Assessment of the accuracy of the Gail model in women with atypical hyperplasia

Following the High-Risk Patient: Breast Cancer Risk-Based Screening

Breast cancer (BC) is the most common cancer occurring in women in the USA today, and accounts for more than 40,000 deaths annually (Giaquinto in CA Cancer J Clin 72: 524-541, 2022). While breast cancer survival has improved over the past decades, incidence has increased, and diagnoses are being made at younger ages. This emphasizes the importance of risk evaluation, accurate prediction, and effective mitigation and risk reduction strategies. Enhanced screening can help detect cancers at an earlier stage, thus improving morbidity and mortality. This review addresses the recognition of women at high-risk for BC and monitoring strategies for those at high risk.

Role of Breast Cancer Risk Estimation Models to Identify Women Eligible for Genetic Testing and Risk-Reducing Surgery

Hereditary breast and ovarian cancer (HBOC) syndrome is responsible for approximately 10% of breast cancers (BCs). The HBOC gene panel includes both high-risk genes, i.e., a four times higher risk of BC (BRCA1, BRCA2, PALB2, CDH1, PTEN, STK11 and TP53), and moderate-risk genes, i.e., a two to four times higher risk of BC (BARD1, CHEK2, RAD51C, RAD51D and ATM). Pathogenic germline variants (PGVs) in HBOC genes confer an absolute risk of BC that changes according to the gene considered. We illustrate and compare different BC risk estimation models, also describing their limitations. These models allow us to identify women eligible for genetic testing and possibly to offer surgical strategies for primary prevention, i.e., risk-reducing mastectomies and salpingo-oophorectomies.

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.

Individualizing Breast Cancer Risk Assessment in Clinical Practice

Multiple tools exist to assess a patient's breast cancer risk. The choice of risk model depends on the patient's risk factors and how the calculation will impact care. High-risk patients-those with a lifetime breast cancer risk of ≥20%-are, for instance, eligible for supplemental screening with breast magnetic resonance imaging. Those with an elevated short-term breast cancer risk (frequently defined as a 5-year risk ≥1.66%) should be offered endocrine prophylaxis. High-risk patients should also receive guidance on modification of lifestyle factors that affect breast cancer risk.

Expression-Based Diagnosis, Treatment Selection, and Drug Development for Breast Cancer

There is currently no gene expression assay that can assess if premalignant lesions will develop into invasive breast cancer. This study sought to identify biomarkers for selecting patients with a high potential for developing invasive carcinoma in the breast with normal histology, benign lesions, or premalignant lesions. A set of 26-gene mRNA expression profiles were used to identify invasive ductal carcinomas from histologically normal tissue and benign lesions and to select those with a higher potential for future cancer development (ADHC) in the breast associated with atypical ductal hyperplasia (ADH). The expression-defined model achieved an overall accuracy of 94.05% (AUC = 0.96) in classifying invasive ductal carcinomas from histologically normal tissue and benign lesions (n = 185). This gene signature classified cancer development in ADH tissues with an overall accuracy of 100% (n = 8). The mRNA expression patterns of these 26 genes were validated using RT-PCR analyses of independent tissue samples (n = 77) and blood samples (n = 48). The protein expression of PBX2 and RAD52 assessed with immunohistochemistry were prognostic of breast cancer survival outcomes. This signature provided significant prognostic stratification in The Cancer Genome Atlas breast cancer patients (n = 1100), as well as basal-like and luminal A subtypes, and was associated with distinct immune infiltration and activities. The mRNA and protein expression of the 26 genes was associated with sensitivity or resistance to 18 NCCN-recommended drugs for treating breast cancer. Eleven genes had significant proliferative potential in CRISPR-Cas9/RNAi screening. Based on this gene expression signature, the VEGFR inhibitor ZM-306416 was discovered as a new drug for treating breast cancer.

Screening MRI Does Not Increase Cancer Detection or Result in an Earlier Stage at Diagnosis for Patients with High-Risk Breast Lesions: A Propensity Score Analysis

BACKGROUND

Guidelines recommend consideration of screening MRI for patients with high-risk breast lesions (HRLs), acknowledging limited data for this moderate-risk population.

METHODS

This study identified patients with atypical ductal/lobular hyperplasia (ADH/ALH), lobular carcinoma in situ, (LCIS) or both evaluated at our high-risk clinic. Patients were categorized as having received screening mammography (MMG) alone vs. MMG and breast MRI (MMG+MRI). Inverse probability weighting based on propensity scores (PS) representing likelihood of MRI use was applied to Kaplan-Meier and Cox regression analyses to determine cancer detection and biopsy rates by screening group.

RESULTS

Among 908 eligible patients, 699 (77%) patients with available follow-up data were analyzed (542 with ADH/ALH and 157 with LCIS). Of the 699 patients, 540 (77%) received MMG alone, and 159 (23%) received MMG + MRI. The median follow-up period was 25 months, during which a median of two MRIs were performed. After PS-weighting, the characteristics of each screening group were well-balanced with respect to age, race, body mass index (BMI), menopausal status, breast density, family history, HRL type, and chemoprevention use. The 4 year breast cancer detection rate was 3.6% with both MMG alone and MMG+MRI (p = 0.89). The breast biopsy rates were significantly higher with MMG+MRI (30.5% vs12.6%; hazard ratio [HR], 2.67; p < 0.001). All breast cancers were clinically node-negative and pathologic stage 0 or 1. Among five cancers in the MMG+MRI group, two were MRI-detected, two were MMG-detected, and one was detected on clinical exam.

CONCLUSIONS

Screening MRI did not improve cancer detection, and cancer characteristics were favorable whether screened with MMG alone or MMG + MRI. These findings question the benefit of MRI for patients with HRL, although longer-term follow-up study is needed.

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.

Risk management recommendations and patient acceptance vary with high-risk breast lesions

INTRODUCTION

Lobular carcinoma in situ (LCIS), atypical ductal and lobular hyperplasia (AH) increase breast cancer risk. We examined risk management recommendations (RMR) and acceptance in AH/LCIS.

METHODS

All patients with AH/LCIS on core needle biopsy from 2013 to 2016 at our institution were identified; cancer patients were excluded. Univariate and multivariate analysis examined factors associated with management.

