Breast cancer risk prediction using machine learning: a systematic review

Background

Breast cancer is the leading cause of cancer-related fatalities among women worldwide. Conventional screening and risk prediction models primarily rely on demographic and patient clinical history to devise policies and estimate likelihood. However, recent advancements in artificial intelligence (AI) techniques, particularly deep learning (DL), have shown promise in the development of personalized risk models. These models leverage individual patient information obtained from medical imaging and associated reports. In this systematic review, we thoroughly investigated the existing literature on the application of DL to digital mammography, radiomics, genomics, and clinical information for breast cancer risk assessment. We critically analyzed these studies and discussed their findings, highlighting the promising prospects of DL techniques for breast cancer risk prediction. Additionally, we explored ongoing research initiatives and potential future applications of AI-driven approaches to further improve breast cancer risk prediction, thereby facilitating more effective screening and personalized risk management strategies.

Objective and methods

This study presents a comprehensive overview of imaging and non-imaging features used in breast cancer risk prediction using traditional and AI models. The features reviewed in this study included imaging, radiomics, genomics, and clinical features. Furthermore, this survey systematically presented DL methods developed for breast cancer risk prediction, aiming to be useful for both beginners and advanced-level researchers.

Results

A total of 600 articles were identified, 20 of which met the set criteria and were selected. Parallel benchmarking of DL models, along with natural language processing (NLP) applied to imaging and non-imaging features, could allow clinicians and researchers to gain greater awareness as they consider the clinical deployment or development of new models. This review provides a comprehensive guide for understanding the current status of breast cancer risk assessment using AI.

Conclusion

This study offers investigators a different perspective on the use of AI for breast cancer risk prediction, incorporating numerous imaging and non-imaging features.

The Gail Model and Its Use in Preventive Screening: A Comparison of the Corbelli Study

Background This study aims to determine the usage of the Gail model in screening for breast cancer during physical examinations of women by sampling primary care physicians in two regions of Texas - Hidalgo County and Johnson County. A Gail score of 1.66% or higher indicates increased breast cancer risk. Three specialties are surveyed: internal medicine (IM), family medicine (FM), and gynecology (GYN). The null hypothesis for this study is that primary care physicians do not use the Gail model in screening for breast cancer during physical examinations of women. Methods A survey was distributed to 100 physicians with specialties in IM, FM, and GYN from May 2022 to July 2022. The survey assessed the physician's frequency of use of the Gail model and chemoprevention. Data were collected by distributing survey questionnaires to physicians in person. Descriptive statistics were used for response distributions. Fisher's exact probability test was used for comparisons across specialties. Results The response rate was 34% (34/100). Thirty-eight percent of the physicians surveyed reported using the Gail model in their practice (IM 46%, FM 23%, and GYN 31%). All 13 of the physicians using the Gail model were open to using chemoprevention. Conclusions Only 38% of the physicians surveyed responded that they use the Gail model in their practice. The study concluded that a minority of primary care physicians used the Gail model to decrease breast cancer risk. Further research would help to define better the Gail model and its use in preventing breast cancer in women. The Gail model appears to be beneficial to breast cancer risk reduction; however, risk reduction medication side effects need to be minimized.

Low-dose acetylsalicylic acid reduces local inflammation and tissue perfusion in dense breast tissue in postmenopausal women

PURPOSE

One major risk factor for breast cancer is high mammographic density. It has been estimated that dense breast tissue contributes to ~ 30% of all breast cancer. Prevention targeting dense breast tissue has the potential to improve breast cancer mortality and morbidity. Anti-estrogens, which may be associated with severe side-effects, can be used for prevention of breast cancer in women with high risk of the disease per se. However, no preventive therapy targeting dense breasts is currently available. Inflammation is a hallmark of cancer. Although the biological mechanisms involved in the increased risk of cancer in dense breasts is not yet fully understood, high mammographic density has been associated with increased inflammation. We investigated whether low-dose acetylsalicylic acid (ASA) affects local breast tissue inflammation and/or structural and dynamic changes in dense breasts.

METHODS

Postmenopausal women with mammographic dense breasts on their regular mammography screen were identified. A total of 53 women were randomized to receive ASA 160 mg/day or no treatment for 6 months. Magnetic resonance imaging (MRI) was performed before and after 6 months for a sophisticated and continuous measure breast density by calculating lean tissue fraction (LTF). Additionally, dynamic quantifications including tissue perfusion were performed. Microdialysis for sampling of proteins in vivo from breasts and abdominal subcutaneous fat, as a measure of systemic effects, before and after 6 months were performed. A panel of 92 inflammatory proteins were quantified in the microdialysates using proximity extension assay.

RESULTS

After correction for false discovery rate, 20 of the 92 inflammatory proteins were significantly decreased in breast tissue after ASA treatment, whereas no systemic effects were detected. In the no-treatment group, protein levels were unaffected. Breast density, measured by LTF on MRI, were unaffected in both groups. ASA significantly decreased the perfusion rate. The perfusion rate correlated positively with local breast tissue concentration of VEGF.

CONCLUSIONS

ASA may shape the local breast tissue microenvironment into an anti-tumorigenic state. Trials investigating the effects of low-dose ASA and risk of primary breast cancer among postmenopausal women with maintained high mammographic density are warranted. Trial registration EudraCT: 2017-000317-22.

Breast Cancer Polygenic-Risk Score Influence on Risk-Reducing Endocrine Therapy Use: Genetic Risk Estimate (GENRE) Trial 1-Year and 2-Year Follow-Up

Refinement of breast cancer risk estimates with a polygenic-risk score (PRS) may improve uptake of risk-reducing endocrine therapy (ET). A previous clinical trial assessed the influence of adding a PRS to traditional risk estimates on ET use. We stratified participants according to PRS-refined breast cancer risk and evaluated ET use and ET-related quality of life (QOL) at 1-year (previously reported) and 2-year follow-ups. Of 151 participants, 58 (38.4%) initiated ET, and 22 (14.6%) discontinued ET by 2 years; 42 (27.8%) and 36 (23.8%) participants were using ET at 1- and 2-year follow-ups, respectively. At the 2-year follow-up, 39% of participants with a lifetime breast cancer risk of 40.1% to 100.0%, 18% with a 20.1% to 40.0% risk, and 16% with a 0.0% to 20.0% risk were taking ET (overall P = 0.01). Moreover, 40% of participants whose breast cancer risk increased by 10% or greater with addition of the PRS to a traditional breast cancer-risk model were taking ET versus 0% whose risk decreased by 10% or greater (P = 0.004). QOL was similar for participants taking or not taking ET at 1- and 2-year follow-ups, although most who discontinued ET did so because of adverse effects. However, these QOL results may have been skewed by the long interval between QOL surveys and lack of baseline QOL data. PRS-informed breast cancer prevention counseling has a lasting, but waning, effect over time. Additional follow-up studies are needed to address the effect of PRS on ET adherence, ET-related QOL, supplemental breast cancer screening, and other risk-reducing behaviors.

PREVENTION RELEVANCE

Risk-reducing medications for breast cancer are considerably underused. Informing women at risk with precise and individualized risk assessment tools may substantially affect the incidence of breast cancer. In our study, a risk assessment tool (IBIS-polygenic-risk score) yielded promising results, with 39% of women at highest risk starting preventive medication.

Breast cancer therapies reduce risk of Alzheimer's disease and promote estrogenic pathways and action in brain

Worldwide, an ever-increasing number of women are prescribed estrogen-modulating therapies (EMTs) for the treatment of breast cancer. In parallel, aging of the global population of women will contribute to risk of both breast cancer and Alzheimer's disease. To address the impact of anti-estrogen therapies on risk of Alzheimer's and neural function, we conducted medical informatic and molecular pharmacology analyses to determine the impact of EMTs on risk of Alzheimer's followed by determination of EMT estrogenic mechanisms of action in neurons. Collectively, these data provide both clinical and mechanistic data indicating that select EMTs exert estrogenic agonist action in neural tissue that are associated with reduced risk of Alzheimer's disease while simultaneously acting as effective estrogen receptor antagonists in breast.

Impact of Pharmacogenomics in Clinical Practice

Polymorphisms of genes encoding drug metabolizing enzymes and transporters can significantly modify pharmacokinetics, and this can be associated with significant differences in drug efficacy, safety, and tolerability. Moreover, genetic variants of some components of the immune system can explain clinically relevant drug-related adverse events. However, the implementation of drug dose individualization based on pharmacogenomics remains scarce. In this narrative review, the impact of genetic variations on the disposition, safety, and tolerability of the most commonly prescribed drugs is reported. Moreover, reasons for poor implementation of pharmacogenomics in everyday clinical settings are discussed. The literature analysis showed that knowledge of how genetic variations can modify the effectiveness, safety, and tolerability of a drug can lead to the adjustment of usually recommended drug dosages, improve effectiveness, and reduce drug-related adverse events. Despite some efforts to introduce pharmacogenomics in clinical practice, presently very few centers routinely use genetic tests as a guide for drug prescription. The education of health care professionals seems critical to keep pace with the rapidly evolving field of pharmacogenomics. Moreover, multimodal algorithms that incorporate both clinical and genetic factors in drug prescribing could significantly help in this regard. Obviously, further studies which definitively establish which genetic variations play a role in conditioning drug effectiveness and safety are needed. Many problems must be solved, but the advantages for human health fully justify all the efforts.

