Diagnostic accuracy of the Gail model in the Black Women's Health Study

Disparities in Breast Cancer Care-How Factors Related to Prevention, Diagnosis, and Treatment Drive Inequity

Breast cancer survival has increased significantly over the last few decades due to more effective strategies for prevention and risk modification, advancements in imaging detection, screening, and multimodal treatment algorithms. However, many have observed disparities in benefits derived from such improvements across populations and demographic groups. This review summarizes published works that contextualize modern disparities in breast cancer prevention, diagnosis, and treatment and presents potential strategies for reducing disparities. We conducted searches for studies that directly investigated and/or reported disparities in breast cancer prevention, detection, or treatment. Demographic factors, social determinants of health, and inequitable healthcare delivery may impede the ability of individuals and communities to employ risk-mitigating behaviors and prevention strategies. The disparate access to quality screening and timely diagnosis experienced by various groups poses significant hurdles to optimal care and survival. Finally, barriers to access and inequitable healthcare delivery patterns reinforce inequitable application of standards of care. Cumulatively, these disparities underlie notable differences in the incidence, severity, and survival of breast cancers. Efforts toward mitigation will require collaborative approaches and partnerships between communities, governments, and healthcare organizations, which must be considered equal stakeholders in the fight for equity in breast cancer care and outcomes.

Screening Programs for Breast Cancer: Toward Individualized, Risk-Adapted Strategies of Early Detection

Early detection of breast cancer (BC) comprises two approaches: screening of asymptomatic women in a specified target population at risk (usually a target age range for women at average risk), and early diagnosis for women with BC signs and symptoms. Screening for BC is a key health intervention for early detection. While population-based screening programs have been implemented for age-selected women, the pivotal clinical trials have not addressed the global utility nor the improvement of screening performance by utilizing more refined parameters for patient eligibility, such as individualized risk stratification. In addition, with the exception of the subset of women known to carry germline pathogenetic mutations in (high- or moderately-penetrant) cancer predisposition genes, such as BRCA1 and BRCA2, there has been less success in outreach and service provision for the unaffected relatives of women found to carry a high-risk mutation (i.e., "cascade testing") as it is in these individuals for whom such actionable information can result in cancers (and/or cancer deaths) being averted. Moreover, even in the absence of clinical cancer genetics services, as is the case for the immediate and at least near-term in most countries globally, the capacity to stratify the risk of an individual to develop BC has existed for many years, is available for free online at various sites/platforms, and is increasingly being validated for non-Caucasian populations. Ultimately, a precision approach to BC screening is largely missing. In the present chapter, we aim to address the concept of risk-adapted screening of BC, in multiple facets, and understand if there is a value in the implementation of adapted screening strategies in selected women, outside the established screening prescriptions, in the terms of age-range, screening modality and schedules of imaging.

The Landmark Series-Addressing Disparities in Breast Cancer Screening: New Recommendations for Black Women

Randomized, clinical trials have established the efficacy of screening mammography in improving survival from breast cancer for women through detection of early, asymptomatic disease. However, disparities in survival rates between black women and women from other racial and ethnic groups following breast cancer diagnosis persist. Various professional groups have different, somewhat conflicting, guidelines with regards to recommended age for commencing screening as well as recommended frequency of screening exams, but the trials upon which these recommendations are based were not specifically designed to examine benefit among black women. Furthermore, these recommendations do not appear to incorporate the unique epidemiological circumstances of breast cancer among black women, including higher rates of diagnosis before age 40 years and greater likelihood of advanced stage at diagnosis, into their formulation. In this review, we examined the epidemiologic and socioeconomic factors that are associated with breast cancer among black women and assess the implications of these factors for screening in this population. Specifically, we recommend that by no later than age 25 years, all black women should undergo baseline assessment for future risk of breast cancer utilizing a model that incorporates race (e.g., Breast Cancer Risk Assessment Tool [BCRAT], formerly the Gail model) and that this assessment should be conducted by a breast specialist or a healthcare provider (e.g., primary care physician or gynecologist) who is trained to assess breast cancer risk and is aware of the increased risks of early (i.e., premenopausal) and biologically aggressive (e.g., late-stage, triple-negative) breast cancer among black women.