RESULTS

98 % of patients were evaluated by breast surgeons and 53 % underwent risk model calculation (RC). 77 % had new RMR. RMR of MRI screening (MRI), genetic counselling (GC) and medical oncology (MO) referral were 41 %, 18 %, 77 %, respectively. MRI screening was more likely recommended in those with strong family history (p = 0.01), and high RC (p < 0.001). Uptake of at least one RMR did not occur in 84 % of patients. Use of RC correlated with MO acceptance (p = 0.049).

CONCLUSIONS

Diagnosis of atypia has the potential to change risk management for most, however only 16 % of patients accepted all RMR.

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.

Somatic genetic aberrations in benign breast disease and the risk of subsequent breast cancer

It is largely unknown how the development of breast cancer (BC) is transduced by somatic genetic alterations in the benign breast. Since benign breast disease is an established risk factor for BC, we established a case-control study of women with a history of benign breast biopsy (BBB). Cases developed BC at least one year after BBB and controls did not develop BC over an average of 17 years following BBB. 135 cases were matched to 69 controls by age and type of benign change: non-proliferative or proliferation without atypia (PDWA). Whole-exome sequencing (WES) was performed for the BBB. Germline DNA (available from n = 26 participants) was utilized to develop a mutation-calling pipeline, to allow differentiation of somatic from germline variants. Among the 204 subjects, two known mutational signatures were identified, along with a currently uncatalogued signature that was significantly associated with triple negative BC (TNBC) (p = 0.007). The uncatalogued mutational signature was validated in 109 TNBCs from TCGA (p = 0.001). Compared to non-proliferative samples, PDWA harbors more abundant mutations at PIK3CA pH1047R (p < 0.001). Among the 26 BBB whose somatic copy number variation could be assessed, deletion of MLH3 is significantly associated with the mismatch repair mutational signature (p < 0.001). Matched BBB-cancer pairs were available for ten cases; several mutations were shared between BBB and cancers. This initial study of WES of BBB shows its potential for the identification of genetic alterations that portend breast oncogenesis. In future larger studies, robust personalized breast cancer risk indicators leading to novel interception paradigms can be assessed.

Prospective Analysis Using a Novel CNN Algorithm to Distinguish Atypical Ductal Hyperplasia From Ductal Carcinoma in Situ in Breast

INTRODUCTION

We previously developed a convolutional neural networks (CNN)-based algorithm to distinguish atypical ductal hyperplasia (ADH) from ductal carcinoma in situ (DCIS) using a mammographic dataset. The purpose of this study is to further validate our CNN algorithm by prospectively analyzing an unseen new dataset to evaluate the diagnostic performance of our algorithm.

MATERIALS AND METHODS

In this institutional review board-approved study, a new dataset composed of 280 unique mammographic images from 140 patients was used to test our CNN algorithm. All patients underwent stereotactic-guided biopsy of calcifications and underwent surgical excision with available final pathology. The ADH group consisted of 122 images from 61 patients with the highest pathology diagnosis of ADH. The DCIS group consisted of 158 images from 79 patients with the highest pathology diagnosis of DCIS. Two standard mammographic magnification views (craniocaudal and mediolateral/lateromedial) of the calcifications were used for analysis. Calcifications were segmented using an open source software platform 3D slicer and resized to fit a 128 × 128 pixel bounding box. Our previously developed CNN algorithm was used. Briefly, a 15 hidden layer topology was used. The network architecture contained 5 residual layers and dropout of 0.25 after each convolution. Diagnostic performance metrics were analyzed including sensitivity, specificity, accuracy, and area under the receiver operating characteristic curve. The "positive class" was defined as the pure ADH group in this study and thus specificity represents minimizing the amount of falsely labeled pure ADH cases.

RESULTS

Area under the receiver operating characteristic curve was 0.90 (95% confidence interval, ± 0.04). Diagnostic accuracy, sensitivity, and specificity was 80.7%, 63.9%, and 93.7%, respectively.

CONCLUSION

Prospectively tested on new unseen data, our CNN algorithm distinguished pure ADH from DCIS using mammographic images with high specificity.

Assessment of common risk factors and validation of the Gail model for breast cancer: A hospital-based study from Western India

Objective

Modified Gail Model is a noninvasive, easy to implement risk estimation tool for absolute breast cancer risk. It was developed with data collected from non African American females and further modified for African-American, the Hispanic, and Native American populations. The use of this model for population outside the US and European country is not yet validated. We evaluated the prevalent risk factors and the effectiveness of the Gail model for risk assessment in our local Indian population.

Materials and Methods

A retrospective analysis of a prospectively maintained database was conducted on patients treated between 2008 and 2013. Six hundred and fifty patients were included in each group. Six questions were taken as per the breast cancer risk assessment tool calculator. A value of over 1.67% was taken as a high risk for breast cancer development.

Results

The mean age of the participant was 50 ± 21.3 years in cases and 41 ± 16.4 years in controls. Age and age at first childbirth >30 years were found to be significant and associated with increased risk of breast carcinoma, but the age at menarche, family history, previous breast biopsy, and atypical hyperplasia was no significant. The Gail model was assessed, and sensitivity was 10.30% and 96.30% specificity for our population. Positive and negative predictive values were 73.62% and 51.77%.

Conclusion

Our study concluded that the Gail model is not an appropriate risk assessment tool for the population in its present form. For the future application of this model, we need to perform a bigger study with a higher sample size representing a maximum number of local variabilities in the Indian population.

Importance of family history and indications for genetic testing

Family history is an important cancer risk assessment tool, and it is easy to use. The family history is integral in identifying an individual's risk for primary cancer and assists in the assessment of risk for a second primary cancer. For oncology providers, the critical family history is defined as including first- and second-degree family history, maternal and paternal history, type of primary cancer, and age at diagnosis and ethnicity. Family history should be taken at diagnosis and updated periodically. Despite the importance of family history to patient care, there are significant barriers to taking a family history. We review the impact of collecting complete family history data with respect to calculation of cancer risk, recommendations for screening, and prevention strategies and referral for genetic testing.

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.

