Modeling risks of cardiovascular and cancer mortality following a diagnosis of loco-regional breast cancer.

BACKGROUND: Many women with breast cancer also have a high likelihood of cardiovascular mortality, and while there are several cardiovascular risk prediction models, none have been validated in a cohort of breast cancer patients. We first compared the performance of commonly-used cardiovascular models, and then derived a new model where breast cancer and cardiovascular mortality were modeled simultaneously, to account for the competing risk endpoints and commonality of risk factors between the two events. METHODS: We included 20,462 women diagnosed with stage I-III breast cancer between 2000 and 2010 in Kaiser Permanente Northern California (KPNC) with follow-up through April 30, 2015, and examined the performance of the Framingham, CORE and SCOREOP cardiovascular risk models by area under the receiver operating characteristic curve (AUC), and observed-to -expected (O/E) ratio. We developed a multi-state model based on cause-specific hazards (CSH) to jointly model the causes of mortality. RESULTS: The extended models including breast cancer characteristics (grade, tumor size, nodal involvement) with CVD risk factors had better discrimination at 5-years with AUCs of 0.85 (95% CI 0.83, 0.86) for cardiovascular death and 0.80 (95% CI 0.78, 0.87) for breast cancer death compared with the existing cardiovascular models evaluated at 5 years AUCs ranging 0.71-0.78. Five-year calibration for breast and cardiovascular mortality from our multi-state model was also excellent (O/E = 1.01, 95% CI 0.91-1.11). CONCLUSION: A model incorporating cardiovascular risk factors, breast cancer characteristics, and competing events, outperformed traditional models of cardiovascular disease by simultaneously estimating cancer and cardiovascular mortality risks.

Considerations When Using Breast Cancer Risk Models for Women with Negative BRCA1/BRCA2 Mutation Results.

The performance of breast cancer risk models for women with a family history but negative BRCA1 and/or BRCA2 mutation test results is uncertain. We calculated the cumulative 10-year invasive breast cancer risk at cohort entry for 14 657 unaffected women (96.1% had an affected relative) not known to carry BRCA1 or BRCA2 mutations at baseline using three pedigree-based models (Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm, BRCAPRO, and International Breast Cancer Intervention Study). During follow-up, 482 women were diagnosed with invasive breast cancer. Mutation testing was conducted independent of incident cancers. All models underpredicted risk by 26.3%-56.7% for women who tested negative but whose relatives had not been tested (n = 1363; 63 breast cancers). Although replication studies with larger sample sizes are needed, until these models are recalibrated for women who test negative and have no relatives tested, caution should be used when considering changing the breast cancer risk management intensity of such women based on risk estimates from these models.

10-year performance of four models of breast cancer risk: a validation study.