Validation of Breast Cancer Risk Models by Race/Ethnicity, Family History and Molecular Subtypes

Simple Summary

Several statistical models exist to predict a person’s risk of breast cancer. Risk assessment models can guide cancer screening approaches by identifying individuals who would benefit from additional screening. In this study, we compared the performance of four models in predicting the 5-year risk of breast cancer in a cohort of women aged 40–84 years who underwent screening mammography at three large health systems. Models showed comparable discrimination (ability to distinguish between cases and non-cases) and calibration (ability to accurately predict risk) overall, with no difference by race. Model discrimination was poorer for some cancer subtypes, and better for women with high BMI. The combined BRCAPRO+BCRAT model had improved calibration and discrimination among women with a family history of breast cancer. Our results can inform risk-based screening approaches by identifying women at a high risk of breast cancer.

Abstract

(1) Background: The purpose of this study is to compare the performance of four breast cancer risk prediction models by race, molecular subtype, family history of breast cancer, age, and BMI. (2) Methods: Using a cohort of women aged 40–84 without prior history of breast cancer who underwent screening mammography from 2006 to 2015, we generated breast cancer risk estimates using the Breast Cancer Risk Assessment tool (BCRAT), BRCAPRO, Breast Cancer Surveillance Consortium (BCSC) and combined BRCAPRO+BCRAT models. Model calibration and discrimination were compared using observed-to-expected ratios (O/E) and the area under the receiver operator curve (AUC) among patients with at least five years of follow-up. (3) Results: We observed comparable discrimination and calibration across models. There was no significant difference in model performance between Black and White women. Model discrimination was poorer for HER2+ and triple-negative subtypes compared with ER/PR+HER2−. The BRCAPRO+BCRAT model displayed improved calibration and discrimination compared to BRCAPRO among women with a family history of breast cancer. Across models, discriminatory accuracy was greater among obese than non-obese women. When defining high risk as a 5-year risk of 1.67% or greater, models demonstrated discordance in 2.9% to 19.7% of patients. (4) Conclusions: Our results can inform the implementation of risk assessment and risk-based screening among women undergoing screening mammography.

Essentialism and Exclusion: Racism in Cancer Risk Prediction Models

Cancer risk prediction models have the potential to revolutionize the science and practice of cancer prevention and control by identifying the likelihood that a patient will develop cancer at some point in the future, likely experience more benefit than harm from a given intervention, and survive their cancer for a certain number of years. The ability of risk prediction models to produce estimates that are valid and reliable for people from diverse socio-demographic backgrounds-and consequently their utility for broadening the reach of precision medicine to marginalized populations-depends on ensuring that the risk factors included in the model are represented as thoroughly and as accurately as possible. However, cancer risk prediction models created in the United States have a critical limitation, the origins of which stem from the country's earliest days: they either erroneously treat the social construct of race as an immutable biological factor (ie, they "essentialize" race), or they exclude from the model those socio-contextual factors that are associated with both race and health outcomes. Models that essentialize race and/or exclude socio-contextual factors sometimes incorporate "race corrections" that adjust a patient's risk estimate up or down based on their race. This commentary discusses the origins of race corrections, potential flaws with such corrections, and strategies for developing cohorts for developing risk prediction models that do not essentialize race or exclude key socio-contextual factors. Such models will help move the science of cancer prevention and control towards its goal of eliminating cancer disparities and achieving health equity.

Performance of the IBIS/Tyrer-Cuzick model of breast cancer risk by race and ethnicity in the Women's Health Initiative

BACKGROUND

The IBIS/Tyrer-Cuzick model is used clinically to guide breast cancer screening and prevention, but was developed primarily in non-Hispanic White women. Little is known about its long-term performance in a racially/ethnically diverse population.

METHODS

The Women's Health Initiative study enrolled postmenopausal women from 1993-1998. Women were included who were aged <80 years at enrollment with no prior breast cancer or mastectomy and with data required for IBIS/Tyrer-Cuzick calculation (weight; height; ages at menarche, first birth, and menopause; menopausal hormone therapy use; and family history of breast or ovarian cancer). Calibration was assessed by the ratio of observed breast cancer cases to the number expected by the IBIS/Tyrer-Cuzick model (O/E; calculated as the sum of cumulative hazards). Differential discrimination was tested for by self-reported race/ethnicity (non-Hispanic White, non-Hispanic Black, Hispanic, Asian or Pacific Islander, and American Indian or Alaskan Native) using Cox regression. Exploratory analyses, including simulation of a protective single-nucleotide polymorphism (SNP), rs140068132 at 6q25, were performed.

