The University of North Carolina Cancer Survivorship Cohort: A resource for collaborative survivorship research.

BACKGROUND: Rapid growth in the number of U.S. cancer survivors drives the need for ongoing research efforts to improve outcomes and experiences after cancer. Here we describe the University of North Carolina (UNC) Cancer Survivorship Cohort, a medical center-based cohort of adults with cancer that integrates medical record-abstracted cancer information, patient-reported outcomes, and biologic specimens. METHODS: Participants ages 18+ were recruited from UNC oncology clinics between April 2010 and August 2016. After enrollment, participants completed questionnaires on a range of topics including demographics, health history, health care access and utilization, quality of life, and symptoms. Blood samples and tumor tissue specimens were collected and processed by study staff, and cancer characteristics and other clinical data were abstracted from electronic medical records. Participants consented to recontact for future studies and linkage of their data with other data resources. RESULTS: In total, 3,999 participants with a cancer diagnosis were enrolled in the cohort. The most common cancer types among those enrolled included breast (N=866), uterine (N=458), colorectal (N=300), prostate (N=296), and head and neck (N=248). Blood specimens were collected for 3,027 (76%). Additional participants without cancer (N=1,299) were also enrolled, and the majority (62%) provided biospecimen samples. CONCLUSIONS: We encourage wide collaboration with investigators across institutions seeking to advance research in cancer survivorship. Procedures are in place to support proposals for use of existing or linked data and for proposals that require participant recontact or analysis of biospecimens. IMPACT: The UNC Cancer Survivorship Cohort is a unique resource for cancer survivorship research.

Cancer information and population health resource: a resource for catchment area data and cancer outcomes research.

BACKGROUND: The University of North Carolina at Chapel Hill Lineberger Comprehensive Cancer Center has developed a novel data resource, the Cancer Information and Population Health Resource (CIPHR), for conducting catchment area evaluation and cancer population health research that links the North Carolina Central Cancer Registry (NCCCR) to medical and pharmacy claims data from Medicare, Medicaid, and private plans operating within North Carolina. This study's aim was to describe the CIPHR data and provide examples of potential cohorts available in those data. METHODS: We present the underlying populations included in the NCCCR and claims data before linkage and demonstrate estimated sample sizes when these data are linked and commonly used insurance enrollment criteria are applied. RESULTS: Data for the years 2003-2020 are present in CIPHR and include 947 977 cancer cases from the NCCCR and 21.6 million enrollees in public and private health insurance (cancer and noncancer cases). When limited to first or only cancers (n = 672 377), 86% could be linked to insurance enrollment for at least 1 month during 2003-2020 (n = 582 638), with 62% of individuals linking to enrollment during the month of cancer diagnosis. Among all registry cancer cases, 47% (n = 317 898) had continuous insurance enrollment for at least 12 months before and after cancer diagnosis. CONCLUSION: CIPHR illustrates the utility of establishing and maintaining a statewide, comprehensive cancer population health database. This resource serves to characterize the cancer center catchment area and aids in tracking cancer outcomes and trends in care delivery as well as identifying disparities that require intervention and policy focus.

Supply and demand effects between tobacco retailer density and smoking prevalence.

OBJECTIVE: Places with more tobacco retailers have higher smoking prevalence levels, but whether this is because retailers locate where people who smoke live or whether tobacco availability prompts tobacco use is unknown. In this study, we compare the role of consumer demand with that of tobacco supply in longitudinal, area-based associations of tobacco retailer density with smoking prevalence. METHODS: We merged annual adult smoking prevalence estimates derived from the USA Behavioural Risk Factor Surveillance System data with annual county estimates of tobacco retailer density calculated from the National Establishment Time Series data for 3080 counties between 2000 and 2010. We analysed relationships between retailer density and smoking in 3080 counties, using random intercept cross-lagged panel models and employing two measures of tobacco retailer density capturing the number of likely tobacco retailers in a county divided by either the population or land area. RESULTS: Both density models provided evidence of significant demand and supply effects; in the population-based model, the association of smoking prevalence in 1 year with tobacco retailer density in the next year (standardised coefficient=0.038, p<0.01) was about double the association between tobacco retailer density with subsequent smoking prevalence (0.017, p<0.01). The reverse was true in the land area-based model, where the supply effect (0.042, p<0.01) was more than 10 times stronger than the demand effect (0.003, p<0.01). CONCLUSIONS: Policies that restrict access to retail tobacco have the potential to reduce smoking prevalence, but pairing such policies with interventions to reduce consumer demand remains important.