Breast cancer risk prediction in women aged 35-50 years: impact of including sex hormone concentrations in the Gail model

Background

Models that accurately predict risk of breast cancer are needed to help younger women make decisions about when to begin screening. Premenopausal concentrations of circulating anti-Müllerian hormone (AMH), a biomarker of ovarian reserve, and testosterone have been positively associated with breast cancer risk in prospective studies. We assessed whether adding AMH and/or testosterone to the Gail model improves its prediction performance for women aged 35–50.

Methods

In a nested case-control study including ten prospective cohorts (1762 invasive cases/1890 matched controls) with pre-diagnostic serum/plasma samples, we estimated relative risks (RR) for the biomarkers and Gail risk factors using conditional logistic regression and random-effects meta-analysis. Absolute risk models were developed using these RR estimates, attributable risk fractions calculated using the distributions of the risk factors in the cases from the consortium, and population-based incidence and mortality rates. The area under the receiver operating characteristic curve (AUC) was used to compare the discriminatory accuracy of the models with and without biomarkers.

Results

The AUC for invasive breast cancer including only the Gail risk factor variables was 55.3 (95% CI 53.4, 57.1). The AUC increased moderately with the addition of AMH (AUC 57.6, 95% CI 55.7, 59.5), testosterone (AUC 56.2, 95% CI 54.4, 58.1), or both (AUC 58.1, 95% CI 56.2, 59.9). The largest AUC improvement (4.0) was among women without a family history of breast cancer.

Conclusions

AMH and testosterone moderately increase the discriminatory accuracy of the Gail model among women aged 35–50. We observed the largest AUC increase for women without a family history of breast cancer, the group that would benefit most from improved risk prediction because early screening is already recommended for women with a family history.

Electronic supplementary material

The online version of this article (10.1186/s13058-019-1126-z) contains supplementary material, which is available to authorized users.

Accuracy of Distinguishing Atypical Ductal Hyperplasia From Ductal Carcinoma In Situ With Convolutional Neural Network-Based Machine Learning Approach Using Mammographic Image Data

OBJECTIVE. The purpose of this study was to test the hypothesis that convolutional neural networks can be used to predict which patients with pure atypical ductal hyperplasia (ADH) may be safely monitored rather than undergo surgery. MATERIALS AND METHODS. A total of 298 unique images from 149 patients were used for our convolutional neural network algorithm. A total of 134 images from 67 patients with ADH that had been diagnosed by stereotactic-guided biopsy of calcifications but had not been upgraded to ductal carcinoma in situ or invasive cancer at the time of surgical excision. A total of 164 images from 82 patients with mammographic calcifications indicated that ductal carcinoma in situ was the final diagnosis. Two standard mammographic magnification views of the calcifications (a craniocaudal view and a mediolateral or lateromedial view) were used for analysis. Calcifications were segmented using an open-source software platform and images were resized to fit a bounding box of 128 × 128 pixels. A topology with 15 hidden layers was used to implement the convolutional neural network. The network architecture contained five residual layers and dropout of 0.25 after each convolution. Patients were randomly separated into a training-and-validation set (80% of patients) and a test set (20% of patients). Code was implemented using open-source software on a workstation with an open-source operating system and a graphics card. RESULTS. The AUC value was 0.86 (95% CI, ± 0.03) for the test set. Aggregate sensitivity and specificity were 84.6% (95% CI, ± 4.0%) and 88.2% (95% CI, ± 3.0%), respectively. Diagnostic accuracy was 86.7% (95% CI, ± 2.9). CONCLUSION. It is feasible to apply convolutional neural networks to distinguish pure atypical ductal hyperplasia from ductal carcinoma in situ with the use of mammographic images. A larger dataset will likely result in further improvement of our prediction model.

Risk factors associated with gastric cancer in Mexico: education, breakfast and chili

BACKGROUND AND AIM

the aim of the study was to use a validated questionnaire to identify factors associated with the development of gastric cancer (GC) in the Mexican population.

METHODS

the study included cases and controls that were paired by sex and ± 10 years of age at diagnosis. In relation to cases, 46 patients with a confirmed histopathological diagnosis of adenocarcinoma-type GC, as reported in the hospital records, were selected, and 46 blood bank donors from the same hospital were included as controls. The previously validated Questionnaire to Find Factors Associated with Gastric Cancer (QUFA-GC©) was used to collect data. Odds ratio (OR) and 95% confidence interval (IC) were estimated via univariate analysis (paired OR). Multivariate analysis was performed by logistic regression. A decision tree was constructed using the J48 algorithm.

RESULTS

an association was found by univariate analysis between GC risk and a lack of formal education, having smoked for ≥ 10 years, eating rapidly, consuming very hot food and drinks, a non-suitable breakfast within two hours of waking, pickled food and capsaicin. In contrast, a protective association against GC was found with taking recreational exercise and consuming fresh fruit and vegetables. No association was found between the development of GC and having an income that reflected poverty, using a refrigerator, perception of the omission of breakfast and time period of alcoholism. In the final multivariate analysis model, having no formal education (OR = 17.47, 95% CI = 5.17-76.69), consuming a non-suitable breakfast within two hours of waking (OR = 8.99, 95% CI = 2.85-35.50) and the consumption of capsaicin ˃ 29.9 mg capsaicin per day (OR = 3.77, 95% CI = 1.21-13.11) were factors associated with GC.

CONCLUSIONS

an association was found by multivariate analysis between the presence of GC and education, type of breakfast and the consumption of capsaicin. These variables are susceptible to intervention and can be identified via the QUFA-GC

Evaluation of 2 breast cancer risk models in a benign breast disease cohort

BACKGROUND

More than 1.5 million women per year have a benign breast biopsy resulting in concern about their future breast cancer (BC) risk. This study examined the performance of 2 BC risk models that integrate clinical and histologic findings in this population.

METHODS

The BC risk at 5 and 10 years was estimated with the Breast Cancer Surveillance Consortium (BCSC) and Benign Breast Disease to Breast Cancer (BBD-BC) models for women diagnosed with benign breast disease (BBD) at the Mayo Clinic from 1997 to 2001. Women with BBD were eligible for the BBD-BC model, but the BCSC model also required a screening mammogram. Calibration and discrimination were assessed.

