Medication delivery factors and adjuvant endocrine therapy adherence in breast cancer.

PURPOSE: Over 50% of breast cancer patients prescribed a 5-year course of daily oral adjuvant endocrine therapy (ET) are nonadherent. We investigated the role of costs and cancer medication delivery mode and other medication delivery factors on adherence. METHODS: We conducted a retrospective cohort study of commercially insured and Medicare advantage patients with newly diagnosed breast cancer in 2007-2015 who initiated ET. We examined the association between 12-month ET adherence (proportion of days covered by fills ≥ 0.80) and ET copayments, 90-day prescription refill use, mail order pharmacy use, number of pharmacies, and synchronization of medications. We used regression models to estimate nonadherence risk ratios adjusted for demographics (age, income, race, urbanicity), comorbidities, total medications, primary cancer treatments, and generic AI availability. Sensitivity analyses were conducted using alternative specifications for independent variables. RESULTS: Mail order users had higher adherence in both commercial and Medicare-insured cohorts. Commercially insured patients who used mail order were more likely to be adherent if they had low copayments (< $5) and 90-day prescription refills. For commercially insured patients who used local pharmacies, use of one pharmacy and better synchronized refills were also associated with adherence. Among Medicare patients who used mail order pharmacies, only low copayments were associated with adherence, while among Medicare patients using local pharmacies both low copayments and 90-day prescriptions were associated with ET adherence. CONCLUSION: Out-of-pocket costs, medication delivery mode, and other pharmacy-related medication delivery factors are associated with adherence to breast cancer ET. Future work should investigate whether interventions aimed at streamlining medication delivery could improve adherence for breast cancer patients.

Nonparametric failure time: Time-to-event machine learning with heteroskedastic Bayesian additive regression trees and low information omnibus Dirichlet process mixtures.

Many popular survival models rely on restrictive parametric, or semiparametric, assumptions that could provide erroneous predictions when the effects of covariates are complex. Modern advances in computational hardware have led to an increasing interest in flexible Bayesian nonparametric methods for time-to-event data such as Bayesian additive regression trees (BART). We propose a novel approach that we call nonparametric failure time (NFT) BART in order to increase the flexibility beyond accelerated failure time (AFT) and proportional hazard models. NFT BART has three key features: (1) a BART prior for the mean function of the event time logarithm; (2) a heteroskedastic BART prior to deduce a covariate-dependent variance function; and (3) a flexible nonparametric error distribution using Dirichlet process mixtures (DPM). Our proposed approach widens the scope of hazard shapes including nonproportional hazards, can be scaled up to large sample sizes, naturally provides estimates of uncertainty via the posterior and can be seamlessly employed for variable selection. We provide convenient, user-friendly, computer software that is freely available as a reference implementation. Simulations demonstrate that NFT BART maintains excellent performance for survival prediction especially when AFT assumptions are violated by heteroskedasticity. We illustrate the proposed approach on a study examining predictors for mortality risk in patients undergoing hematopoietic stem cell transplant (HSCT) for blood-borne cancer, where heteroskedasticity and nonproportional hazards are likely present.

Improved Prediction of Older Adult Discharge After Trauma Using a Novel Machine Learning Paradigm.

BACKGROUND: The ability to reliably predict outcomes after trauma in older adults (age ≥ 65 y) is critical for clinical decision making. Using novel machine-learning techniques, we sought to design a nonlinear, competing risks paradigm for prediction of older adult discharge disposition following injury. MATERIALS AND METHODS: The National Trauma Databank (NTDB) was used to identify patients 65+ y between 2007 and 2014. Training was performed on an enriched cohort of diverse patients. Factors included age, comorbidities, length of stay, and physiologic parameters to predict in-hospital mortality and discharge disposition (home versus skilled nursing/long-term care facility). Length of stay and discharge status were analyzed via competing risks survival analysis with Bayesian additive regression trees and a multinomial mixed model. RESULTS: The resulting sample size was 47,037 patients. Admission GCS and age were important in predicting mortality and discharge disposition. As GCS decreased, patients were more likely to die (risk ratio increased by average of 1.4 per 2-point drop in GCS, P < 0.001). As GCS decreased, patients were also more likely to be discharged to a skilled nursing or long-term care facility (risk ratio decreased by 0.08 per 2-point decrease in GCS, P< 0.001). The area under curve for prediction of discharge home was improved in the competing risks model 0.73 versus 0.43 in the traditional multinomial mixed model. CONCLUSIONS: Predicting older adult discharge disposition after trauma is improved using machine learning over traditional regression analysis. We confirmed that a nonlinear, competing risks paradigm enhances prediction on any given hospital day post injury.