BACKGROUND: Independent validation is essential to justify use of models of breast cancer risk prediction and inform decisions about prevention options and screening. Few independent validations had been done using cohorts for common breast cancer risk prediction models, and those that have been done had small sample sizes and short follow-up periods, and used earlier versions of the prediction tools. We aimed to validate the relative performance of four commonly used models of breast cancer risk and assess the effect of limited data input on each one's performance. METHODS: In this validation study, we used the Breast Cancer Prospective Family Study Cohort (ProF-SC), which includes 18 856 women from Australia, Canada, and the USA who did not have breast cancer at recruitment, between March 17, 1992, and June 29, 2011. We selected women from the cohort who were 20-70 years old and had no previous history of bilateral prophylactic mastectomy or ovarian cancer, at least 2 months of follow-up data, and information available about family history of breast cancer. We used this selected cohort to calculate 10-year risk scores and compare four models of breast cancer risk prediction: the Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm model (BOADICEA), BRCAPRO, the Breast Cancer Risk Assessment Tool (BCRAT), and the International Breast Cancer Intervention Study model (IBIS). We compared model calibration based on the ratio of the expected number of breast cancer cases to the observed number of breast cancer cases in the cohort, and on the basis of their discriminatory ability to separate those who will and will not have breast cancer diagnosed within 10 years as measured with the concordance statistic (C-statistic). We did subgroup analyses to compare the performance of the models at 10 years in BRCA1 or BRCA2 mutation carriers (ie, BRCA-positive women), tested non-carriers and untested participants (ie, BRCA-negative women), and participants younger than 50 years at recruitment. We also assessed the effect that limited data input (eg, restriction of the amount of family history and non-genetic information included) had on the models' performance. FINDINGS: After median follow-up of 11·1 years (IQR 6·0-14·4), 619 (4%) of 15 732 women selected from the ProF-SC cohort study were prospectively diagnosed with breast cancer after recruitment, of whom 519 (84%) had histologically confirmed disease. BOADICEA and IBIS were well calibrated in the overall validation cohort, whereas BRCAPRO and BCRAT underpredicted risk (ratio of expected cases to observed cases 1·05 [95% CI 0·97-1·14] for BOADICEA, 1·03 [0·96-1·12] for IBIS, 0·59 [0·55-0·64] for BRCAPRO, and 0·79 [0·73-0·85] for BRCAT). The estimated C-statistics for the complete validation cohort were 0·70 (95% CI 0·68-0·72) for BOADICEA, 0·71 (0·69-0·73) for IBIS, 0·68 (0·65-0·70) for BRCAPRO, and 0·60 (0·58-0·62) for BCRAT. In subgroup analyses by BRCA mutation status, the ratio of expected to observed cases for BRCA-negative women was 1·02 (95% CI 0·93-1·12) for BOADICEA, 1·00 (0·92-1·10) for IBIS, 0·53 (0·49-0·58) for BRCAPRO, and 0·97 (0·89-1·06) for BCRAT. For BRCA-positive participants, BOADICEA and IBIS were well calibrated, but BRCAPRO underpredicted risk (ratio of expected to observed cases 1·17 [95% CI 0·99-1·38] for BOADICEA, 1·14 [0·96-1·35] for IBIS, and 0·80 [0·68-0·95] for BRCAPRO). We noted similar patterns of calibration for women younger than 50 years at recruitment. Finally, BOADICEA and IBIS predictive scores were not appreciably affected by limiting input data to family history for first-degree and second-degree relatives. INTERPRETATION: Our results suggest that models that include multigenerational family history, such as BOADICEA and IBIS, have better ability to predict breast cancer risk, even for women at average or below-average risk of breast cancer. Although BOADICEA and IBIS performed similarly, further improvements in the accuracy of predictions could be possible with hybrid models that incorporate the polygenic risk component of BOADICEA and the non-family-history risk factors included in IBIS. FUNDING: US National Institutes of Health, National Cancer Institute, Breast Cancer Research Foundation, Australian National Health and Medical Research Council, Victorian Health Promotion Foundation, Victorian Breast Cancer Research Consortium, Cancer Australia, National Breast Cancer Foundation, Queensland Cancer Fund, Cancer Councils of New South Wales, Victoria, Tasmania, and South Australia, and Cancer Foundation of Western Australia.

Mortality after breast cancer as a function of time since diagnosis by estrogen receptor status and age at diagnosis.

Our aim was to estimate how long-term mortality following breast cancer diagnosis depends on age at diagnosis, tumor estrogen receptor (ER) status, and the time already survived. We used the population-based Australian Breast Cancer Family Study which followed-up 1,196 women enrolled during 1992-1999 when aged <60 years at diagnosis with a first primary invasive breast cancer, over-sampled for younger ages at diagnosis, for whom tumor pathology features and ER status were measured. There were 375 deaths (median follow-up = 15.7; range = 0.8-21.4, years). We estimated the mortality hazard as a function of time since diagnosis using a flexible parametric survival analysis with ER status a time-dependent covariate. For women with ER-negative tumors compared with those with ER-positive tumors, 5-year mortality was initially higher (p < 0.001), similar if they survived to 5 years (p = 0.4), and lower if they survived to 10 years (p = 0.02). The estimated mortality hazard for ER-negative disease peaked at ~3 years post-diagnosis, thereafter declined with time, and at 7 years post-diagnosis became lower than that for ER-positive disease. This pattern was more pronounced for women diagnosed at younger ages. Mortality was also associated with lymph node count (hazard ratio (HR) per 10 nodes = 2.52 [95% CI:2.11-3.01]) and tumor grade (HR per grade = 1.62 [95% CI:1.34-1.96]). The risk of death following a breast cancer diagnosis differs substantially and qualitatively with diagnosis age, ER status and time survived. For women who survive >7 years, those with ER-negative disease will on average live longer, and more so if younger at diagnosis.