RESULTS

Fifty-six cases of BC were diagnosed among the 2142 women with BBD (median age, 50 years) within 5 years (118 were diagnosed within 10 years). The BBD-BC model had slightly better calibration at 5 years (0.89; 95% confidence interval [CI], 0.71-1.21) versus 10 years (0.81; 95% CI, 0.70-1.00) but similar discrimination in the 2 time periods: 0.68 (95% CI, 0.60-0.75) and 0.66 (95% CI, 0.60-0.71), respectively. In contrast, among the 1089 women with screening mammograms (98 cases of BC within 10 years), the BCSC model had better calibration (0.94; 95% CI, 0.85-1.43) and discrimination (0.63; 95% CI, 0.56-0.71) at 10 years versus 5 years (calibration, 1.31; 95% CI, 0.94-2.25; discrimination, 0.59; 95% CI, 0.46-0.71) where discrimination was not different from chance.

CONCLUSIONS

The BCSC and BBD-BC models were validated in the Mayo BBD cohort, although their performance differed by 5-year risk versus 10-year risk. Further enhancement of these models is needed to provide accurate BC risk estimates for women with BBD.

When Does Atypical Ductal Hyperplasia Require Surgical Excision?

Atypical ductal hyperplasia (ADH) is a proliferative, nonobligate precursor breast lesion and a marker of increased risk for breast carcinoma. Surgical excision remains the standard recommendation following a core needle biopsy result consistent with ADH. Recent research suggests that women with no mass lesion or discordance, removal of greater than or equal to 90% of calcifications at the time of core needle biopsy, involvement of less than or equal to 2 terminal duct lobular units, and absence of cytologic atypia or necrosis are likely to have a less than 5% chance of a missed cancer.

Model for Predicting Breast Cancer Risk in Women With Atypical Hyperplasia

Purpose Women with atypical hyperplasia (AH) on breast biopsy have an aggregate increased risk of breast cancer (BC), but existing risk prediction models do not provide accurate individualized estimates of risk in this subset of high-risk women. Here, we used the Mayo benign breast disease cohort to develop and validate a model of BC risk prediction that is specifically for women with AH, which we have designated as AH-BC. Patients and Methods Retrospective cohorts of women age 18 to 85 years with pathologically confirmed benign AH from Rochester, MN, and Nashville, TN, were used for model development and external validation, respectively. Clinical risk factors and histologic features of the tissue biopsy were selected using L1-penalized Cox proportional hazards regression. Identified features were included in a Fine and Gray regression model to estimate BC risk, with death as a competing risk. Model discrimination and calibration were assessed in the model-building set and an external validation set. Results The model-building set consisted of 699 women with AH, 142 of whom developed BC (median follow-up, 8.1 years), and the external validation set consisted of 461 women with 114 later BC events (median follow-up, 11.4 years). The final AH-BC model included three covariates: age at biopsy, age at biopsy squared, and number of foci of AH. At 10 years, the AH-BC model demonstrated good discrimination (0.63 [95% CI, 0.57 to 0.70]) and calibration (0.87 [95% CI, 0.66 to 1.24]). In the external validation set, the model showed acceptable discrimination (0.59 [95% CI, 0.51 to 0.67]) and calibration (0.91 [95% CI, 0.65 to 1.42]). Conclusion We have created a new model with which to refine BC risk prediction for women with AH. The AH-BC model demonstrates good discrimination and calibration, and it validates in an external data set.

Assessment of performance of the Gail model for predicting breast cancer risk: a systematic review and meta-analysis with trial sequential analysis

BACKGROUND

The Gail model has been widely used and validated with conflicting results. The current study aims to evaluate the performance of different versions of the Gail model by means of systematic review and meta-analysis with trial sequential analysis (TSA).

METHODS

Three systematic review and meta-analyses were conducted. Pooled expected-to-observed (E/O) ratio and pooled area under the curve (AUC) were calculated using the DerSimonian and Laird random-effects model. Pooled sensitivity, specificity and diagnostic odds ratio were evaluated by bivariate mixed-effects model. TSA was also conducted to determine whether the evidence was sufficient and conclusive.

RESULTS

Gail model 1 accurately predicted breast cancer risk in American women (pooled E/O = 1.03; 95% CI 0.76-1.40). The pooled E/O ratios of Caucasian-American Gail model 2 in American, European and Asian women were 0.98 (95% CI 0.91-1.06), 1.07 (95% CI 0.66-1.74) and 2.29 (95% CI 1.95-2.68), respectively. Additionally, Asian-American Gail model 2 overestimated the risk for Asian women about two times (pooled E/O = 1.82; 95% CI 1.31-2.51). TSA showed that evidence in Asian women was sufficient; nonetheless, the results in American and European women need further verification. The pooled AUCs for Gail model 1 in American and European women and Asian females were 0.55 (95% CI 0.53-0.56) and 0.75 (95% CI 0.63-0.88), respectively, and the pooled AUCs of Caucasian-American Gail model 2 for American, Asian and European females were 0.61 (95% CI 0.59-0.63), 0.55 (95% CI 0.52-0.58) and 0.58 (95% CI 0.55-0.62), respectively. The pooled sensitivity, specificity and diagnostic odds ratio of Gail model 1 were 0.63 (95% CI 0.27-0.89), 0.91 (95% CI 0.87-0.94) and 17.38 (95% CI 2.66-113.70), respectively, and the corresponding indexes of Gail model 2 were 0.35 (95% CI 0.17-0.59), 0.86 (95% CI 0.76-0.92) and 3.38 (95% CI 1.40-8.17), respectively.

CONCLUSIONS

The Gail model was more accurate in predicting the incidence of breast cancer in American and European females, while far less useful for individual-level risk prediction. Moreover, the Gail model may overestimate the risk in Asian women and the results were further validated by TSA, which is an addition to the three previous systematic review and meta-analyses.

TRIAL REGISTRATION

PROSPERO CRD42016047215 .

Vacuum assisted breast biopsy (VAB) excision of subcentimeter microcalcifications as an alternative to open biopsy for atypical ductal hyperplasia

OBJECTIVE

Atypical ductal hyperplasia (ADH) is a proliferative lesion associated with a variable increased risk of breast malignancy, but the management of the patients is still not completely defined, with mandatory surgical excision in most cases. To report the results of the conservative management with mammographic checks of patients with ADH diagnosed by vacuum assisted breast biopsy (VAB), without residual calcifications.