Feasibility of a pharmacist-led symptom monitoring and management intervention to improve breast cancer endocrine therapy adherence.

BACKGROUND: Adjuvant endocrine therapy (AET) for breast cancer reduces mortality, but one-third to one-half of patients discontinue it early or are nonadherent. OBJECTIVE: We developed a pilot single-site study of patients with evidence of early nonadherence to AET to assess the feasibility of a novel, clinical pharmacist-led intervention targeting symptom and medication management. METHODS: Patients with prescription fill records showing nonadherence were enrolled in a single-arm feasibility study. Automated reminders were sent by e-mail or text with a link to symptom monitoring assessments weekly for 1 month and monthly until 6 months. Clinical oncology pharmacists used guideline-based symptom management and other medication management tools to support adherence and ameliorate symptoms reported on the assessments. Patient-reported outcome assessments included physical, mental, and social health domains and self-efficacy to manage symptoms and medications. Feasibility outcomes included completion of symptom reports and pharmacist recommendations. RESULTS: Of 19 participants who were nonadherent who enrolled and completed initial assessments, 18 completed all final study procedures, with 14 completing all assessments and no patient missing more than 3 assessments. All 18 participants reported at least one of 3 symptom types, and the majority reported attempting pharmacist recommendations. Patient-reported measures of physical, mental, and social health and self-efficacy improved, and 44% of the patients became adherent. CONCLUSION: An intervention using pharmacists in an oncology practice to systematically monitor and manage symptoms shows promise to reduce symptoms, enhance support and self-efficacy, and improve adherence to AET.

Impact of Pre-visit Contextual Data Collection on Patient-Physician Communication and Patient Activation: a Randomized Trial.

BACKGROUND: Patient contextual data (PCD) are often missing from electronic health records, limiting the opportunity to incorporate preferences and life circumstances into care. Engaging patients through tools that collect and summarize such data may improve communication and patient activation. However, differential tool adoption by race might widen health care disparities. OBJECTIVE: Determine if a digital tool designed to collect and present PCD improves communication and patient activation; secondarily, evaluate if use impacts outcomes by race. DESIGN, SETTING, AND PARTICIPANTS: A pragmatic, two-armed, non-blinded, randomized controlled trial conducted during 2019 in a primary care setting. INTERVENTION: The PCD tool (PatientWisdom) invited patients to identify preferences, values, goals, and barriers to care. Patients were randomized to a standard pre-visit email or facilitated enrollment with dedicated outreach to encourage use of the tool. MAIN OUTCOMES AND MEASURES: Outcomes of interest were post-visit patient communication and patient activation measured by the Communication Assessment Tool (CAT) and Patient Activation Measure (PAM), respectively. Outcomes were evaluated using treatment-on-the-treated (TOT) and intention-to-treat (ITT) principles. KEY RESULTS: A total of 301 patients were enrolled. Facilitated enrollment resulted in a five-fold increase in uptake of the PCD tool. TOT analysis indicated that the PCD tool was associated with notable increases in specific CAT items rated as excellent: "treated me with respect" (+ 13 percentage points; p = 0.04), "showed interest in my ideas" (+ 14 percentage points; p = 0.03), "showed care and concern" (+ 16 percentage points; p = 0.02), and "spent about the right amount of time with me" (+ 11 percentage points; p = 0.05). There were no significant pre/post-visit differences in PAM scores between arms (- 4.41 percentage points; p = 0.58). ITT results were similar. We saw no evidence of the treatment effect varying by race in ITT or TOT analyses. CONCLUSIONS AND RELEVANCE: The inclusion of PCD enhanced essential aspects of patient-provider communication but did not affect patient activation. Outcomes did not differ by race. TRIAL REGISTRATION: Clincaltrials.gov identifier: NCT03766841.

Pharmacy deserts and patients with breast cancer receipt of influenza vaccines.

