Health Insurance Literacy Improvements Among Recently Diagnosed Adolescents and Young Adults With Cancer: Results From a Pilot Randomized Controlled Trial.

PURPOSE: Adolescents and young adults (AYAs; age 18-39 years) with cancer report needing support with health insurance. We conducted a pilot randomized controlled trial to assess the feasibility and acceptability of a virtual health insurance navigation intervention (HIAYA CHAT) to improve health insurance literacy (HIL), awareness of Affordable Care Act (ACA) protections, financial toxicity, and stress. MATERIALS AND METHODS: HIAYA CHAT is a four-session navigator delivered program; it includes psychoeducation on insurance, navigating one's plan, insurance-related laws, and managing costs. Participants were eligible if they could access an internet-capable device, were <1 year from diagnosis, and received treatment from University of Utah Healthcare or Intermountain Health systems. We assessed the feasibility, acceptability, and preliminary efficacy of HIAYA CHAT compared with usual navigation care, including HIL (nine items), insurance knowledge (13 items), ACA protections (eight items), COmprehensive Score for financial Toxicity (COST; 11 items), and Perceived Stress Scale (PSS; four items), using t tests and Cohen's d. RESULTS: From November 2020 to December 2021, N = 86 AYAs enrolled (44.6% participation) and 89.3% completed the 5-month follow-up survey; 68.6% were female, 72.1% were White, 23.3% were Hispanic, 65.1% were age 26-39 years, and 87.2% were privately insured. Of intervention participants (n = 45), 67.4% completed all four sessions; among an exit interview subset (n = 10), all endorsed the program (100%). At follow-up, compared with usual navigation care, intervention participants had greater improvements in HIL, insurance and ACA protections knowledge, and PSS; effect sizes ranged from moderate to large (0.42-0.77). COST did not differ. CONCLUSION: The results support the feasibility and acceptability of HIAYA CHAT with related improvements in HIL.

COVID-19-Related Employment Disruptions and Increased Financial Burden Among Survivors of Adolescent and Young Adult Cancer.

Background: Financial burden is a major concern for survivors of adolescent and young adult (AYA) cancers. We identified if employment disruptions during the COVID-19 pandemic affected AYA survivors' financial burden. Methods: AYAs who were enrolled in a cancer patient navigation program were e-mailed a survey in fall 2020. Survey items included sociodemographics, employment disruption, and two measures of financial burden: COmprehensive Score for Financial Toxicity (COST) and material and behavioral financial hardship items (for any reason, COVID-19 induced, cancer induced). Financial burden outcomes were dichotomized at the median (COST = 21; financial hardship = 3). The association of employment disruptions and sociodemographics with financial burden was assessed using multivariable logistic regression models. Results: Reduced hours/job loss was reported by 24.0% of 341 participants. Survivors with a high school education or less (odds ratio [OR]: 2.70; 95% confidence interval [CI]: 1.21-6.03) or who had decreased hours or job loss (OR: 3.97; 95% CI: 2.01-7.84) had greater odds for high financial toxicity. Reduced hours/job loss was the only factor associated with high material and behavioral financial hardship for both any reason (OR: 2.75; 95% CI: 1.41-5.33) and owing to COVID-19 (OR: 4.98; 95% CI: 2.28-10.92). Cancer treatment since March 2020 was associated with cancer-induced high material and behavioral financial hardship (OR: 3.31; 95% CI: 1.96-5.58). Conclusion: Employment disruptions owing to the COVID-19 pandemic, lower education levels, and cancer treatment were associated with high financial burden among AYA cancer survivors. Our findings suggest the need for multilevel interventions to identify and address financial burden among vulnerable cancer survivors.

Sources of informal financial support among adolescent and young adult cancer survivors: a mixed methods analysis from the HIAYA CHAT study.

PURPOSE: The purpose of this exploratory sequential mixed methods study was to describe the sources of informal financial support used by adolescent and young adult (AYA) cancer survivors and how financial toxicity and demographic factors were associated with different types and magnitudes of informal financial support. METHODS: This analysis is part of a larger health insurance literacy study that included pre-trial interviews and a randomized controlled trial (RCT) for AYA cancer survivors. Eligible study participants were 18 years of age, diagnosed with cancer as an AYA (15-39 years), insured, and for the RCT sample less than 1 year from diagnosis. Interview audio was transcribed, quality checked, and thematically analyzed. RCT baseline and follow-up surveys captured informal financial support use. Chi-squared and Fisher's exact tests were used to assess differences in informal financial support type use and frequency by financial toxicity and AYA demographics. RESULTS: A total of N = 24 and N = 86 AYAs participated in pre-trial interviews and the RCT respectively. Interview participants reported a variety of informal financial support sources including savings, community, family/friends, and fundraisers. However, only half of participants reported their informal financial support to be sufficient. High financial toxicity was associated with the most types of informal financial support and a higher magnitude of use. The lowest income group accessed informal financial supports less frequently than higher income groups. CONCLUSION: Our study demonstrates that AYA survivors experiencing financial toxicity frequently turn to informal sources of financial support and the magnitude is associated with financial toxicity. However, low-income survivors, and other at-risk survivors, may not have access to informal sources of financial support potentially widening inequities.