Tobacco retailer density and its association with birth outcomes in the USA: 2000-2016.

INTRODUCTION: Significant progress has been made in reducing maternal exposure to tobacco smoke and subsequent adverse birth outcomes, however, reductions may require strategies that reduce the availability of tobacco retailers. In this study, we investigated the relationship between tobacco retailer density and birth outcomes across the USA and predicted the potential impact of a tobacco retailer density cap on these outcomes. METHODS: Annual US county (n=3105), rates of preterm birth, low birth weight, small-for-gestational age, all-cause infant mortality and sudden infant death syndrome (SIDS) were calculated using National Vital Statistics System data. Tobacco retailers were identified from the National Establishment Time-Series Database. We used Poisson regression to estimate the effect of capping retailer density at 1.4 retailers per 1000 population, controlling for county demographics and air pollution, using propensity score weighting. RESULTS: Tobacco retailer density was positively associated with most adverse birth outcomes. We estimate that a nationwide cap on tobacco retailer density, implemented in 2016, would have resulted in a reduction of 4275 (95% CI 2210 to 6392) preterm births, 6096 (95% CI 4421 to 7806) small-for-gestational-age births, 3483 (95% CI 2615 to 4378) low birthweight births, 538 (95% CI 345 to 733) all-cause infant deaths and 107 (95% CI 55 to 158) SIDS deaths in that year. CONCLUSION: Higher rates of adverse birth outcomes were seen in counties with high tobacco retailer density compared with those with low density. These results provide further support for regulating tobacco retail density to reduce adverse health outcomes associated with tobacco use.

Structural Racism and Treatment Delay Among Black and White Patients With Breast Cancer.

PURPOSE: Structural racism (SR) is a potential driver of health disparities, but research quantifying its impacts on cancer outcomes has been limited. We aimed to develop a multidimensional county-level SR measure and to examine the association of SR with breast cancer (BC) treatment delays among Black and White patients. METHODS: The cohort included 32,095 individuals from the North Carolina Central Cancer Registry with stage I to III BC diagnosed between 2004 and 2017 and linked to multipayer insurance claims from the Cancer Information and Population Health Resource. County-level data were drawn from multiple public sources aggregated in the Robert Wood Johnson County Health Rankings database. Racial gaps in eight social determinants across five domains were quantified at the county level and ranked on a 0-100 minimum-maximum scale. Domain scores were averaged to create a SR Composite Index (SRCI) score. We used multilevel logistic regression with random intercepts and multiple cross-level interaction terms to evaluate the association between county-level SRCI and patient-level treatment delays, adjusting for patient-level characteristics and stratified by race. RESULTS: The SRCI score ranged from 21 to 75 with a median (IQR) of 39.0 (31.8, 45.7). For Black patients, a 10-unit increase in SRCI score was associated with increased odds of delay (Adjusted odds ratios [aOR], 1.25; 95% confidence limits [CL], 1.08 to 1.45). No such association was found for White patients (OR, 1.05; 95% CL, 0.97 to 1.15). CONCLUSION: Area-level SR measured by a composite index is associated with higher odds of BC treatment delays among Black, but not White patients. Increasing county-level SR is associated with increasing Black-White disparities in treatment delay. Further research is needed to refine the measurement of SR and to examine its association with other cancer care disparities.

Functional Status Associations With Treatment Receipt and Outcomes Among Older Adults Newly Diagnosed With Multiple Myeloma.