BACKGROUND: Yearly influenza vaccination is strongly recommended at age 65 and reimbursed by Medicare without copays or deductibles at pharmacies and clinical settings. Uptake is low among patients with a high risk for influenza complications and good access to specialist care, such as recent cancer survivors. We hypothesized that more accessible pharmacies could be associated with higher immunization uptake in such patients. OBJECTIVES: To determine whether pharmacy access is associated with influenza vaccination in subjects recently diagnosed with breast cancer, and whether this association differs by additional risk factors for influenza complications. METHODS: We examined a cohort of patients with stage 0-III breast cancer diagnosed 2011-2015 from the Surveillance, Epidemiology, and End Results-Medicare cancer registry. All retail pharmacies in the United States were identified, and pharmacy access was measured by assessing supply and demand in each census tract using a 2-stage floating catchment area approach that accounted for pharmacy driving distances recommended by the Centers for Medicare and Medicaid Services. We examined the association of pharmacy access with influenza vaccination after breast cancer diagnosis in regression models. RESULTS: More than 11% of 45,722 patients with breast cancer lived in census tracts where no pharmacies were within recommended driving distances from the population-weighted tract center. Vaccination in the year after diagnosis was less likely for patients in these very low-access tracts (adjusted odds ratio 0.92 [95% CI 0.86-0.96]), black (0.55 [0.51-0.60]) and Hispanic (0.76 [0.70-0.83]) women, and Medicaid recipients (0.74 [0.69-0.79]). Vaccination was inversely associated with per capita income in the subject's census tract, but there was no difference in the pharmacy effect by race, ethnicity, or census tract income. CONCLUSION: Very low pharmacy access is associated with modest reductions in vaccination that could be useful for policy and planning regarding vaccinator resources and outreach.

A dependent Dirichlet process model for survival data with competing risks.

In this paper, we first propose a dependent Dirichlet process (DDP) model using a mixture of Weibull models with each mixture component resembling a Cox model for survival data. We then build a Dirichlet process mixture model for competing risks data without regression covariates. Next we extend this model to a DDP model for competing risks regression data by using a multiplicative covariate effect on subdistribution hazards in the mixture components. Though built on proportional hazards (or subdistribution hazards) models, the proposed nonparametric Bayesian regression models do not require the assumption of constant hazard (or subdistribution hazard) ratio. An external time-dependent covariate is also considered in the survival model. After describing the model, we discuss how both cause-specific and subdistribution hazard ratios can be estimated from the same nonparametric Bayesian model for competing risks regression. For use with the regression models proposed, we introduce an omnibus prior that is suitable when little external information is available about covariate effects. Finally we compare the models' performance with existing methods through simulations. We also illustrate the proposed competing risks regression model with data from a breast cancer study. An R package "DPWeibull" implementing all of the proposed methods is available at CRAN.

Prevalence and scope of advanced practice provider oncology care among Medicare beneficiaries with breast cancer.

PURPOSE: Advanced practice providers (APPs) have increasingly become members of the oncology care team. Little is known about the scope of care that APPs are performing nationally. We determined the prevalence and extent of APP practice and examined associations between APP care and scope of practice regulations, phase of cancer care, and patient characteristics. METHODS: We performed an observational study among women identified from Medicare claims as having had incident breast cancer in 2008 with claims through 2012. Outpatient APP care included at least one APP independently billing for cancer visits/services. APP scope of practice was classified as independent, reduced, or restricted. A logistic regression model with patient-level random effects was estimated to determine the probability of receiving APP care at any point during active treatment or surveillance. RESULTS: Among 42,550 women, 6583 (15%) received APP care, of whom 83% had APP care during the surveillance phase and 41% during the treatment phase. Among women who received APP care during a given year of surveillance, the overall proportion of APP-billed clinic visits increased with each additional year of surveillance (36% in Year 1 to 61% in Year 4). Logistic regression model results indicate that women were more likely to receive APP care if they were younger, black, healthier, had higher income status, or lived in a rural county or state with independent APP scope of practice. CONCLUSIONS: This study provides important clinical and policy-relevant findings regarding national practice patterns of APP oncology care. Among Medicare beneficiaries with incident breast cancer, 15% received outpatient oncology care that included APPs who were billing; most of this care was during the surveillance phase. Future studies are needed to define the degree of APP oncology practice and training that maximizes patient access and satisfaction while optimizing the efficiency and quality of cancer care.

The impact of generic aromatase inhibitors on initiation, adherence, and persistence among women with breast cancer: Applying multi-state models to understand the dynamics of adherence.