HIAYA CHAT study protocol: a randomized controlled trial of a health insurance education intervention for newly diagnosed adolescent and young adult cancer patients.

BACKGROUND: For adolescent and young adult (AYA) cancer patients aged 18 to 39 years, health insurance literacy is crucial for an effective use of the health care system. AYAs often face high out-of-pocket costs or have unmet health care needs due to costs. Improving health insurance literacy could help AYAs obtain appropriate and affordable health care. This protocol illustrates a randomized controlled trial testing a virtual health insurance education intervention among AYA patients. METHODS: This is a two-arm multisite randomized controlled trial. A total of 80 AYAs diagnosed with cancer in the Mountain West region will be allocated to either usual navigation care or tailored health insurance education intervention with a patient navigator that includes usual care. All participants will complete a baseline and follow-up survey 5 months apart. The primary outcomes are feasibility (number enrolled and number of sessions completed) and acceptability (5-point scale on survey measuring satisfaction of the intervention). The secondary outcomes are preliminary efficacy measured by the Health Insurance Literacy Measure and the COmprehensive Score for financial Toxicity. DISCUSSION: This trial makes a timely contribution to test the feasibility and acceptability of a virtual AYA-centered health insurance education program. TRIAL REGISTRATION: ClinicalTrials.gov NCT04448678. Registered on June 26, 2020.

"I thought there would be more I understood": health insurance literacy among adolescent and young adult cancer survivors.

BACKGROUND: Health insurance literacy is crucial for navigating the US healthcare system. Low health insurance literacy may be especially concerning for adolescent and young adult (AYA) cancer survivors. To describe AYAs' health insurance literacy, we conducted semi-structured interviews with AYA survivors, on and off of treatment. METHODS: We interviewed 24 AYA cancer survivors (aged 18-39 years) between November 2019 and March 2020. Interviews were recorded, transcribed, and quality-checked. Using two cycles of structured coding, we explored AYAs' health insurance literacy and examined thematic differences by policy holder status and age. RESULTS: AYAs were 58.3% female, 79.2% non-Hispanic White, 91.7% heterosexual, and 62.5% receiving cancer treatment. Most participants had employer-sponsored health insurance (87.5%), and 41.7% were their own policy holder. Four themes emerged; in the first theme, most AYAs described beginning their cancer treatment with little to no understanding of their health insurance. This led to the three subsequent themes in which AYAs reported: unclear expectations of what their insurance would cover and their out-of-pocket costs; learning about insurance and costs by trial and error; and how their health insurance literacy negatively impacted their ability to navigate the healthcare system. CONCLUSIONS: Our findings, while requiring confirmation in larger samples and in other health systems, suggest that the health insurance literacy needed to navigate insurance and cancer care is low among US AYA survivors and may have health and financial implications. As the burden of navigating insurance is often put on patients, health insurance education is an important supportive service for AYA survivors on and off of treatment.

Assessment of Regional Variability in COVID-19 Outcomes Among Patients With Cancer in the United States.

