Multilevel Interventions and Dental Attendance in Pediatric Primary Care: A Cluster Randomized Clinical Trial.

Importance: Untreated tooth decay is disproportionately present among low-income young children. While American Academy of Pediatrics (AAP) guidelines require pediatric clinicians to implement oral health care, the effectiveness of these oral health interventions has been inconclusive. Objective: To test the effectiveness of multilevel interventions in increasing dental attendance and reducing untreated decay among young children attending well-child visits (WCVs). Design, Setting, and Participants: The Pediatric Providers Against Cavities in Children's Teeth study is a cluster randomized clinical trial that was conducted at 18 pediatric primary care practices in northeast Ohio. The trial data were collected between November 2017 and July 2022, with data analyses conducted from August 2022 to March 2023. Eligible participants included Medicaid-enrolled preschoolers aged 3 to 6 years attending WCVs at participating practices who were enrolled at baseline (WCV 1) and followed-up for 2 consecutive examinations (WCV 2 and WCV 3). Interventions: Clinicians in the intervention group received both the practice-level (electronic medical record changes to document oral health) and clinician-level (common-sense model of self-regulation theory-based oral health education and skills training) interventions. Control group clinicians received AAP-based standard oral health education alone. Main Outcomes and Measures: Dental attendance was determined through clinical dental examinations conducted by hygienists utilizing International Caries Detection and Assessment System criteria and also from Medicaid claims data. Untreated decay was determined through clinical examinations. A generalized estimating equations (GEE) approach was used for both clinical examinations and Medicaid claims data. Results: Eighteen practices were randomized to either intervention or control. Participants included 63 clinicians (mean [SD] age, 47.0 [11.3] years; 48 female [76.2%] and 15 male [23.8%]; 28 in the intervention group [44.4%]; 35 in the control group [55.6%]) and 1023 parent-child dyads (mean [SD] child age, 56.1 [14.0] months; 555 male children [54.4%] and 466 female children [45.6%]; 517 in the intervention group [50.5%]; 506 in the control group [49.5%]). Dental attendance from clinical examinations was significantly higher in the intervention group (170 children [52.0%]) vs control group (150 children [43.1%]) with a difference of 8.9% (95% CI, 1.4% to 16.4%; P = .02). The GEE model using clinical examinations showed a significant increase in dental attendance in the intervention group vs control group (adjusted odds ratio, 1.34; 95% CI, 1.07 to 1.69). From Medicaid claims, the control group had significantly higher dental attendance than the intervention group at 2 years (332 children [79.6%] vs 330 children [73.7%]; P = .04) but not at 3 years. A clinically but not statistically significant reduction in mean number of untreated decay was found in the intervention group compared with controls (B = -0.27; 95% CI, -0.56 to 0.02). Conclusions and Relevance: In this cluster randomized clinical trial, children in the intervention group had better dental outcomes as was evidenced by increased dental attendance and lower untreated decay. These findings suggest that intervention group clinicians comprehensively integrated oral health services into WCVs. Trial Registration: ClinicalTrials.gov Identifier: NCT03385629.

Association of School Instructional Mode with Community COVID-19 Incidence during August-December 2020 in Cuyahoga County, Ohio.

Remote and hybrid modes of instruction were employed as alternatives to in-person instruction as part of early mitigation efforts in response to the COVID-19 pandemic. We investigated the impact of a public school district's instructional mode on cumulative incidence and transmission in the surrounding community by employing a generalized estimating equations approach to estimate the association with weekly COVID-19 case counts by zip code in Cuyahoga County, Ohio, from August to December 2020. Remote instruction only (RI) was employed by 7 of 20 school districts; 13 used some non-remote instruction (NRI) (2-15 weeks). Weekly incidence increased in all zip codes from August to peak in late fall before declining. The zip code cumulative incidence within NRI school districts was higher than in those offering only RI (risk ratio = 1.12, p = 0.01; risk difference = 519 per 100,000, 95% confidence interval (123-519)). The mean effect for NRI on emergent cases 2 weeks after mode exposure, controlling for Social Vulnerability Index (SVI), was significant only for high SVI zip codes 1.30, p < 0.001. NRI may be associated with increased community COVID-19 incidence, particularly in communities with high SVI. Vulnerable communities may need more resources to open schools safely.

Assessing the Clinical Utility of Published Prostate Cancer Polygenic Risk Scores in a Large Biobank Data Set.

BACKGROUND AND OBJECTIVE: Polygenic risk scores (PRSs) have been developed to identify men with the highest risk of prostate cancer. Our aim was to compare the performance of 16 PRSs in identifying men at risk of developing prostate cancer and then to evaluate the performance of the top-performing PRSs in differentiating individuals at risk of aggressive prostate cancer. METHODS: For this case-control study we downloaded 16 published PRSs from the Polygenic Score Catalog on May 28, 2021 and applied them to Michigan Genomics Initiative (MGI) patients. Cases were matched to the Michigan Urological Surgery Improvement Collaborative (MUSIC) registry to obtain granular clinical and pathological data. MGI prospectively enrolls patients undergoing surgery at the University of Michigan, and MUSIC is a multi-institutional registry that prospectively tracks demographic, treatment, and clinical variables. The predictive performance of each PRS was evaluated using the area under the covariate-adjusted receiver operating characteristic curve (aAUC), and the association between PRS and disease aggressiveness according to prostate biopsy data was measured using logistic regression. KEY FINDINGS AND LIMITATIONS: We included 18 050 patients in the analysis, of whom 15 310 were control subjects and 2740 were prostate cancer cases. The median age was 66.1 yr (interquartile range 59.9-71.6) for cases and 56.6 yr (interquartile range 42.6-66.7) for control subjects. The PRS performance in predicting the risk of developing prostate cancer according to aAUC ranged from 0.51 (95% confidence interval 0.51-0.53) to 0.67 (95% confidence interval 0.66-0.68). By contrast, there was no association between PRS and disease aggressiveness. CONCLUSIONS AND CLINICAL IMPLICATIONS: Prostate cancer PRSs have modest real-world performance in identifying patients at higher risk of developing prostate cancer; however, they are limited in distinguishing patients with indolent versus aggressive disease. PATIENT SUMMARY: Risk scores using data for multiple genes (called polygenic risk scores) can identify men at higher risk of developing prostate cancer. However, these scores need to be refined to be able to identify men with the highest risk for clinically significant prostate cancer.