PURPOSE: Multiple myeloma (MM) is a prevalent hematologic malignancy in older adults, who often experience physical disability, increased health care usage, and reduced treatment tolerance. Home health (HH) services are frequently used by this group, but the relationship between disability, HH use, and MM treatment receipt is unclear. This study examines the connections between disability, treatment receipt, and survival outcomes in older adults with newly diagnosed MM using a nationwide data set. METHODS: The SEER-Medicare data set was used to identify adults aged 66 years and older diagnosed with MM from 2010 to 2017, who used HH services the year before diagnosis. Disability was assessed with the Outcome and Assessment Information Set, using a composite score derived from items related to ability to complete activities of daily living. Mortality, therapy receipt, and health care utilization patterns were evaluated. RESULTS: Of 37,280 older adults with MM, 6,850 (18.2%) used HH services before diagnosis. Moderate disability at HH assessment resulted in similar MM-directed therapy receipt as mild disability, with comparable health care usage after diagnosis to severe disability. HH users had a higher comorbidity burden and higher mortality (adjusted risk ratio for 3-year mortality: 1.59 [95% CI, 1.55 to 1.64]). Severe functional disability before diagnosis was strongly related to postdiagnosis mortality. CONCLUSION: Among older adults with MM receiving HH services, disability is a predictor of early mortality. Moderately disabled individuals undergo similar therapy intensity as the mildly disabled but experience increased acute care utilization. Previous HH use could identify patients with MM requiring intensive support during therapy initiation.

Simulating the population impact of interventions to reduce racial gaps in breast cancer treatment.

BACKGROUND: Inequities in guideline-concordant treatment receipt contribute to worse survival in Black patients with breast cancer. Inequity-reduction interventions (eg, navigation, bias training, tracking dashboards) can close such treatment gaps. We simulated the population-level impact of statewide implementation of inequity-reduction interventions on racial breast cancer inequities in North Carolina. METHODS: Using registry-linked multipayer claims data, we calculated inequities between Black and White patients receiving endocrine therapy (n = 12 033) and chemotherapy (n = 1819). We then built cohort-stratified (endocrine therapy and chemotherapy) and race-stratified Markov models to simulate the potential increase in the proportion of patients receiving endocrine therapy or chemotherapy and subsequent improvements in breast cancer outcomes if inequity-reducing intervention were implemented statewide. We report uncertainty bounds representing 95% of simulation results. RESULTS: In total, 75.6% and 72.1% of Black patients received endocrine therapy and chemotherapy, respectively, over the 2006-2015 and 2004-2015 periods (vs 79.3% and 78.9% of White patients, respectively). Inequity-reduction interventions could increase endocrine therapy and chemotherapy receipt among Black patients to 89.9% (85.3%, 94.6%) and 85.7% (80.7%, 90.9%). Such interventions could also decrease 5-year and 10-year breast cancer mortality gaps from 3.4 to 3.2 (3.0, 3.3) and from 6.7 to 6.1 (5.9, 6.4) percentage points in the endocrine therapy cohorts and from 8.6 to 8.1 (7.7, 8.4) and from 8.2 to 7.8 (7.3, 8.1) percentage points in the chemotherapy cohorts. CONCLUSIONS: Inequity-focused interventions could improve cancer outcomes for Black patients, but they would not fully close the racial breast cancer mortality gap. Addressing other inequities along the cancer continuum (eg, screening, pre- and postdiagnosis risk factors) is required to achieve full equity in breast cancer outcomes.

Challenges and Opportunities of Epidemiological Studies to Reduce the Burden of Cancers in Young Adults.

There are >1.9 million survivors of adolescent and young adult cancers (AYA, diagnosed at ages 15-39) living in the U.S. today. Epidemiologic studies to address the cancer burden in this group have been a relatively recent focus of the research community. In this article, we discuss approaches and data resources for cancer epidemiology and health services research in the AYA population. We consider research that uses data from cancer registries, vital records, healthcare utilization, and surveys, and the accompanying challenges and opportunities of each. To illustrate the strengths of each data source, we present example research questions or areas that are aligned with these data sources and salient to AYAs. Integrating the respective strengths of cancer registry, vital records, healthcare data, and survey-based studies sets the foundation for innovative and impactful research on AYA cancer treatment and survivorship to inform a comprehensive understanding of diverse AYA needs and experiences.

