association between annual mammographic density change (MDC) and breast cancer (BC) risk, and how annual MDC influences the association between baseline mammographic density (MD) and BC risk.

METHODS

We used the Karolinska Mammography Project for Risk Prediction of Breast Cancer cohort of Swedish women (N = 43 810) aged 30-79 years with full access to BC risk factors and mammograms. MD was measured as dense area (cm2) and percent MD using the STRATUS method. We used the contralateral mammogram for women with BC and randomly selected a mammogram from either left or right breast for healthy women. We calculated relative area MDC between repeated examinations. Relative area MDC was categorized as decreased (>10% decrease per year), stable (no change), or increased (>10% increase per year). We used Cox proportional hazards regression to estimate the association of BC with MDC and interaction analysis to investigate how MDC modified the association between baseline MD and BC risk. All tests of statistical significance were two-sided.

RESULTS

In all, 563 women were diagnosed with BC. Compared with women with a decreased MD over time, no statistically significant difference in BC risk was seen for women with either stable MD or increasing MD (hazard ratio = 1.01, 95% confidence interval = 0.82 to 1.23, P = .90; and hazard ratio = 0.98, 95% confidence interval = 0.80 to 1.22, P = .90, respectively). Categorizing baseline MD and subsequently adding MDC did not seem to influence the association between baseline MD and BC risk.

CONCLUSIONS

Our results suggest that annual MDC does not influence BC risk. Furthermore, MDC does not seem to influence the association between baseline MD and BC risk.

Influence of Family History of Breast or Ovarian Cancer on Pathological Complete Response and Long-Term Prognosis in Breast Cancer Patients Treated with Neoadjuvant Chemotherapy

Purpose

In breast cancer, a pathological complete response (pCR) has been described as generally resulting in a favorable prognosis. However, there are subgroups, such as patients with a mutation in BRCA1 or BRCA2, in which the effect of pCR on the prognosis is suspected to be weaker. Patients with a family history of breast and/or ovarian cancer may therefore react differently in relation to pCR and prognosis, and this is investigated in this study.

Patients and Methods

Breast cancer patients were identified from a clinical breast cancer registry. The study subjects had been treated with neoadjuvant chemotherapy from 2001 to 2018 and their pathological and clinical information as well as medical family history were available. They were considered to have a positive family history if they had at least 1 first-degree relative with breast and/or ovarian cancer. Multivariate logistic regression analyses were performed to study the association between family history, pCR (ypT0; ypN0), and disease-free survival (DFS).

Results

Of 1,480 patients, 228 (15.4%) had a positive family history. The pCR rates were 24.9% in all patients, and 24.4% and 27.6% in those without/with a family history, respectively. Family history was not associated with a higher pCR rate (adjusted odds ratio [OR] 1.23; 95% confidence interval [CI] 0.85-1.76; p = 0.27) or a different disease-free survival (DFS; adjusted hazard ratio [HR] 1.15; 95% CI 0.88-1.52; p = 0.30). pCR did not affect the prognosis differently in relation to family history.

Conclusions

In this retrospective analysis, family history was not associated with pCR and DFS. pCR improved survival, independently of family history.

RANKL and OPG and their influence on breast volume changes during pregnancy in healthy women

Breast cancer risk is reduced by number of pregnancies and breastfeeding duration, however studies of breast changes during or after pregnancy are rare. Breast volume changes - although not linked to breast cancer risk - might be an interesting phenotype in this context for correlative studies, as changes of breast volume vary between pregnant women. Serum receptor activator of nuclear factor kappa B ligand (RANKL) and its antagonist osteoprotegerin (OPG) were measured prospectively before gestational week 12, and three-dimensional breast volume assessments were performed. A linear regression model including breast volume at the start of pregnancy, RANKL, OPG, and other factors was used to predict breast volume at term. The mean breast volume was 413 mL at gestational week 12, increasing by a mean of 99 mL up to gestational week 40. In addition to body mass index and breast volume at the beginning of pregnancy, RANKL and OPG appeared to influence breast volume with a mean increase by 32 mL (P = 0.04) and a mean reduction by 27 mL (P = 0.04), respectively. Linking the RANKL/RANK/OPG pathway with breast volume changes supports further studies aiming at analysing breast changes during pregnancy with regard to breast cancer risk.

A review of the influence of mammographic density on breast cancer clinical and pathological phenotype

PURPOSE

It is well established that high mammographic density (MD), when adjusted for age and body mass index, is one of the strongest known risk factors for breast cancer (BC), and also associates with higher incidence of interval cancers in screening due to the masking of early mammographic abnormalities. Increasing research is being undertaken to determine the underlying histological and biochemical determinants of MD and their consequences for BC pathogenesis, anticipating that improved mechanistic insights may lead to novel preventative or treatment interventions. At the same time, technological advances in digital and contrast mammography are such that the validity of well-established relationships needs to be re-examined in this context.

