Cancer treatment and survivorship statistics, 2022.

The number of cancer survivors continues to increase in the United States due to the growth and aging of the population as well as advances in early detection and treatment. To assist the public health community in better serving these individuals, the American Cancer Society and the National Cancer Institute collaborate triennially to estimate cancer prevalence in the United States using incidence and survival data from the Surveillance, Epidemiology, and End Results cancer registries, vital statistics from the Centers for Disease Control and Prevention's National Center for Health Statistics, and population projections from the US Census Bureau. Current treatment patterns based on information in the National Cancer Database are presented for the most prevalent cancer types by race, and cancer-related and treatment-related side-effects are also briefly described. More than 18 million Americans (8.3 million males and 9.7 million females) with a history of cancer were alive on January 1, 2022. The 3 most prevalent cancers are prostate (3,523,230), melanoma of the skin (760,640), and colon and rectum (726,450) among males and breast (4,055,770), uterine corpus (891,560), and thyroid (823,800) among females. More than one-half (53%) of survivors were diagnosed within the past 10 years, and two-thirds (67%) were aged 65 years or older. One of the largest racial disparities in treatment is for rectal cancer, for which 41% of Black patients with stage I disease receive proctectomy or proctocolectomy compared to 66% of White patients. Surgical receipt is also substantially lower among Black patients with non-small cell lung cancer, 49% for stages I-II and 16% for stage III versus 55% and 22% for White patients, respectively. These treatment disparities are exacerbated by the fact that Black patients continue to be less likely to be diagnosed with stage I disease than White patients for most cancers, with some of the largest disparities for female breast (53% vs 68%) and endometrial (59% vs 73%). Although there are a growing number of tools that can assist patients, caregivers, and clinicians in navigating the various phases of cancer survivorship, further evidence-based strategies and equitable access to available resources are needed to mitigate disparities for communities of color and optimize care for people with a history of cancer. CA Cancer J Clin. 2022;72:409-436.

Health insurance status and cancer stage at diagnosis and survival in the United States.

Previous studies using data from the early 2000s demonstrated that patients who were uninsured were more likely to present with late-stage disease and had worse short-term survival after cancer diagnosis in the United States. In this report, the authors provide comprehensive data on the associations of health insurance coverage type with stage at diagnosis and long-term survival in individuals aged 18-64 years who were diagnosed between 2010 and 2013 with 19 common cancers from the National Cancer Database, with survival follow-up through December 31, 2019. Compared with privately insured patients, Medicaid-insured and uninsured patients were significantly more likely to be diagnosed with late-stage (III/IV) cancer for all stageable cancers combined and separately. For all stageable cancers combined and for six cancer sites-prostate, colorectal, non-Hodgkin lymphoma, oral cavity, liver, and esophagus-uninsured patients with Stage I disease had worse survival than privately insured patients with Stage II disease. Patients without private insurance coverage had worse short-term and long-term survival at each stage for all cancers combined; patients who were uninsured had worse stage-specific survival for 12 of 17 stageable cancers and had worse survival for leukemia and brain tumors. Expanding access to comprehensive health insurance coverage is crucial for improving access to cancer care and outcomes, including stage at diagnosis and survival.

The Affordable Care Act and access to care across the cancer control continuum: A review at 10 years.

Lack of health insurance coverage is strongly associated with poor cancer outcomes in the United States. The uninsured are less likely to have access to timely and effective cancer prevention, screening, diagnosis, treatment, survivorship, and end-of-life care than their counterparts with health insurance coverage. On March 23, 2010, the Patient Protection and Affordable Care Act (ACA) was signed into law, representing the largest change to health care delivery in the United States since the introduction of the Medicare and Medicaid programs in 1965. The primary goals of the ACA are to improve health insurance coverage, the quality of care, and patient outcomes, and to maintain or lower costs by catalyzing changes in the health care delivery system. In this review, we describe the main components of the ACA, including health insurance expansions, coverage reforms, and delivery system reforms, provisions within these components, and their relevance to cancer screening and early detection, care, and outcomes. We then highlight selected, well-designed studies examining the effects of the ACA provisions on coverage, access to cancer care, and disparities throughout the cancer control continuum. Finally, we identify research gaps to inform evaluation of current and emerging health policies related to cancer outcomes.