Prediction of breast cancer risk for sisters of women attending screening

BACKGROUND

Risk assessment is important for breast cancer prevention and early detection. We aimed to examine whether common risk factors, mammographic features, and breast cancer risk prediction scores of a woman were associated with breast cancer risk for her sisters.

METHODS

We included 53 051 women from the Karolinska Mammography Project for Risk Prediction of Breast Cancer (KARMA) study. Established risk factors were derived using self-reported questionnaires, mammograms, and single nucleotide polymorphism genotyping. Using the Swedish Multi-Generation Register, we identified 32 198 sisters of the KARMA women (including 5352 KARMA participants and 26 846 nonparticipants). Cox models were used to estimate the hazard ratios of breast cancer for both women and their sisters, respectively.

RESULTS

A higher breast cancer polygenic risk score, a history of benign breast disease, and higher breast density in women were associated with an increased risk of breast cancer for both women and their sisters. No statistically significant association was observed between breast microcalcifications and masses in women and breast cancer risk for their sisters. Furthermore, higher breast cancer risk scores in women were associated with an increased risk of breast cancer for their sisters. Specifically, the hazard ratios for breast cancer per 1 standard deviation increase in age-adjusted KARMA, Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm (BOADICEA), and Tyrer-Cuzick risk scores were 1.16 (95% confidence interval [CI] = 1.07 to 1.27), 1.23 (95% CI = 1.12 to 1.35), and 1.21 (95% CI = 1.11 to 1.32), respectively.

CONCLUSION

A woman's breast cancer risk factors are associated with her sister's breast cancer risk. However, the clinical utility of these findings requires further investigation.

NOXA expression is downregulated in human breast cancer undergoing incomplete pathological response and senescence after neoadjuvant chemotherapy

Neoadjuvant chemotherapy (NAC) is a frequently utilized approach to treat locally advanced breast cancer, but, unfortunately, a subset of tumors fails to undergo complete pathological response. Apoptosis and therapy-induced senescence (TIS) are both cell stress mechanisms but their exact role in mediating the pathological response to NAC is not fully elucidated. We investigated the change in expression of PAMIP1, the gene encoding for the pro-apoptotic protein, NOXA, following NAC in two breast cancer gene datasets, and the change in NOXA protein expression in response to NAC in 55 matched patient samples (pre- and post-NAC). PAMIP1 expression significantly declined in post-NAC in the two sets, and in our cohort, 75% of the samples exhibited a downregulation in NOXA post-NAC. Matched samples that showed a decline in NOXA post-NAC were examined for TIS based on a signature of downregulated expression of Lamin-B1 and Ki-67 and increased p16INK4a, and the majority exhibited a decrease in Lamin B1 (66%) and Ki-67 (80%), and increased p16INK4a (49%). Since our cohort consisted of patients that did not develop complete pathological response, such findings have clinical implications on the role of TIS and NOXA downregulation in mediating suboptimal responses to the currently established NAC.

Study protocol for development and validation of a single tool to assess risks of stroke, diabetes mellitus, myocardial infarction and dementia: DemNCD-Risk

INTRODUCTION

Current efforts to reduce dementia focus on prevention and risk reduction by targeting modifiable risk factors. As dementia and cardiometabolic non-communicable diseases (NCDs) share risk factors, a single risk-estimating tool for dementia and multiple NCDs could be cost-effective and facilitate concurrent assessments as compared with a conventional single approach. The aim of this study is to develop and validate a new risk tool that estimates an individual's risk of developing dementia and other NCDs including diabetes mellitus, stroke and myocardial infarction. Once validated, it could be used by the public and general practitioners.

METHODS AND ANALYSIS

Ten high-quality cohort studies from multiple countries were identified, which met eligibility criteria, including large representative samples, long-term follow-up, data on clinical diagnoses of dementia and NCDs, recognised modifiable risk factors for the four NCDs and mortality data. Pooled harmonised data from the cohorts will be used, with 65% randomly allocated for development of the predictive model and 35% for testing. Predictors include sociodemographic characteristics, general health risk factors and lifestyle/behavioural risk factors. A subdistribution hazard model will assess the risk factors' contribution to the outcome, adjusting for competing mortality risks. Point-based scoring algorithms will be built using predictor weights, internally validated and the discriminative ability and calibration of the model will be assessed for the outcomes. Sensitivity analyses will include recalculating risk scores using logistic regression.

ETHICS AND DISSEMINATION

Ethics approval is provided by the University of New South Wales Human Research Ethics Committee (UNSW HREC; protocol numbers HC200515, HC3413). All data are deidentified and securely stored on servers at Neuroscience Research Australia. Study findings will be presented at conferences and published in peer-reviewed journals. The tool will be accessible as a public health resource. Knowledge translation and implementation work will explore strategies to apply the tool in clinical practice.

EZH2 Expression and Survival for ER+/tamoxifen Treated Breast Cancer Patients with rs2302427 C>G: A Novel Prognostic and Risk Predictive Biomarker

BACKGROUND AND OBJECTIVES

Overexpression of the EZH2 gene silences several genes involved in DNA repair, cell-cell adhesion, and tumor suppressor genes, resulting in the development of several types of cancers. In the present study, a genetic polymorphism analysis was performed by selecting three SNPs (rs.2302427C>G, rs.3757441C>T, and rs.6950683T>C) of the EZH2 gene based on our previous in silico studies.

METHODS

A total of 250 breast cancer patients and 250 healthy individuals were recruited for the study. Patients with pre-operative breast cancer with different clinical-pathological variables and age-matched healthy women were recruited for the EZH2 gene expression analysis.

RESULTS

The genetic polymorphism analysis revealed two SNPs (rs.2302427C>G and rs.6950683T>C) of the three studied SNPs of the EZH2 gene have a protective role in all three genetic models. The haplotype analysis predicted that two haplotypes ACGT and ACGC were significantly associated with a lower risk of breast cancer.

INTERPRETATION AND CONCLUSIONS

Three significant findings of the SNP rs.2302427C>G (Asp193His) i.e., protective role against breast cancer, survival advantage in ER+/tamoxifen treated breast cancer patients, and decreased expression due to the presence of mutant GG genotype, suggests considering it as an important prognostic biomarker for a good survival outcome of breast cancer patients treated with ER+/tamoxifen. Compared with other studies, the other SNP rs.3757441T>C was observed to have a protective effect in breast cancer biology but plays an antagonistic role in colorectal cancer (CRC) biology. To our knowledge, this is the first detailed study on computationally validated EZH2 SNPs in breast cancer.

Identification of BRCA1/2 mutation female carriers using circulating microRNA profiles

Identifying germline BRCA1/2 mutation carriers is vital for reducing their risk of breast and ovarian cancer. To derive a serum miRNA-based diagnostic test we used samples from 653 healthy women from six international cohorts, including 350 (53.6%) with BRCA1/2 mutations and 303 (46.4%) BRCA1/2 wild-type. All individuals were cancer-free before and at least 12 months after sampling. RNA-sequencing followed by differential expression analysis identified 19 miRNAs significantly associated with BRCA mutations, 10 of which were ultimately used for classification: hsa-miR-20b-5p, hsa-miR-19b-3p, hsa-let-7b-5p, hsa-miR-320b, hsa-miR-139-3p, hsa-miR-30d-5p, hsa-miR-17-5p, hsa-miR-182-5p, hsa-miR-421, hsa-miR-375-3p. The final logistic regression model achieved area under the receiver operating characteristic curve 0.89 (95% CI: 0.87-0.93), 93.88% sensitivity and 80.72% specificity in an independent validation cohort. Mutated gene, menopausal status or having preemptive oophorectomy did not affect classification performance. Circulating microRNAs may be used to identify BRCA1/2 mutations in patients of high risk of cancer, offering an opportunity to reduce screening costs.

Breast Cancer: Risk Assessment, Screening, and Primary Prevention

This review provides an outline of a risk-based approach to breast cancer screening and prevention. All women should be assessed for breast cancer risk starting at age 18 with identification of modifiable and non-modifiable risk factors. Patients can then be stratified into average, moderate, and high-risk groups with personalized screening and prevention plans. Counseling on breast awareness and lifestyle changes is recommended for all women, regardless of risk category. High-risk individuals may benefit from additional screening modalities such as MRI and chemoprevention and should be managed closely by a multidisciplinary team.

Reassessing the Benefits and Harms of Risk-Reducing Medication Considering the Persistent Risk of Breast Cancer Mortality in Estrogen Receptor-Positive Breast Cancer

PURPOSE

Recent studies, including a meta-analysis of 88 trials, have shown higher than expected rates of recurrence and death in hormone receptor-positive breast cancer. These new findings suggest a need to re-evaluate the use of risk-reducing medication to avoid invasive breast cancer and breast cancer death in high-risk women.

