Hormone replacement therapy use dramatically increases breast oestrogen receptor expression in obese postmenopausal women

BACKGROUND: It is known that use of hormone replacement therapy (HRT) by postmenopausal women increases the risk of breast cancer. METHOD: In this study, oestrogen receptor (ER)-α expression is examined using standard immunoperoxidase technique. RESULTS: Normal breast samples of 11 Australian postmenopausal women have been included in the ER-α study; the result showed a strong correlation (r(2) = 0.80) between ER-α expression in normal breast epithelial cells and body mass index (BMI) in normal women who currently use HRT. CONCLUSION: This finding confirms that the possibility of increased risk of breast cancer associated with increased ER-α expression in normal breast epithelial cells, in turn associated with high BMI and the use of HRT

Borderline breast core needle histology: predictive values for malignancy in lesions of uncertain malignant potential (B3)

Breast core needle biopsy (CNB) is an accurate test but may result in borderline histology (lesions of uncertain malignant potential or B3). This is an evaluation of the largest series (to date) of B3 histology, which focusses on estimating positive predictive values (PPV) for malignancy. We identified all B3 CNBs over a 10-year period in a single institution (N=372) from a series of 4035 consecutive needle biopsies. We describe the imaging findings, and report excision histology outcomes (N=279) and category-specific PPV for B3 lesions using two approaches including estimates based on subjects who had either excision or follow-up (N=328). B3 represented 9.2% of all CNB results. Excision histology was benign in 181 (64.9%) and malignant in 98 (35.1%) subjects (61 ductal carcinoma in situ, 37 invasive carcinoma). Positive predictive value for malignancy (based on excision histology) was 35.1% (95% CI: 29.5–40.7) and PPV (based on excision or review) was 29.9% (95% CI: 24.9–34.8). Lesion-specific PPV (estimates in parentheses for excision or follow-up) was atypical ductal hyperplasia 44.7% (40.6%); lobular intraepithelial neoplasia 60.9% (58.3%); papillary lesion 22.7% (15.9%); radial scar 16.7% (12.3%); phyllodes tumour 12.5% (12.5%); and B3 not specified 20.0%. Approximately one-third of CNB results classified as B3 are malignant on excision, and the likelihood of malignancy varies substantially between specific lesion groups. Whereas cases may be selectively managed without surgery, the majority warrant excision biopsy based on our estimates. Research is needed to improve differentiation between malignant and benign diseases in B3 lesions using diagnostic or predictive methods

A randomized controlled trial of digital breast tomosynthesis versus digital mammography in population-based screening in Bergen: interim analysis of performance indicators from the To-Be trial

Objectives To describe a randomized controlled trial (RCT) of digital breast tomosynthesis including synthesized two-dimensional mammograms (DBT) versus digital mammography (DM) in a population-based screening program for breast cancer and to compare selected secondary screening outcomes for the two techniques. Methods This RCT, performed in Bergen as part of BreastScreen Norway, was approved by the Regional Committees for Medical Health Research Ethics. All screening attendees in Bergen were invited to participate, of which 89% (14,274/15,976) concented during the first year, and were randomized to DBT (n = 7155) or DM (n = 7119). Secondary screening outcomes were stratified by mammographic density and compared using two-sample t-tests, chi-square tests, ANOVA, negative binomial regression and tests of proportions (z tests). Results Mean reading time was 1 min 11 s for DBT and 41 s for DM (p < 0.01). Mean time spent at consensus was 3 min 12 s for DBT and 2 min 12 s for DM (p < 0.01), while the rate of cases discussed at consensus was 6.4% and 7.4%, respectively for DBT and DM (p = 0.03). The recall rate was 3.0% for DBT and 3.6% for DM (p = 0.03). For women with non-dense breasts, recall rate was 2.2% for DBT versus 3.4% for DM (p = 0.04). The rate did not differ for women with dense breasts (3.6% for both). Mean glandular dose per examination was 2.96 mGy for DBT and 2.95 mGy for DM (p = 0.433). Conclusions Interim analysis of a screening RCT showed that DBT took longer to read than DM, but had significantly lower recall rate than DM. We found no differences in radiation dose between the two techniques. Key Points • In this RCT, DBT was associated with longer interpretation time than DM • Recall rates were lower for DBT than for DM • Mean glandular radiation dose did not differ between DBT and DMpublishedVersio

Early prediction of pathologic response to neoadjuvant therapy in breast cancer: Systematic review of the accuracy of MRI

Abstract Magnetic resonance imaging (MRI) has been proposed to have a role in predicting final pathologic response when undertaken early during neoadjuvant chemotherapy (NAC) in breast cancer. This paper examines the evidence for MRI's accuracy in early response prediction. A systematic literature search (to February 2011) was performed to identify studies reporting the accuracy of MRI during NAC in predicting pathologic response, including searches of MEDLINE, PREMEDLINE, EMBASE, and Cochrane databases. 13 studies were eligible (total 605 subjects, range 16–188). Dynamic contrast-enhanced (DCE) MRI was typically performed after 1–2 cycles of anthracycline-based or anthracycline/taxane-based NAC, and compared to a pre-NAC baseline scan. MRI parameters measured included changes in uni- or bidimensional tumour size, three-dimensional volume, quantitative dynamic contrast measurements (volume transfer constant [Ktrans], exchange rate constant [ k ep ], early contrast uptake [ECU]), and descriptive patterns of tumour reduction. Thresholds for identifying response varied across studies. Definitions of response included pathologic complete response (pCR), near-pCR, and residual tumour with evidence of NAC effect (range of response 0–58%). Heterogeneity across MRI parameters and the outcome definition precluded statistical meta-analysis. Based on descriptive presentation of the data, sensitivity/specificity pairs for prediction of pathologic response were highest in studies measuring reductions in Ktrans (near-pCR), ECU (pCR, but not near-pCR) and tumour volume (pCR or near-pCR), at high thresholds (typically >50%); lower sensitivity/specificity pairs were evident in studies measuring reductions in uni- or bidimensional tumour size. However, limitations in study methodology and data reporting preclude definitive conclusions. Methods proposed to address these limitations include: statistical comparison between MRI parameters, and MRI vs other tests (particularly ultrasound and clinical examination); standardising MRI thresholds and pCR definitions; and reporting changes in NAC based on test results. Further studies adopting these methods are warranted