METHODS

With attention to old versus new technologies, we conducted a literature review to summarise the relationships between clinicopathologic features of BC and the density of the surrounding breast tissue on mammography, including the associations with BC biological features inclusive of subtype, and implications for the clinical disease course encompassing relapse, progression, treatment response and survival.

RESULTS AND CONCLUSIONS

There is reasonable evidence to support positive relationships between high MD (HMD) and tumour size, lymph node positivity and local relapse in the absence of radiotherapy, but not between HMD and LVI, regional relapse or distant metastasis. Conflicting data exist for associations of HMD with tumour location, grade, intrinsic subtype, receptor status, second primary incidence and survival, which need further confirmatory studies. We did not identify any relationships that did not hold up when data involving newer imaging techniques were employed in analysis.

Saliva samples as a source of DNA for high throughput genotyping: an acceptable and sufficient means in improvement of risk estimation throughout mammographic diagnostics

Background

Breast cancer screening programs seem to be an insufficient tool for women at high genetic risk for breast cancer. These women are not adequately monitored yet. Genetic testing may improve clearly the quality of breast cancer prevention programs. At present, blood samples are favored for obtaining high-quality DNA; however, DNA can also be obtained by collecting saliva. The aim of this study was, on the one hand, to determine whether saliva sampling is a practicable means to obtain sufficient quantity and quality of DNA and, on the other hand, whether it is accepted by patients throughout mammographic diagnostics.

Methods

67 consecutive women with diagnostic need for mammography with or without a family history for breast cancer were asked for their basic willingness to undergo a genetic testing by saliva sample in addition to standard diagnostics. Saliva samples were analyzed in terms of DNA quantity and quality.

Results

64 (95.6%) women agreed to provide a saliva sample; 3 of them denied participation. And even 63 out of 64 (98.4%) were interested in their specific results. 45 out of 64 samples contained a DNA concentration above 50 ng/µl, 12 samples were between 25 and 50 ng/µl and only 7 of them were under 25 ng/µl with the standard extraction procedure.

Conclusion

A high number of patients seem to accept salvia samples as a risk assessment tool in breast diagnostics and are interested in their specific risk situation. At the same time, it could be demonstrated that it is an effective way to provide high-quality DNA for breast cancer gene analysis. However, it remains to be shown whether it would be possible to integrate it with the same acceptance in a nationwide breast cancer screening program.

Electronic supplementary material

The online version of this article (10.1186/s40001-018-0318-9) contains supplementary material, which is available to authorized users.

Association between mammographic density and pregnancies relative to age and BMI: a breast cancer case-only analysis

PURPOSE

Percentage mammographic density (PMD) is a major risk factor for breast cancer (BC). It is strongly associated with body mass index (BMI) and age, which are themselves risk factors for breast cancer. This analysis investigated the association between the number of full-term pregnancies and PMD in different subgroups relative to age and BMI.

METHODS

Patients were identified in the breast cancer database of the University Breast Center for Franconia. A total of 2410 patients were identified, for whom information on parity, age, and BMI, and a mammogram from the time of first diagnosis were available for assessing PMD. Linear regression analyses were conducted to investigate the influence on PMD of the number of full-term pregnancies (FTPs), age, BMI, and interaction terms between them.

RESULTS

As in previous studies, age, number of FTPs, and BMI were found to be associated with PMD in the expected direction. However, including the respective interaction terms improved the prediction of PMD even further. Specifically, the association between PMD and the number of FTPs differed in young patients under the age of 45 (mean decrease of 0.37 PMD units per pregnancy) from the association in older age groups (mean decrease between 2.29 and 2.39 PMD units). BMI did not alter the association between PMD and the number of FTPs.

CONCLUSIONS

The effect of pregnancies on mammographic density does not appear to become apparent before the age of menopause. The mechanism that drives the effect of pregnancies on mammographic density appears to be counter-regulated by other influences on mammographic density in younger patients.

Predicting Triple-Negative Breast Cancer Subtype Using Multiple Single Nucleotide Polymorphisms for Breast Cancer Risk and Several Variable Selection Methods

INTRODUCTION

Studies of triple-negative breast cancer have recently been extending the inclusion criteria and incorporating additional molecular markers into the selection criteria, opening up scope for targeted therapies. The screening phases required for studies of this type are often prolonged, since the process of determining the molecular subtype and carrying out additional biomarker assessment is time-consuming. Parameters such as germline genotypes capable of predicting the molecular subtype before it becomes available from pathology might be helpful for treatment planning and optimizing the timing and cost of screening phases. This appears to be feasible, as rapid and low-cost genotyping methods are becoming increasingly available. The aim of this study was to identify single nucleotide polymorphisms (SNPs) for breast cancer risk capable of predicting triple negativity, in addition to clinical predictors, in breast cancer patients.