METHODS

The authors accessed the institutional database of radiological, surgical and pathological anatomy. Inclusion criteria were: ADH diagnosed by VAB on a single group of microcalcifications, without residual post-procedure; follow-up at least of 12 months. Exclusion criteria were the presence of personal history of breast cancer or other high-risk lesions; association with other synchronous lesions, both more and less advanced proliferative lesions.

RESULTS

The 65 included patients were all females, with age range of 40-79 years (mean 54 years). The maximum diameter range of the groups of microcalcifications was 4-11 mm (mean 6.2 mm), all classified as BI-RADS 4b (Breast Imaging Reporting and Data System 4b) and defined as fine pleomorphic in 29 cases (45%) or amorphous in 36 cases (55%). The range of follow-up length was 12-156 months (mean 67 months). Only one patients developed new microcalcifications, in the same breast, 48 months after and 15 mm from the first VAB, interpreted as low-grade ductal carcinoma in situ (DCIS) at surgical excision.

CONCLUSION

These results could justify the conservative management, in a selected group of patients, being the malignancy rate lower than 2%, considered in the literature as the "probably benign" definition. Advances in knowledge: Increasing the length of follow-up of selected patients conservatively managed can improve the management of ADH cases.

Discovery and replication of microRNAs for breast cancer risk using genome-wide profiling

Background

Genome-wide miRNA expression may be useful for predicting breast cancer risk and/or for the early detection of breast cancer.

Results

A 41-miRNA model distinguished breast cancer risk in the discovery study (accuracy of 83.3%), which was replicated in the independent study (accuracy = 63.4%, P=0.09). Among the 41 miRNA, 20 miRNAs were detectable in serum, and predicted breast cancer occurrence within 18 months of blood draw (accuracy 53%, P=0.06). These risk-related miRNAs were enriched for HER-2 and estrogen-dependent breast cancer signaling.

Materials and Methods

MiRNAs were assessed in two cross-sectional studies of women without breast cancer and a nested case-control study of breast cancer. Using breast tissues, a multivariate analysis was used to model women with high and low breast cancer risk (based upon Gail risk model) in a discovery study of women without breast cancer (n=90), and applied to an independent replication study (n=71). The model was then assessed using serum samples from the nested case-control study (n=410).

Conclusions

Studying breast tissues of women without breast cancer revealed miRNAs correlated with breast cancer risk, which were then found to be altered in the serum of women who later developed breast cancer. These results serve as proof-of-principle that miRNAs in women without breast cancer may be useful for predicting breast cancer risk and/or as an adjunct for breast cancer early detection. The miRNAs identified herein may be involved in breast carcinogenic pathways because they were first identified in the breast tissues of healthy women.

Benign Breast Diseases: Evaluation and Management

Benign breast disease is a spectrum of common disorders. The majority of patients with a clinical breast lesion will have benign process. Management involves symptom control when present, pathologic-based and imaging-based evaluation to distinguish from a malignant process, and counseling for patients that have an increased breast cancer risk due to the benign disorder.

Subsequent Breast Cancer Risk Following Diagnosis of Atypical Ductal Hyperplasia on Needle Biopsy

Importance

Atypical ductal hyperplasia (ADH) is a known risk factor for breast cancer. Published risk estimates are based on cohorts that included women whose ADH was diagnosed before widespread use of screening mammograms and did not differentiate between the methods used to diagnose ADH, which may be related to the size of the ADH focus. These risks may overestimate the risk in women with presently diagnosed ADH.

Objective

To examine the risk of invasive cancer associated with ADH diagnosed using core needle biopsy vs excisional biopsy.

Design

A cohort study was conducted comparing the 10-year cumulative risk of invasive breast cancer in 955 331 women undergoing mammography with and without a diagnosis of ADH. Data were obtained from 5 breast imaging registries that participate in the National Cancer Institute-funded Breast Cancer Surveillance Consortium.

Exposures

Diagnosis of ADH on core needle biopsy or excisional biopsy in women undergoing mammography.

Main Outcomes and Measures

Ten-year cumulative risk of invasive breast cancer.

Results

The sample included 955 331 women with 1727 diagnoses of ADH, 1058 (61.3%) of which were diagnosed by core biopsy and 635 (36.8%) by excisional biopsy. The mean (interquartile range) age of the women at diagnosis was 52.6 (46.9-60.4) years. From 1996 to 2012, the proportion of ADH diagnosed by core needle biopsy increased from 21% to 77%. Ten years following a diagnosis of ADH, the cumulative risk of invasive breast cancer was 2.6 (95% CI, 2.0-3.4) times higher than the risk in women with no ADH. Atypical ductal hyperplasia diagnosed via excisional biopsy was associated with an adjusted hazard ratio (HR) of 3.0 (95% CI, 2-4.5) and, via core needle biopsy, with an adjusted HR of 2.2 (95% CI, 1.5-3.4). Ten years after an ADH diagnosis, an estimated 5.7% (95% CI, 4.3%-10.1%) of the women had a diagnosis of invasive cancer. Women with ADH diagnosed on excisional biopsy had a slightly higher risk (6.7%; 95% CI, 3.0%-12.8%) compared with those with ADH diagnosed via core needle biopsy (5%; 95% CI, 2.2%-8.9%).

Conclusions and Relevance

Current 10-year risks of invasive breast cancer after a diagnosis of ADH may be lower than those previously reported. The risk associated with ADH is slightly lower for women whose ADH was diagnosed by needle core biopsy compared with excisional biopsy.

Preventive and Risk Reduction Strategies for Women at High Risk of Developing Breast Cancer: a Review

Breast cancer is the most commonly diagnosed invasive cancer among women. Many factors, both genetic and non-genetic, determine a woman's risk of developing breast cancer and several breast cancer risk prediction models have been proposed. It is vitally important to risk stratify patients as there are now effective preventive strategies available. All women need to be counseled regarding healthy lifestyle recommendations to decrease breast cancer risk. As such, management of these women requires healthcare professionals to be familiar with additional risk factors so that timely recommendations can be made on surveillance/risk-reducing strategies. Breast cancer risk reduction strategies can be better understood by encouraging the women at risk to participate in clinical trials to test new strategies for decreasing the risk. This article reviews the advances in the identification of women at high risk of developing breast cancer and also reviews the strategies available for breast cancer prevention.