METHODS

We adapted an established Cancer Intervention and Surveillance Modeling Network model to evaluate the lifetime benefits and harms of risk-reducing medication in women with a ≥ 3% 5-year risk of developing breast cancer according to the Breast Cancer Surveillance Consortium risk calculator. Model input parameters were derived from meta-analyses, clinical trials, and large observational data. We evaluated the effects of 5 years of risk-reducing medication (tamoxifen/aromatase inhibitors) with annual screening mammography ± magnetic resonance imaging (MRI) compared with no screening, MRI, or risk-reducing medication. The modeled outcomes included invasive breast cancer, breast cancer death, side effects, false positives, and overdiagnosis. We conducted subgroup analyses for individual risk factors such as age, family history, and prior biopsy.

RESULTS

Risk-reducing tamoxifen with annual screening (± MRI) decreased the risk of invasive breast cancer by 40% and breast cancer death by 57%, compared with no tamoxifen or screening. This is equivalent to an absolute reduction of 95 invasive breast cancers, and 42 breast cancer deaths per 1,000 high-risk women. However, these drugs are associated with side effects. For example, tamoxifen could increase the number of endometrial cancers up to 11 per 1,000 high-risk women. Benefits and harms varied by individual characteristics.

CONCLUSION

The addition of risk-reducing medication to screening could further decrease the risk of breast cancer death. Clinical guidelines for high-risk women should consider integrating shared decision making for risk-reducing medication and screening on the basis of individual risk factors.

Novel Non-Cyclooxygenase Inhibitory Derivative of Sulindac Inhibits Breast Cancer Cell Growth In Vitro and Reduces Mammary Tumorigenesis in Rats

The nonsteroidal anti-inflammatory drug (NSAID) sulindac demonstrates attractive anticancer activity, but the toxicity resulting from cyclooxygenase (COX) inhibition and the suppression of physiologically important prostaglandins precludes its long-term, high dose use in the clinic for cancer prevention or treatment. While inflammation is a known tumorigenic driver, evidence suggests that sulindac's antineoplastic activity is partially or fully independent of its COX inhibitory activity. One COX-independent target proposed for sulindac is cyclic guanosine monophosphate phosphodiesterase (cGMP PDE) isozymes. Sulindac metabolites, i.e., sulfide and sulfone, inhibit cGMP PDE enzymatic activity at concentrations comparable with those associated with cancer cell growth inhibitory activity. Additionally, the cGMP PDE isozymes PDE5 and PDE10 are overexpressed during the early stages of carcinogenesis and appear essential for cancer cell proliferation and survival based on gene silencing experiments. Here, we describe a novel amide derivative of sulindac, sulindac sulfide amide (SSA), which was rationally designed to eliminate COX-inhibitory activity while enhancing cGMP PDE inhibitory activity. SSA was 68-fold and 10-fold less potent than sulindac sulfide (SS) in inhibiting COX-1 and COX-2, respectively, but 10-fold more potent in inhibiting growth and inducing apoptosis in breast cancer cells. The pro-apoptotic activity of SSA was associated with inhibition of cGMP PDE activity, elevation of intracellular cGMP levels, and activation of cGMP-dependent protein kinase (PKG) signaling, as well as the inhibition of β-catenin/Tcf transcriptional activity. SSA displayed promising in vivo anticancer activity, resulting in a 57% reduction in the incidence and a 62% reduction in the multiplicity of tumors in the N-methyl-N-nitrosourea (MNU)-induced model of breast carcinogenesis. These findings provide strong evidence for cGMP/PKG signaling as a target for breast cancer prevention or treatment and the COX-independent anticancer properties of sulindac. Furthermore, this study validates the approach of optimizing off-target effects by reducing the COX-inhibitory activity of sulindac for future targeted drug discovery efforts to enhance both safety and efficacy.

Prospective validation of the BOADICEA multifactorial breast cancer risk prediction model in a large prospective cohort study

BACKGROUND

The multifactorial Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm (BOADICEA) breast cancer risk prediction model has been recently extended to consider all established breast cancer risk factors. We assessed the clinical validity of the model in a large independent prospective cohort.

METHODS

We validated BOADICEA (V.6) in the Swedish KARolinska Mammography Project for Risk Prediction of Breast Cancer (KARMA) cohort including 66 415 women of European ancestry (median age 54 years, IQR 45-63; 816 incident breast cancers) without previous cancer diagnosis. We calculated 5-year risks on the basis of questionnaire-based risk factors, pedigree-structured first-degree family history, mammographic density (BI-RADS), a validated breast cancer polygenic risk score (PRS) based on 313-SNPs, and pathogenic variant status in 8 breast cancer susceptibility genes: BRCA1, BRCA2, PALB2, CHEK2, ATM, RAD51C, RAD51D and BARD1. Calibration was assessed by comparing observed and expected risks in deciles of predicted risk and the calibration slope. The discriminatory ability was assessed using the area under the curve (AUC).

RESULTS

Among the individual model components, the PRS contributed most to breast cancer risk stratification. BOADICEA was well calibrated in predicting the risks for low-risk and high-risk women when all, or subsets of risk factors are included in the risk prediction. Discrimination was maximised when all risk factors are considered (AUC=0.70, 95% CI: 0.66 to 0.73; expected-to-observed ratio=0.88, 95% CI: 0.75 to 1.04; calibration slope=0.97, 95% CI: 0.95 to 0.99). The full multifactorial model classified 3.6% women as high risk (5-year risk ≥3%) and 11.1% as very low risk (5-year risk <0.33%).

CONCLUSION

The multifactorial BOADICEA model provides valid breast cancer risk predictions and a basis for personalised decision-making on disease prevention and screening.

Optimal breast cancer risk reduction policies tailored to personal risk level

Depending on personal and hereditary factors, each woman has a different risk of developing breast cancer, one of the leading causes of death for women. For women with a high-risk of breast cancer, their risk can be reduced by two main therapeutic approaches: 1) preventive treatments such as hormonal therapies (i.e., tamoxifen, raloxifene, exemestane); or 2) a risk reduction surgery (i.e., mastectomy). Existing national clinical guidelines either fail to incorporate or have limited use of the personal risk of developing breast cancer in their proposed risk reduction strategies. As a result, they do not provide enough resolution on the benefit-risk trade-off of an intervention policy as personal risk changes. In addressing this problem, we develop a discrete-time, finite-horizon Markov decision process (MDP) model with the objective of maximizing the patient's total expected quality-adjusted life years. We find several useful insights some of which contradict the existing national breast cancer risk reduction recommendations. For example, we find that mastectomy is the optimal choice for the border-line high-risk women who are between ages 22 and 38. Additionally, in contrast to the National Comprehensive Cancer Network recommendations, we find that exemestane is a plausible, in fact, the best, option for high-risk postmenopausal women.

The Effect of Anastrozole on the Lipid Profile: Systematic Review and Meta-analysis of Randomized Controlled Trials

PURPOSE

We aimed to investigate the impact of anastrozole administration on the traditional components of the lipid profile (ie, total cholesterol [TC], LDL-C, HDL-C, and triglycerides [TGs]) by means of a systematic review and meta-analysis of randomized controlled trials.

METHODS

We searched the PubMed/Medline, Scopus, Embase, and Web of Science databases for relevant randomized controlled trials published in the English language until January 18, 2022. The weighted mean difference (WMD) and 95% CIs were calculated using a random-effects model (DerSimonian and Laird methods).

FINDINGS

Anastrozole administration significantly lowered TC concentrations when the treatment duration was ≤3 months (WMD = -2.73 mg/dL; 95% CI, -5.09 to -0.38 mg/dL; P = 0.02) and when the baseline TC concentration was ≥200 mg/dL (WMD = -3.64 mg/dL; 95% CI, -6.30 to -0.98 mg/dL; P = 0.007). HDL-C levels decreased after anastrozole administration when the treatment duration was >3 months (WMD = -1.67 mg/dL; 95% CI, -3.24 to -0.10 mg/dL; P = 0.03). Anastrozole administration had no impact on TG or LDL-C values.

IMPLICATIONS

Anastrozole administration in humans can decrease TC and HDL-C levels but has no effect on LDL-C or TG concentrations.

Cellular and molecular mechanisms of breast cancer susceptibility

There is a plethora of recognized risk factors for breast cancer (BC) with poorly understood or speculative biological mechanisms. The lack of prevention options highlights the importance of understanding the mechanistic basis of cancer susceptibility and finding new targets for breast cancer prevention. Until now, we have understood risk and cancer susceptibility primarily through the application of epidemiology and assessing outcomes in large human cohorts. Relative risks are assigned to various human behaviors and conditions, but in general the associations are weak and there is little understanding of mechanism. Aging is by far the greatest risk factor for BC, and there are specific forms of inherited genetic risk that are well-understood to cause BC. We propose that bringing focus to the biology underlying these forms of risk will illuminate biological mechanisms of BC susceptibility.