Risk-Reducing Oophorectomy and Breast Cancer Risk Across the Spectrum of Familial Risk.

There remains debate about whether risk-reducing salpingo-oophorectomy (RRSO), which reduces ovarian cancer risk, also reduces breast cancer risk. We examined the association between RRSO and breast cancer risk using a prospective cohort of 17 917 women unaffected with breast cancer at baseline (7.2% known carriers of BRCA1 or BRCA2 mutations). During a median follow-up of 10.7 years, 1046 women were diagnosed with incident breast cancer. Modeling RRSO as a time-varying exposure, there was no association with breast cancer risk overall (hazard ratio [HR] = 1.04, 95% confidence interval [CI] = 0.87 to 1.24) or by tertiles of predicted absolute risk based on family history (HR = 0.68, 95% CI = 0.32 to 1.47, HR = 0.94, 95% CI = 0.70 to 1.26, and HR = 1.10, 95% CI = 0.88 to 1.39, for lowest, middle, and highest tertile of risk, respectively) or for BRCA1 and BRCA2 mutation carriers when examined separately. There was also no association after accounting for hormone therapy use after RRSO. These findings suggest that RRSO should not be considered efficacious for reducing breast cancer risk.

Advancing Understanding of the Characteristics and Capacity of African American Women Who Serve as Lay Health Advisors in Community-Based Settings.

Lay Health Advisor (LHA) programs hold tremendous promise for reducing health disparities and addressing social determinants of health in medically underserved communities, including African American populations. Very little is understood about the capacity of LHAs in these roles and the broader contributions they make to their communities. This article seeks to address this gap by describing the characteristics and capacity of a sample of 76 female African American LHAs from a nationally disseminated evidence-based LHA program for breast and cervical cancer screening (The National Witness Project), as well as potential differences between cancer survivors and nonsurvivors who serve as LHAs. A conceptual model for understanding LHA capacity and contributions in underserved communities at the individual, social, and organizational levels is presented. We describe LHA experiences and characteristics (e.g., experiences of mistrust and discrimination, racial pride, sociodemographics), capacity at the individual level (e.g., psychological and physical health, health behaviors), capacity at the social level (e.g., social networks, social support), and capacity at the organizational level (e.g., role-related competencies, self-efficacy, leadership, role benefits/challenges). Data were obtained through interview-administered telephone surveys between 2010 and 2011. Findings highlight the critical capacity that LHAs bring to their communities and the importance of supporting LHAs to sustain these programs and to address racial/ethnic health disparities.

Predictors of activity level and retention among African American lay health advisors (LHAs) from The National Witness Project: Implications for the implementation and sustainability of community-based LHA programs from a longitudinal study.