Multi-level predictors of being up-to-date with colorectal cancer screening.

PURPOSE: Assessing factors associated with being up-to-date with colorectal cancer (CRC) screening is important for identifying populations for which targeted interventions may be needed. METHODS: This study used Medicare and private insurance claims data for residents of North Carolina to identify up-to-date status in the 10th year of continuous enrollment in the claims data and in available subsequent years. USPSTF guidelines were used to define up-to-date status for multiple recommended modalities. Area Health Resources Files provided geographic and health care service provider data at the county level. A generalized estimating equation logistic regression model was used to examine the association between individual- and county-level characteristics and being up-to-date with CRC screening. RESULTS: From 2012-2016, 75% of the sample (n = 274,660) age 59-75 was up-to-date. We identified several individual- (e.g., sex, age, insurance type, recent visit with a primary care provider, distance to nearest endoscopy facility, insurance type) and county-level (e.g., percentage of residents with a high school education, without insurance, and unemployed) predictors of being up-to-date. For example, individuals had higher odds of being up-to-date if they were age 73-75 as compared to age 59 [OR: 1.12 (1.09, 1.15)], and if living in counties with more primary care physicians [OR: 1.03 (1.01, 1.06)]. CONCLUSION: This study identified 12 individual- and county-level demographic characteristics related to being up-to-date with screening to inform how interventions may optimally be targeted.

Race, geography, and risk of breast cancer treatment delays: A population-based study 2004-2015.

BACKGROUND: Treatment delays affect breast cancer survival and constitute poor-quality care. Black patients experience more treatment delay, but the relationship of geography to these disparities is poorly understood. METHODS: We studied a population-based, retrospective, observational cohort of patients with breast cancer in North Carolina between 2004 and 2017 from the Cancer Information and Population Health Resource, which links cancer registry and sociodemographic data to multipayer insurance claims. We included patients >18 years with Stage I-III breast cancer who received surgery or chemotherapy as their first treatment. Delay was defined as >60 days from diagnosis to first treatment. Counties were aggregated into nine Area Health Education Center regions. Race was dichotomized as Black versus non-Black. RESULTS: Among 32,626 patients, 6190 (19.0%) were Black. Black patients were more likely to experience treatment delay >60 days (15.0% of Black vs. 8.0% of non-Black). Using race-stratified modified Poisson regression, age-adjusted relative risk of delay in the highest risk region was approximately twice that in the lowest risk region among Black (relative risk, 2.1; 95% CI, 1.6-2.6) and non-Black patients (relative risk, 1.9; 95% CI, 1.5-2.3). Adjustment for clinical and sociodemographic features only slightly attenuated interregion differences. The magnitude of the racial gap in treatment delay varied by region, from 0.0% to 9.4%. CONCLUSIONS: Geographic region was significantly associated with risk of treatment delays for both Black and non-Black patients. The magnitude of racial disparities in treatment delay varied markedly between regions. Future studies should consider both high-risk geographic regions and high-risk patient groups for intervention to prevent delays.

Cross-Sectional Analysis of Clinical Trial Availability and North Carolina Neighborhood Social Vulnerability.

PURPOSE: Residents of communities facing social vulnerability (eg, poverty) have limited access to clinical trials, leaving them susceptible to experiencing poor health outcomes. We examined the association between North Carolina county-level social vulnerability and available multiple myeloma (MM) trials. METHODS: Using a novel data linkage between ClinicalTrials.gov, the 2019 American Community Survey, and the Centers for Disease Control and Prevention's Social Vulnerability Index, we investigated at the county level (1) availability of MM trial sites and (2) the relationship between Social Vulnerability Index and MM trial site availability using logistic regression. RESULTS: Between 2002 and 2021, 229 trials were registered across 462 nonunique trial sites in 34 counties. Nearly 50% of trial sites were in academic medical centers, 80% (n = 372) of all trials were industry-sponsored, 60% (n = 274) were early-phase, and 50% (n = 232) were for patients with relapsed or refractory MM. Counties with low as opposed to high poverty rates had six times greater odds of having ≥ 1 MM trial sites (odds ratio [OR], 5.60; 95% CI, 1.85 to 19.64; P = .004). Counties with the lowest percentage of Black Indigenous Persons of Color and non-native English speakers had 77% lower odds (OR, 0.23; 95% CI, 0.07 to 0.69; P = .011) of having ≥ 1 trial sites. The effect remained significant after accounting for the presence of five academic medical centers (n = 95; OR, 0.18; 95% CI, 0.05 to 0.6; P = .008) and adjustment for metropolitan, suburban, or rural status (OR, 0.25; 95% CI, 0.07 to 0.81; P = .025). CONCLUSION: Counties with the lowest poverty rates had more MM trial sites, whereas those with the lowest percentage of Black Indigenous Persons of Color populations had fewer MM trial sites. Multilevel efforts are needed to improve the availability and access to trials for socially vulnerable populations.