METHODS

This cross-sectional observational study included 1271 women with invasive breast cancer who were treated at a university hospital. A total of 76 validated breast cancer risk SNPs were successfully genotyped. Univariate associations between each SNP and triple negativity were explored using logistic regression analyses. Several variable selection and regression techniques were applied to identify a set of SNPs that together improve the prediction of triple negativity in addition to the clinical predictors of age at diagnosis and body mass index (BMI). The most accurate prediction method was determined by cross-validation.

RESULTS

The SNP rs10069690 (TERT, CLPTM1L) was the only significant SNP (corrected p = 0.02) after correction of p values for multiple testing in the univariate analyses. This SNP and three additional SNPs from the genes RAD51B, CCND1, and FGFR2 were selected for prediction of triple negativity. The addition of these SNPs to clinical predictors increased the cross-validated area under the curve (AUC) from 0.618 to 0.625. Age at diagnosis was the strongest predictor, stronger than any genetic characteristics.

CONCLUSION

Prediction of triple-negative breast cancer can be improved if SNPs associated with breast cancer risk are added to a prediction rule based on age at diagnosis and BMI. This finding could be used for prescreening purposes in complex molecular therapy studies for triple-negative breast cancer.

Qualitative Versus Quantitative Mammographic Breast Density Assessment: Applications for the US and Abroad

Mammographic breast density (MBD) has been proven to be an important risk factor for breast cancer and an important determinant of mammographic screening performance. The measurement of density has changed dramatically since its inception. Initial qualitative measurement methods have been found to have limited consistency between readers, and in regards to breast cancer risk. Following the introduction of full-field digital mammography, more sophisticated measurement methodology is now possible. Automated computer-based density measurements can provide consistent, reproducible, and objective results. In this review paper, we describe various methods currently available to assess MBD, and provide a discussion on the clinical utility of such methods for breast cancer screening.

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.

Cyclic endogenous estrogen and progesterone vary by mammographic density phenotypes in premenopausal women

Estrogen and progesterone are key factors in the development of breast cancer, but it remains unclear whether these hormones are associated with mammographic density phenotypes in premenopausal women. We measured percent mammographic density, nondense area, and absolute mammographic density using computer-assisted breast density readings (Madena) from digitized mammograms taken on a scheduled day of the menstrual cycle (day 7-12) among 202 healthy, premenopausal women (Energy Balance and Breast cancer Aspects Study-I). Daily salivary concentrations of 17β-estradiol and progesterone throughout an entire menstrual cycle and fasting morning serum concentrations of hormones on 3 specific days of the menstrual cycle were assessed. Salivary and serum 17β-estradiol and progesterone were positively associated with percent mammographic density, we observed by 1 SD increase in overall salivary estradiol (β-value equal to 2.07, P=0.044), luteal salivary progesterone (β-value equal to 2.40, P=0.020). Women with above-median percent mammographic density had a 20% higher mean salivary 17β-estradiol level throughout the menstrual cycle. The odds ratio for having above-median percent mammographic density (>28.5%) per 1 SD increase in overall salivary 17β-estradiol was 1.66 (95% confidence interval 1.13-2.45). Women in the top tertile of the overall average daily 17β-estradiol concentrations had an odds ratio of 2.54 (confidence interval 1.05-6.16) of above-median percent mammographic density compared with women in the bottom tertile. Our finding of a relationship between estrogen, progesterone, and percent mammographic density and not with other mammographic density phenotypes in premenopausal women is biologically plausible, but needs to be replicated in larger studies.

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.

Current strategies for the prevention of breast cancer

Due to the high incidence of breast cancer in the United States, optimal strategies for its prevention are imperative. This entails identification of women who are at an increased risk for breast cancer and an integrative approach that includes effective screening methods as well as nutritional, pharmacologic, and surgical management. Several breast cancer risk-assessment tools, such as the Gail and Claus models, can help clinicians determine the quantitative risk of breast cancer. The role of selective estrogen receptor modulators, such as tamoxifen and raloxifene, for the prevention of breast cancer has been well established. Several other agents, such as aromatase inhibitors, are currently being investigated. The potential adverse effects of these chemopreventive agents, which include an impact on the quality of life, must be discussed with the patient before deciding on this approach. Additionally, breast cancer risk factors have been identified over the years; some of them are modifiable, but others are not. Although there is no conclusive evidence to suggest the protective role of specific dietary components, alcohol consumption and obesity are associated with an increased breast cancer risk; thus lifestyle changes can lead to a lower risk of developing breast cancer. Surgical approaches, including bilateral risk-reduction mastectomy and salpingo-oophorectomy, are usually limited to women with a hereditary predisposition to development of breast cancer. The objective of this review is to summarize the various approaches directed at reducing the incidence of breast cancer.

