Prostate Cancer Incidence and Aggressiveness in Appalachia versus Non-Appalachia Populations in Pennsylvania by Urban-Rural Regions, 2004-2014

Differences in Rural Versus Urban Patients With Prostate Cancer in Diagnosis and Treatment: An Analysis of a Population-Based Cohort

PURPOSE

Patients living in rural communities have greater barriers to cancer care and poorer outcomes. We hypothesized that rural patients with prostate cancer have less access and receive different treatments compared with urban patients.

METHODS

We used a population-based prospective cohort, the North Carolina Prostate Cancer Comparative Effectiveness and Survivorship Study, to compare differences in prostate cancer diagnosis, access to care, and treatment in patients by geographic residence. The 2013 rural-urban continuum code (RUCC) was used to determine urban (RUCC 1-3) versus rural (RUCC 4-9) location of residence.

RESULTS

Patients with rural residence comprised 25% of the cohort (364 of 1,444); they were less likely to be White race and had lower income and educational attainment. Rural patients were more likely to have <12 cores on biopsy (47.1% v 35.7%; P < .001) and less likely (40.8% v 47.6%; P = .04) to receive multidisciplinary consultation. We observed significant differences in treatment between urban and rural patients, including rural patients receiving less active surveillance or observation (22.6% v 28.7%), especially in low-risk cancer (33.2% v 40.7%). On multivariable analysis that adjusted for patient and diagnostic factors, rural residence was associated with less use of active surveillance or observation over radical treatment (ie, surgery or radiation therapy; odds ratio, 0.49 v urban; P < .001) in patients with low-risk cancer.

CONCLUSION

Patients with prostate cancer who live in rural versus urban areas experience several differences in care that are likely clinically meaningful, including fewer cores in the diagnostic biopsy, less utilization of multidisciplinary consultation, less use of active surveillance, or observation for low-risk disease. Future studies are needed to assess the efficacy of interventions in mitigating these disparities.

Spatial-temporal Bayesian accelerated failure time models for survival endpoints with applications to prostate cancer registry data

Prostate cancer is the most common cancer after non-melanoma skin cancer and the second leading cause of cancer deaths in US men. Its incidence and mortality rates vary substantially across geographical regions and over time, with large disparities by race, geographic regions (i.e., Appalachia), among others. The widely used Cox proportional hazards model is usually not applicable in such scenarios owing to the violation of the proportional hazards assumption. In this paper, we fit Bayesian accelerated failure time models for the analysis of prostate cancer survival and take dependent spatial structures and temporal information into account by incorporating random effects with multivariate conditional autoregressive priors. In particular, we relax the proportional hazards assumption, consider flexible frailty structures in space and time, and also explore strategies for handling the temporal variable. The parameter estimation and inference are based on a Monte Carlo Markov chain technique under a Bayesian framework. The deviance information criterion is used to check goodness of fit and to select the best candidate model. Extensive simulations are performed to examine and compare the performances of models in different contexts. Finally, we illustrate our approach by using the 2004-2014 Pennsylvania Prostate Cancer Registry data to explore spatial-temporal heterogeneity in overall survival and identify significant risk factors.

Patterns of Cancer-Related Healthcare Access across Pennsylvania: Analysis of Novel Census Tract-Level Indicators of Persistent Poverty

BACKGROUND

Persistent poverty census tracts have had ≥20% of the population living below the federal poverty line for 30+ years. We assessed the relationship between persistent poverty and cancer-related healthcare access across census tracts in Pennsylvania.

METHODS

We gathered publicly available census tract-level data on persistent poverty, rurality, and sociodemographic variables, as well as potential access to healthcare (i.e., prevalence of health insurance, last-year check-up), realized access to healthcare (i.e., prevalence of screening for cervical, breast, and colorectal cancers), and self-reported cancer diagnosis. We used multivariable spatial regression models to assess the relationships between persistent poverty and each healthcare access indicator.