Temporal Changes in Treatment Patterns for Rural and Urban Patients With Early-Stage Non-Small Cell Lung Cancer.

BACKGROUND Our objectives were to evaluate geographic access to lung cancer treatment modalities in North Carolina and to characterize how practice patterns are changing over time. We hypothesized that rural patients would be less likely to undergo treatment compared to urban patients, with widening disparities over time.METHODS We identified patients with Stage I non-small cell lung cancer (NSCLC) from 2006 to 2015 using the North Carolina Central Cancer Registry linked with Medicaid, Medicare, and private insurance claims. The primary outcome was first-course treatment: surgery, radiation, or no treatment. Calendar years were split into earlier (2006-2010) and later (2011-2015) periods. We estimated the adjusted odds ratio (OR) of rural/urban status and time period with 1) surgery and 2) any treatment (surgery or radiation) using multivariable logistic regression.RESULTS Among 5504 patients, 3206 (58%) underwent surgery as initial therapy, 1309 (24%) received radiation as initial therapy, and 989 (18%) had no therapy. There were no rural-urban disparities in treatment patterns. For rural and urban patients, the odds of surgery decreased over time and the odds of radiation increased. We also found that only 48% of those receiving no treatment ever reached a surgeon or radiation oncologist.LIMITATIONS This was an insured, single-state population. Treatment preferences are unknown.CONCLUSIONS Among all treated patients, whether urban or rural, there was increasing use of radiation and decreasing use of surgery over time. Many patients without treatment never had a consultation with a surgeon/radiation oncologist, and this is an actionable target for improving treatment access for early-stage NSCLC.

Trends in the Number and Type of Tobacco Product Retailers, United States, 2000-2017.

INTRODUCTION: Tobacco product retailers provide access to tobacco products and exposure to tobacco marketing. Without a national tobacco retailer licensing system in the United States, there are no estimates of national trends in tobacco retailer numbers and store type over time. METHODS: We developed a protocol to identify likely tobacco retailers across the United States between 2000 and 2017 using industry codes and retailer names in the annual National Establishment Time Series (NETS) database. We calculated annual counts of tobacco retailers in seven store-type categories and annual numbers of tobacco retailers that opened and closed. RESULTS: We estimate that there were 317 492 tobacco product retailers in 2000; the number grew to 412 536 in 2009 before falling to 356 074 in 2017, for a net 12% increase overall. Gas/convenience stores and grocery stores accounted for more than two thirds of all retailers. On average, new openings accounted for 8.0% of the total retailers, whereas 7.3% of retailers closed or stopped selling tobacco each year, with stronger market volatility following the Great Recession. Since 2011, there was a disproportionate reduction in tobacco-selling pharmacies and an increase in both tobacco-specialty shops and tobacco-selling discount stores. CONCLUSIONS: During two decades when smoking declined, tobacco retailer availability increased in the United States. The economic climate, corporate and public policies, and new tobacco products may all contribute to trends in tobacco retailer availability. State and local jurisdictions considering tobacco retailer policies may find retailer trend information useful for forecasting or evaluating potential policy impacts. IMPLICATIONS: This study provides historic data tracking tobacco retailers in the United States between 2000 and 2017, documenting trends that unfolded as the general economic market contracted and grew, with greater regulation of the tobacco retailer environment. These data provide a context for better understanding future changes in the tobacco retailer market. In addition, the protocol established in this study could be applied in any US-based location without tobacco retailer licensing to allow identification of stores and tracking of trends.