Cancer treatment and survivorship statistics, 2019.

The number of cancer survivors continues to increase in the United States because of the growth and aging of the population as well as advances in early detection and treatment. To assist the public health community in better serving these individuals, the American Cancer Society and the National Cancer Institute collaborate every 3 years to estimate cancer prevalence in the United States using incidence and survival data from the Surveillance, Epidemiology, and End Results cancer registries; vital statistics from the Centers for Disease Control and Prevention's National Center for Health Statistics; and population projections from the US Census Bureau. Current treatment patterns based on information in the National Cancer Data Base are presented for the most prevalent cancer types. Cancer-related and treatment-related short-term, long-term, and late health effects are also briefly described. More than 16.9 million Americans (8.1 million males and 8.8 million females) with a history of cancer were alive on January 1, 2019; this number is projected to reach more than 22.1 million by January 1, 2030 based on the growth and aging of the population alone. The 3 most prevalent cancers in 2019 are prostate (3,650,030), colon and rectum (776,120), and melanoma of the skin (684,470) among males, and breast (3,861,520), uterine corpus (807,860), and colon and rectum (768,650) among females. More than one-half (56%) of survivors were diagnosed within the past 10 years, and almost two-thirds (64%) are aged 65 years or older. People with a history of cancer have unique medical and psychosocial needs that require proactive assessment and management by follow-up care providers. Although there are growing numbers of tools that can assist patients, caregivers, and clinicians in navigating the various phases of cancer survivorship, further evidence-based resources are needed to optimize care.

Protecting Caribbean patients diagnosed with cancer from compounding disasters.

Caribbean small island developing states are becoming increasingly vulnerable to compounding disasters, prominently featuring climate-related hazards and pandemic diseases, which exacerbate existing barriers to cancer control in the region. We describe the complexities of cancer prevention and control efforts throughout the Caribbean small island developing states, including the unique challenges of people diagnosed with cancer in the region. We highlight potential solutions and strategies that concurrently address disaster adaptation and cancer control. Because Caribbean small island developing states are affected first and worst by the hazards of compounding disasters, the innovative solutions developed in the region are relevant for climate mitigation, disaster adaptation, and cancer control efforts globally. In the age of complex and cascading disaster scenarios, developing strategies to mitigate their effect on the cancer control continuum, and protecting the health and safety of people diagnosed with cancer from extreme events become increasingly urgent. The equitable development of such strategies relies on collaborative efforts among professionals whose diverse expertise from complementary fields infuses the local community perspective while focusing on implementing solutions.

Changes in cancer incidence rates by stage during the COVID-19 pandemic in the US.

The coronavirus disease 2019 (COVID-19) pandemic led to health care disruptions and declines in cancer diagnoses in the United States. However, the impact of the pandemic on cancer incidence rates by stage at diagnosis and race and ethnicity is unknown. This cross-sectional study calculated delay- and age-adjusted incidence rates, stratified by stage at diagnosis and race and ethnicity, and rate ratios (RRs) comparing changes in year-over-year incidence rates (eg, 2020 vs 2019) from 2016 to 2020 for 22 cancer types based on data obtained from the Surveillance, Epidemiology, and End Results 22-registry database. From 2019 to 2020, the incidence of local-stage disease statistically significantly declined for 19 of the 22 cancer types, ranging from 4% (RR = 0.96; 95%CI, 0.93-0.98) for urinary bladder cancer to 18% for colorectal (RR = 0.82; 95%CI, 0.81-0.84) and laryngeal (RR = 0.82; 95%CI, 0.78-0.88) cancers, deviating from pre-COVID stable year-over-year changes. Incidence during the corresponding period also declined for 16 cancer types for regional-stage and six cancer types for distant-stage disease. By race and ethnicity, the decline in local-stage incidence for screening-detectable cancers was generally greater in historically marginalized populations. The decline in cancer incidence rates during the first year of the COVID-19 pandemic occurred mainly for local- and regional-stage diseases across racial and ethnic groups. Whether these declines will lead to increases in advanced-stage disease and mortality rates remain to be investigated with additional data years. Nevertheless, the findings reinforce the importance of strengthening the return to preventive care campaigns and outreach for detecting cancers at early and more treatable stages.