Initiation and tolerance of chemoprevention among women with high-risk breast lesions: the potential of low-dose tamoxifen

PURPOSE

High-risk lesions (HRLs) of the breast are an indication for chemoprevention, yet uptake is low, largely due to concerns about side effects. In 2019, low-dose (5 mg) tamoxifen was demonstrated to reduce breast cancer risk with improved tolerance. We describe chemoprevention uptake in an academic clinic before and after the introduction of low-dose tamoxifen.

METHODS

Females age ≥ 35 with HRLs who established care from April 2017 through January 2020 and eligible for chemoprevention were included. Rates of chemoprevention initiation before and after the introduction of low-dose tamoxifen (pre-2019 vs. post-2019) were compared with chi-squared tests. Logistic regression identified demographic and clinical factors associated with chemoprevention initiation. Kaplan-Meier methods determined the rates of discontinuation.

RESULTS

Among 660 eligible females with HRLs, 22.7% initiated chemoprevention. Median time from first visit to chemoprevention initiation was 54 days (interquartile range (IQR): 0-209); 31.0% (46/150) started chemoprevention > 6 months after their initial visit. Chemoprevention uptake was not significantly different pre-2019 vs. post-2019 (21.2% vs. 26.3%, p = 0.16); however, post-2019, low-dose tamoxifen became the most popular option (41.5%, 34/82). On multivariable analyses, age and breast cancer family history were significantly associated with chemoprevention initiation. Discontinuation rates at 1 year were lowest for low-dose tamoxifen (6.7%) vs. tamoxifen 20 mg (15.0%), raloxifene (20.4%), or an aromatase inhibitor (20.0%).

CONCLUSION

In this modern cohort, 22.7% of females with HRLs initiated chemoprevention with 31.0% initiating chemoprevention > 6 months after their first visit. Low-dose tamoxifen is now the most popular choice for chemoprevention, with low discontinuation rates at 1 year.

Identifying and Managing Patients with Elevated Breast Cancer Risk Presenting for Screening Mammography

BACKGROUND

Identifying the prevalence and management of patients at high-risk for breast cancer can improve resource utilization and provide individualized screening strategies.

OBJECTIVE

The purpose of this study was to identify the prevalence of high-risk patients in our institution who presented for screening mammography and to understand how they utilized downstream resources offered to them.

MATERIALS AND METHODS

This single institution retrospective study utilized the Tyrer-Cuzick risk assessment model to provide lifetime risk of breast cancer of patients presenting for screening mammography over a one-year period. Their subsequent management and resource utilization were collated.

RESULTS

High-risk patients comprised 7.7% (701/9061) of our screening population. Of those high-risk women offered a Breast Center (BC) consultation, 75.2% (276/367) participated in the consultation, with 51.1% (141/276) of those patients completing MRI for supplemental screening. Risk reducing medication was adopted by 7.6% (6/79) of those offered. Of patients offered a genetics consultation, 66.3% (53/80) participated in the consultation, and 50.0% (40/80) completed genetic testing.

CONCLUSIONS

Identifying and understanding high-risk patient cohorts, whether locally or in a population-based context, is important for individualized patient care and practice efficiency.

Role of Exemestane in the Treatment of Estrogen-Receptor-Positive Breast Cancer: A Narrative Review of Recent Evidence

INTRODUCTION

Breast cancer (BC) is the most common type of cancer diagnosed among women worldwide with an estimated 2.3 million new cases every year. Almost two-thirds of all patients with BC have estrogen receptor-positive (ER+) tumors. In this review, the clinical evidence of exemestane in different treatment settings in ER+ BC is presented and summarized.

SEARCH STRATEGY

A search strategy with the keywords "breast cancer [MeSH Terms]" AND "exemestane [Title/Abstract]" was devised and a search was performed in PubMed.

RESULTS

The efficacy of exemestane in different treatment settings has been established by numerous clinical studies. Exemestane is recommended as an adjuvant treatment in postmenopausal women previously treated with tamoxifen in trials comparing 5 years of tamoxifen with 2-3 years of tamoxifen combined with 2-3 years of exemestane, which proved that treatment with exemestane provided better survival outcomes. Similarly, exemestane could be considered as a safe treatment option for neoadjuvant treatment, prevention of chemotherapy, and treatment of advanced BC either alone or in combination with other targeted therapy drugs in both pre- and postmenopausal women.

CONCLUSION

Exemestane could be considered as a reasonable therapeutic option in the treatment of ER+ BC at any stage in pre- and postmenopausal women.

OUP accepted manuscript

Mammographic density change has proven to be a reliable proxy for tamoxifen therapy response. The primary aim of this study was to identify time to tamoxifen-induced mammographic density change. We also analyzed side effects and adherence to therapy. In all, 42 women were randomized to 10 or 20 mg of daily oral tamoxifen. Mammograms were taken at baseline, 3, 6, and 9 months. Mammographic density change was measured using the automated STRATUS tool. Adverse events were monitored through a web-based questionnaire based on the FACT-ES tool. Nine out of the 42 (21%) participants discontinued therapy due to adverse events leaving 33 women in the study. A significant decrease in density was seen after 3 months of therapy. Dose did not seem to affect density change, side effects or adherence. Given the size of the study, additional studies are needed to confirm our data.

Breast cancer risk reduction: who, why, and what?

Women at increased risk of breast cancer have options to mitigate that risk. Understanding factors that increase risk and utilizing tools for quantitative estimates are important to be able to adequately counsel and target strategies for patients. On the basis of these estimates, patients may be able to engage in risk reduction interventions and increased screening, including chemoprevention or surgical risk reduction. Multiple organizations have published guidelines supporting risk assessment, genetic assessment, increased screening, and prevention measures for these women.

Mammographic density, endocrine therapy and breast cancer risk: a prognostic and predictive biomarker review

BACKGROUND

Endocrine therapy is effective at preventing or treating breast cancer. Some forms of endocrine therapy have been shown to reduce mammographic density. Reduced mammographic density for women receiving endocrine therapy could be used to estimate the chance of breast cancer returning or developing breast cancer in the first instance (a prognostic biomarker). In addition, changes in mammographic density might be able to predict how well a woman responds to endocrine therapy (a predictive biomarker). The role of breast density as a prognostic or predictive biomarker could help improve the management of breast cancer.

OBJECTIVES

To assess the evidence that a reduction in mammographic density following endocrine therapy for breast cancer prevention in women without previous breast cancer, or for treatment in women with early-stage hormone receptor-positive breast cancer, is a prognostic or predictive biomarker.

SEARCH METHODS

We searched the Cochrane Breast Cancer Group Specialised Register, CENTRAL, MEDLINE, Embase, and two trials registers on 3 August 2020 along with reference checking, bibliographic searching, and contact with study authors to obtain further data.

SELECTION CRITERIA

We included randomised, cohort and case-control studies of adult women with or without breast cancer receiving endocrine therapy. Endocrine therapy agents included were selective oestrogen receptor modulators and aromatase inhibitors. We required breast density before start of endocrine therapy and at follow-up. We included studies published in English.

DATA COLLECTION AND ANALYSIS

We used standard methodological procedures expected by Cochrane. Two review authors independently extracted data and assessed risk of bias using adapted Quality in Prognostic Studies (QUIPS) and Risk Of Bias In Non-randomised Studies - of Interventions (ROBINS-I) tools. We used the GRADE approach to evaluate the certainty of the evidence. We did not perform a quantitative meta-analysis due to substantial heterogeneity across studies.