BACKGROUND: Lay health advisor (LHA) programs are increasingly being implemented in the USA and globally in the context of health promotion and disease prevention. LHAs are effective in addressing health disparities when used to reach medically underserved populations, with strong evidence among African American and Hispanic women. Despite their success and the evidence supporting implementation of LHA programs in community settings, there are tremendous barriers to sustaining LHA programs and little is understood about their implementation and sustainability in "real-world" settings. The purpose of this study was to (1) propose a conceptual framework to investigate factors at individual, social, and organizational levels that impact LHA activity and retention; and (2) use prospective data to investigate the individual, social, and organizational factors that predict activity level and retention among a community-based sample of African American LHAs participating in an effective, evidence-based LHA program (National Witness Project; NWP). METHODS: Seventy-six LHAs were recruited from eight NWP sites across the USA. Baseline predictor data was collected from LHAs during a telephone questionnaire administered between 2010 and 2011. Outcome data on LHA participation and program activity levels were collected in the fall of 2012 from NWP program directors. Chi-square and ANOVA tests were used to identify differences between retained and completely inactive LHAs, and LHAs with high/moderate vs. low/no activity levels. Multivariable logistic regression models were conducted to identify variables that predicted LHA retention and activity levels. RESULTS: In multivariable models, LHAs based at sites with academic partnerships had increased odds of retention and high/moderate activity levels, even after adjusting for baseline LHA activity level. Higher religiosity among LHAs was associated with decreased odds of being highly/moderately active. LHA role clarity and self-efficacy were associated with retention and high/moderate activity in multivariable models unadjusted for baseline LHA activity level. CONCLUSIONS: Organizational and role-related factors are critical in influencing the retention and activity levels of LHAs. Developing and fostering partnerships with academic institutions will be important strategies to promote successful implementation and sustainability of LHA programs. Clarifying role expectations and building self-efficacy during LHA recruitment and training should be further explored to promote LHA retention and participation.

Non-initiation and early discontinuation of adjuvant trastuzumab in women with localized HER2-positive breast cancer.

One year of trastuzumab therapy is recommended for women with HER2-positive breast cancer ≥ 1.0 cm in size to increase survival and is considered for women with tumors 0.5-0.9 cm in size. We analyzed compliance with trastuzumab among women with HER2-positive breast cancer in a prospective cohort study. Of 1145 recruited patients with breast cancer, 152 were HER2-positive (13.2 %), of whom 126 had tumors ≥ 1.0 cm; 110/126 (87.3 %) of these initiated trastuzumab. Non-receipt was associated with older age, better prognosis tumors, and with non-receipt of adjuvant chemotherapy. Of the 110 who initiated treatment, 18 (15 %) did not complete treatment, 15 (83 %) of them because of cardiotoxicity. Of 20 women with tumors 0.5-0.9 cm, 5 (25 %) initiated trastuzumab. Compliance with trastuzumab was very high among those with HER2-positive breast cancer, as was the completion of the recommended therapy.

Changes in the availability of screening mammography, 2000-2010.

BACKGROUND: Rates of screening mammography have plateaued, and the number of mammography facilities has declined in the past decade. The objective of this study was to assess changes over time and geographic disparities in the availability of mammography services. METHODS: Using information from the US Food and Drug Administration and the US Census, county-level mammography capacity was defined as the number of mammography machines per 10,000 women aged ≥ 40 years. Cross-sectional variation and longitudinal changes in capacity were examined in relation to county characteristics. RESULTS: Between 2000 and 2010, the number of mammography facilities declined 10% from 9434 to 8469, the number of mammography machines declined 10% from 13,100 to 11,762, and the median county mammography capacity decreased nearly 20% from 1.77 to 1.42 machines per 10,000 women aged ≥ 40 years. In cross-sectional analysis, counties with greater percentages of uninsured residents, less educated residents, greater population density, and higher managed care penetration had lower mammography capacity. Conversely, counties with more hospital beds per 100,000 population had higher capacity. High initial mammography capacity, growth in both the percentage of the population aged ≥ 65 years and the percentage living in poverty, and increased managed care penetration were all associated with a decrease in mammography capacity between 2000 and 2010. Only the percentage of rural residents was associated with an increase in capacity. CONCLUSIONS: Geographic variation in mammography capacity and declines in capacity over time are associated with demographic, socioeconomic, and health care market characteristics. Maldistribution of mammography resources may explain geographic disparities in breast cancer screening rates.

Racial disparities in posttraumatic stress after diagnosis of localized breast cancer: the BQUAL study.