The National Cancer Database Conforms to the Standardized Framework for Registry and Data Quality.

BACKGROUND: Standardization of procedures for data abstraction by cancer registries is fundamental for cancer surveillance, clinical and policy decision-making, hospital benchmarking, and research efforts. The objective of the current study was to evaluate adherence to the four components (completeness, comparability, timeliness, and validity) defined by Bray and Parkin that determine registries' ability to carry out these activities to the hospital-based National Cancer Database (NCDB). METHODS: Tbis study used data from U.S. Cancer Statistics, the official federal cancer statistics and joint effort between the Centers for Disease Control and Prevention (CDC) and the National Cancer Institute (NCI), which includes data from National Program of Cancer Registries (NPCR) and Surveillance, Epidemiology, and End Results (SEER) to evaluate NCDB completeness between 2016 and 2020. The study evaluated comparability of case identification and coding procedures. It used Commission on Cancer (CoC) standards from 2022 to assess timeliness and validity. RESULTS: Completeness was demonstrated with a total of 6,828,507 cases identified within the NCDB, representing 73.7% of all cancer cases nationwide. Comparability was followed using standardized and international guidelines on coding and classification procedures. For timeliness, hospital compliance with timely data submission was 92.7%. Validity criteria for re-abstracting, recording, and reliability procedures across hospitals demonstrated 94.2% compliance. Additionally, data validity was shown by a 99.1% compliance with histologic verification standards, a 93.6% assessment of pathologic synoptic reporting, and a 99.1% internal consistency of staff credentials. CONCLUSION: The NCDB is characterized by a high level of case completeness and comparability with uniform standards for data collection, and by hospitals with high compliance, timely data submission, and high rates of compliance with validity standards for registry and data quality evaluation.

The Intersectionality of Climate Change and Post-Stroke Aphasia.

Persons with communication disabilities including persons with post-stroke aphasia (PWAs) possess a vulnerability to climate change as a result of their communication impairments. The disproportionate effects of climate change are likely to exacerbate preexisting inequities in social determinants of health. Communication disability intersecting with other characteristics subject to discrimination (e.g., race, age, sex, income) may lead to inequities in climate-related adaptive capacity. This article echoes earlier concerns related to climate change and further educates healthcare professionals about the impact of climate change on the global human population, with particular consideration of PWAs. The aims of this article are the following: (1) to broaden the understanding of aphasiologists and clinicians caring for PWAs about climate change and the contributions of human activity (anthropogenic) to this crisis; (2) to describe climate change and its impact on health; (3) to detail the intersectionality of climate and health; (4) to explore climate change and its potential effects on PWAs; and (5) to offer hope through emissions reduction, adaptation, resilience, and immediate change.

Changes in cancer diagnoses and stage distribution during the first year of the COVID-19 pandemic in the USA: a cross-sectional nationwide assessment.