RESULTS

During follow-up (median 18.9 years, maximum 23.4 years), 6783 breast cancer cases occurred among 90,967 women. IBIS/Tyrer-Cuzick was well calibrated overall (O/E ratio = 0.95; 95% CI, 0.93-0.97) and in most racial/ethnic groups, but overestimated risk for Hispanic women (O/E ratio = 0.75; 95% CI, 0.62-0.90). Discrimination did not differ by race/ethnicity. Exploratory simulation of the protective SNP suggested improved IBIS/Tyrer-Cuzick calibration for Hispanic women (O/E ratio = 0.80; 95% CI, 0.66-0.96).

CONCLUSIONS

The IBIS/Tyrer-Cuzick model is well calibrated for several racial/ethnic groups over 2 decades of follow-up. Studies that incorporate genetic and other risk factors, particularly among Hispanic women, are essential to improve breast cancer-risk prediction.

Breast Cancer Risk Assessment and Chemoprevention Use Among Veterans Affairs Primary Care Providers: A National Online Survey

INTRODUCTION

Breast cancer is the most common cancer diagnosed among women and the second most common cause of cancer death among women. There are ways to reduce a woman's risk of breast cancer; however, most eligible women in the United States are neither offered personalized screening nor chemoprevention. Surveys have found that primary care providers are largely unaware of breast cancer risk assessment models or chemoprevention. This survey aims to investigate Veterans Health Administration primary care providers' comfort level, practice patterns, and knowledge of breast cancer risk assessment and chemoprevention.

MATERIALS AND METHODS

An online, Research Electronic Data Capture-generated survey was distributed to VHA providers in internal medicine, family medicine, and obstetrics/gynecology. Survey domains were provider demographics, women's health experience, comfort level, practice patterns, barriers to using risk models and chemoprevention, and knowledge of chemoprevention.

RESULTS

Of the 167 respondents, 33.1% used the Gail model monthly or more often and only 2.4% prescribed chemoprevention in the past 2 years. Most VHA primary care providers did not answer chemoprevention knowledge questions correctly. Designated women's health providers were more comfortable with risk assessment (P < 0.018) and chemoprevention (P < 0.011) and used both breast cancer risk models (P < 0.0045) and chemoprevention more often (P < 0.153). Reported barriers to chemoprevention were lack of education and provider time.

CONCLUSIONS

VHA providers and women Veterans would benefit from a system to ensure that women at increased risk of breast cancer are identified with risk modeling and that risk reduction options, such as chemoprevention, are offered when appropriate. VHA providers requested risk reduction education, which could improve primary care provider comfort level with chemoprevention.

Molecular genetic testing strategies used in diagnostic flow for hereditary endocrine tumour syndromes

INTRODUCTION

Although current guidelines prefer the use of targeted testing or small-scale gene panels for identification of genetic susceptibility of hereditary endocrine tumour syndromes, next generation sequencing based strategies have been widely introduced into every day clinical practice. The application of next generation sequencing allows rapid testing of multiple genes in a cost effective manner. Increasing knowledge about these techniques and the demand from health care providers and society, shift the molecular genetic testing towards using high-throughput approaches.

PURPOSE

In this expert opinion, the authors consider the molecular diagnostic workflow step by step, evaluating options and challenges of gathering family information, pre- and post-test genetic counselling, technical and bioinformatical analysis related issues and difficulties in clinical interpretation focusing on molecular genetic testing of hereditary endocrine tumour syndromes.

RESULT AND CONCLUSION

Considering all these factors, a diagnostic genetic workflow is also proposed for selection of the best approach for testing of patients with hereditary genetic tumour syndromes in order to minimalize difficult interpretation, unwanted patient anxiety, unnecessary medical interventions and cost. There are potential benefits of utilizing high throughput approaches however, important limitations have to be considered and should discussed towards the clinicians and patients.

Outcomes by Race in Breast Cancer Screening With Digital Breast Tomosynthesis Versus Digital Mammography

Purpose:

Digital breast tomosynthesis (DBT) in conjunction with digital mammography (DM) is becoming the preferred imaging modality for breast cancer screening compared with DM alone, on the basis of improved recall rates (RR) and cancer detection rates (CDRs). The aim of this study was to investigate racial differences in the utilization and performance of screening modality.

Methods:

Retrospective data from 63 US breast imaging facilities from 2015 to 2019 were reviewed. Screening outcomes were linked to cancer registries. RR, CDR per 1,000 examinations, and positive predictive value for recall (cancers/recalled patients) were compared.