MAIN RESULTS

Eight studies met our inclusion criteria, of which seven provided data on outcomes listed in the protocol (5786 women). There was substantial heterogeneity across studies in design, sample size (349 to 1066 women), participant characteristics, follow-up (5 to 14 years), and endocrine therapy agent. There were five breast density measures and six density change definitions. All studies had at least one domain as at moderate or high risk of bias. Common concerns were whether the study sample reflected the review target population, and likely post hoc definitions of breast density change. Most studies on prognosis for women receiving endocrine therapy reported a reduced risk associated with breast density reduction. Across endpoints, settings, and agents, risk ratio point estimates (most likely value) were between 0.1 and 1.5, but with substantial uncertainty. There was greatest consistency in the direction and magnitude of the effect for tamoxifen (across endpoints and settings, risk ratio point estimates were between 0.3 and 0.7). The findings are summarised as follows. Prognostic biomarker findings: Treatment Breast cancer mortality Two studies of 823 women on tamoxifen (172 breast cancer deaths) reported risk ratio point estimates of ~0.4 and ~0.5 associated with a density reduction. The certainty of the evidence was low. Recurrence Two studies of 1956 women on tamoxifen reported risk ratio point estimates of ~0.4 and ~0.7 associated with a density reduction. There was risk of bias in methodology for design and analysis of the studies and considerable uncertainty over the size of the effect. One study of 175 women receiving an aromatase inhibitor reported a risk ratio point estimate of ~0.1 associated with a density reduction. There was considerable uncertainty about the effect size and a moderate or high risk of bias in all domains. One study of 284 women receiving exemestane or tamoxifen as part of a randomised controlled trial reported risk ratio point estimates of ~1.5 (loco-regional recurrence) and ~1.3 (distance recurrence) associated with a density reduction. There was risk of bias in reporting and study confounding, and uncertainty over the size of the effects. The certainty of the evidence for all recurrence endpoints was very low. Incidence of a secondary primary breast cancer Two studies of 451 women on exemestane, tamoxifen, or unknown endocrine therapy reported risk ratio point estimates of ~0.5 and ~0.6 associated with a density reduction. There was risk of bias in reporting and study confounding, and uncertainty over the effect size. The certainty of the evidence was very low. We were unable to find data regarding the remaining nine outcomes prespecified in the review protocol. Prevention Incidence of invasive breast cancer and ductal carcinoma in situ (DCIS) One study of 507 women without breast cancer who were receiving preventive tamoxifen as part of a randomised controlled trial (51 subsequent breast cancers) reported a risk ratio point estimate of ~0.3 associated with a density reduction. The certainty of the evidence was low. Predictive biomarker findings: One study of a subset of 1065 women from a randomised controlled trial assessed how much the effect of endocrine therapy could be explained by breast density declines in those receiving endocrine therapy. This study evaluated the prevention of invasive breast cancer and DCIS. We found some evidence to support the hypothesis, with a risk ratio interaction point estimate ~0.5. However, the 95% confidence interval included unity, and data were based on 51 women with subsequent breast cancer in the tamoxifen group. The certainty of the evidence was low.

AUTHORS' CONCLUSIONS

There is low-/very low-certainty evidence to support the hypothesis that breast density change following endocrine therapy is a prognostic biomarker for treatment or prevention. Studies suggested a potentially large effect size with tamoxifen, but the evidence was limited. There was less evidence that breast density change following tamoxifen preventive therapy is a predictive biomarker than prognostic biomarker. Evidence for breast density change as a prognostic treatment biomarker was stronger for tamoxifen than aromatase inhibitors. There were no studies reporting mammographic density change following endocrine therapy as a predictive biomarker in the treatment setting, nor aromatase inhibitor therapy as a prognostic or predictive biomarker in the preventive setting. Further research is warranted to assess mammographic density as a biomarker for all classes of endocrine therapy and review endpoints.

Targeting the Pro-Survival Protein BCL-2 to Prevent Breast Cancer

Current chemopreventive strategies require 3-5 years of continuous treatment and have the concerns of significant side effects; therefore, new chemopreventive agents that require shorter and safer treatments are urgently needed. In this study, we developed a new murine model of breast cancer that mimics human breast cancer initiation and is ideal for testing the efficacy of chemopreventive therapeutics. In this model, introduction of lentivirus carrying a PIK3CA gene mutant commonly found in breast cancers infects a small number of the mammary cells, leading to atypia first and then to ductal carcinomas that are positive for both estrogen receptor and progesterone receptor. Venetoclax is a BH3 mimetic that blocks the anti-apoptotic protein BCL-2 and has efficacy in treating breast cancer. We found that venetoclax treatment of atypia-bearing mice delayed the progression to tumors, improved overall survival, and reduced pulmonary metastasis. Therefore, prophylactic treatment to inhibit the pro-survival protein BCL-2 may provide an alternative to the currently available regimens in breast cancer prevention.

Identifying women with increased risk of breast cancer and implementing risk-reducing strategies and supplemental imaging

Breast cancer (BC) is the second most common cancer in women, affecting 1 in 8 women in the United States (12.5%) in their lifetime. However, some women have a higher lifetime risk of BC because of genetic and lifestyle factors, mammographic breast density, and reproductive and hormonal factors. Because BC risk is variable, screening and prevention strategies should be individualized after considering patient-specific risk factors. Thus, health care professionals need to be able to assess risk profiles, identify high-risk women, and individualize screening and prevention strategies through a shared decision-making process. In this article, we review the risk factors for BC, risk-assessment models that identify high-risk patients, and preventive medications and lifestyle modifications that may decrease risk. We also discuss the benefits and limitations of various supplemental screening methods.

Effects of raloxifene administration on serum levels of insulin-like growth factor-1 and insulin-like growth factor-binding protein 3 levels: A systematic review and meta-analysis of randomized controlled trials

OBJECTIVE

To ascertain the clinical magnitude of raloxifene administration on insulin-like growth factor-1 (IGF-1) and insulin-like growth factor-binding protein 3 (IGFBP-3) levels.

METHODS

A systematic comprehensive search was performed without language limitation up to 14 December 2020. We included only trials that assessed the effect of raloxifene on IGF-1 and IGFBP-3 in adults. Meta-analysis was performed using the Stata software (Stata Corp. College Station, Texas, USA).

RESULTS

Seven arms were included, encompassing postmenopausal women with type 2 diabetes mellitus, postmenopausal women with breast cancer, healthy postmenopausal women, and healthy elderly men. Raloxifene therapy significantly reduced IGF-1 levels (WMD: -2.92 nmol/L, 95% CI: -3.49, -2.35, p < 0.001) compared to placebo. Raloxifene dosage ˃60 mg/day (WMD: -3.29 ng/mL, 95% CI: -3.50 to -3.08, I² = 0.0%) decreased IGF-1 levels more than 60 mg/day (WMD: -2.29 ng/mL, 95% CI: -2.90 to -1.69, I² = 16%). Moreover, intervention duration ˃26 weeks (WMD: -3.48 ng/mL, 95% CI: -5.26 to -1.69, I² = 0.0%) reduced IGF-1 levels more than ˂26 weeks (WMD: -2.55 ng/mL, 95% CI: -3.31 to -1.79, I² = 92%). In contrast, overall results from the random-effects model did not suggest a significant change in IGFBP-3 levels upon raloxifene therapy.

CONCLUSION

Raloxifene therapy significantly reduced serum levels of IGF-1 levels but without changes in IGFPB-3 levels.

Elevated risk thresholds predict endocrine risk-reducing medication use in the Athena screening registry

Risk-reducing endocrine therapy use, though the benefit is validated, is extremely low. The FDA has approved tamoxifen and raloxifene for a 5-year Breast Cancer Risk Assessment Tool (BCRAT) risk ≥ 1.67%. We examined the threshold at which high-risk women are likely to be using endocrine risk-reducing therapies among Athena Breast Health Network participants from 2011-2018. We identified high-risk women by a 5-year BCRAT risk ≥ 1.67% and those in the top 10% and 2.5% risk thresholds by age. We estimated the odds ratio (OR) of current medication use based on these thresholds using logistic regression. One thousand two hundred and one (1.2%) of 104,223 total participants used medication. Of the 33,082 participants with 5-year BCRAT risk ≥ 1.67%, 772 (2.3%) used medication. Of 2445 in the top 2.5% threshold, 209 (8.6%) used medication. Participants whose 5-year risk exceeded 1.67% were more likely to use medication than those whose risk was below this threshold, OR 3.94 (95% CI = 3.50-4.43). The top 2.5% was most strongly associated with medication usage, OR 9.50 (8.13-11.09) compared to the bottom 97.5%. Women exceeding a 5-year BCRAT ≥ 1.67% had modest medication use. We demonstrate that women in the top 2.5% have higher odds of medication use than those in the bottom 97.5% and compared to a risk of 1.67%. The top 2.5% threshold would more effectively target medication use and is being tested prospectively in a randomized control clinical trial.

CYP2D6 genotype predicts tamoxifen discontinuation and drug response: a secondary analysis of the KARISMA trial

BACKGROUND

Guidelines regarding whether tamoxifen should be prescribed based on women's cytochrome P450 2D6 (CYP2D6) genotypes are conflicting and have caused confusion. This study aims to investigate if CYP2D6 metabolizer status is associated with tamoxifen-related endocrine symptoms, tamoxifen discontinuation, and mammographic density change.

PATIENTS AND METHODS

We used data from 1440 healthy women who participated the KARISMA dose determination trial. Endocrine symptoms were measured using a modified Functional Assessment of Cancer Therapy - Endocrine Symptoms (FACT-ES) questionnaire. Change in mammographic density was measured and used as a proxy for tamoxifen response. Participants were genotyped and categorized as poor, intermediate, normal, or ultrarapid CYP2D6 metabolizers.

RESULTS

The median endoxifen level per mg oral tamoxifen among poor, intermediate, normal and ultrarapid CYP2D6 metabolizers were 0.18 ng/ml, 0.38 ng/ml, 0.56 ng/ml and 0.67 ng/ml, respectively. Ultrarapid CYP2D6 metabolizers were more likely than other groups to report a clinically relevant change in cold sweats, hot flash, mood swings, being irritable, as well as the overall modified FACT-ES score, after taking tamoxifen. The 6-month tamoxifen discontinuation rates among poor, intermediate, normal, and ultrarapid CYP2D6 metabolizers were 25.7%, 23.6%, 28.6%, and 44.4%, respectively. Among those who continued and finished the 6-month tamoxifen intervention, the mean change in dense area among poor, intermediate, normal, and ultrarapid CYP2D6 metabolizers were -0.8 cm², -4.5 cm², -4.1 cm², and -8.0 cm² respectively.