BACKGROUND: The emergence of COVID-19 disrupted health care, with consequences for cancer diagnoses and outcomes, especially for early stage diagnoses, which generally have favourable prognoses. We aimed to examine nationwide changes in adult cancer diagnoses and stage distribution during the first year of the COVID-19 pandemic by cancer type and key sociodemographic factors in the USA. METHODS: In this cross-sectional study, adults (aged ≥18 years) newly diagnosed with a first primary malignant cancer between Jan 1, 2018, and Dec 31, 2020, were identified from the US National Cancer Database. We included individuals across 50 US states and the District of Columbia who were treated in hospitals that were Commission on Cancer-accredited during the study period. Individuals whose cancer stage was 0 (except for bladder cancer), occult, or without an applicable American Joint Committee on Cancer staging scheme were excluded. Our primary outcomes were the change in the number and the change in the stage distribution of new cancer diagnoses between 2019 (Jan 1 to Dec 31) and 2020 (Jan 1 to Dec 31). Monthly counts and stage distributions were calculated for all cancers combined and for major cancer types. We also calculated annual change in stage distribution from 2019 to 2020 and adjusted odds ratios (aORs) using multivariable logistic regression, adjusted for age group, sex, race and ethnicity, health insurance status, comorbidity score, US state, zip code-level social deprivation index, and county-level age-adjusted COVID-19 mortality in 2020. Separate models were stratified by sociodemographic and clinical factors. FINDINGS: We identified 2 404 050 adults who were newly diagnosed with cancer during the study period (830 528 in 2018, 849 290 in 2019, and 724 232 in 2020). Mean age was 63·5 years (SD 13·5) and 1 287 049 (53·5%) individuals were women, 1 117 001 (46·5%) were men, and 1 814 082 (75·5%) were non-Hispanic White. The monthly number of new cancer diagnoses (all stages) decreased substantially after the start of the COVID-19 pandemic in March, 2020, although monthly counts returned to near pre-pandemic levels by the end of 2020. The decrease in diagnoses was largest for stage I disease, leading to lower odds of being diagnosed with stage I disease in 2020 than in 2019 (aOR 0·946 [95% CI 0·939-0·952] for stage I vs stage II-IV); whereas, the odds of being diagnosed with stage IV disease were higher in 2020 than in 2019 (1·074 [1·066-1·083] for stage IV vs stage I-III). This pattern was observed in most cancer types and sociodemographic groups, although was most prominent among Hispanic individuals (0·922 [0·899-0·946] for stage I; 1·110 [1·077-1·144] for stage IV), Asian American and Pacific Islander individuals (0·924 [0·892-0·956] for stage I; 1·096 [1·052-1·142] for stage IV), uninsured individuals (0·917 [0·875-0·961] for stage I; 1·102 [1·055-1·152] for stage IV), Medicare-insured adults younger than 65 years (0·909 [0·882-0·937] for stage I; 1·105 [1·068-1·144] for stage IV), and individuals living in the most socioeconomically deprived areas (0·931 [0·917-0·946] for stage I; 1·106 [1·087-1·125] for stage IV). INTERPRETATION: Substantial cancer underdiagnosis and decreases in the proportion of early stage diagnoses occurred during 2020 in the USA, particularly among medically underserved individuals. Monitoring the long-term effects of the pandemic on morbidity, survival, and mortality is warranted. FUNDING: None.

Evaluation of the Impact of the COVID-19 Pandemic on Reliability of Cancer Surveillance Data in the National Cancer Database.

PURPOSE: This study evaluated the reliability of cancer cases reported to the National Cancer Database (NCDB) during 2020, the first year of the COVID-19 pandemic. METHODS: Total number of cancer cases reported to the NCDB between January 2018 and December 2020 were calculated for all cancers and 21 selected cancer sites. The additive outlier method was used to identify structural breaks in trends compared with previous years. The difference between expected (estimated using the vector autoregressive method) and observed number of cases diagnosed in 2020 was estimated using generalized estimating equation under assumptions of the Poisson distribution for count data. Interrupted time series analysis was used to compare changes in the number of records processed by registrars each month of 2020. All models accounted for seasonality, regional variation, and random error. RESULTS: There was a statistically significant decrease (structural break) in the number of cases diagnosed in April 2020, with no recovery in number of cases during subsequent months, leading to a 12.4% deficit in the number of cases diagnosed during the first year of the pandemic. While the number of cancer records initiated by cancer registrars also decreased, the number of records marked completed increased during the first months of the pandemic. CONCLUSION: There was a significant deficit in the number of cancer diagnoses in 2020 that was not due to cancer registrars' inability to extract data during the pandemic. Future studies can use NCDB data to evaluate the impact of the pandemic on cancer care and outcomes.