Society of Surgical Oncology Breast Disease Working Group Statement on Prophylactic (Risk-Reducing) Mastectomy

Over the past several years, there has been an increasing rate of bilateral prophylactic mastectomy (BPM) and contralateral prophylactic mastectomy (CPM) surgeries. Since publication of the 2007 SSO position statement on the use of risk-reducing mastectomy, there have been significant advances in the understanding of breast cancer biology and treatment. The purpose of this manuscript is to review the current literature as a resource to facilitate a shared and informed decision-making process regarding the use of risk-reducing mastectomy.

Dense Breasts: What Do Our Patients Need to Be Told and Why?

More than 50 % of states have state-mandated density notification for patients with heterogeneously or extremely dense breasts. Increased breast density carries a risk of masking a cancer and delaying diagnosis. Supplemental imaging is optional and often recommended for certain patients. There are no evidence-based consensus guidelines for screening patients with density as their only risk factor. Breast cancer risk assessment and breast cancer prevention strategies should be discussed with women with dense breasts.

Extent of atypical hyperplasia stratifies breast cancer risk in 2 independent cohorts of women

BACKGROUND

Women with atypical hyperplasia (AH) on breast biopsy have a substantially increased risk of breast cancer (BC). Here the BC risk for the extent and subtype of AH is reported for 2 separate cohorts.

METHODS

All samples containing AH were included from 2 cohorts of women with benign breast disease (Mayo Clinic and Nashville). Histology review quantified the number of foci of atypical ductal hyperplasia (ADH) and atypical lobular hyperplasia (ALH). The BC risk was stratified for the number of AH foci within AH subtypes.

RESULTS

The study included 708 Mayo AH subjects and 466 Nashville AH subjects. In the Mayo cohort, an increasing number of foci of AH was associated with a significant increase in the risk of BC both for ADH (relative risks of 2.61, 5.21, and 6.36 for 1, 2, and ≥3 foci, respectively; P for linear trend = .006) and for ALH (relative risks of 2.56, 3.50, and 6.79 for 1, 2, and ≥3 foci, respectively; P for linear trend = .001). In the Nashville cohort, the relative risks of BC for ADH were 2.70, 5.17, and 15.06 for 1, 2, and ≥3 foci, respectively (P for linear trend < .001); for ALH, the relative risks also increased but not significantly (2.61, 3.48, and 4.02, respectively; P = .148). When the Mayo and Nashville samples were combined, the risk increased significantly for 1, 2, and ≥3 foci: the relative risks were 2.65, 5.19, and 8.94, respectively, for ADH (P < .001) and 2.58, 3.49, and 4.97, respectively, for ALH (P = .001).

CONCLUSIONS

In 2 independent cohort studies of benign breast disease, the extent of atypia stratified the long-term BC risk for ADH and ALH. Cancer 2016;122:2971-2978. © 2016 American Cancer Society.

Addressing barriers to uptake of breast cancer chemoprevention for patients and providers

Breast cancer is the most common malignancy among women in the United States, and the primary prevention of this disease is a major public health issue. Because there are relatively few modifiable breast cancer risk factors, pharmacologic interventions with antiestrogens have the potential to significantly affect the primary prevention setting. Breast cancer chemoprevention with selective estrogen receptor modulators (SERMs) tamoxifen and raloxifene, and with aromatase inhibitors (AIs) exemestane and anastrozole, is underutilized despite several randomized controlled trials demonstrating up to a 50% to 65% relative risk reduction in breast cancer incidence among women at high risk. An estimated 10 million women in the United States meet high-risk criteria for breast cancer and are potentially eligible for chemoprevention, but less than 5% of women at high risk who are offered antiestrogens for primary prevention agree to take it. Reasons for low chemoprevention uptake include lack of routine breast cancer risk assessment in primary care, inadequate time for counseling, insufficient knowledge about antiestrogens among patients and providers, and concerns about side effects. Interventions designed to increase chemoprevention uptake, such as decision aids and incorporating breast cancer risk assessment into clinical practice, have met with limited success. Clinicians can help women make informed decisions about chemoprevention by effectively communicating breast cancer risk and enhancing knowledge about the risks and benefits of antiestrogens. Widespread adoption of chemoprevention will require a major paradigm shift in clinical practice for primary care providers (PCPs). However, enhancing uptake and adherence to breast cancer chemoprevention holds promise for reducing the public health burden of this disease.

Incorporating Biomarkers in Studies of Chemoprevention

Despite Food and Drug Administration approval of tamoxifen and raloxifene for breast cancer risk reduction and endorsement by multiple agencies, uptake of these drugs for primary prevention in the United States is only 4% for risk eligible women likely to benefit from their use. Side effects coupled with incomplete efficacy and lack of a survival advantage are the likely reasons. This disappointing uptake, after the considerable effort and expense of large Phase III cancer incidence trials required for approval, suggests that a new paradigm is required. Current prevention research is focused on (1) refining risk prediction, (2) exploring behavioral and natural product interventions, and (3) utilizing novel translational trial designs for efficacy. Risk biomarkers will play a central role in refining risk estimates from traditional models and selecting cohorts for prevention trials. Modifiable risk markers called surrogate endpoint or response biomarkers will continue to be used in Phase I and II prevention trials to determine optimal dose or exposure and likely effectiveness from an intervention. The majority of Phase II trials will continue to assess benign breast tissue for response and mechanism of action biomarkers. Co-trials are those in which human and animal cohorts receive the same effective dose and the same tissue biomarkers are assessed for modulation due to the intervention, but then additional animals are allowed to progress to cancer development. These collaborations linking biomarker modulation and cancer prevention may obviate the need for cancer incidence trials for non-prescription interventions.