Geospatial analysis of multiple cancers in individuals in the US, 2004-2014.

BACKGROUND: There is a projected rapid increase in cancer survivors in the US population, from 15.5 million in 2016 to 26.1 million by 2040. Improvements in treatment and detection have led to increased survival, however, there is now a risk of developing new cancers as a result of environment toxins, behavioral risk factors, genetic predisposition, and late-term effects of radiation and chemotherapeutic treatments. This study takes a geospatial approach to examining the place of occurrence of multiple cancers originating in the population of four screenable cancers-female breast, colorectal, prostate, and cervical cancers-among the US population. METHODS: During 2004-2014, 6,523,532 primary cancer patients with one of these four screenable cancers were examined, and subsequent primary cancers (multiple cancers of any type) were noted. Individual level analyses estimated the odds of diagnosis with multiple cancers controlling for age, sex, and race-ethnicity. Change in effects on odds of multiple cancer diagnoses with age, sex, and race-ethnicity were evaluated controlling separately for late-stage diagnosis of the primary cancer or each primary cancer diagnosis type. County-level spatial cluster analysis was employed to identify and visualize higher than average multiple cancer rates. RESULTS: Over half of the study population were female and almost 30% of the study population were diagnosed at late-stage for their first cancer. Multiple occurrences of all cancers increased during the time period for patients with initial breast or colorectal cancers. Among BC primary cancer cases, subsequent multiple cancers were mostly new breast cancers. By contrast, for CRC primary cancer cases, subsequent multiple cancers were about equally likely to be new CRC cases or other cancer types. Sex, age and race-ethnicity were all significantly associated with multiple cancers. In the model controlling for CRC as the primary type, the age and race-ethnicity effects were somewhat different than for all the other models. Thus, there was something distinctly different about the multiple cancer incidence among patients with CRC as their primary cancer as compared to patients with BC, CVC, or PC primaries. In subsequent analyses by county, there were distinct geospatial patterns in multiple cancer rates with most high-rate clusters occurring in the north- and mid-west US. CONCLUSIONS: There were distinct individual level and geospatial disparities in multiple cancer diagnoses for the study population of all primary breast, colorectal, cervical, or prostate cancer patients during the decade studied. It is importance to emphasize continued screening for cancer survivors and research on personal and environmental drivers of multiple primary cancers.

Validation of a 5-Year Mortality Prediction Model among U.S. Medicare Beneficiaries.

BACKGROUND/OBJECTIVES: A claims-based model predicting 5-year mortality (Lund-Lewis) was developed in a 2008 cohort of North Carolina (NC) Medicare beneficiaries and included indicators of comorbid conditions, frailty, disability, and functional impairment. The objective of this study was to validate the Lund-Lewis model externally within a nationwide sample of Medicare beneficiaries. DESIGN: Retrospective validation study. SETTING: U.S. Medicare population. PARTICIPANTS: From a random sample of Medicare beneficiaries, we created four annual cohorts from 2008 to 2011 of individuals aged 66 and older with an office visit in that year. The annual cohorts ranged from 1.13 to 1.18 million beneficiaries. MEASUREMENTS: The outcome was 5-year all-cause mortality. We assessed clinical indicators in the 12 months before the qualifying office visit and estimated predicted 5-year mortality for each beneficiary in the nationwide sample by applying estimates derived in the original NC cohort. Model performance was assessed by quantifying discrimination, calibration, and reclassification metrics compared with a model fit on a comorbidity score. RESULTS: Across the annual cohorts, 5-year mortality ranged from 24.4% to 25.5%. The model had strong discrimination (C-statistics ranged across cohorts from .823 to .826). Reclassification measures showed improvement over a comorbidity score model for beneficiaries who died but reduced performance among beneficiaries who survived. The calibration slope ranged from .83 to .86; the model generally predicted a higher risk than observed. CONCLUSION: The Lund-Lewis model showed strong and consistent discrimination in a national U.S. Medicare sample, although calibration indicated slight overfitting. Future work should investigate methods for improving model calibration and evaluating performance within specific disease settings.

