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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. [ABSTRACT FROM AUTHOR]

PURPOSE: Previous randomized controlled trials have demonstrated benefit from remote symptom monitoring (RSM) with electronic patient-reported outcomes. However, the racial diversity of enrolled patients was low and did not reflect the real-world racial proportions for individuals with cancer. METHODS: This secondary, cross-sectional analysis evaluated engagement of patients with cancer in a RSM program. Patient-reported race was grouped as Black, Other, or White. Patient address was used to map patient residence to determine rurality using Rural-Urban Commuting Area Codes and neighborhood disadvantage using Area Deprivation Index. Key outcomes included (1) being approached for RSM enrollment, (2) declining enrollment, (3) adherence with RSM via continuous completion of symptom surveys, and (4) withdrawal from RSM participation. Risk ratios (RR) and 95% CI were estimated from modified Poisson models with robust SEs. RESULTS: Between May 2021 and May 2023, 883 patients were approached to participate, of which 56 (6%) declined RSM. Of those who enrolled in RSM, a total of 27% of patients were Black or African American and 67% were White. In adjusted models, all patient population subgroups of interest had similar likelihoods of being approached for RSM participation; however, Black or African American patients were more than 3× more likely to decline participation than White participants (RR, 3.09 [95% CI, 1.73 to 5.53]). Patients living in more disadvantaged neighborhoods were less likely to decline (RR, 0.49 [95% CI, 0.24 to 1.02]), but less likely to adhere to surveys (RR, 0.81 [95% CI, 0.68 to 0.97]). All patient populations had a similar likelihood of withdrawing. CONCLUSION: Black patients and individuals living in more disadvantaged neighborhoods are at risk for lower engagement in RSM. Further work is needed to identify and overcome barriers to equitable participation. Black patients and individuals living in more disadvantaged neighborhoods are at risk for lower engagement in remote symptom monitoring [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Background: The American Indian (AI) population in North Carolina has limited access to the Indian Health Service. Consequently, cancer burden and disparities may differ from national estimates. We describe the AI cancer population and examine AI-White disparities in cancer incidence and mortality. Methods: We identified cancer cases diagnosed among adult AI and White populations between 2014 and 2018 from the North Carolina Central Cancer Registry. We estimated incidence and mortality rate ratios (IRR and MRR) by race. In addition, between the AI and White populations, we estimated the ratio of relative frequency differences [RRF, with 95% confidence limits (CL)] of clinical and sociodemographic characteristics. Finally, we evaluated the geographic distribution of incident diagnoses among AI populations. Results: Our analytic sample included 2,161 AI and 204,613 White individuals with cancer. Compared with the White population, the AI population was more likely to live in rural areas (48% vs. 25%; RRF, 1.89; 95% CL, 1.81-1.97) and to have Medicaid (18% vs. 7%; RRF, 2.49; 95% CL, 2.27-2.71). Among the AI population, the highest age-standardized incidence rates were female breast, followed by prostate and lung and bronchus. Liver cancer incidence was significantly higher among the AI population than White population (IRR, 1.27; 95% CL, 1.01-1.59). AI patients had higher mortality rates for prostate (MRR, 1.72; CL, 1.09-2.70), stomach (MRR, 1.82; 95% CL, 1.15-2.86), and liver (MRR, 1.70; 95% CL, 1.25-2.33) cancers compared with White patients. Conclusions: To reduce prostate, stomach, and liver cancer disparities among AI populations in North Carolina, multi-modal interventions targeting risk factors and increasing screening and treatment are needed. [ABSTRACT FROM AUTHOR]

Background: Severe skin and soft tissue infections related to injection drug use have increased in concordance with a shift to heroin and illicitly manufactured fentanyl. Opioid agonist therapy medications (methadone and buprenorphine) may improve long-term outcomes by reducing injection drug use. We aimed to examine the association of medication use with mortality among people with opioid use-related skin or soft tissue infections. Methods: An observational cohort study of Medicaid enrollees aged 18 years or older following their first documented medical encounters for opioid use-related skin or soft tissue infections during 2007–2018 in North Carolina. The exposure was documented medication use (methadone or buprenorphine claim) in the first 30 days following initial infection compared with no medication claim. Using Kaplan–Meier estimators, we examined the difference in 3-year incidence of mortality by medication use, weighted for year, age, comorbidities, and length of hospital stay. Results: In this sample, there were 13,286 people with opioid use-related skin or soft tissue infections. The median age was 37 years, 68% were women, and 78% were white. In Kaplan–Meier curves for the total study population, 12 of every 100 patients died during the first 3 years. In weighted models, for every 100 people who used medications, there were four fewer deaths over 3 years (95% confidence interval = 2, 6). Conclusion: In this study, people with opioid use-related skin and soft tissue infections had a high risk of mortality following their initial healthcare visit for infections. Methadone or buprenorphine use was associated with reductions in mortality. [ABSTRACT FROM AUTHOR]