Access to Care Among Adults with Limited English Proficiency.

BACKGROUND: There are approximately 25.6 million individuals with limited English proficiency (LEP) in the USA, and this number is increasing. OBJECTIVE: Investigate associations between LEP and access to care in adults. DESIGN: Cross-sectional nationally representative survey. PARTICIPANTS: Adults with (n = 18,908) and without (n = 98,060) LEP aged ≥ 18 years identified from the 2014-2018 Medical Expenditure Panel Survey MAIN MEASURES: Associations between LEP and access to healthcare and preventive services were evaluated with multivariable logistic regression models, stratified by age group (18-64 and ≥ 65 years). The official government definition of LEP (answers "not at all/not well/well" to the question "How well do you speak English?") was used. Access to care included having a usual source of care (and if so, distance from usual source of care, difficulty contacting usual source of care, and provision of extended hours), visiting a medical provider in the past 12 months, having to forego or delay care, and having trouble paying for medical bills. Preventive services included blood pressure and cholesterol check, flu vaccination, and cancer screening. KEY RESULTS: Adults aged 18-64 years with LEP were significantly more likely to lack a usual source of care (adjusted odds ratios [aOR] = 2.48; 95% confidence interval [CI] = 2.27-2.70), not have visited a medical provider (aOR = 2.02; CI = 1.89-2.16), and to be overdue for receipt of preventive services, including blood pressure check (aOR = 2.00; CI = 1.79-2.23), cholesterol check (aOR = 1.22; CI = 1.03-1.44), and colorectal cancer screening (aOR = 1.58; CI = 1.37-1.83) than adults without LEP. Results were similar among adults aged ≥ 65 years. CONCLUSIONS: Adults with LEP had consistently worse access to care than adults without LEP. System-level interventions, such as expanding access to health insurance coverage, providing language services, improving provider training in cultural competence, and increasing diversity in the medical workforce may minimize barriers and improve equity in access to care.

The first year of the COVID-19 pandemic and health among cancer survivors in the United States.

BACKGROUND: Cancer survivors represent a population with high health care needs. If and how cancer survivors were affected by the first year of the coronavirus disease 2019 (COVID-19) pandemic are largely unknown. METHODS: Using data from the nationwide, population-based Behavioral Risk Factor Surveillance System (2017-2020), the authors investigated changes in health-related measures during the COVID-19 pandemic among cancer survivors and compared them with changes among adults without a cancer history in the United States. Sociodemographic and health-related measures such as insurance coverage, employment status, health behaviors, and health status were self-reported. Adjusted prevalence ratios of health-related measures in 2020 versus 2017-2019 were calculated with multivariable logistic regressions and stratified by age group (18-64 vs. ≥65 years). RESULTS: Among adults aged 18-64 years, the uninsured rate did not change significantly in 2020 despite increases in unemployment. The prevalence of unhealthy behaviors, such as insufficient sleep and smoking, decreased in 2020, and self-rated health improved, regardless of cancer history. Notably, declines in smoking were larger among cancer survivors than nonelderly adults without a cancer history. Few changes were observed for adults aged ≥65 years. CONCLUSIONS: Further research is needed to confirm the observed positive health behavior and health changes and to investigate the role of potential mechanisms, such as the national and regional policy responses to the pandemic regarding insurance coverage, unemployment benefits, and financial assistance. As polices related to the public health emergency expire, ongoing monitoring of longer term effects of the pandemic on cancer survivorship is warranted.

Twenty-Five Years of Cancer Follow-Up; Is the Data Worth the Effort?