Impact of preventive therapy on the risk of breast cancer among women with benign breast disease

There are three main ways in which women can be identified as being at high risk of breast cancer i) family history of breast and/or ovarian cancer, which includes genetic factors ii) mammographically identified high breast density, and iii) certain types of benign breast disease. The last category is the least common, but in some ways the easiest one for which treatment can be offered, because these women have already entered into the treatment system. The highest risk is seen in women with lobular carcinoma in situ (LCIS), but this is very rare. More common is atypical hyperplasia (AH), which carries a 4-5-fold risk of breast cancer as compared to general population. Even more common is hyperplasia of the usual type and carries a roughly two-fold increased risk. Women with aspirated cysts are also at increased risk of subsequent breast cancer. Tamoxifen has been shown to be particularly effective in preventing subsequent breast cancer in women with AH, with a more than 70% reduction in the P1 trial and a 60% reduction in IBIS-I. The aromatase inhibitors (AIs) also are highly effective for AH and LCIS. There are no published data on the effectiveness of tamoxifen or the AIs for breast cancer prevention in women with hyperplasia of the usual type, or for women with aspirated cysts. Improving diagnostic consistency, breast cancer risk prediction and education of physicians and patients regarding therapeutic prevention in women with benign breast disease may strengthen breast cancer prevention efforts.

Breast Density and Benign Breast Disease: Risk Assessment to Identify Women at High Risk of Breast Cancer

PURPOSE

Women with proliferative breast lesions are candidates for primary prevention, but few risk models incorporate benign findings to assess breast cancer risk. We incorporated benign breast disease (BBD) diagnoses into the Breast Cancer Surveillance Consortium (BCSC) risk model, the only breast cancer risk assessment tool that uses breast density.

METHODS

We developed and validated a competing-risk model using 2000 to 2010 SEER data for breast cancer incidence and 2010 vital statistics to adjust for the competing risk of death. We used Cox proportional hazards regression to estimate the relative hazards for age, race/ethnicity, family history of breast cancer, history of breast biopsy, BBD diagnoses, and breast density in the BCSC.

RESULTS

We included 1,135,977 women age 35 to 74 years undergoing mammography with no history of breast cancer; 17% of the women had a prior breast biopsy. During a mean follow-up of 6.9 years, 17,908 women were diagnosed with invasive breast cancer. The BCSC BBD model slightly overpredicted risk (expected-to-observed ratio, 1.04; 95% CI, 1.03 to 1.06) and had modest discriminatory accuracy (area under the receiver operator characteristic curve, 0.665). Among women with proliferative findings, adding BBD to the model increased the proportion of women with an estimated 5-year risk of 3% or higher from 9.3% to 27.8% (P<.001).

CONCLUSION

The BCSC BBD model accurately estimates women's risk for breast cancer using breast density and BBD diagnoses. Greater numbers of high-risk women eligible for primary prevention after BBD diagnosis are identified using the BCSC BBD model.

Triple-modality screening trial for familial breast cancer underlines the importance of magnetic resonance imaging and questions the role of mammography and ultrasound regardless of patient mutation status, age, and breast density

PURPOSE

To evaluate the breast cancer screening efficacy of mammography, ultrasound, and magnetic resonance imaging (MRI) in a high-risk population and in various population subgroups.

PATIENTS AND METHODS

In a single-center, prospective, nonrandomized comparison study, BRCA mutation carriers and women with a high familial risk (> 20% lifetime risk) for breast cancer were offered screening with mammography, ultrasound, and MRI every 12 months. Diagnostic performance was compared between individual modalities and their combinations. Further comparisons were based on subpopulations dichotomized by screening rounds, mutation status, age, and breast density.

RESULTS

There were 559 women with 1,365 complete imaging rounds included in this study. The sensitivity of MRI (90.0%) was significantly higher (P < .001) than that of mammography (37.5%) and ultrasound (37.5%). Of 40 cancers, 18 (45.0%) were detected by MRI alone. Two cancers were found by mammography alone (a ductal carcinoma in situ [DCIS] with microinvasion and a DCIS with < 10-mm invasive areas). This did not lead to a significant increase of sensitivity compared with using MRI alone (P = .15). No cancers were detected by ultrasound alone. Similarly, of 14 DCISs, all were detected by MRI, whereas mammography and ultrasound each detected five DCISs (35.7%). Age, mutation status, and breast density had no influence on the sensitivity of MRI and did not affect the superiority of MRI over mammography and ultrasound.

CONCLUSION

MRI allows early detection of familial breast cancer regardless of patient age, breast density, or risk status. The added value of mammography is limited, and there is no added value of ultrasound in women undergoing MRI for screening.

Breast cancer risk associated with benign breast disease: systematic review and meta-analysis

Benign breast disease (BBD) is a broad category of diagnoses reported to convey a variable degree of increased risk of developing breast cancer. A meta-analysis of the existing literature was performed to quantify the risk estimate associated with BBD. Pubmed, Google Scholar, and EMBASE databases were searched in January 2011. English retrospective and prospective observational studies published from 1972 to 2010 evaluating BBD and the risk of breast cancer were included with data acquisition reported from 1930 to 2007. Eligibility was performed independently following a standardized protocol for full-text publication review by a single reviewer and reviewed by a second author. Of the 3,409 articles retrieved from the literature search, 32 studies met the selection criteria. Reported risk estimates, including relative risk, odds ratio, standardized incidence ratios, rate ratio, hazards ratio, and incidence rate ratio, were the primary outcomes extracted. The most commonly reported pathologies were decided prior to extraction and organized into the following categories for analysis of the extracted risk estimate: non-proliferative disease (NPD), proliferative disease without atypia, benign breast disease not otherwise specified (BBD), and atypical hyperplasia not otherwise specified (AHNOS). The mean age at benign breast biopsy was 46.1 years and the mean age of developing breast cancer was 55.9 years. The mean follow-up length was 12.8 years (range 3.3-20.6). The summary risk estimate of developing breast cancer for NPD was 1.17 (N = 8; 95% CI 0.94-1.47). Proliferative disease without atypia was associated with significantly increased risk of future breast cancer, summary relative risk 1.76 (N = 15; 95% CI 1.58-1.95). The summary risk estimate for AHNOS was 3.93 (N = 13; 95% CI 3.24-4.76). This meta-analysis demonstrates that proliferative benign breast disease with or without atypia is associated with a significant increase in risk of developing breast cancer. These data support management strategies for women with benign breast disease such as additional screening methods or chemoprevention.