PURPOSE: Clinical trials have clearly documented the survival benefit of aromatase inhibitors (AIs); however, many women fail to initiate (primary nonadherence) or remain adherent to AIs (secondary nonadherence). Prior studies have found that costs impact secondary nonadherence to medications but have failed to examine primary nonadherence. The purpose of this study is to examine primary and secondary adherence following the reduction in copays due to the introduction of generic AIs. METHODS: Using Surveillance, Epidemiology, and End Results-Medicare data, we identified 50 054 women diagnosed with incident breast cancer between 2008 and 2013. We compare women whose copays would change and those whose would not, due to the receipt of cost-sharing subsidies before and after generics were introduced using a difference-in-difference (DinD) analysis. To examine primary and secondary nonadherence, we rely on a multistate model with four states (Not yet initiated, User, Not Using, and Death). We adjusted for baseline factors using inverse probability treatment weights and then simulated adherence for 36 months following diagnosis. RESULTS: The generic introduction of AIs resulted in patients initiating AIs faster (DinD = -4.7%, 95%CI = -7.0, -2.3; patients not yet initiating treatment at 6-months), being more adherent (DinD ranging in absolute increase of 8.1%-10.4%) and being less likely to not be using the therapy (DinD range in absolute decrease of 1.2% at 6 months to 8.8% at 24 months) for women that do not receive a subsidy after generics were available. CONCLUSIONS: Introduction of generic alternatives to AIs significantly reduced primary and secondary nonadherence.

Housing discrimination and racial cancer disparities among the 100 largest US metropolitan areas.

BACKGROUND: Cancer contributes substantially to the life expectancy gap between US blacks and whites, and racial cancer disparities remain stubborn to eradicate. Disparities vary geographically, suggesting that they are not inevitable. METHODS: The authors examined the relationship between housing discrimination and the size of cancer disparities across large US metropolitan statistical areas (MSAs). MSA-level cancer disparities were measured using data from the US Centers for Disease Control and Prevention. Mortgage discrimination for each MSA was estimated using the Home Mortgage Disclosure Act database, and MSA racial segregation was determined using US Census data. Patterns of housing discrimination and cancer disparities were mapped, and the associations between these place-based factors and cancer disparities across MSAs were measured. RESULTS: Black-to-white cancer mortality disparities (rate ratios) varied geographically, ranging from 1.50 to 0.86; 88% of mortality ratios were >1, indicating higher mortality for blacks. In areas with greater mortgage discrimination, the gap between black and white cancer mortality rates was larger (correlation coefficient [r] = 0.32; P = .001). This relationship persisted in sex-specific analyses (males, r = 0.37; P < .001; females, r = 0.23; P = .02) and in models controlling for confounders. In contrast, segregation was inconsistently associated with disparities. Adjusting for incidence disparities attenuated, but did not eliminate, the correlation between mortgage discrimination and mortality disparities (r = 0.22-0.24), suggesting that cancer incidence and survival each account for part of the mortality disparity. CONCLUSIONS: Mortgage discrimination is associated with larger black-to-white cancer mortality disparities. Some areas are exceptions to this trend. Examination of these exceptions and of policies related to housing discrimination may offer novel strategies for explaining and eliminating cancer disparities.

The association of pharmacy fill synchronization with breast cancer endocrine therapy adherence.

BACKGROUND: One-third to one-half of patients prescribed adjuvant endocrine therapy are nonadherent during the recommended 5-year endocrine therapy course. This study investigated whether poor pharmacy synchronization of medication fills (requiring refills on different days) acts as a barrier to adherence. METHODS: A cohort of older women with stage 0 to III endocrine receptor-positive breast cancer in 2011 was identified from the Surveillance, Epidemiology, and End Result-Medicare claims-linked cancer registry. Women with endocrine therapy and at least 1 other medication fill were identified, and the 3-month synchronization of their fills was calculated as 1 minus the quotient of the number of pharmacy visits and the number of filled medications. Regression models were used to examine the association between synchronization (in quartiles adjusted for the number of medications) and adherence to endocrine therapy (defined as a medication possession ratio ≥80%) over the subsequent year. RESULTS: During the 3 months after the first endocrine therapy prescription, the study cohort of 3212 women had a mean of 8.6 pharmacy visits (standard deviation, 4.7) with a mean synchronization of 0.3 (standard deviation, 0.2). Those in the third (odds ratio, 1.29; 95% confidence interval, 1.04-1.59) and fourth (most) medication number-adjusted synchronization quartiles (odds ratio, 1.49; 95% confidence interval, 1.19-1.86) were more likely to be adherent than those in the least. Multivariate model predictions showed that the proportion of patients who were adherent over 1 year varied from 68.9% in the least synchronized quartile to 76.6% in the most synchronized one. CONCLUSIONS: Prescription refill synchronization is strongly associated with adherence to endocrine therapy. Efforts to improve adherence should address this.