CONCLUSIONS

Poor CYP2D6 metabolizers are likely to experience an impaired response to tamoxifen, measured through mammographic density reduction. In contrast, ultrarapid CYP2D6 metabolizers are at risk for exaggerated response with pronounced adverse effects that may lead to treatment discontinuation.

Toward robust mammography-based models for breast cancer risk

Improved breast cancer risk models enable targeted screening strategies that achieve earlier detection and less screening harm than existing guidelines. To bring deep learning risk models to clinical practice, we need to further refine their accuracy, validate them across diverse populations, and demonstrate their potential to improve clinical workflows. We developed Mirai, a mammography-based deep learning model designed to predict risk at multiple timepoints, leverage potentially missing risk factor information, and produce predictions that are consistent across mammography machines. Mirai was trained on a large dataset from Massachusetts General Hospital (MGH) in the United States and tested on held-out test sets from MGH, Karolinska University Hospital in Sweden, and Chang Gung Memorial Hospital (CGMH) in Taiwan, obtaining C-indices of 0.76 (95% confidence interval, 0.74 to 0.80), 0.81 (0.79 to 0.82), and 0.79 (0.79 to 0.83), respectively. Mirai obtained significantly higher 5-year ROC AUCs than the Tyrer-Cuzick model ( P < 0.001) and prior deep learning models Hybrid DL ( P < 0.001) and Image-Only DL ( P < 0.001), trained on the same dataset. Mirai more accurately identified high-risk patients than prior methods across all datasets. On the MGH test set, 41.5% (34.4 to 48.5) of patients who would develop cancer within 5 years were identified as high risk, compared with 36.1% (29.1 to 42.9) by Hybrid DL ( P = 0.02) and 22.9% (15.9 to 29.6) by the Tyrer-Cuzick model ( P < 0.001).

Development and pilot of an online, personalized risk assessment tool for a breast cancer precision medicine trial

Breast cancer risk reduction has been validated by large-scale clinical trials, but uptake remains low. A risk communication tool could provide personalized risk-reduction information for high-risk women. A low-literacy-friendly, visual, and personalized tool was designed as part of the Women Informed to Screen Depending On Measures of risk (WISDOM) study. The tool integrates genetic, polygenic, and lifestyle factors, and quantifies the risk-reduction from undertaking medication and lifestyle interventions. The development and design process utilized feedback from clinicians, decision-making scientists, software engineers, and patient advocates. We piloted the tool with 17 study participants, collecting quantitative and qualitative feedback. Overall, participants felt they better understood their personalized breast cancer risk, were motivated to reduce their risk, and considered lifestyle interventions. The tool will be used to evaluate whether risk-based screening leads to more informed decisions and higher uptake of risk-reduction interventions among those most likely to benefit.

Making Sense of Genetic Information: The Promising Evolution of Clinical Stratification and Precision Oncology Using Machine Learning

Precision medicine is a medical approach to administer patients with a tailored dose of treatment by taking into consideration a person's variability in genes, environment, and lifestyles. The accumulation of omics big sequence data led to the development of various genetic databases on which clinical stratification of high-risk populations may be conducted. In addition, because cancers are generally caused by tumor-specific mutations, large-scale systematic identification of single nucleotide polymorphisms (SNPs) in various tumors has propelled significant progress of tailored treatments of tumors (i.e., precision oncology). Machine learning (ML), a subfield of artificial intelligence in which computers learn through experience, has a great potential to be used in precision oncology chiefly to help physicians make diagnostic decisions based on tumor images. A promising venue of ML in precision oncology is the integration of all available data from images to multi-omics big data for the holistic care of patients and high-risk healthy subjects. In this review, we provide a focused overview of precision oncology and ML with attention to breast cancer and glioma as well as the Bayesian networks that have the flexibility and the ability to work with incomplete information. We also introduce some state-of-the-art attempts to use and incorporate ML and genetic information in precision oncology.

Screening High-Risk Women Veterans for Breast Cancer

BACKGROUND

Within the US Department of Veterans Affairs (VA), breast cancer prevalence has more than tripled from 1995 to 2012. Women veterans may be at an increased breast cancer risk based on service-related exposures and posttraumatic stress disorder (PTSD).

METHODS

Women veterans aged ≥ 35 years with no personal history of breast cancer were enrolled at 2 urban VA medical centers. We surveyed women veterans for 5-year and lifetime risks of invasive breast cancer using the Gail Breast Cancer Risk Assessment Tool (BCRAT). Data regarding demographics, PTSD status, eligibility for chemoprevention, and genetic counseling were also collected. Descriptive statistics were used to determine results.

RESULTS

A total of 99 women veterans participated, of which 60% were Black. In total, 35% were high risk with a 5-year BCRAT > 1.66%. Breast biopsies had been performed in 22% of our entire population; 57% had a family history positive for breast cancer. Comparatively, in our high-risk Black population, 33% had breast biopsies and 94% had a family history. High-risk patients were referred for chemoprevention; 5 accepted and 13 were referred for genetic counseling. PTSD was present in 31% of the high-risk subgroup.

CONCLUSIONS

A high percentage of Black patients participated in this pilot study, which also showed an above average rate of PTSD among women veterans who are at high risk for developing breast cancer. Historically, breast cancer rates among Black women are lower than those found in the general population. High participation among Black women veterans in this pilot study uncovered the potential for further study of this population, which is otherwise underrepresented in research. Limitations included a small sample size, exclusively urban population, and self-selection for screening. Future directions include the evaluation of genetic and molecular mutations in high risk Black women veterans, possibly even a role for PTSD epigenetic changes.

Assessing Risk of Breast Cancer: A Review of Risk Prediction Models

Accurate and individualized breast cancer risk assessment can be used to guide personalized screening and prevention recommendations. Existing risk prediction models use genetic and nongenetic risk factors to provide an estimate of a woman's breast cancer risk and/or the likelihood that she has a BRCA1 or BRCA2 mutation. Each model is best suited for specific clinical scenarios and may have limited applicability in certain types of patients. For example, the Breast Cancer Risk Assessment Tool, which identifies women who would benefit from chemoprevention, is readily accessible and user-friendly but cannot be used in women under 35 years of age or those with prior breast cancer or lobular carcinoma in situ. Emerging research on deep learning-based artificial intelligence (AI) models suggests that mammographic images contain risk indicators that could be used to strengthen existing risk prediction models. This article reviews breast cancer risk factors, describes the appropriate use, strengths, and limitations of each risk prediction model, and discusses the emerging role of AI for risk assessment.

A streamlined model for use in clinical breast cancer risk assessment maintains predictive power and is further improved with inclusion of a polygenic risk score

Five-year absolute breast cancer risk prediction models are required to comply with national guidelines regarding risk reduction regimens. Models including the Gail model are under-utilized in the general population for various reasons, including difficulty in accurately completing some clinical fields. The purpose of this study was to determine if a streamlined risk model could be designed without substantial loss in performance. Only the clinical risk factors that were easily answered by women will be retained and combined with an objective validated polygenic risk score (PRS) to ultimately improve overall compliance with professional recommendations. We first undertook a review of a series of 2,339 Caucasian, African American and Hispanic women from the USA who underwent clinical testing. We first used deidentified test request forms to identify the clinical risk factors that were best answered by women in a clinical setting and then compared the 5-year risks for the full model and the streamlined model in this clinical series. We used OPERA analysis on previously published case-control data from 11,924 Gail model samples to determine clinical risk factors to include in a streamlined model: first degree family history and age that could then be combined with the PRS. Next, to ensure that the addition of PRS to the streamlined model was indeed beneficial, we compared risk stratification using the Streamlined model with and without PRS for the existing case-control datasets comprising 1,313 cases and 10,611 controls of African-American (n = 7421), Caucasian (n = 1155) and Hispanic (n = 3348) women, using the area under the curve to determine model performance. The improvement in risk discrimination from adding the PRS risk score to the Streamlined model was 52%, 46% and 62% for African-American, Caucasian and Hispanic women, respectively, based on changes in log OPERA. There was no statistically significant difference in mean risk scores between the Gail model plus risk PRS compared to the Streamlined model plus PRS. This study demonstrates that validated PRS can be used to streamline a clinical test for primary care practice without diminishing test performance. Importantly, by eliminating risk factors that women find hard to recall or that require obtaining medical records, this model may facilitate increased clinical adoption of 5-year risk breast cancer risk prediction test in keeping with national standards and guidelines for breast cancer risk reduction.