County-level associations between tobacco retailer density and smoking prevalence in the USA, 2012.

We examine whether county-level tobacco retailer density and adult smoking prevalence are positively associated in the United States and determine whether associations differ in metropolitan vs. nonmetropolitan counties. We merged a list of likely tobacco retailers from the 2012 National Establishment Time-Series with smoking prevalence data from the Behavioral Risk Factor Surveillance System for 2828 US counties, as well as state tobacco policy information and county-level demographic data for the same year. We modeled adult smoking prevalence as a function of tobacco retailer density, accounting for clustering of counties within states. Average density in US counties was 1.25 retailers per 1000 people (range = 0.3-4.5). Smoking prevalence was 0.86 percentage points higher in the most retailer-dense counties, compared to the least. This association, however, was only significant for metropolitan counties. Metropolitan counties in the highest tobacco retailer density quartile had smoking prevalence levels that were 1.9 percentage points higher than metropolitan counties in the lowest density quartile. Research should examine whether policies limiting the quantity, type and location of tobacco retailers could reduce smoking prevalence.

Update on triple-negative breast cancer disparities for the United States: A population-based study from the United States Cancer Statistics database, 2010 through 2014.

BACKGROUND: Triple-negative breast cancer (TNBC) has been associated with a more aggressive histology, poorer prognosis, and nonresponsiveness to hormone therapy. It is imperative that cancer research identify factors that drive disparities and focus on prevention. METHODS: Using the United States Cancer Statistics database, the authors examined differences between TNBCs compared with all other breast cancers with regard to age, race/ethnicity, and stage at diagnosis. RESULTS: A total of 1,151,724 cases of breast cancer were identified from 2010 through 2014, with the triple-negative phenotype accounting for approximately 8.4% of all cases. In unadjusted analyses, non-Hispanic black women (odds ratio [OR], 2.27; 95% CI, 2.23-2.31) and Hispanic women (OR, 1.22; 95% CI, 1.19-1.25) had higher odds of diagnosis when compared with non-Hispanic white women. Women aged <40 years had the highest odds of diagnosis compared with women aged 50 to 64 years (OR, 1.95; 95% CI, 1.90-2.01). Diagnosis at American Joint Committee on Cancer stage III and beyond conferred higher odds of the diagnosis of TNBC (OR for stage III, 1.69 [95% CI, 1.68-1.72]; and OR for stage IV, 1.47 [95% CI, 1.43-1.51]). Results varied slightly in adjusted analyses. CONCLUSIONS: The results of the current study demonstrated that there is a significant burden of disease in TNBC diagnosed among women of color, specifically non-Hispanic black women, and younger women. Additional studies are needed to determine drivers of disparities between race, age, and stage of disease at diagnosis.

Development and validation of a 5-year mortality prediction model using regularized regression and Medicare data.

PURPOSE: De-implementation of low-value services among patients with limited life expectancy is challenging. Robust mortality prediction models using routinely collected health care data can enhance health care stakeholders' ability to identify populations with limited life expectancy. We developed and validated a claims-based prediction model for 5-year mortality using regularized regression methods. METHODS: Medicare beneficiaries age 66 or older with an office visit and at least 12 months of pre-visit continuous Medicare A/B enrollment were identified in 2008. Five-year mortality was assessed through 2013. Secondary outcomes included 30-, 90-, and 180-day and 1-year mortality. Claims-based predictors, including comorbidities and indicators of disability, frailty, and functional impairment, were selected using regularized logistic regression, applying the least absolute shrinkage and selection operator (LASSO) in a random 80% training sample. Model performance was assessed and compared with the Gagne comorbidity score in the 20% validation sample. RESULTS: Overall, 183 204 (24%) individuals died. In addition to demographics, 161 indicators of comorbidity and function were included in the final model. In the validation sample, the c-statistic was 0.825 (0.823-0.828). Median-predicted probability of 5-year mortality was 14%; almost 4% of the cohort had a predicted probability greater than 80%. Compared with the Gagne score, the LASSO model led to improved 5-year mortality classification (net reclassification index = 9.9%; integrated discrimination index = 5.2%). CONCLUSIONS: Our claims-based model predicting 5-year mortality showed excellent discrimination and calibration, similar to the Gagne score model, but resulted in improved mortality classification. Regularized regression is a feasible approach for developing prediction tools that could enhance health care research and evaluation of care quality.