Racial disparities of liver cancer mortality in Wisconsin.

PURPOSE: To calculate tract-level estimates of liver cancer mortality in Wisconsin and identify relationships with racial and socioeconomic variables. METHODS: County-level standardized mortality ratios (SMRs) of liver cancer in Wisconsin were calculated using traditional indirect adjustment methods for cases from 2003 to 2012. Tract-level SMRs were calculated using adaptive spatial filtering (ASF). The tract-level SMRs were checked for correlations to a socioeconomic advantage index (SEA) and percent racial composition. Non-spatial and spatial regression analyses with tract-level SMR as the outcome were conducted. RESULTS: County-level SMR estimates were shown to mask much of the variance within counties across their tracts. Liver cancer mortality was strongly correlated with the percent of Black residents in a census tract and moderately associated with SEA. In the multivariate spatially-adjusted regression analysis, only Percent Black composition remained significantly associated with an increased liver cancer SMR. CONCLUSIONS: Using ASF, we developed a high-resolution map of liver cancer mortality in Wisconsin. This map provided details on the distribution of liver cancer that were inaccessible in the county-level map. These tract-level estimates were associated with several racial and socioeconomic variables.

Randomized controlled trial of individualized treatment summary and survivorship care plans for hematopoietic cell transplantation survivors.

Survivorship Care Plans (SCPs) may facilitate long-term care for cancer survivors, but their effectiveness has not been established in hematopoietic cell transplantation recipients. We evaluated the impact of individualized SCPs on patient-reported outcomes among transplant survivors. Adult (≥18 years at transplant) survivors who were 1-5 years post transplantation, proficient in English, and without relapse or secondary cancers were eligible for this multicenter randomized trial. SCPs were developed based on risk-factors and treatment exposures using patient data routinely submitted by transplant centers to the Center for International Blood and Marrow Transplant Research and published guidelines for long-term follow up of transplant survivors. Phone surveys assessing patient-reported outcomes were conducted at baseline and at 6 months. The primary end point was confidence in survivorship information, and secondary end points included cancer and treatment distress, knowledge of transplant exposures, health care utilization, and health-related quality of life. Of 495 patients enrolled, 458 completed a baseline survey and were randomized (care plan=231, standard care=227); 200 (87%) and 199 (88%) completed the 6-month assessments, respectively. Patients' characteristics were similar in the two arms. Participants on the care plan arm reported significantly lower distress scores at 6 months and an increase in the Mental Component Summary quality of life score assessed by the Short Form 12 (SF-12) instrument. No effect was observed on the end point of confidence in survivorship information or other secondary outcomes. Provision of individualized SCPs generated using registry data was associated with reduced distress and improved mental domain of quality of life among 1-5 year hematopoietic cell transplantation survivors. Trial registered at clinicaltrials.gov 02200133.

Transcriptomic analysis reveals inflammatory and metabolic pathways that are regulated by renal perfusion pressure in the outer medulla of Dahl-S rats.

Studies exploring the development of hypertension have traditionally been unable to distinguish which of the observed changes are underlying causes from those that are a consequence of elevated blood pressure. In this study, a custom-designed servo-control system was utilized to precisely control renal perfusion pressure to the left kidney continuously during the development of hypertension in Dahl salt-sensitive rats. In this way, we maintained the left kidney at control blood pressure while the right kidney was exposed to hypertensive pressures. As each kidney was exposed to the same circulating factors, differences between them represent changes induced by pressure alone. RNA sequencing analysis identified 1,613 differently expressed genes affected by renal perfusion pressure. Three pathway analysis methods were applied, one a novel approach incorporating arterial pressure as an input variable allowing a more direct connection between the expression of genes and pressure. The statistical analysis proposed several novel pathways by which pressure affects renal physiology. We confirmed the effects of pressure on p-Jnk regulation, in which the hypertensive medullas show increased p-Jnk/Jnk ratios relative to the left (0.79 ± 0.11 vs. 0.53 ± 0.10, P < 0.01, n = 8). We also confirmed pathway predictions of mitochondrial function, in which the respiratory control ratio of hypertensive vs. control mitochondria are significantly reduced (7.9 ± 1.2 vs. 10.4 ± 1.8, P < 0.01, n = 6) and metabolomic profile, in which 14 metabolites differed significantly between hypertensive and control medullas ( P < 0.05, n = 5). These findings demonstrate that subtle differences in the transcriptome can be used to predict functional changes of the kidney as a consequence of pressure elevation.