Polymorphisms in the RANK/RANKL genes and their effect on bone specific prognosis in breast cancer patients

The receptor activator of NF-κB (RANK) pathway is involved in bone health as well as breast cancer (BC) pathogenesis and progression. Whereas the therapeutic implication of this pathway is established for the treatment of osteoporosis and bone metastases, the application in adjuvant BC is currently investigated. As genetic variants in this pathway have been described to influence bone health, aim of this study was the prognostic relevance of genetic variants in RANK and RANKL. Single nucleotide polymorphisms in RANK(L) (rs1054016/rs1805034/rs35211496) were genotyped and analyzed with regard to bone metastasis-free survival (BMFS), disease-free survival, and overall survival for a retrospective cohort of 1251 patients. Cox proportional hazard models were built to examine the prognostic influence in addition to commonly established prognostic factors. The SNP rs1054016 seems to influence BMFS. Patients with two minor alleles had a more favorable prognosis than patients with at least one common allele (HR 0.37 (95% CI: 0.17, 0.84)), whereas other outcome parameters remained unaffected. rs1805034 and rs35211496 had no prognostic relevance. The effect of rs1054016(RANKL) adds to the evidence that the RANK pathway plays a role in BC pathogenesis and progression with respect to BMFS, emphasizing the connection between BC and bone health.

[Future of mammography-based imaging]

Mammography is the central diagnostic method for clinical diagnostics of breast cancer and the breast cancer screening program. In the clinical routine complementary methods, such as ultrasound, tomosynthesis and optional magnetic resonance imaging (MRI) are already combined for the diagnostic procedure. Future developments will utilize investigative procedures either as a hybrid (combination of several different imaging modalities in one instrument) or as a fusion method (the technical fusion of two or more of these methods) to implement fusion imaging into diagnostic algorithms. For screening there are reasonable hypotheses to aim for studies that individualize the diagnostic process within the screening procedure. Individual breast cancer risk prediction and individualized knowledge about sensitivity and specificity for certain diagnostic methods could be tested. The clinical implementation of these algorithms is not yet in sight.

Mammographic Density and Prediction of Nodal Status in Breast Cancer Patients

Aim: Nodal status remains one of the most important prognostic factors in breast cancer. The cellular and molecular reasons for the spread of tumor cells to the lymph nodes are not well understood and there are only few predictors in addition to tumor size and multifocality that give an insight into additional mechanisms of lymphatic spread. Aim of our study was therefore to investigate whether breast characteristics such as mammographic density (MD) add to the predictive value of the presence of lymph node metastases in patients with primary breast cancer. Methods: In this retrospective study we analyzed primary, metastasis-free breast cancer patients from one breast center for whom data on MD and staging information were available. A total of 1831 patients were included into this study. MD was assessed as percentage MD (PMD) using a semiautomated method and two readers for every patient. Multiple logistic regression analyses with nodal status as outcome were used to investigate the predictive value of PMD in addition to age, tumor size, Ki-67, estrogen receptor (ER), progesterone receptor (PR), grading, histology, and multi-focality. Results: Multifocality, tumor size, Ki-67 and grading were relevant predictors for nodal status. Adding PMD to a prediction model which included these factors did not significantly improve the prediction of nodal status (p = 0.24, likelihood ratio test). Conclusion: Nodal status could be predicted quite well with the factors multifocality, tumor size, Ki-67 and grading. PMD does not seem to play a role in the lymphatic spread of tumor cells. It could be concluded that the amount of extracellular matrix and stromal cell content of the breast which is reflected by MD does not influence the probability of malignant breast cells spreading from the primary tumor to the lymph nodes.

Re-excision Rates and Local Recurrence in Breast Cancer Patients Undergoing Breast Conserving Therapy

Background: Controversy continues over the impact of re-excision (RE) on local recurrence (LR) in patients with invasive breast cancer. Patients and Methods: We investigated factors which could effect RE rates in patients undergoing breast-conserving or oncoplastic surgery. Between 2000 and 2003, 489 patients with stage pT1-pT2 or pN0/1 tumors were evaluated. 74 patients fulfilled the inclusion criteria. Patients were categorized into 3 groups: no RE (n = 25), RE during primary surgery (n = 28), and RE performed during secondary or even tertiary procedure (n = 21). All tumor slides were re-evaluated by a pathologist specializing in breast cancer. Results: Mean follow-up was 70 months with an overall LR rate of 4.1 %. Binary logistic regression revealed no tumor-specific risk factors for RE. There was no LR in the group of patients who did not have RE. There was one case of LR in the group of patients who had RE during primary surgery. Two cases of LR were observed in the group of patients who had two or more surgical procedures. Conclusion: New risk factors for increased RE rates were not observed, reflecting the inconsistent data on risk factors for RE. However, breast cancers should be excised in a single procedure and oncoplastic procedures should be considered.