RESULTS

Among Pennsylvania's census tracts, 2,789 (89.8%) were classified as non-persistent poverty, and 316 (10.2%) were classified as persistent poverty (113 did not have valid data on persistent poverty). Persistent poverty tracts had lower prevalence of health insurance [estimate = -1.70, standard error (SE) = 0.10], screening for cervical cancer (estimate = -4.00, SE = 0.17) and colorectal cancer (estimate = -3.13, SE = 0.20), and cancer diagnosis (estimate = -0.34, SE = 0.05), compared with non-persistent poverty tracts (all P < 0.001). However, persistent poverty tracts had higher prevalence of last-year check-up (estimate = 0.22, SE = 0.08) and screening for breast cancer (estimate = 0.56, SE = 0.15; both P < 0.01).

CONCLUSIONS

Relationships between persistent poverty and cancer-related healthcare access outcomes differed in direction and magnitude. Health promotion interventions should leverage data at fine-grained geographic units (e.g., census tracts) to motivate focus on communities or outcomes.

IMPACT

Future studies should extend these analyses to other states and outcomes to inform public health research and interventions to reduce geographic disparities.

LionVu: A Data-Driven Geographical Web-GIS Tool for Community Health and Decision-Making in a Catchment Area

In 2018, the Penn State Cancer Institute developed LionVu, a web mapping tool to educate and inform community health professionals about the cancer burden in Pennsylvania and its catchment area of 28 counties in central Pennsylvania. LionVu, redesigned in 2023, uses several open-source JavaScript libraries (i.e., Leaflet, jQuery, Chroma, Geostats, DataTables, and ApexChart) to allow public health researchers the ability to map, download, and chart 21 publicly available datasets for clinical, educational, and epidemiological audiences. County and census tract data used in choropleth maps were all downloaded from the sources website and linked to Pennsylvania and catchment area county and census tract geographies, using a QGIS plugin and Leaflet JavaScript. Two LionVu demonstrations are presented, and 10 other public health related web-GIS applications are reviewed. LionVu fills a role in the public health community by allowing clinical, educational, and epidemiological audiences the ability to visualize and utilize health data at various levels of aggregation and geographical scales (i.e., county, or census tracts). Also, LionVu is a novel application that can translate and can be used, for mapping and graphing purposes. A dialog to demonstrate the potential value of web-based GIS to a wider audience, in the public health research community, is needed.

Ambient air exposures to arsenic and cadmium and overall and prostate cancer-specific survival among prostate cancer cases in Pennsylvania, 2004 to 2014

BACKGROUND

Exposures to arsenic (As) and cadmium (Cd) have been associated with higher prostate cancer (PC) mortality; however, these associations have been inconsistent. The authors investigated whether higher ambient air concentrations of As and Cd are associated with lower overall and PC-specific survival among PC cases in Pennsylvania.

METHODS

Incident PC cases of patients, aged 40 years or older, with a clinical diagnosis and nonmetastatic disease were identified in the 2004 to 2014 Pennsylvania Cancer Registry. Demographic, clinical, and pathologic information were extracted from the Pennsylvania Cancer Registry. The 3- and 5-year average and cumulative air concentrations of As and Cd were extracted from the Environmental Protection Agency's Toxics Release Inventory database. Spatial-temporal hierarchical accelerated failure time models were used to examine the associations between air concentrations of As and Cd and overall and PC-specific survival for the total population and stratified by geographical region defined by rurality and Appalachia status, after adjusting for confounders.

RESULTS

There were 78,914 PC cases included. Increasing 3- and 5-year average and cumulative air concentrations of As and Cd were significantly associated with lower overall and PC-specific survival among cases, after adjusting for confounders, for the total population, and stratified by geographical region for most of the estimates.

CONCLUSIONS

Data suggest that increasing ambient air exposures to As and Cd may play a role in overall and PC-specific mortality risk among PC cases. Exposures to As and Cd are modifiable and may provide insight into potential strategies to improve PC health outcomes.

LAY SUMMARY

Arsenic and cadmium exposures linked to increased prostate cancer deaths remain unclear. We investigated whether air levels of arsenic and cadmium reported to be released from industries decrease overall and prostate cancer-specific survival among prostate cancer cases identified in the 2004 to 2014 Pennsylvania Cancer Registry. Among the 78,914 prostate cancer cases, increasing air levels of arsenic and cadmium are found to be associated with lower overall and prostate cancer-specific survival for the total population and within rural and urban Appalachia and urban non-Appalachia counties in Pennsylvania. Reducing exposures to arsenic and cadmium have the potential to decrease prostate cancer deaths.