Importance: The COVID-19 pandemic has had a distinct spatiotemporal pattern in the United States. Patients with cancer are at higher risk of severe complications from COVID-19, but it is not well known whether COVID-19 outcomes in this patient population were associated with geography. Objective: To quantify spatiotemporal variation in COVID-19 outcomes among patients with cancer. Design, Setting, and Participants: This registry-based retrospective cohort study included patients with a historical diagnosis of invasive malignant neoplasm and laboratory-confirmed SARS-CoV-2 infection between March and November 2020. Data were collected from cancer care delivery centers in the United States. Exposures: Patient residence was categorized into 9 US census divisions. Cancer center characteristics included academic or community classification, rural-urban continuum code (RUCC), and social vulnerability index. Main Outcomes and Measures: The primary outcome was 30-day all-cause mortality. The secondary composite outcome consisted of receipt of mechanical ventilation, intensive care unit admission, and all-cause death. Multilevel mixed-effects models estimated associations of center-level and census division-level exposures with outcomes after adjustment for patient-level risk factors and quantified variation in adjusted outcomes across centers, census divisions, and calendar time. Results: Data for 4749 patients (median [IQR] age, 66 [56-76] years; 2439 [51.4%] female individuals, 1079 [22.7%] non-Hispanic Black individuals, and 690 [14.5%] Hispanic individuals) were reported from 83 centers in the Northeast (1564 patients [32.9%]), Midwest (1638 [34.5%]), South (894 [18.8%]), and West (653 [13.8%]). After adjustment for patient characteristics, including month of COVID-19 diagnosis, estimated 30-day mortality rates ranged from 5.2% to 26.6% across centers. Patients from centers located in metropolitan areas with population less than 250 000 (RUCC 3) had lower odds of 30-day mortality compared with patients from centers in metropolitan areas with population at least 1 million (RUCC 1) (adjusted odds ratio [aOR], 0.31; 95% CI, 0.11-0.84). The type of center was not significantly associated with primary or secondary outcomes. There were no statistically significant differences in outcome rates across the 9 census divisions, but adjusted mortality rates significantly improved over time (eg, September to November vs March to May: aOR, 0.32; 95% CI, 0.17-0.58). Conclusions and Relevance: In this registry-based cohort study, significant differences in COVID-19 outcomes across US census divisions were not observed. However, substantial heterogeneity in COVID-19 outcomes across cancer care delivery centers was found. Attention to implementing standardized guidelines for the care of patients with cancer and COVID-19 could improve outcomes for these vulnerable patients.

Enrollment of adolescents and young adults onto SWOG cancer research network clinical trials: A comparative analysis by treatment site and era.

BACKGROUND: Few adolescents and young adults (AYAs, 15-39 years old) enroll onto cancer clinical trials, which hinders research otherwise having the potential to improve outcomes in this unique population. Prior studies have reported that AYAs are more likely to receive cancer care in community settings. The National Cancer Institute (NCI) has led efforts to increase trial enrollment through its network of NCI-designated cancer centers (NCICC) combined with community outreach through its Community Clinical Oncology Program (CCOP; replaced by the NCI Community Oncology Research Program in 2014). METHODS: Using AYA proportional enrollment (the proportion of total enrollments who were AYAs) as the primary outcome, we examined enrollment of AYAs onto SWOG therapeutic trials at NCICC, CCOP, and non-NCICC/non-CCOP sites from 2004 to 2013 by type of site, study period (2004-08 vs 2009-13), and patient demographics. RESULTS: Overall, AYA proportional enrollment was 10.1%. AYA proportional enrollment decreased between 2004-2008 and 2009-2013 (13.1% vs 8.5%, P < .001), and was higher at NCICCs than at CCOPs and non-NCICC/non-CCOPs (14.1% vs 8.3% and 9.2%, respectively; P < .001). AYA proportional enrollment declined significantly at all three site types. Proportional enrollment of AYAs who were Black or Hispanic was significantly higher at NCICCs compared with CCOPs or non-NCICC/non-CCOPs (11.5% vs 8.8, P = .048 and 11.5% vs 8.6%, P = .03, respectively). CONCLUSION: Not only did community sites enroll a lower proportion of AYAs onto cancer clinical trials, but AYA enrollment decreased in all study settings. Initiatives aimed at increasing AYA enrollment, particularly in the community setting with attention to minority status, are needed.

Inside Dynamics of Integrodifference Equations with Mutations.

The method of inside dynamics provides a theory that can track the dynamics of neutral gene fractions in spreading populations. However, the role of mutations has so far been absent in the study of the gene flow of neutral fractions via inside dynamics. Using integrodifference equations, we develop a neutral genetic mutation model by extending a previously established scalar inside dynamics model. To classify the mutation dynamics, we define a mutation class as the set of neutral fractions that can mutate into one another. We show that the spread of neutral genetic fractions is dependent on the leading edge of population as well as the structure of the mutation matrix. Specifically, we show that the neutral fractions that contribute to the spread of the population must belong to the same mutation class as the neutral fraction found in the leading edge of the population. We prove that the asymptotic proportion of individuals at the leading edge of the population spread is given by the dominant right eigenvector of the associated mutation matrix, independent of growth and dispersal parameters. In addition, we provide numerical simulations to demonstrate our mathematical results, to extend their generality and to develop new conjectures about our model.

Age-Related Differences in Financial Toxicity and Unmet Resource Needs Among Adolescent and Young Adult Cancer Patients.

Financial toxicity may differ by age at diagnosis between adolescents and young adults (AYAs) with cancer. We surveyed 52 AYA cancer patients about unmet needs and financial toxicity using the COmprehensive Score for financial Toxicity (COST). We compared outcomes by age at diagnosis (15-25-year olds [n = 25, 48%] vs. 26-39-year olds [n = 27, 52%]). AYAs diagnosed ages 26-39 reported that cancer negatively affected their finances more than 15-25-year olds (77.8% vs. 37.5%, p = 0.0005). Lower mean COST scores among those diagnosed ages 26-39 indicated greater financial toxicity compared to those 15-25 years (18.22 vs. 24.84, p = 0.02). Financial burden appears to be greater for older AYAs with cancer.