Results:

A total of 385,503 women contributed 542,945 DBT and 261,359 DM screens. A lower proportion of screenings for Black women were performed using DBT plus DM (referred to as DBT) (44% for Black, 48% for other, 63% for Asian, and 61% for White). Non-White women were less likely to undergo more than one mammographic examination. RRs were lower for DBT among all women (8.74 versus 10.06, P < .05) and lower across all races and within age categories. RRs were significantly higher for women with only one mammogram. CDRs were similar or higher in women undergoing DBT compared with DM, overall (4.73 versus 4.60, adjusted P = .0005) and by age and race. Positive predictive value for recall was greater for DBT overall (5.29 versus 4.45, adjusted P < .0001) and by age, race, and screening frequency.

Conclusions:

All racial groups had improved outcomes with DBT screening, but disparities were observed in DBT utilization. These data suggest that reducing inequities in DBT utilization may improve the effectiveness of breast cancer screening.

Risk assessment and genetic counseling for hereditary breast and ovarian cancer syndromes-Practice resource of the National Society of Genetic Counselors

Cancer risk assessment and genetic counseling for hereditary breast and ovarian cancer (HBOC) are a communication process to inform and prepare patients for genetic test results and the related medical management. An increasing number of healthcare providers are active in the delivery of cancer risk assessment and testing, which can have enormous benefits for enhanced patient care. However, genetics professionals remain key in the multidisciplinary care of at-risk patients and their families, given their training in facilitating patients' understanding of the role of genetics in cancer development, the potential psychological, social, and medical implications associated with cancer risk assessment and genetic testing. A collaborative partnership of non-genetics and genetics experts is the ideal approach to address the growing number of patients at risk for hereditary breast and ovarian cancer. The goal of this practice resource is to provide allied health professionals an understanding of the key components of risk assessment for HBOC as well as the use of risk models and published guidelines for medical management. We also highlight what patient types are appropriate for genetic testing, what are the most appropriate test(s) to consider, and when to refer individuals to a genetics professional. This practice resource is intended to serve as a resource for allied health professionals in determining their approach to delivering comprehensive care for families and individuals facing HBOC. The cancer risk and prevalence figures in this document are based on cisgender women and men; the risks for transgender or non-binary individuals have not been studied and therefore remain poorly understood.

Inflammation markers on benign breast biopsy are associated with risk of invasive breast cancer in African American women

PURPOSE

Markers of inflammation, including crown-like structures of the breast (CLS-B) and infiltrating lymphocytes (IL), have been identified in breast tissue and associated with increased risk of breast cancer (BrCa), however most of this work has been performed in primarily non-Hispanic white women. Here, we examined whether CLS-B and IL are associated with invasive BrCa in African American (AA) women.

METHODS

We assessed breast biopsies from three 5-year age-matched groups: BrCa-free AA women (50 Volunteer) from the Komen Normal Tissue Bank (KTB) and AA women with a clinically-indicated biopsy diagnosed with benign breast disease (BBD) from our Detroit cohort who developed BrCa (55 BBD-cancer) or did not develop BrCa (47 BBD only, year of biopsy matched to BBD-cancer). Mean adipocyte diameter and total adipose area were estimated from digital images using the Adiposoft plugin from ImageJ. Associations between CLS-B, IL, and BrCa among KTB and Detroit biopsies were assessed using multivariable multinomial and conditional logistic regression models.

RESULTS

Among all biopsies, Volunteer and BBD only biopsies did not harbor CLS-B or IL at significantly different rates after adjusting for logarithm of adipocyte area, adipocyte diameter, and BMI. Among clinically-indicated BBD biopsies, BBD-cancer biopsies were more likely to exhibit CLS-B (odds ratio (OR) = 3.36, 95% Confidence Interval (CI): 1.33-8.48) or IL (OR = 4.95, 95% CI 1.76-13.9) than BBD only biopsies after adjusting for total adipocyte area, adipocyte diameter, proliferative disease, and BMI.

CONCLUSIONS

CLS-B and IL may serve as histological markers of BrCa risk in benign breast biopsies from AA women.

Gail Model Underestimates Breast Cancer Risk in Thai Population

Background: The Gail model is the most widely used method for breast cancer risk estimation. This model has been studied and verified for its validity in many groups but there has yet to be a study to validate the Gail model in a Thai population. This study aims to evaluate whether the Gail model can accurately calculate the risk of breast cancer among Thai women. Methods: The subjects were recruited from the Division of Head, Neck, and Breast Surgery, Department of Surgery, Siriraj Hospital. The patients attending the division were asked to enroll in the study and complete questionnaires. Gail model scores were then calculated. Relationships between parameters were examined using the Pearson’s chi-square test, Fisher’s exact test, and independent-samples t-test. Results: There were 514 women recruited. Age, parity, age at first-live birth, and history of atypical ductal hyperplasia (ADH) were significant risk factors for breast cancer. The 5-year and lifetime risk score for breast cancer calculated by the Gail model were not significantly different between the patient and the control subjects. The proportions of the subjects with lifetime risk ≥20% were significantly higher in breast cancer patients (p=0.049). Conclusion: The Gail model underestimated the risk of breast cancer in Thai women. Calibration of the model is still required before adoption in Thai population.