Prevalence and Consequences of Axillary Lymph Node Dissection in the Era of Sentinel Lymph Node Biopsy for Breast Cancer.

BACKGROUND: Despite clear guidelines for its use and wide adoption, no population-based study has examined the extent to which patients with early stage breast cancer are benefiting from sentinel lymph node biopsy (SLNB) by being spared a potentially avoidable axillary lymph node dissection (ALND) and its associated morbidity. OBJECTIVE: Examine variation in type of axillary surgery performed by surgeon volume; investigate the extent and consequences of potentially avoidable ALND. RESEARCH DESIGN/SUBJECTS: Observational study of older women with pathologically node-negative stage I-II invasive breast cancer who underwent surgery in a SEER state in 2008-2009. MEASURES: Surgeon annual volume of breast cancer cases and type of axillary surgery were determined by Medicare claims. An estimated probability of excess lymphedema due to ALND was calculated. RESULTS: Among 7686 pathologically node-negative women, 49% underwent ALND (either initially or after SLNB) and 25% were operated on by low-volume surgeons. Even after adjusting for demographic and tumor characteristics, women treated by higher volume surgeons were less likely to undergo ALND [medium volume: odds ratio, 0.69 (95% confidence interval, 0.51-0.82); high volume: odds ratio, 0.59 (95% confidence interval, 0.45-0.76)]. Potentially avoidable ALND cases were estimated to represent 21% of all expected lymphedema cases. CONCLUSIONS: In this pathologically node-negative population-based breast cancer cohort, only half underwent solely SLNB. Patients treated by low-volume surgeons were more likely to undergo ALND. Resources and guidelines on the appropriate training and competency of surgeons to assure the optimal performance of SLNB should be considered to decrease rates of potentially avoidable ALND and lymphedema.

Socioeconomic Disparities in Mortality Among Women With Incident Breast Cancer Before and After Implementation of Medicare Part D.

BACKGROUND: Breast cancer patients exhibit survival disparities based on socioeconomic status (SES). Disparities may be attributable to access to expensive oral endocrine agents. OBJECTIVES: Define recent socioeconomic disparities in breast cancer survival and determine whether these improved after implementation of the Medicare Part D program. DESIGN: Difference-in-difference natural experiment of women diagnosed and treated before or after implementation of Medicare Part D. SUBJECTS: Female Medicare beneficiaries with early-stage breast cancer: 54,772 diagnosed in 2001 and 46,371 in 2007. MEASURES: SES was based on Medicaid enrollment and zip code per capita income, all-cause mortality from Medicare, and cause of death from National Death Index. RESULTS: Among women diagnosed pre-Part D, 40.5% of poor beneficiaries had died within 5 years compared with 20.3% of high-income women (P<0.0001). Post-Part D, 33.6% of poor women and 18.4% of high-income women died by 5 years. After adjustment for potential confounders, improvement in all-cause mortality post-Part D was greater for poorer women compared with more affluent women (P=0.002). However, absolute improvement in breast cancer-specific mortality was 1.8%, 1.2%, and 0.8% (P=0.88 for difference in improvement by SES), respectively for poor, near-poor, and high-income women, whereas analogous improvement in mortality from other causes was 5.1%, 3.8%, and 0.9% (P=0.067 for difference in improvement by SES). CONCLUSIONS: Large survival disparities by SES exist among breast cancer patients. The Part D program successfully ameliorated SES disparities in all-cause mortality. However, improvement was concentrated in causes of death other than breast cancer, suggesting remaining gaps in care.

A Bayesian subgroup analysis using collections of ANOVA models.