BACKGROUND: Little is known about the development of posttraumatic stress disorder (PTSD) over time among women diagnosed with breast cancer. This study examines changes in PTSD symptoms in the first 6 months after diagnosis and assesses racial/ethnic differences in PTSD symptomatology over time. METHODS: We recruited women with newly diagnosed breast cancer, stages I to III, from three sites in the United States. Three telephone interviews were conducted: baseline at about 2 to 3 months after diagnosis, first follow-up at 4 months after diagnosis, and second follow-up at 6 months after diagnosis. We measured traumatic stress in each interview using the Impact of Events Scale; recorded sociodemographic, tumor, and treatment factors; and used generalized estimating equations and polytomous logistic regression modeling to examine the associations between variables of interest and PTSD. RESULTS: Of 1139 participants, 23% reported symptoms consistent with a diagnosis of PTSD at baseline, 16.5% at first follow-up, and 12.6% at the second follow-up. Persistent PTSD was observed among 12.1% participants, as defined by having PTSD at two consecutive interviews. Among participants without PTSD at baseline, 6.6% developed PTSD at the first follow-up interview. Younger age at diagnosis, being black (odds ratio [OR] = 1.48 vs white, 95% confidence interval [CI] =1.04 to 2.10), and being Asian (OR = 1.69 vs white, 95% CI = 1.10 to 2.59) were associated with PTSD. CONCLUSIONS: Nearly one-quarter of women newly diagnosed with breast cancer reported symptoms consistent with PTSD shortly after diagnosis, with increased risk among black and Asian women. Early identification of PTSD may present an opportunity to provide interventions to manage symptoms.

Interpersonal influences and attitudes about adjuvant therapy treatment decisions among non-metastatic breast cancer patients: an examination of differences by age and race/ethnicity in the BQUAL study.

Patients are increasingly involved in cancer treatment decisions and yet little research has explored factors that may affect patient attitudes and beliefs about their therapeutic choices. This paper examines psychosocial factors (e.g., attitudes, social support), provider-related factors (e.g., communication, trust), and treatment considerations in a prospective study of a sample of non-metastatic breast cancer patients eligible for chemotherapy and/or hormonal therapy (BQUAL cohort). The data come from a multisite cohort study of white, black, Hispanic, and Asian non-metastatic breast cancer patients recruited in New York City, Northern California, and Detroit, Michigan. Baseline surveys were conducted over the telephone between 2006 and 2010 among a total of 1,145 women. Most participants were white (69 %), had more than a high school education (76 %), and were diagnosed with stage I disease (51 %). The majority of women reported discussing chemotherapy and hormonal therapy with their doctor (90 and 83 %, respectively); these discussions primarily took place with medical oncologists. Nearly a quarter of women reported that the treatment decision was difficult, and the majority were accompanied to the doctor (76 %) and involved a friend or family member in making the decision (54 %). Positive considerations (e.g., beliefs about treatment reducing risk of recurrence) were important in making treatment decisions. Participants preferred a shared decision-making style, but results suggested that there is room for improvement in terms of actual patient's involvement in making the decision and provider communication, particularly among black patients. Patients 65 years and older reported fewer provider discussions of chemotherapy, poorer patient-provider communication, higher rates of being assisted by family members in making the decision, and more negative attitudes and beliefs toward treatment.

Noninitiation of adjuvant chemotherapy in women with localized breast cancer: the breast cancer quality of care study.