Validation of a genetic risk score for Arkansas women of color

African American women in the state of Arkansas have high breast cancer mortality rates. Breast cancer risk assessment tools developed for African American underestimate breast cancer risk. Combining African American breast cancer associated single-nucleotide polymorphisms (SNPs) into breast cancer risk algorithms may improve individualized estimates of a woman's risk of developing breast cancer and enable improved recommendation of screening and chemoprevention for women at high risk. The goal of this study was to confirm with an independent dataset consisting of Arkansas women of color, whether a genetic risk score derived from common breast cancer susceptibility SNPs can be combined with a clinical risk estimate provided by the Breast Cancer Risk Assessment Tool (BCRAT) to produce a more accurate individualized breast cancer risk estimate. A population-based cohort of African American women representative of Arkansas consisted of 319 cases and 559 controls for this study. Five-year and lifetime risks from the BCRAT were measured and combined with a risk score based on 75 independent susceptibility SNPs in African American women. We used the odds ratio (OR) per adjusted standard deviation to evaluate the improvement in risk estimates produced by combining the polygenic risk score (PRS) with 5-year and lifetime risk scores estimated using BCRAT. For 5-year risk OR per standard deviation increased from 1.84 to 2.08 with the addition of the polygenic risk score and from 1.79 to 2.07 for the lifetime risk score. Reclassification analysis indicated that 13% of cases had their 5-year risk increased above the 1.66% guideline threshold (NRI = 0.020 (95% CI -0.040, 0.080)) and 6.3% of cases had their lifetime risk increased above the 20% guideline threshold by the addition of the polygenic risk score (NRI = 0.034 (95% CI 0.000, 0.070)). Our data confirmed that discriminatory accuracy of BCRAT is improved for African American women in Arkansas with the inclusion of specific SNP breast cancer risk alleles.

Social factors matter in cancer risk and survivorship

Greater attention to social factors, such as race/ethnicity, socioeconomic position, and others, are needed across the cancer continuum, including breast cancer, given differences in tumor biology and genetic variants have not completely explained the persistent Black/White breast cancer mortality disparity. In this commentary, we use examples in breast cancer risk assessment and survivorship to demonstrate how the failure to appropriately incorporate social factors into the design, recruitment, and analysis of research studies has resulted in missed opportunities to reduce persistent cancer disparities. The conclusion offers recommendations for how to better document and use information on social factors in cancer research and care by (1) increasing education and awareness about the importance of inclusion of social factors in clinical research; (2) improving testing and documentation of social factors by incorporating them into journal guidelines and reporting stratified results; and (3) including social factors to refine extant tools that assess cancer risk and assign cancer care. Implementing the recommended changes would enable more effective design and implementation of interventions and work toward eliminating cancer disparities by accounting for the social and environmental contexts in which cancer patients live and are treated.

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 .

Cross-sectional study to assess the association of population density with predicted breast cancer risk

The Gail and CARE models estimate breast cancer risk for white and African-American (AA) women, respectively. The aims of this study were to compare metropolitan and nonmetropolitan women with respect to predicted breast cancer risks based on known risk factors, and to determine if population density was an independent risk factor for breast cancer risk. A cross-sectional survey was completed by 15,582 women between 35 and 85 years of age with no history of breast cancer. Metropolitan and nonmetropolitan women were compared with respect to risk factors, and breast cancer risk estimates, using general linear models adjusted for age. For both white and AA women, tisk factors used to estimate breast cancer risk included age at menarche, history of breast biopsies, and family history. For white women, age at first childbirth was an additional risk factor. In comparison to their nonmetropolitan counterparts, metropolitan white women were more likely to report having a breast biopsy, have family history of breast cancer, and delay childbirth. Among white metropolitan and nonmetropolitan women, mean estimated 5-year risks were 1.44% and 1.32% (p < 0.001), and lifetime risks of breast cancer were 10.81% and 10.01% (p < 0.001), respectively. AA metropolitan residents were more likely than those from nonmetropolitan areas to have had a breast biopsy. Among AA metropolitan and nonmetropolitan women, mean estimated 5-year risks were 1.16% and 1.12% (p = 0.039) and lifetime risks were 8.94%, and 8.85% (p = 0.344). Metropolitan residence was associated with higher predicted breast cancer risks for white women. Among AA women, metropolitan residence was associated with a higher predicted breast cancer risk at 5 years, but not over a lifetime. Population density was not an independent risk factor for breast cancer.