Implementation of Risk-reducing Strategies for Breast Cancer is Long Overdue

Despite strong evidence that it is efficacious, chemoprevention has been underused in eligible women. Reasons offered not to adopt and initiate strategies to reduce the risk of breast cancer include the fear of adverse effects, medication costs, lack of reasonably accurate and feasible methods for assessing an individual's personal risk, and lack of established risk thresholds that maximize benefit and minimize harms. The article by Macdonald and colleagues remind us that the problem of lack of uptake of risk-reducing medications for breast cancer remains a worldwide clinical challenge despite endorsements from national and international organizations that recommend the use of risk-reducing medications for breast cancer with level I evidence. Several strategies are suggested to improve uptake and utilization of safe and effective chemoprevention medications with high therapeutic indices.See related article by Macdonald et al., p. 131.

Oncology Advanced Practitioners and Breast Cancer Prevention

One in eight American women will be diagnosed with breast cancer. Advanced practitioners in oncology can offer risk assessments, counseling, genetic testing, and make both behavioral and pharmacologic recommendations for breast cancer risk reduction. The role of oncology advanced practitioners in conjunction with genetic counselors is key in what is now considered the standard of care. This article will summarize the current state of breast cancer prevention and the role of oncology advanced practitioners.

Impact of Personalized Genetic Breast Cancer Risk Estimation With Polygenic Risk Scores on Preventive Endocrine Therapy Intention and Uptake

Endocrine therapy is underutilized to reduce breast cancer incidence among women at increased risk. Polygenic risk scores (PRSs) assessing 77 breast cancer genetic susceptibility loci personalizes risk estimates. We examined effect of personalized PRS breast cancer risk prediction on intention to take and endocrine therapy uptake among women at increased risk. Eligible participants had a 10-year breast cancer risk ≥5% by Tyrer-Cuzick model [International Breast Cancer Intervention Study (IBIS)] or ≥3.0 % 5-year Gail Model risk with no breast cancer history or hereditary breast cancer syndrome. Breast cancer risk was estimated, endocrine therapy options were discussed, and endocrine therapy intent was assessed at baseline. After genotyping, PRS-updated breast cancer risk estimates, endocrine therapy options, and intent to take endocrine therapy were reassessed; endocrine therapy uptake was assessed during follow-up. From March 2016 to October 2017, 151 patients were enrolled [median (range) age, 56.1 (36.0-76.4 years)]. Median 10-year and lifetime IBIS risks were 7.9% and 25.3%. Inclusion of PRS increased lifetime IBIS breast cancer risk estimates for 81 patients (53.6%) and reduced risk for 70 (46.4%). Of participants with increased breast cancer risk by PRS, 39 (41.9%) had greater intent to take endocrine therapy; of those with decreased breast cancer risk by PRS, 28 (46.7%) had less intent to take endocrine therapy (P < 0.001). On multivariable regression, increased breast cancer risk by PRS was associated with greater intent to take endocrine therapy (P < 0.001). Endocrine therapy uptake was greater among participants with increased breast cancer risk by PRS (53.4%) than with decreased risk (20.9%; P < 0.001). PRS testing influenced intent to take and endocrine therapy uptake. Assessing PRS effect on endocrine therapy adherence is needed.Prevention Relevance: Counseling women at increased breast cancer risk using polygenic risk score (PRS) risk estimates can significantly impact preventive endocrine therapy uptake. Further development of PRS testing to personalize breast cancer risk assessments and endocrine therapy counselling may serve to potentially reduce the incidence of breast cancer in the future.

Tamoxifen Accelerates Endothelial Healing by Targeting ERα in Smooth Muscle Cells

RATIONALE

Tamoxifen prevents the recurrence of breast cancer and is also beneficial against bone demineralization and arterial diseases. It acts as an ER (estrogen receptor) α antagonist in ER-positive breast cancers, whereas it mimics the protective action of 17β-estradiol in other tissues such as arteries. However, the mechanisms of these tissue-specific actions remain unclear.

OBJECTIVE

Here, we tested whether tamoxifen is able to accelerate endothelial healing and analyzed the underlying mechanisms.

METHODS AND RESULTS

Using 3 complementary mouse models of carotid artery injury, we demonstrated that both tamoxifen and estradiol accelerated endothelial healing, but only tamoxifen required the presence of the underlying medial smooth muscle cells. Chronic treatment with 17β-estradiol and tamoxifen elicited differential gene expression profiles in the carotid artery. The use of transgenic mouse models targeting either whole ERα in a cell-specific manner or ERα subfunctions (membrane/extranuclear versus genomic/transcriptional) demonstrated that 17β-estradiol-induced acceleration of endothelial healing is mediated by membrane ERα in endothelial cells, while the effect of tamoxifen is mediated by the nuclear actions of ERα in smooth muscle cells.

CONCLUSIONS

Whereas tamoxifen acts as an antiestrogen and ERα antagonist in breast cancer but also on the membrane ERα of endothelial cells, it accelerates endothelial healing through activation of nuclear ERα in smooth muscle cells, inviting to revisit the mechanisms of action of selective modulation of ERα.

Shared decision making in breast cancer treatment guidelines: Development of a quality assessment tool and a systematic review

BACKGROUND

It is not clear whether clinical practice guidelines (CPGs) and consensus statements (CSs) are adequately promoting shared decision making (SDM).

OBJECTIVE

To evaluate the recommendations about SDM in CPGs and CSs concerning breast cancer (BC) treatment.

SEARCH STRATEGY

Following protocol registration (Prospero no.: CRD42018106643), CPGs and CSs on BC treatment were identified, without language restrictions, through systematic search of bibliographic databases (MEDLINE, EMBASE, Web of Science, Scopus, CDSR) and online sources (12 guideline databases and 51 professional society websites) from January 2010 to December 2019.

INCLUSION CRITERIA

CPGs and CSs on BC treatment were selected whether published in a journal or in an online document.

DATA EXTRACTION AND SYNTHESIS

A 31-item SDM quality assessment tool was developed and used to extract data in duplicate.

MAIN RESULTS

There were 167 relevant CPGs (139) and CSs (28); SDM was reported in only 40% of the studies. SDM was reported more often in recent publications after 2015 (42/101 (41.6 %) vs 46/66 (69.7 %), P = .0003) but less often in medical journal publications (44/101 (43.5 %) vs 17/66 (25.7 %), P = .009). In CPGs and CSs with SDM, only 8/66 (12%) met one-fifth (6 of 31) of the quality items; only 14/66 (8%) provided clear and precise SDM recommendations.

DISCUSSION AND CONCLUSIONS

SDM descriptions and recommendations in CPGs and CSs concerning BC treatment need improvement. SDM was more frequently reported in CPGs and CSs in recent years, but surprisingly it was less often covered in medical journals, a feature that needs attention.

A Pre-Test-Post-Test Trial of a Breast Cancer Risk Report for Women in Their 40s

INTRODUCTION

Guidelines recommend individualized breast cancer screening and prevention interventions for women in their 40s. Yet, few primary care clinicians assess breast cancer risk.

STUDY DESIGN

Pretest-Posttest trial.

SETTING/PARTICIPANTS

Women aged 40-49 years were recruited from one large Boston-based academic primary care practice between July 2017 and April 2019.

INTERVENTION

Participants completed a pretest, received a personalized breast cancer risk report, saw their primary care clinician, and completed a posttest.

MAIN OUTCOME MEASURES

Using mixed effects models, changes in screening intentions (0-100 scale [0=will not screen to 100=will screen]), mammography knowledge, decisional conflict, and receipt of screening were examined. Analyses were conducted from June 2019 to February 2020.

RESULTS

Patient (n=337) mean age was 44.1 (SD=2.9) years, 61.4% were non-Hispanic white, and 76.6% were college graduates; 306 (90.5%) completed follow-up (203 with 5-year breast cancer risk <1.1%). Screening intentions declined from pre- to post-visit (79.3 to 68.0, p<0.0001), especially for women with 5-year risk <1.1% (77.2 to 63.3, p<0.0001), but still favored screening. In the 2 years prior, 37.6% had screening mammography compared with 41.8% over a mean 16 months follow-up (p=0.17). Mammography knowledge increased and decisional conflict declined. Eleven (3.3%) women met criteria for breast cancer prevention medications (ten discussed medications with their clinicians), 22 (6.5%) for MRI (19 discussed MRI with their clinician), and 67 (19.8%) for genetic counseling (47 discussed with the clinician).

CONCLUSIONS

Receipt of a personalized breast cancer report was associated with women in their 40s making more-informed and less-conflicted mammography screening decisions and with high-risk women discussing breast cancer prevention interventions with clinicians.

TRIAL REGISTRATION

This study is registered at www.clinicaltrials.govNCT03180086.