BACKGROUND: Substantial resources are dedicated to long-term follow-up within cancer registries; however, the completeness of these data is poorly characterized. Our objectives were to quantify long-term cancer follow-up data completeness and the effort required to collect these data using the National Cancer Database (NCDB). METHODS: To quantify data completeness, patients diagnosed with cancer in 1989 were identified in the NCDB and loss to follow-up rates were assessed for 25 years after diagnosis. To quantify data collection effort, patients diagnosed from 1989 to 2014 who were alive and eligible for follow-up in 2014 were identified and the effort to perform patient follow-up was obtained via a survey of tumor registrars. The effort to perform follow-up beyond various intervals after diagnosis was calculated. RESULTS: In total, 484,201 patients at 958 hospitals were diagnosed with cancer in 1989. After 5 years, 6.5% of patients were lost to follow-up (13.1% of living patients), 50.3% were deceased, and 43.2% had ongoing follow-up. After 15 years, 22.9% were lost to follow-up (68.7% of living patients), 66.7% were deceased, and 10.5% had ongoing follow-up. By 25 years, loss to follow-up increased to 28.6% (93.7% of living patients), 69.5% were deceased, and 1.9% had ongoing follow-up. In 2014, 522,838 h were spent performing follow-up for 2,091,353 patients at 1456 hospitals who were >15 years from their initial cancer diagnosis. CONCLUSIONS: While 5-year follow-up is excellent in the NCDB, loss to follow-up increases over time. The impact of curtailing data collection is under investigation and follow-up duration requirements will be re-evaluated.

Paid Sick Leave Among Working Cancer Survivors and Its Associations With Use of Preventive Services in the United States.

BACKGROUND: We sought to examine the lack of paid sick leave among working cancer survivors by sociodemographic/socioeconomic and employment characteristics and its association with preventive services use in the United States. METHODS: Working cancer survivors (ages 18-64 years; n=7,995; weighted n=3.43 million) were identified using 2001-2018 National Health Interview Survey data. Adjusted prevalence of lack of paid sick leave by sociodemographic and socioeconomic characteristics, as well as job sector, working hours, and employer size, were generated using multivariable logistic regression models. Separate analyses examined the associations of lack of paid sick leave with use of various preventive services. RESULTS: Of all working cancer survivors, 36.4% lacked paid sick leave (n=2,925; weighted n=1.25 million), especially those working in food/agriculture/construction/personal services occupations or industries (ranging from 54.9% to 88.5%). In adjusted analyses, working cancer survivors with lower household income (<200% of the federal poverty level, 48.7%), without a high school degree (43.3%), without health insurance coverage (70.6%), and who were self-employed (89.5%), were part-time workers (68.2%), or worked in small businesses (<50 employees, 48.8%) were most likely to lack paid sick leave. Lack of paid sick leave was associated with lower use of influenza vaccine (ages 18-39 years, 21.3% vs 33.3%; ages 40-49 years, 25.8% vs 38.3%; ages 50-64 years, 46.3% vs 52.4%; P<.001 for all), cholesterol screening (ages 18-39 years, 43.1% vs 62.5%; P<.05), and blood pressure check (ages 18-39 years, 43.1% vs 62.5%; P<.05) compared with survivors having paid sick leave. CONCLUSIONS: In the United States, more than one-third of all working cancer survivors and more than half of survivors working for small employers and in certain occupations/industries lack paid sick leave. Survivors with lower household income or educational attainment are particularly vulnerable. Moreover, lack of paid sick leave is associated with lower use of some recommended preventive services, suggesting that ensuring working cancer survivors have access to paid sick leave may be an important mechanism for reducing health disparities.

Evaluating information loss in the National Cancer Database from cases lost to follow-up.