Use of the Gail model and breast cancer preventive therapy among three primary care specialties

BACKGROUND

Breast cancer is an issue of serious concern among women of all ages. The extent to which providers across primary care specialties assess breast cancer risk and discuss chemoprevention is unknown.

METHODS

Cross-sectional web-based survey completed by 316 physicians in internal medicine (IM), family medicine (FM), and gynecology (GYN) from February to April of 2012. Survey items assessed respondents' frequency of use of the Gail model and chemoprevention, and their attitudes behind practice patterns. Descriptive statistics were used to generate response distributions, and chi-squared tests were used to compare responses among specialties.

RESULTS

The response rate was 55.0 % (316/575). Only 40% of providers report having used the Gail model (37% IM, 33% FM, 60% GYN) and 13% report having recommended or prescribed chemoprevention (9% IM, 8% FM, 30% GYN). Among providers who use the Gail model, a minority use it regularly in patients who may be at increased breast cancer risk. Among providers who have prescribed chemoprevention, most have done so five times or fewer. Lack of both time and familiarity were commonly cited barriers to use of the Gail score and chemoprevention.

CONCLUSIONS

An overall minority of providers, most notably in FM and IM, use the Gail model to assess, and chemoprevention to decrease, breast cancer risk. Until providers are more consistent in their use of the Gail model (or other breast cancer risk calculator) and chemoprevention, opportunities to intervene in women at increased risk will likely continue to be missed.

Perceived versus objective breast cancer risk in diverse women

BACKGROUND

Prior research suggests that women do not accurately estimate their risk for breast cancer. Estimating and informing women of their risk is essential for tailoring appropriate screening and risk reduction strategies.

METHODS

Data were collected for BreastCARE, a randomized controlled trial designed to evaluate a PC-tablet based intervention providing multiethnic women and their primary care physicians with tailored information about breast cancer risk. We included women ages 40-74 visiting general internal medicine primary care clinics at one academic practice and one safety net practice who spoke English, Spanish, or Cantonese, and had no personal history of breast cancer. We collected baseline information regarding risk perception and concern. Women were categorized as high risk (vs. average risk) if their family history met criteria for referral to genetic counseling or if they were in the top 5% of risk for their age based on the Gail or Breast Cancer Surveillance Consortium Model (BCSC) breast cancer risk model.

RESULTS

Of 1,261 participants, 25% (N=314) were classified as high risk. More average risk than high risk women had correct risk perception (72% vs. 18%); 25% of both average and high risk women reported being very concerned about breast cancer. Average risk women with correct risk perception were less likely to be concerned about breast cancer (odds ratio [OR]=0.3; 95% confidence interval [CI]=0.2-0.4) while high risk women with correct risk perception were more likely to be concerned about breast cancer (OR=5.1; 95%CI=2.7-9.6).

CONCLUSIONS

Many women did not accurately perceive their risk for breast cancer. Women with accurate risk perception had an appropriate level of concern about breast cancer. Improved methods of assessing and informing women of their breast cancer risk could motivate high risk women to apply appropriate prevention strategies and allay unnecessary concern among average risk women.

Cancer risk models and preselection for screening

OBJECTIVE

The invitation to population screening is based on age criteria in many countries. Screening is not offered to younger or older participants, because the benefits in these age groups do not outweigh the harms. One could argue that it is not so much age that determines the benefits but the risk of developing preclinical and treatable cancer. Cancer risk varies with age but is also affected by other factors.

METHODS

We performed a systematic review for risk models for the three types of cancer for which population screening programs exist: breast, cervical and colon cancer. We used an evaluation scheme that distinguishes three phases of model development: model derivation, validation and impact analysis. Data were collected in August 2010.

RESULTS

We identified two colorectal, four breast and three cervix cancer risk models. One colorectal, four breast and none of the cervix cancer models have been externally validated. We could not identify evaluations of the impact on population screening effectiveness.

CONCLUSION

We conclude that risk models for the pre-selection of screening have been developed. These models could improve the pre-selection for screening, help in making personal decisions about participation, and reduce adverse effects of population screening. The validity of this hypothesis, as well as practicalities and issues of equity and reliability, have to be tested in further studies.