PURPOSE: For some women, adjuvant chemotherapy for nonmetastatic breast cancer decreases recurrences and increases survival; however, patient-physician decisions regarding chemotherapy receipt can be influenced by medical and nonmedical factors. PATIENTS AND METHODS: We used a prospective cohort design and multivariate modeling to investigate factors related to noninitiation of chemotherapy among women with newly diagnosed breast cancer recruited from three US sites. We interviewed patients at baseline and during treatment on sociodemographic, tumor, and treatment decision-making factors. Patients were categorized according to National Comprehensive Cancer Network guidelines as those for whom chemotherapy was definitely indicated, clinically discretionary, or discretionary based on age greater than 70 years. RESULTS: Of 1,145 patients recruited, chemotherapy was clinically indicated for 392 patients, clinically discretionary for 459 patients, discretionary because of age for 169 patients, and not indicated for 93 patients; data were insufficient for 32 patients. Chemotherapy rates were 90% for those in whom chemotherapy was clinically indicated, 36% for those in whom it was discretionary because of clinical factors, and 19% for those in whom it was discretionary based on age greater than 70 years. Nonreceipt of chemotherapy was associated with older age, more negative beliefs about treatment efficacy, less positive beliefs about chemotherapy, and more concern about adverse effects. In the two discretionary groups, clinical predictors of worse outcome (greater tumor size, positive nodes, worse grade, and estrogen receptor- and progesterone receptor-negative status) were associated with increased chemotherapy initiation. CONCLUSION: Utilization of adjuvant chemotherapy was most common among patients who, based on clinical criteria, would most likely benefit from it, patients with more positive than negative beliefs regarding treatment efficacy, and patients with few concerns about adverse effects.

Non-initiation of adjuvant hormonal therapy in women with hormone receptor-positive breast cancer: The Breast Cancer Quality of Care Study (BQUAL).

Adjuvant hormonal therapy for non-metastatic hormone receptor (HR)-positive breast cancer decreases risk of breast cancer recurrence and increases survival. However, some women do not initiate this life-saving treatment. We used a prospective cohort design to investigate factors related to non-initiation of hormonal therapy among women with newly diagnosed, non-metastatic HR-positive breast cancer recruited from three U.S. sites. Serial interviews were conducted at baseline and during treatment to examine sociodemographic factors, tumor characteristics, and treatment decision-making factors. Multivariate modeling assessed associations between variables of interest and hormonal therapy initiation. Of 1,050 breast cancer patients recruited, 725 (69%) had HR-positive breast cancer, of whom 87 (12.0%) based on self-report and 122 (16.8%) based on medical record/pharmacy fill rates did not initiate hormonal therapy. In a multivariable analysis, non-initiation of hormonal therapy, defined by medical record/pharmacy, was associated with having greater negative beliefs about efficacy of treatment (OR 1.42, 95% CI 1.18-1.70). Non-initiation was less likely in those who found the quality of patient/physician communication to be higher (OR 0.96, 95% CI 0.93-0.99), the hormonal therapy treatment decision an easy one to make (OR 0.45, 95% CI 0.23-0.90) or neither easy nor difficult (OR 0.34, 95% CI 0.20-0.58); and had more positive beliefs about hormonal therapy efficacy (OR 0.40, 95% CI 0.34-0.62). Factors influencing non-initiation of adjuvant hormonal therapy are complex and influenced by patient beliefs regarding treatment efficacy and side effects. Educational interventions to women about the benefits of hormonal therapy may decrease negative beliefs and increase hormone therapy initiation.

Mammography capacity and appointment wait times: barriers to breast cancer screening.

OBJECTIVE: To assess the impact of mammography capacity on appointment wait times. METHODS: We surveyed by telephone all mammography facilities federally certified in 2008 in California, Connecticut, Georgia, Iowa, New Mexico, and New York using a simulated patient format. County-level mammography capacity, defined as the number of mammography machines per 10,000 women aged 40 and older, was estimated from FDA facility certification records and US Census data. RESULTS: 1,614 (86%) of 1,882 mammography facilities completed the survey. Time until next available screening mammogram appointment was <1 week at 55% of facilities, 1-4 weeks at 34% of facilities, and >1 month at 11% of facilities. Facilities in counties with lower capacity had longer wait times, and a one-unit increase in county capacity was associated with 21% lower odds of a facility reporting a wait time >1 month (p < 0.01). There was no association between wait time and the availability of evening or weekend appointments or digital mammography. CONCLUSION: Lower mammography capacity is associated with longer wait times for screening mammograms. IMPACT: Enhancement of mammography resources in areas with limited capacity may reduce wait times for screening mammogram appointments, thereby increasing access to services and rates of breast cancer screening.