Improving breast cancer screening in Australia: a public health perspective.

There are currently no single disruptors to breast cancer screening akin to the impact of human papillomavirus testing and vaccination on cervical cancer screening. However, there is a groundswell of interest to review the BreastScreen Australia program to consider more risk-based screening protocols and to establish whether to routinely inform women about their breast density. We propose a framework for a considered, evidence-based review. Population-level effectiveness of breast cancer screening is ultimately measured through its impact on breast cancer mortality, and this has been realised in Australia. Effectiveness can also be measured through treatment intensity, estimated overdiagnosis, false-positive screens and health economics measures. Key levers to improve such population-level outcomes include screening participation, screening test sensitivity and specificity, risk assessment and screening protocols. We propose that the review of the program should fall under an evidence-based, consensus-guided framework comprising four complementary elements: improved evidence on current program performance for population risk subgroups; regularly updated evidence on key levers for change; clinical trials and population simulation modelling working in tandem; and consensus-based decision making about the degree of improvement required to justify change. Informing women about their breast density is feasible and would be valued by some BreastScreen clients to help understand the accuracy of their screening test. However, without agreed protocols for screening women with dense breasts, increases in supplemental screening as observed in other settings would, in Australia, shift screening costs to clients and Medicare. This would reduce equity of access to population screening, and maintaining BreastScreen’s usual standard of monitoring and quality management (such as screen-detected and interval cancer diagnoses, and imaging and biopsy rates) would require data linkage between BreastScreen and other services. The proposed framework assesses screening effectiveness in the era of personalised medicine, allows review of multiple factors that may together warrant change, and gives full, evidence-based consideration of the benefits, harms and costs of various approaches to breast cancer screening. To be effective, the framework requires a coordinated approach to generating the evidence required for policy makers, with time to prepare appropriate health services

Overview of radiomics in breast cancer diagnosis and prognostication.

Diagnosis of early invasive breast cancer relies on radiology and clinical evaluation, supplemented by biopsy confirmation. At least three issues burden this approach: a) suboptimal sensitivity and suboptimal positive predictive power of radiology screening and diagnostic approaches, respectively; b) invasiveness of biopsy with discomfort for women undergoing diagnostic tests; c) long turnaround time for recall tests. In the screening setting, radiology sensitivity is suboptimal, and when a suspicious lesion is detected and a biopsy is recommended, the positive predictive value of radiology is modest. Recent technological advances in medical imaging, especially in the field of artificial intelligence applied to image analysis, hold promise in addressing clinical challenges in cancer detection, assessment of treatment response, and monitoring disease progression. Radiomics include feature extraction from clinical images; these features are related to tumor size, shape, intensity, and texture, collectively providing comprehensive tumor characterization, the so-called radiomics signature of the tumor. Radiomics is based on the hypothesis that extracted quantitative data derives from mechanisms occurring at genetic and molecular levels. In this article we focus on the role and potential of radiomics in breast cancer diagnosis and prognostication

Breast cancer Ki-67 expression prediction by digital breast tomosynthesis radiomics features

The aim of this paper was to investigate whether quantitative radiomic features extracted from digital breast tomosynthesis (DBT) are associated with Ki-67 expression of breast cancer. This was a prospective ethically approved study of 70 women diagnosed with invasive breast cancer in 2018, including 40 low Ki-67 expression (Ki-67 proliferation index <14%) cases and 30 high Ki-67 expression (Ki-67 proliferation index ≥ 14%) cases. A set of 106 quantitative radiomic features, including morphological, grey/scale statistics, and texture features, were extracted from DBT images. After applying least absolute shrinkage and selection operator (LASSO) method to select the most predictive features set for the classifiers, low versus high Ki-67 expression was evaluated by the area under the curve (AUC) at receiver operating characteristic analysis. Correlation coefficient was calculated for the most significant features

A randomized controlled trial of digital breast tomosynthesis versus digital mammography in population-based screening in Bergen: interim analysis of performance indicators from the To-Be trial

The aim of this paper was to describe a randomized controlled trial (RCT) of digital breast tomosynthesis including synthesized two-dimensional mammograms (DBT) versus digital mammography (DM) in a population-based screening program for breast cancer and to compare selected secondary screening outcomes for the two techniques. This RCT, performed in Bergen as part of BreastScreen Norway, was approved by the Regional Committees for Medical Health Research Ethics. All screening attendees in Bergen were invited to participate, of which 89% (14,274/15,976) concented during the first year, and were randomized to DBT (n = 7155) or DM (n = 7119). Secondary screening outcomes were stratified by mammographic density and compared using two-sample t-tests, chi-square tests, ANOVA, negative binomial regression and tests of proportions (z tests)