A case-control study on risk factors of breast cancer in China

INTRODUCTION

To screen the risk factors associated with breast cancer among Chinese women in order to evaluate the individual risk of developing breast cancer among women in China.

MATERIAL AND METHODS

A case-control study on 416 breast cancer patients and 1156 matched controls was conducted in 14 hospitals in 8 provinces of China in 2008. Controls were age- and region-matched to the cases. Clinicians conducted in-person interviews with the subjects to collect information on demographics and suspected risk factors for breast cancer that are known worldwide. Conditional logistic regression was used to derive odds ratios (OR) and 95% confidence intervals (CI) for the associations between risk factors and breast cancer.

RESULTS

Compared with matched controls, women with breast cancer were significantly more likely to have higher body mass index (BMI, OR = 4.07, 95% CI: 2.98-5.55), history of benign breast disease (BBD) biopsy (OR = 1.68, 95% CI: 1.19-2.38), older age of menarche (AOM) (OR = 1.41, 95% CI: 1.07-1.87), stress anticipation (SA), for grade 1-4, OR = 2.15, 95% CI: 1.26-3.66; for grade 5-9, OR = 3.48, 95% CI: 2.03-5.95) and menopause (OR = 2.22, 95% CI: 1.50-3.282) at the level of p < 0.05. Family history of breast cancer (FHBC) in first-degree relatives (OR = 1.66, 95% CI: 0.77-3.59) and use of oral contraceptives (OC) (OR = 1.59, 95% CI: 0.83-3.05) were associated with an increased risk of breast cancer at the level of p < 0.20.

CONCLUSIONS

Our results showed that BMI, history of BBD biopsy, older AOM, SA and menopause were associated with increased risk of breast cancer among Chinese women. The findings derived from the study provided some suggestions for population-based prevention and control of breast cancer in China.

Tailored supplemental screening for breast cancer: what now and what next?

OBJECTIVE

This article reviews breast cancer risk assessment and the rationale for current screening guidelines, including when to consider using supplemental screening with MRI or sonography in addition to mammography, and discusses other emerging technologies. Radiologists can help identify women who may benefit from supplemental screening and can help to recommend when and which techniques to perform for this additional screening.

CONCLUSION

Mammography remains the mainstay of breast cancer screening. Mammography should be performed as digital imaging when possible in women with dense breasts. In women at high risk, particularly if they also have dense breasts, annual MRI is recommended, although further validation of outcomes is needed. In intermediate-risk women with dense breasts, especially those with other risk factors, and in high-risk women with dense breasts who are unable to tolerate MRI, supplemental sonography screening is an option at facilities with availability of qualified personnel. Developing technologies are not appropriate for screening at this time, although further study is encouraged.

BRCA1/2 in high-risk African American women with breast cancer: providing genetic testing through various recruitment strategies

BACKGROUND

Due to the disproportionate numbers of African American women affected with early onset breast cancer, we sought to investigate mutation frequency of BRCA1 and BRCA2 (BRCA1/2) in a sample of African American women, recruited through a variety of methods.

METHODS

We conducted a study investigating BRCA1/2 among 51 African American breast cancer patients with a personal or family history suggestive of hereditary predisposition to breast cancer. All individuals underwent genetic counseling and BRCA1/2 mutation analysis, through protein-truncation test on exon 11 of BRCA1 and exons 10 and 11 of BRCA2, which together account for approximately 50% of mutations observed within these genes.

RESULTS

Of the 51 women tested for BRCA1/2 mutations, 3 were identified as mutation carriers (5.9%), including 1 in BRCA1 and 2 in BRCA2. Recruitment strategies varied and included physician referrals from the Moffitt Cancer Center Breast Program (18), community-based oncologists (13), primary care physicians (3), newspaper advertisements and brochures (5), community or support group referrals (7), self/family referral through word of mouth (2), and the Florida State Cancer Registry (3).

CONCLUSIONS

Our results suggest that (1) BRCA1/2 mutations are seen in high-risk African American women with breast cancer, and (2) strategies for recruitment of African American women in studies of genetic testing for breast cancer genes have varied levels of success. Our study highlights the need for further studies in this population group.

Combined screening with ultrasound and mammography vs mammography alone in women at elevated risk of breast cancer

CONTEXT

Screening ultrasound may depict small, node-negative breast cancers not seen on mammography.

OBJECTIVE

To compare the diagnostic yield, defined as the proportion of women with positive screen test results and positive reference standard, and performance of screening with ultrasound plus mammography vs mammography alone in women at elevated risk of breast cancer.