Robustness of movement models: can models bridge the gap between temporal scales of data sets and behavioural processes?

Discrete-time random walks and their extensions are common tools for analyzing animal movement data. In these analyses, resolution of temporal discretization is a critical feature. Ideally, a model both mirrors the relevant temporal scale of the biological process of interest and matches the data sampling rate. Challenges arise when resolution of data is too coarse due to technological constraints, or when we wish to extrapolate results or compare results obtained from data with different resolutions. Drawing loosely on the concept of robustness in statistics, we propose a rigorous mathematical framework for studying movement models' robustness against changes in temporal resolution. In this framework, we define varying levels of robustness as formal model properties, focusing on random walk models with spatially-explicit component. With the new framework, we can investigate whether models can validly be applied to data across varying temporal resolutions and how we can account for these different resolutions in statistical inference results. We apply the new framework to movement-based resource selection models, demonstrating both analytical and numerical calculations, as well as a Monte Carlo simulation approach. While exact robustness is rare, the concept of approximate robustness provides a promising new direction for analyzing movement models.

Preoperative assessment of the pancreas in multiple endocrine neoplasia type 1.

BACKGROUND: Many serologic and radiographic modalities are used for monitoring multiple endocrine neoplasia type 1 (MEN 1) patients for pancreaticoduodenal neuroendocrine tumors (PNETs). We compared serum markers and imaging studies obtained preoperatively with the gross pathology and immunohistochemical findings and correlated preoperative testing with postoperative outcome. METHODS: From 2000 to 2008, 52 MEN 1 patients [32 (62%) female; median age = 43 years, range 19-74 years] underwent 56 pancreatic operations [49 (88%) distal pancreatectomies] for suspected PNETs. Preoperative serum markers [human pancreatic polypeptide (HPP), gastrin, and glucagon] and imaging [CT, (111)In pentetreotide scintigraphy, and endoscopic ultrasound (EUS)] were compared to the pathologic findings. Postoperative serum markers and survival were followed. RESULTS: Human pancreatic polypeptide had the highest agreement between an elevated serum level and positive tumor immunostaining (83% vs. 50% agreement for gastrin vs. 67% agreement for glucagon). Preoperative CT had 81% sensitivity and positive predictive value (PPV) of 97% for PNETs. (111)In pentetreotide scintigraphy had 84% sensitivity and PPV of 96%. Preoperative endoscopic ultrasonography (EUS) had 100% sensitivity and PPV, with close correlation (r (s) = 0.93) between the largest lesion seen on EUS and pathology. Median follow-up was 4.3 years (range = 0.1-10.9 years). Overall survival was 89% at 5-year follow-up. CONCLUSIONS: Our study substantiates EUS as providing the highest preoperative sensitivity and PPV in assessing the presence of PNETs in MEN 1 patients. CT and octreotide scintigraphy can yield both false-positive and false-negative results. HPP, gastrin, and glucagon were the most commonly measured tumor markers in our series but did not always correlate with immunostaining. With an aggressive surgical approach, satisfactory rates of biochemical improvement and long-term survival were observed.

Mechanistic home range models capture spatial patterns and dynamics of coyote territories in Yellowstone.

Patterns of space-use by individuals are fundamental to the ecology of animal populations influencing their social organization, mating systems, demography and the spatial distribution of prey and competitors. To date, the principal method used to analyse the underlying determinants of animal home range patterns has been resource selection analysis (RSA), a spatially implicit approach that examines the relative frequencies of animal relocations in relation to landscape attributes. In this analysis, we adopt an alternative approach, using a series of mechanistic home range models to analyse observed patterns of territorial space-use by coyote packs in the heterogeneous landscape of Yellowstone National Park. Unlike RSAs, mechanistic home range models are derived from underlying correlated random walk models of individual movement behaviour, and yield spatially explicit predictions for patterns of space-use by individuals. As we show here, mechanistic home range models can be used to determine the underlying determinants of animal home range patterns, incorporating both movement responses to underlying landscape heterogeneities and the effects of behavioural interactions between individuals. Our analysis indicates that the spatial arrangement of coyote territories in Yellowstone is determined by the spatial distribution of prey resources and an avoidance response to the presence of neighbouring packs. We then show how the fitted mechanistic home range model can be used to correctly predict observed shifts in the patterns of coyote space-use in response to perturbation.