We develop a Bayesian approach to subgroup analysis using ANOVA models with multiple covariates, extending an earlier work. We assume a two-arm clinical trial with normally distributed response variable. We also assume that the covariates for subgroup finding are categorical and are a priori specified, and parsimonious easy-to-interpret subgroups are preferable. We represent the subgroups of interest by a collection of models and use a model selection approach to finding subgroups with heterogeneous effects. We develop suitable priors for the model space and use an objective Bayesian approach that yields multiplicity adjusted posterior probabilities for the models. We use a structured algorithm based on the posterior probabilities of the models to determine which subgroup effects to report. Frequentist operating characteristics of the approach are evaluated using simulation. While our approach is applicable in more general cases, we mainly focus on the 2 × 2 case of two covariates each at two levels for ease of presentation. The approach is illustrated using a real data example.

Bone Mineral Density Testing Disparities Among Patients With Breast Cancer Prescribed Aromatase Inhibitors.

OBJECTIVES: Aromatase inhibitors (AIs) are standard adjuvant therapy for postmenopausal women with early-stage, estrogen receptor-positive breast cancer. We designed our study to determine whether women initiating adjuvant therapy with an AI underwent baseline bone mineral density testing, as well as what factors predicted adherence with testing guidelines. METHODS: Medicare Parts A, B, and D claims were used to identify a cohort of women aged 67 years and older with incident breast cancer in 2006 and 2007 who started AI therapy. Medicare claims provided information about bone density testing, as well as demographic and other treatment data through 2012. We also ascertained which patients were treated with bisphosphonates and studied the relationship of bisphosphonate therapy with bone density testing. RESULTS: Approximately two-thirds of patients had baseline bone density testing. Older age, comorbidity, low income, and black race were associated with lower rates of baseline bone density testing. Testing rates decreased substantially with increasing age from 73% for women aged 67 to 70 years to 51% for those 85 years of age and older (adjusted odds ratio for not being tested, 2.48 [Cl, 2.17-2.82]). The proportion of women who had neither bone density testing nor bisphosphonate therapy increased with age as well. CONCLUSIONS: Despite the importance of age as a risk factor for fractures, older women starting treatment with AIs for treatment of breast cancer are less likely to undergo recommended bone density assessment.

Nonparametric survival analysis using Bayesian Additive Regression Trees (BART).

Bayesian additive regression trees (BART) provide a framework for flexible nonparametric modeling of relationships of covariates to outcomes. Recently, BART models have been shown to provide excellent predictive performance, for both continuous and binary outcomes, and exceeding that of its competitors. Software is also readily available for such outcomes. In this article, we introduce modeling that extends the usefulness of BART in medical applications by addressing needs arising in survival analysis. Simulation studies of one-sample and two-sample scenarios, in comparison with long-standing traditional methods, establish face validity of the new approach. We then demonstrate the model's ability to accommodate data from complex regression models with a simulation study of a nonproportional hazards scenario with crossing survival functions and survival function estimation in a scenario where hazards are multiplicatively modified by a highly nonlinear function of the covariates. Using data from a recently published study of patients undergoing hematopoietic stem cell transplantation, we illustrate the use and some advantages of the proposed method in medical investigations. Copyright © 2016 John Wiley & Sons, Ltd.

Breast and Colorectal Cancer Survival Disparities in Southeastern Wisconsin.

BACKGROUND: Cancer health disparities by race, ethnicity, socioeconomic status, and geography are a top public health priority. Breast and colorectal cancer, in particular, have been shown to exhibit significant disparities and contribute a large proportion of morbidity and mortality from cancer. In addition, breast and colorectal cancer offer targets for prevention and control, including nutrition, physical activity, screening, and effective treatments to prolong and enhance the quality of survival. However, despite the investment of significant time and resources over many years, breast and colorectal cancer disparities persist, and in some cases, may be growing. METHODS: This paper examines breast and colorectal cancer survival disparities in an 8-county region in southeastern Wisconsin, including the City of Milwaukee. Cox proportional hazards models were used to examine survival trends, and a new adaptation of adaptive spatial filtering--a disease mapping method--was used to examine spatial patterns of survival. RESULTS: Disparities by race and ethnicity are revealed, and spatial analyses identify specific areas within the study region that have lower than expected survival rates. CONCLUSIONS: Cancer control efforts in southeastern Wisconsin should focus on black/African American and Hispanic/Latina women to reduce breast cancer survival disparities, and black/African American populations to reduce colorectal cancer disparities. Evidence indicates that targeted interventions may be needed to serve populations in the Milwaukee and Kenosha metropolitan areas, as well as areas of Walworth, Ozaukee, and Waukesha counties.