Risk for breast cancer and management of unaffected individuals with non-BRCA hereditary breast cancer

About 5%-10% of breast cancer is hereditary with BRCA1 and BRCA2 being the most common genes associated with hereditary breast cancer (HBC). Several additional genes have recently been associated with HBC. These genes can be classified as highly or moderately penetrant genes with lifetime risk >30% or 17%-30%, respectively. Highly penetrant genes associated with HBC include TP53, PTEN, CDH1, STK11, and PALB2. While, moderately penetrant genes include CHEK2, ATM, BARD1, BRIP1, NBN, NF1, RAD51D, and MSH6. Breast cancer risk and recommendations for screening and risk-reduction vary by gene. In general, screening breast MRI is recommended for women at >20% lifetime risk, which includes women with mutations in highly penetrant genes and the majority (but not all) moderately penetrant genes. Consideration of chemoprevention is recommended for women with mutations in high and moderately penetrant genes. Risk-reducing mastectomy does reduce the risk of breast cancer to the greatest extent and can be considered for women with highly penetrant genes. However, this procedure is associated with significant morbidities that should be considered, especially given the benefit of using screening breast MRI for high-risk women. BSO is only recommended for women with mutations in genes associate with increased risk for ovarian cancer and not as a breast cancer risk-reducing strategy. As more women undergo testing, additional genes may be identified and risk estimates for current genes and management recommendations may be modified.

Estimating the magnitude of clinical benefit of systemic therapy in patients with DCIS or pre-invasive disease of the breast

The challenge of effective management of ductal carcinoma in situ (DCIS) and other pre-malignant disorders of the breast is to select patients who will not progress to invasive carcinoma from those at the highest risk who require radiotherapy and/or endocrine therapy to minimize the risk of a subsequent invasive recurrence. Although IBIS-II and NSABP-B35 DCIS phase III trials proved that tamoxifen 20 mg/day and anastrozole reduce the risk of ipsilateral and contralateral events, the toxicities of both drugs have hampered the drug uptake by high-risk women. We recently reported results of a 3-year placebo-controlled trial of low-dose (5 mg/d) tamoxifen in 500 women with intraepithelial neoplasia (70% DCIS). At a median follow-up of 5 years, women randomly assigned to low-dose tamoxifen had half the number of subsequent diagnoses of DCIS or invasive cancer compared with those randomly assigned to placebo but no increase in thromboembolic events or endometrial cancers. The 5-year number needed to treat was 22 (95% CI, 20-27). Our attention is now focused on prognostic and predictive markers to identify patients who can derive the greatest benefits from low dose tamoxifen, such as for instance the expression of 23 genes involved in cell cycle progression (CCP). In conclusion, we endorse an active treatment of DCIS as the standard of care.

Disparities in Risk Reduction Therapy Recommendations for Young Women With Lobular Carcinoma In-Situ

BACKGROUND

Endocrine therapy (ET) significantly reduces the risk of breast cancer development in high-risk patients diagnosed with lobular carcinoma in situ (LCIS). However, the variables impacting recommendation and use of ET in young adults (YAs) is not well-studied. We examined the role of provider recommendation and patient acceptance for ET for YAs with LCIS.

MATERIALS AND METHODS

The National Cancer Database was queried for women aged < 40 years with primary LCIS between 2000 and 2012. Socioeconomic, demographic, and treatment variables were examined to determine their impact on ET provider recommendation and initial patient acceptance of risk-reducing therapy.

RESULTS

Among 1650 YA patients with LCIS, only 749 (45.4%) were recommended ET. On multivariable analysis, women > 30 years of age were more likely recommended ET than women < 30 years (odds ratio [OR], 1.64; 95% confidence interval [CI], 1.10-2.47), African Americans more than other ethnicities (OR, 1.48; 95% CI, 1.1-2.0), and YAs treated in New England were more likely than those in the rest of the country (OR, 3.26; 95% CI, 2.0-5.2). Among YA women recommended ET, only 20.2% had a documented refusal. Only geography appeared to independently impact the likelihood of refusal, with YAs in the Southeastern-Central United States being most likely to refuse ET (OR, 5.4; 95% CI, 1.2-24.0).

CONCLUSION

ET is underutilized for risk-reduction in YAs with LCIS. This underuse appears dependent on disparities in provider recommendation practices rather than non-acceptance of therapy. This may reflect regional practice patterns, community standards of care, or provider bias regarding the significance of LCIS as a risk factor for development of invasive cancer.

Breast cancer risk reduction: Notable achievements and remaining challenges

Millions of women in the United States are at increased risk of breast cancer. Multiple prospective, randomized clinical trials have demonstrated both the efficacy and safety of selective estrogen receptor modulators and aromatase inhibitors in reducing substantially the risk of invasive breast cancer in women at increased risk. Published tables are available to aid clinicians in shared decision-making regarding drug interventions with their patients who are at increased risk of breast cancer. Both professional and governmental agencies have advised that these interventions should be offered to women at increased risk of breast cancer. Doing so would reduce breast cancer morbidity substantially.

Atypical Ductal Hyperplasia and Lobular Neoplasia: Update and Easing of Guidelines

OBJECTIVE. Atypical ductal hyperplasia (ADH), atypical lobular hyperplasia (ALH), and lobular carcinoma in situ (LCIS) are among high-risk lesions that have been previously recommended for surgical excision when diagnosed on core needle biopsy. Recent studies have examined whether imaging surveillance is a reasonable alternative to surgical management for these lesions. This article synthesizes the evidence regarding management of atypical hyperplasia and LCIS diagnosed on core needle biopsy and clinical implications of these diagnoses on future breast cancer risk as well as highlights areas of further research needed to improve practice guidelines for these high-risk lesions. CONCLUSION. Although surgical excision is still recommended after diagnosis of ADH on core needle biopsy, in specific circumstances ALH and LCIS can safely be managed by imaging surveillance.

Breast cancer chemoprevention: An update on current practice and opportunities for primary care physicians

Several risk assessment models have been validated for the estimation of risk of breast cancer in women. Chemoprevention through hormonal therapy is an effective way to reduce the incidence of breast cancer in women with high risk. Selective estrogen receptor modulators, tamoxifen and raloxifene, are approved for this indication by the United States Food and Drug Administration, and aromatase inhibitors have also shown promise in recent studies. These medications are generally well tolerated, except for reported increased rates of fractures and venous thromboembolic events. Despite strong recommendations from several regulatory bodies, advocacy for chemoprevention has been inadequate in practice, more so among the primary care physicians. Studies have identified several barriers in physicians, patients, and the system, contributing to this problem. Lack of knowledge about risk assessment models and chemoprevention options preclude physicians from prescribing these medications with confidence. Fear of potential adverse events, confusion regarding the purpose of the therapy, and need for continued adherence for five years are among the principal reasons for reduced chemoprevention uptake and early discontinuation among patients. Multifaceted interventions directed at education and training of health care professionals, proper counseling of women at high risk, and promotion of the development of improved medications might help ensure better chemoprevention uptake in the target population.

Breast cancer prevention in high-risk women

Women at high risk of developing breast cancer are a heterogeneous group of women including those with and without high-risk germline mutation/s. Prevention in these women requires a personalised and multidisciplinary approach. Preventive therapy with selective oestrogen receptor modulators (SERMs) like tamoxifen and aromatase inhibitors (AIs) substantially reduces breast cancer risk well beyond the active treatment period. The importance of benign breast disease as a marker of increased breast cancer risk remains underappreciated, and although the benefit of preventive therapy may be greater in such women, preventive therapy remains underutilised in these and other high-risk women. Bilateral Risk-Reducing Mastectomy (BRRM) reduces the risk of developing breast cancer by 90% in high-risk women such as carriers of BRCA mutations. It also improves breast cancer-specific survival in BRCA1 carriers. Bilateral risk-reducing salpingo-oophorectomy may also reduce risk in premenopausal BRCA2 carriers. Further research to improve risk models, to identify surrogate biomarkers of preventive therapy benefit and to develop newer preventive agents is needed.

Use of Endocrine Therapy for Breast Cancer Risk Reduction: ASCO Clinical Practice Guideline Update

PURPOSE

To update the ASCO guideline on pharmacologic interventions for breast cancer risk reduction and provide guidance on clinical issues that arise when deciding to use endocrine therapy for breast cancer risk reduction.

METHODS

An Expert Panel conducted targeted systematic literature reviews to identify new studies.

RESULTS

A randomized clinical trial that evaluated the use of anastrozole for reduction of estrogen receptor–positive breast cancers in postmenopausal women at increased risk of developing breast cancer provided the predominant basis for the update.

UPDATED RECOMMENDATIONS

In postmenopausal women at increased risk, the choice of endocrine therapy now includes anastrozole (1 mg/day) in addition to exemestane (25 mg/day), raloxifene (60 mg/day), or tamoxifen (20 mg/day). The decision regarding choice of endocrine therapy should take into consideration age, baseline comorbidities, and adverse effect profiles. Clinicians should not prescribe anastrozole, exemestane, or raloxifene for breast cancer risk reduction to premenopausal women. Tamoxifen 20 mg/day for 5 years is still considered standard of care for risk reduction in premenopausal women who are at least 35 years old and have completed childbearing. Data on low-dose tamoxifen as an alternative to the standard dose for both pre- and postmenopausal women with intraepithelial neoplasia are discussed in the Clinical Considerations section of this article. Additional information is available at www.asco.org/breast-cancer-guidelines .