Examining determinants of geographic variation in colorectal cancer mortality in North Carolina: A spatial analysis approach.

PURPOSE: A recent study using national data from 2000 to 2009 identified colorectal cancer (CRC) mortality "hotspots" in 11 counties of North Carolina (NC). In this study, we used more recent, state-specific data to investigate the county-level determinants of geographic variation in NC through a geospatial analytic approach. METHOD: Using NC CRC mortality data from 2003 to 2013, we first conducted clustering analysis to confirm spatial dependence. Spatial economic models were then used to incorporate spatial structure to estimate the association between determinants and CRC mortality. We included county-level data on socio-demographic characteristics, access and quality of healthcare, behavioral risk factors (CRC screening, obesity, and cigarette smoking), and urbanicity. Due to correlation among screening, obesity and quality of healthcare, we combined these factors to form a cumulative risk group variable in the analysis. RESULTS: We confirmed the existence of spatial dependence and identified clusters of elevated CRC mortality rates in NC counties. Using a spatial lag model, we found significant interaction effect between CRC risk groups and socioeconomic deprivation. Higher CRC mortality rates were also associated with rural counties with large towns compared to urban counties. CONCLUSION: Our findings depicted a spatial diffusion process of CRC mortality rates across NC counties, demonstrated intertwined effects between SES deprivation and behavioral risks in shaping CRC mortality at area-level, and identified counties with high CRC mortality that were also deprived in multiple factors. These results suggest interventions to reduce geographic variation in CRC mortality should develop multifaceted strategies and work through shared resources in neighboring areas.

What Happened to Disparities in CRC Screening Among FFS Medicare Enrollees Following Medicare Modernization?

The Medicare Modernization Act of 2003, implemented in 2006, increased managed care options for seniors. It introduced insurance plans for prescription drug coverage for all Medicare beneficiaries, whether they were enrolled in FFS or managed care (Medicare Advantage) plans. The availability of drug coverage beginning in 2006 served to free up budgets for FFS Medicare enrollees that could be used to make copayments for colorectal cancer (CRC) screening using endoscopy (colonoscopy or sigmoidoscopy). In 2007, Medicare eliminated the copayments required by seniors for CRC screening by endoscopy. Later in 2008, CRC screening by colonoscopy became part of the gold standard for CRC screening. This legitimized its use and offered even further encouragement to seniors, who may have been reluctant to undergo the procedure because of the non-pecuniary risks associated with it. In addition, 37 CRC screening interventions occurred during this timeframe to enhance compliance with screening standards. Using multilevel analysis of individuals' endoscopy utilization, derived from 100% FFS Medicare claims, along with county-level market and contextual factors, we compare the periods before and after the MMA (2001-2005 to 2006-2009) to determine whether disparities in the utilization of endoscopic CRC screening occurred or changed over the decade. We examined Blacks, Asians, and Hispanics relative to Whites, and Females relative to Males (with race or ethnicity combined). We examined each state separately for evidence of disparities within states, to avoid confounding by geographic disparities. We expected that the net effect of the policy changes and the targeted interventions over the decade would be to increase CRC screening by endoscopy, reducing disparities. We saw improvements over time (reduced disparities relative to Whites) for Blacks and Hispanics residing in several states, and improvements over time for Females relative to Males in many states. For the vast majority of states, however, disparities persisted with Whites and Males exhibiting greater rates of utilization than other groups. States that undertook the interventions were more likely to have had improvements in disparities or positive disparities for women and minorities. While some gains were made over this time period, the gains were unevenly distributed across the USA and more work needs to be done to reduce remaining disparities.