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Background Many women diagnosed with cancer as adolescents and young adults (AYAs, age 15-39 years) want biological children after cancer but lack information on the potential impact of their cancer history on future reproductive outcomes. We investigated the risk of adverse birth outcomes among AYA cancer survivors. Methods We identified insured women diagnosed with AYA breast cancer, thyroid cancer, gynecologic cancers, lymphoma, or melanoma from 2003 to 2016 in the state of North Carolina or the Kaiser Permanente health care systems in northern and southern California. Post-diagnosis births to cancer survivors were each matched with up to 5 births to women without cancer. Risk ratios for preterm birth (<37 completed weeks), very preterm birth (<34 completed weeks), low birth weight (<2500 g), and small for gestational age (SGA, <10th percentile of weight for gestational age) were estimated using modified Poisson regression. Results Analyses included 1648 births to 1268 AYA cancer survivors and 7879 births to 6066 women without cancer. Overall, risk of preterm birth, very preterm birth, low birth weight, and SGA did not significantly differ between births to women with and without cancer. However, births to women with gynecologic cancers had a significantly increased risk of low birth weight (risk ratio = 1.82; 95% confidence interval: 1.03 to 3.21) and suggested increased risk of preterm birth (risk ratio = 1.59; 95% confidence interval: 0.99 to 2.54). Chemotherapy exposure was not associated with increased risk of adverse birth outcomes. Conclusions Women with gynecologic cancers, but not other cancers, had an increased risk of adverse birth outcomes compared to women without cancer. [ABSTRACT FROM AUTHOR]

Background: Population-based linked datasets are vital to generate catchment area and population health research. The novel Cancer Information & Population Health Resource (CIPHR) links statewide cancer registry data, public and private insurance claims, and provider- and area-level data, representing more than 80% of North Carolina's large, diverse population of individuals diagnosed with cancer. This scoping review of articles that used CIPHR data characterizes the breadth of research generated and identifies further opportunities for population-based health research., Methods: Articles published January 2012 - August 2023 were categorized by cancer site and outcomes examined across the care continuum. Statistically significant associations between patient-, provider-, and system/policy-level factors and outcomes were summarized., Results: Among 51 articles, 42 reported results across 23 unique cancer sites and 13 aggregated across multiple sites. The most common outcomes examined were treatment initiation and/or adherence (n = 14), mortality/survival (n = 9), and health care resource utilization (n = 9). Few articles focused on cancer recurrence (n = 1) or distance to care (n = 1) as outcomes. Many articles discussed racial, ethnic, geographic, and socioeconomic inequities in care., Conclusions: These findings demonstrate the value of robust, longitudinal, linked, population-based databases to facilitate catchment area and population health research aimed at elucidating cancer risk factors, outcomes, care delivery trends, and inequities that warrant intervention and policy attention. Lessons learned from years of analytics using CIPHR highlight opportunities to explore less-frequently studied cancers and outcomes, motivate equity-focused interventions, and inform development of similar resources., (© The Author(s) 2024. Published by Oxford University Press.)

Background: The University of North Carolina at Chapel Hill Lineberger Comprehensive Cancer Center (LCCC) 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., Objective: To describe the CIPHR data and provide examples of potential cohorts available in CIPHR data., Methods: We present the underlying populations included in the NCCCR and claims data prior to 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 non-cancer cases). When limited to first or only cancers (n = 672,377) 86% could be linked to insurance enrollment for at least one month during 2003-2020 (n = 582,638), with 61% 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 state-wide, comprehensive cancer population health database. This resource serves to characterize the cancer center catchment area and aids in tracking cancer outcomes, trends in care delivery, as well as identifying disparities that require intervention and policy focus., (© The Author(s) 2024. Published by Oxford University Press.)

Background: No population-based studies have examined chronic opioid use among cancer survivors who are diverse with respect to diagnosis, age group, and insurance status., Methods: We conducted a retrospective cohort study using North Carolina cancer registry data linked with claims from public and private insurance (2006-2016). We included adults with nonmetastatic cancer who had no prior chronic opioid use (n = 38 366). We used modified Poisson regression to assess the adjusted relative risk of chronic opioid use in survivorship (>90-day continuous supply of opioids in the 13-24 months following diagnosis) associated with patient characteristics., Results: Only 3.0% of cancer survivors in our cohort used opioids chronically in survivorship. Predictors included younger age (adjusted risk ratio [aRR] 50-59 vs 60-69 = 1.23, 95% confidence interval [CI] = 1.05 to 1.43), baseline depression (aRR = 1.22, 95% CI = 1.06 to 1.41) or substance use (aRR = 1.43, 95% CI = 1.15 to 1.78) and Medicaid (aRR vs private = 1.93, 95% CI = 1.56 to 2.40). Survivors who used opioids intermittently (vs not at all) before diagnosis were twice as likely to use opioids chronically in survivorship (aRR = 2.62, 95% CI = 2.28 to 3.02). Those who used opioids chronically (vs intermittently or not at all) during active treatment had a nearly 17-fold increased likelihood of chronic use in survivorship (aRR = 16.65, 95% CI = 14.30 to 19.40)., Conclusions: Younger and low-income survivors, those with baseline depression or substance use, and those who require chronic opioid therapy during treatment are at increased risk for chronic opioid use in survivorship. Our findings point to opportunities to improve assessment of psychosocial histories and to engage patients in shared decision-making around long-term pain management, when chronic opioid therapy is required during treatment., (© The Author(s) 2021. Published by Oxford University Press.)

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., (© 2019 The Authors.)