DESIGN, SETTING, AND PARTICIPANTS

From April 2004 to February 2006, 2809 women, with at least heterogeneously dense breast tissue in at least 1 quadrant, were recruited from 21 sites to undergo mammographic and physician-performed ultrasonographic examinations in randomized order by a radiologist masked to the other examination results. Reference standard was defined as a combination of pathology and 12-month follow-up and was available for 2637 (96.8%) of the 2725 eligible participants.

MAIN OUTCOME MEASURES

Diagnostic yield, sensitivity, specificity, and diagnostic accuracy (assessed by the area under the receiver operating characteristic curve) of combined mammography plus ultrasound vs mammography alone and the positive predictive value of biopsy recommendations for mammography plus ultrasound vs mammography alone.

RESULTS

Forty participants (41 breasts) were diagnosed with cancer: 8 suspicious on both ultrasound and mammography, 12 on ultrasound alone, 12 on mammography alone, and 8 participants (9 breasts) on neither. The diagnostic yield for mammography was 7.6 per 1000 women screened (20 of 2637) and increased to 11.8 per 1000 (31 of 2637) for combined mammography plus ultrasound; the supplemental yield was 4.2 per 1000 women screened (95% confidence interval [CI], 1.1-7.2 per 1000; P = .003 that supplemental yield is 0). The diagnostic accuracy for mammography was 0.78 (95% CI, 0.67-0.87) and increased to 0.91 (95% CI, 0.84-0.96) for mammography plus ultrasound (P = .003 that difference is 0). Of 12 supplemental cancers detected by ultrasound alone, 11 (92%) were invasive with a median size of 10 mm (range, 5-40 mm; mean [SE], 12.6 [3.0] mm) and 8 of the 9 lesions (89%) reported had negative nodes. The positive predictive value of biopsy recommendation after full diagnostic workup was 19 of 84 for mammography (22.6%; 95% CI, 14.2%-33%), 21 of 235 for ultrasound (8.9%, 95% CI, 5.6%-13.3%), and 31 of 276 for combined mammography plus ultrasound (11.2%; 95% CI. 7.8%-15.6%).

CONCLUSIONS

Adding a single screening ultrasound to mammography will yield an additional 1.1 to 7.2 cancers per 1000 high-risk women, but it will also substantially increase the number of false positives.

TRIAL REGISTRATION

clinicaltrials.gov Identifier: NCT00072501.

Predicting risk of breast cancer in postmenopausal women by hormone receptor status

BACKGROUND

Strategies for estrogen receptor (ER)-positive breast cancer risk reduction in postmenopausal women require screening of large populations to identify those with potential benefit. We evaluated and attempted to improve the performance of the Breast Cancer Risk Assessment Tool (i.e., the Gail model) for estimating invasive breast cancer risk by receptor status in postmenopausal women.

METHODS

In The Women's Health Initiative cohort, breast cancer risk estimates from the Gail model and models incorporating additional or fewer risk factors and 5-year incidence of ER-positive and ER-negative invasive breast cancers were determined and compared by use of receiver operating characteristics and area under the curve (AUC) statistics. All statistical tests were two-sided.

RESULTS

Among 147,916 eligible women, 3236 were diagnosed with invasive breast cancer. The overall AUC for the Gail model was 0.58 (95% confidence interval [CI]=0.56 to 0.60). The Gail model underestimated 5-year invasive breast cancer incidence by approximately 20% (P<.001), mostly among those with a low estimated risk. Discriminatory performance was better for the risk of ER-positive cancer (AUC = 0.60, 95% CI = 0.58 to 0.62) than for the risk of ER-negative cancer (AUC = 0.50, 95% CI = 0.45 to 0.54). Age and age at menopause were statistically significantly associated with ER-positive but not ER-negative cancers (P=.05 and P=.04 for heterogeneity, respectively). For ER-positive cancers, no additional risk factors substantially improved the Gail model prediction. However, a simpler model that included only age, breast cancer in first-degree relatives, and previous breast biopsy examination performed similarly for ER-positive breast cancer prediction (AUC=0.58, 95% CI= 0.56 to 0.60); postmenopausal women who were 55 years or older with either a previous breast biopsy examination or a family history of breast cancer had a 5-year breast cancer risk of 1.8% or higher.

CONCLUSIONS

In postmenopausal women, the Gail model identified populations at increased risk for ER-positive but not ER-negative breast cancers. A model with fewer variables appears to provide a simpler approach for screening for breast cancer risk.