BACKGROUND AND OBJECTIVES: Cancer registries must focus on data capture which returns value while reducing resource burden with minimal loss of data. Identifying the optimum length of follow-up data collection for patients with cancer achieves this goal. METHODS: A two-step analysis using entropy calculations to assess information gain for each follow-up year, and second-order differences to compare survival outcomes between the defined follow-up periods and lifetime follow-up. A total of 391 567 adult cases, deidentified in the National Cancer Database and diagnosed in 1989. Comparisons examined a subset of 61 908 lung cancer cases, 48 387 colon and rectal cancer cases, and 64 134 breast cancer cases in adults. A total of 4133 pediatric cases were diagnosed in 1989 examining 1065 leukemia cases and 494 lymphoma cases. RESULTS: Annual increases in information gain fell below 1% after 16 years of follow-up for adult cases and 9 years for pediatric cases. Comparison of second-order differences showed 62% of the comparisons were similar between 15 years and lifetime follow-up when examining restricted mean survival time. In addition, 90% of the comparisons were statistically similar when comparing hazard ratios. CONCLUSIONS: Survival analysis using 15 years postdiagnosis follow-up showed minimal differences in information gain compared to lifetime follow-up.

Preexisting Condition Protections Under the Affordable Care Act: Changes in Insurance Coverage, Premium Contributions, and Out-of-Pocket Spending.

OBJECTIVES: In January 2014, the Affordable Care Act (ACA) preexisting condition protections prohibited coverage denials, premium increases, and claim denials on the basis of preexisting conditions. This study aimed to examine changes in coverage and premiums and out-of-pocket spending after the implementation of the preexisting condition protections under the ACA. METHODS: We identified adults aged 18 to 64 years with (n = 59 041) and without preexisting conditions (n = 61 970) from the 2011-2013 and 2015-2017 Medical Expenditure Panel Survey. We used a difference-in-differences and a difference-in-difference-in-differences approach to assess the associations of preexisting condition protections and changes in insurance coverage, premium contributions, and out-of-pocket spending after the ACA. Simple and multivariable logistic or multivariable 2-part models were fitted for the full sample and stratified by family income (low ≤138% federal poverty level [FPL]; middle 139%-400% FPL; and high > 400 FPL). RESULTS: The ACA increased nongroup insurance coverage to a similar extent for individuals with or without preexisting conditions at all income levels. Decreases in premium contributions were observed to a similar extent among families with nongroup private coverage regardless of declinable preexisting condition status, whereas no significant changes were observed among families with group coverage. We found greater decreases in out-of-pocket spending for individuals with preexisting conditions than those without conditions among both individuals covered by nongroup and group insurance, and a greater difference was observed among those covered by nongroup insurance (difference-in-difference-in-differences -$279; 95% confidence interval -$528 to -$29). CONCLUSIONS: The ACA protections were associated with decreases in out-of-pocket spending among adults with preexisting conditions.

Immune and hormonal regulation of the Boa constrictor (Serpentes; Boidae) in response to feeding.

Feeding upregulates immune function and the systemic and local (gastrointestinal tract) concentrations of some immunoregulatory hormones, as corticosterone (CORT) and melatonin (MEL), in mammals and anurans. However, little is known about the immune and hormonal regulation in response to feeding in other ectothermic vertebrates, especially snakes, in which the postprandial metabolic changes are pronounced. Here, we investigated the effects feeding have on hormonal and innate immune responses in the snake, Boa constrictor. We divided juvenile males into two groups: fasting and fed with mice (30% of body mass). We measured the rates of oxygen consumption, plasma CORT levels, heterophil/lymphocyte ratio (HL ratio), plasma bacterial killing ability (BKA), and stomach and intestine MEL in fasting snakes and 48 h after meal intake. We observed increased rates of oxygen consumption, plasma CORT levels, and HL ratio, along with a tendency of decreased stomach and intestine MEL in fed snakes compared to fasting ones. BKA was not affected by feeding. Overall, we found that feeding modulates metabolic rates, CORT levels, and immune cell distribution in boas. Increased baseline CORT may be important to mobilize energy to support the metabolic increment during the postprandial period. Increased HL ratio might be an immunoregulatory effect of increased CORT, which has been shown in different physiological situations such as in response to immune challenge. Our results suggest that feeding activates the hypothalamic-pituitary-adrenal axis and modulates immune cell redistribution, possibly contributing to fighting potential injuries and infections derived from predation and from pathogens present in ingested food.