Sociodemographic and Geographic Disparities of Prostate Cancer Treatment Delay in Tennessee: A Population-Based Study

The relationship of social determinants of health, Appalachian residence, and prostate cancer treatment delay among Tennessee adults is relatively unknown. We used multivariate logistic regression on 2005–2015 Tennessee Cancer Registry data of adults aged ≥18 diagnosed with prostate cancer. The outcome of treatment delay was more than 90 days without surgical or nonsurgical intervention from date of diagnosis. Social determinants in the population-based registry were race (White, Black, Other) and marital status (single, married, divorced/separated, widow/widower). Tennessee residence was classified as Appalachian versus non-Appalachian (urban/rural). Covariates include age at diagnosis (18–54, 54–69, ≥70), health insurance type (none, public, private), derived staging of cancer (localized, regional, distant), and treatment type (non-surgical/surgical). We found that Black and divorced/separated patients had 32% (95% confidence interval [CI]: 1.22–1.42) and 15% (95% CI: 1.01–1.31) increased odds to delay prostate cancer treatment. Patients were at decreased odds of treatment delay when living in an Appalachian county, both urban (odds ratio [OR] = 0.89, 95% CI: 0.82–0.95) and rural (OR = 0.83, 95% CI: 0.78–0.89), diagnosed at ≥70 (OR = 0.59, 95% CI: 0.53–0.66), and received surgical intervention (OR = 0.72, 95% CI: 0.68–0.76). Our study was among the first to comprehensively examine prostate cancer treatment delay in Tennessee, and while we do not make clinical recommendations, there is a critical need to further explore the unique factors that may propagate disparities. Prostate cancer treatment delay in Black patients may be indicative of ongoing health and access disparities in Tennessee, which may further affect quality of life and survivorship among this racial group. Divorced/separated patients may need tailored interventions to improve social support.

Rural-Urban Geographical Disparities in Hepatocellular Carcinoma Incidence Among US Adults, 2004-2017

INTRODUCTION

To evaluate impact of urbanicity and household income on hepatocellular carcinoma (HCC) incidence among US adults.

METHODS

HCC incidence was evaluated by rural-urban geography and median annual household income using 2004-2017 Surveillance, Epidemiology, and End Results data.

RESULTS

Although overall HCC incidence was highest in large metropolitan regions, average annual percent change in HCC incidence was greatest among more rural regions. Individuals in lower income categories had highest HCC incidence and greatest average annual percent change in HCC incidence.

DISCUSSION

Disparities in HCC incidence by urbanicity and income likely reflect differences in risk factors, health-related behaviors, and barriers in access to healthcare services.

Identifying Risk Profiles of Malignant Prostate Cancer Surgical Delay Using a Person-Centered Approach to Understand Prostate Cancer Disparities: The Constellation of Health Determinants Using Latent Class Analysis on Cancer Registry Data

Surgical prostate cancer (PCa) treatment delay (TD) may increase the likelihood of recurrence of disease, and influence quality of life as well as survival disparities between Black and White men. We used latent class analysis (LCA) to identify risk profiles in localized, malignant PCa surgical treatment delays while assessing co-occurring social determinants of health. Profiles were identified by age, marital status, race, county of residence (non-Appalachian or Appalachian), and health insurance type (none/self-pay, public, or private) reported in the Tennessee Department of Health cancer registry from 2005 to 2015 for adults ≥18 years (N = 18,088). We identified three risk profiles. The highest surgical delay profile (11% of the sample) with a 30% likelihood of delaying surgery >90 days were young Black men, <55 years old, living in a non-Appalachian county, and single/never married, with a high probability of having private health insurance. The medium surgical delay profile (46% of the sample) with a 21% likelihood of delay were 55–69 years old, White, married, and having private health insurance. The lowest surgical delay profile (42% of the sample) with a 14% likelihood of delay were ≥70 years with public health insurance as well as had a high probability of being White and married. We identified that even with health insurance coverage, Blacks living in non-Appalachian counties had the highest surgical delay, which was almost double that of Whites in the lowest delay profile. These disparities in PCa surgical delay may explain differences in health outcomes in Blacks who are most at-risk.