Model for individualized prediction of breast cancer risk after a benign breast biopsy

PURPOSE

Optimal early detection and prevention for breast cancer depend on accurate identification of women at increased risk. We present a risk prediction model that incorporates histologic features of biopsy tissues from women with benign breast disease (BBD) and compare its performance to the Breast Cancer Risk Assessment Tool (BCRAT).

METHODS

We estimated the age-specific incidence of breast cancer and death from the Mayo BBD cohort and then combined these estimates with a relative risk model derived from 377 patient cases with breast cancer and 734 matched controls sampled from the Mayo BBD cohort to develop the BBD-to-breast cancer (BBD-BC) risk assessment tool. We validated the model using an independent set of 378 patient cases with breast cancer and 728 matched controls from the Mayo BBD cohort and compared the risk predictions from our model with those from the BCRAT.

RESULTS

The BBD-BC model predicts the probability of breast cancer in women with BBD using tissue-based and other risk factors. The concordance statistic from the BBD-BC model was 0.665 in the model development series and 0.629 in the validation series; these values were higher than those from the BCRAT (0.567 and 0.472, respectively). The BCRAT significantly underpredicted breast cancer risk after benign biopsy (P = .004), whereas the BBD-BC predictions were appropriately calibrated to observed cancers (P = .247).

CONCLUSION

We developed a model using both demographic and histologic features to predict breast cancer risk in women with BBD. Our model more accurately classifies a woman's breast cancer risk after a benign biopsy than the BCRAT.

Acceptance and adherence to chemoprevention among women at increased risk of breast cancer

BACKGROUND

Chemoprevention is an option for women who are at increased risk of breast cancer (five year risk ≥1.7%). It is uncertain, however, how often women accept and complete five years of therapy and whether clinical or demographic factors predict completion.

METHODS

Medical records were abstracted for 219 women whose five year risk of breast cancer was ≥1.7% and who were offered chemoprevention while attending a high risk breast clinic at the Moffitt Cancer Center. We examined the likelihood of accepting chemoprevention and completing five years of therapy, and potential clinical and demographic predictors of these outcomes, using multivariable logistic regression and survival analysis models.

RESULTS

There were 118/219 women (54.4%) who accepted a recommendation for chemoprevention and began therapy. The likelihood of accepting chemoprevention was associated with lifetime breast cancer risk and was higher for women with specific high risk conditions (lobular carcinoma in situ and atypical ductal hyperplasia). Women with osteoporosis and those that consumed alcohol were also more likely to accept medication. There were 58/118 (49.2%) women who stopped medication at least temporarily after starting therapy. Based on survival curves, an estimated 60% of women who begin chemoprevention will complete five years of therapy.

CONCLUSIONS

A substantial percentage of women at increased risk of breast cancer will decline chemoprevention and among those that accept therapy, approximately 40% will not be able to complete five years of therapy because of side effects.

Gastric cancer research in Mexico: A public health priority

This study aimed review studies conducted on Mexican patients diagnosed with gastric cancer and/or diseases associated with its development, in which at least one Mexican institute has participated, and to assess their contributions to the primary and secondary prevention of this disease. A search of the Medline database was conducted using the following keywords: gastric/stomach cancer, Mexico. Studies of the Mexican population were selected in which at least one Mexican Institute had participated and where the findings could support public policy proposals directed towards the primary or secondary prevention of gastric cancer. Of the 148 studies found in the Medline database, 100 were discarded and 48 were reviewed. According to the analysis presented, these studies were classified as: epidemiology of gastric cancer (5/48); risk factors and protectors relating to gastric cancer (9/48); relationship between Helicobacter pylori and pathologies associated with gastric cancer and the development of the disease (16/48); relationship between the Epstein-Barr virus and pathologies associated with gastric cancer and the development of the disease (3/48); molecular markers for the development of diseases associated with gastric cancer and gastric cancer (15/48). Mexico requires a program for the prevention and control of gastric cancer based on national health indicators. This should be produced by a multidisciplinary committee of experts who can propose actions that are relevant in the current national context. The few studies of gastric cancer conducted on the Mexican population in national institutes highlight the poor connection that currently exists between the scientific community and the health sector in terms of resolving this health issue. Public policies for health research should support projects with findings that can be translated into benefits for the population. This review serves to identify national research groups studying gastric cancer in the Mexican population.

Establishing a program for individuals at high risk for breast cancer

Our need to create a program for individuals at high risk for breast cancer development led us to research the available data on such programs. In this paper, we summarize our findings and our thinking process as we developed our own program. Breast cancer incidence is increasing worldwide. Even though there are known risk factors for breast cancer development, approximately 60% of patients with breast cancer have no known risk factor, although this situation will probably change with further research, especially in genetics. For patients with risk factors based on personal or family history, different models are available for assessing and quantifying risk. Assignment of risk levels permits tailored screening and risk reduction strategies. Potential benefits of specialized programs for women with high breast cancer risk include more cost -effective interventions as a result of patient stratification on the basis of risk; generation of valuable data to advance science; and differentiation of breast programs from other breast cancer units, which can result in increased revenue that can be directed to further improvements in patient care. Guidelines for care of patients at high risk for breast cancer are available from various groups. However, running a high-risk breast program involves much more than applying a guideline. Each high-risk program needs to be designed by its institution with consideration of local resources and country legislation, especially related to genetic issues. Development of a successful high-risk program includes identifying strengths, weaknesses, opportunities, and threats; developing a promotion plan; choosing a risk assessment tool; defining "high risk"; and planning screening and risk reduction strategies for the specific population served by the program. The information in this article may be useful for other institutions considering creation of programs for patients with high breast cancer risk.

Chemoprevention of breast cancer

The development of pharmacologic agents for the prevention of breast cancer is a significant milestone in medical and laboratory research. Despite these advances, the endorsement of preventive options has become challenging and complex, as physicians are expected to counsel and tailor their recommendations using a personalized approach taking into account medical comorbidities, degree of risk and patient preferences. This article provides a comprehensive overview of the major breast cancer prevention trials, review of the pharmacologic options available for breast cancer prevention, and strategies for integrating chemoprevention of breast cancer in high-risk women into clinical practice.