Association of obesity and annual health care utilization and spending among long-term cancer survivors.

BACKGROUND: Obesity is associated with a substantial health and economic burden in the general population in the United States. This study estimates the excess health care utilization and medical spending associated with overweight and obesity among long-term cancer survivors. METHODS: Long-term cancer survivors (≥2 years after their diagnosis) aged ≥18 years (N = 12,547) were identified from the nationally representative 2008-2016 Medical Expenditure Panel Survey. A 2-part modeling approach was used to calculate the average annual care utilization and spending by service type. Excess care utilization and spending associated with overweight (25 kg/m2 ≤ body mass index [BMI] < 30 kg/m2 ), obesity (BMI ≥ 30 kg/m2 ), and severe obesity (BMI ≥ 40 kg/m2 ), in comparison with normal weight (18.5 kg/m2 ≤ BMI < 25 kg/m2 ), were estimated. RESULTS: Compared with normal-weight cancer survivors, overweight survivors had comparable care utilization and medical spending; survivors with obesity had an additional $3216 (95% CI, $1940-$4492) of medical spending, including $1243 (95% CI, $417-$2070) on hospital inpatient services and $1130 (95% CI, $756-$1504) on prescriptions per person per year. The excess annual medical spending associated with obesity among long-term cancer survivors translated to $19.7 billion in 2016 in the United States. The excess medical spending was magnified in cancer survivors with severe obesity ($5317 [95% CI, $2849-$7785], which translated to $6.7 billion in 2016). Excess care utilization and medical spending were mostly explained by comorbid conditions related to obesity. CONCLUSIONS: For long-term cancer survivors, obesity was associated with increased health care utilization and substantial excess medical spending. This suggests that policies and practices promoting a healthy lifestyle and achieving and maintaining a healthy body weight for cancer survivors may reduce their health care utilization and economic burden.

Immune and hormonal modulation in the postprandial period of bullfrogs (Lithobates catesbeianus).

Mammals show immune up-regulation and increased plasma and local (gastrointestinal tract) concentrations of some immunoregulatory hormones, such as corticosterone and melatonin, after feeding. However, little is known about the endocrine and immune modulation in the postprandial period of ectothermic animals. This study investigated the effects of feeding on endocrine and immune responses in the bullfrog (Lithobates catesbeianus). Frogs were fasted for 10 days and divided into two groups: fasted and fed with fish feed (5% of body mass). Blood and gastrointestinal tract tissues (stomach and intestine) were collected at 6, 24, 48, 96 and 168 h to measure neutrophil/lymphocyte ratio, plasma bacterial killing ability, phagocytosis of blood leukocytes, plasma corticosterone and melatonin, and stomach and intestine melatonin. Feeding increased plasma corticosterone at 24 h and decreased it at 168 h, and increased neutrophil/lymphocyte ratio at 6, 24 and 96 h. We also observed decreased bacterial killing ability 48 h after feeding. Stomach melatonin increased after 17 days of fasting. We show that feeding activates the hypothalamic-pituitary-interrenal axis and promotes transient immunosuppression, without stimulating an inflammatory response. Increased corticosterone may mobilize energy to support digestive processes and melatonin may protect the stomach during fasting. We conclude that feeding modulates secretion of immunoregulatory hormones, initially increasing plasma corticosterone levels, followed by a decrease at the end of meal digestion, and causes systemic immune cell redistribution, increasing neutrophil/lymphocyte ratio for almost the entire period of meal digestion in bullfrogs. Also, fasting modulates secretion of melatonin in the stomach.