A modular simulation framework for organ allocation.

BACKGROUND: We describe and validate a new simulation framework addressing important limitations of the Simulated Allocation Models (SAMs) long used to project population effects of transplant policy changes. METHODS: We developed the Computational Open-source Model for Evaluating Transplantation (COMET), an agent-based model simulating interactions of individual donors and candidates over time to project population outcomes. COMET functionality is organized into interacting modules. Donors and candidates are synthetically generated using data-driven probability models which are adaptable to account for ongoing or hypothetical donor/candidate population trends and evolving disease management. To validate the first implementation of COMET, COMET-Lung, we attempted to reproduce lung transplant outcomes for U.S. adults from 2018-2019 and in the 6 months following adoption of the Composite Allocation Score (CAS) for lung transplant. RESULTS: Simulated (median [Interquartile Range, IQR]) vs observed outcomes for 2018-2019 were: 0.162 [0.157, 0.167] vs 0.170 waitlist deaths per waitlist year; 1.25 [1.23, 1.28] vs 1.26 transplants per waitlist year; 0.115 [0.112, 0.118] vs 0.113 post-transplant deaths per patient year; 202 [102, 377] vs 165 nautical miles travel distance. The model accurately predicted the observed precipitous decrease in transplants received by type O lung candidates in the six months following CAS implementation. CONCLUSIONS: COMET-Lung closely reproduced most observed outcomes. The use of synthetic populations in the COMET framework paves the way for examining possible transplant policy and clinical practice changes in populations reflecting realistic future states. Its flexible, modular nature can accelerate development of features to address specific research or policy questions across multiple organs.

Understanding the Utility of Less Than Six-Month Prognosis Using Administrative Data Among U.S. Nursing Home Residents With Cancer.

Background: There is a dearth of studies evaluating the utility of reporting prognostication among nursing home (NH) residents with cancer. Objective: To study factors associated with documented less than six-month prognosis, and its relationship with end-of-life (EOL) care quality measures among residents with cancer. Methods: The Surveillance, Epidemiology, and End Results linked with Medicare, and the Minimum Data Set databases was used to identify 20,397 NH residents in the United States with breast, colorectal, lung, pancreatic, or prostate cancer who died between July 2016 and December 2018. Of these, 2205 residents (10.8%) were documented with less than six-month prognosis upon NH admission. Main outcomes were more than one hospitalization, more than one emergency department visit, and any intensive care unit admission within the last 30 days of life as aggressive EOL care markers, as well as admission to hospice, receipt of advance care planning and palliative care, and survival. Specificity and sensitivity of prognosis were assessed using six-month mortality as the outcome. Propensity score matching adjusted for selection biases, and logistic regression examined association. Results: Specificity and sensitivity of documented less than six-month prognosis for mortality were 94.2% and 13.7%, respectively. Residents with documented less than six-month prognosis had greater odds of being admitted to hospice than those without (adjusted odds ratio: 3.27, 95% confidence interval: 2.86-3.62), and lower odds to receive aggressive EOL care. Conclusion: In this cohort study, documented less than six-month prognosis was associated with less aggressive EOL care. Despite its high specificity, however, low sensitivity limits its utility to operationalize care on a larger population of residents with terminal illness.

Creating synthetic populations in transplantation: A Bayesian approach enabling simulation without registry re-sampling.

Computer simulation has played a pivotal role in analyzing alternative organ allocation strategies in transplantation. The current approach to producing cohorts of organ donors and candidates for individual-level simulation requires directly re-sampling retrospective data from a transplant registry. This historical data may reflect outmoded policies and practices as well as systemic inequities in candidate listing, limiting contemporary applicability of simulation results. We describe the development of an alternative approach for generating synthetic donors and candidates using hierarchical Bayesian network probability models. We developed two Bayesian networks to model dependencies among 10 donor and 36 candidate characteristics relevant to waitlist survival, donor-candidate matching, and post-transplant survival. We estimated parameters for each model using Scientific Registry of Transplant Recipients (SRTR) data. For 100 donor and 100 candidate synthetic populations generated, proportions for each categorical donor or candidate attribute, respectively, fell within one percentage point of observed values; the interquartile ranges (IQRs) of each continuous variable contained the corresponding SRTR observed median. Comparisons of synthetic to observed stratified distributions demonstrated the ability of the method to capture complex joint variability among multiple characteristics. We also demonstrated how changing two upstream population parameters can exert cascading effects on multiple relevant clinical variables in a synthetic population. Generating synthetic donor and candidate populations in transplant simulation may help overcome critical limitations related to the re-sampling of historical data, allowing developers and decision makers to customize the parameters of these populations to reflect realistic or hypothetical future states.

Treatment Patterns and Survival Outcomes in Patients With Breast Cancer on Medicaid, Pre- and Post-Expansion.

BACKGROUND: The objective of this study was to evaluate the impact of Medicaid expansion on breast cancer treatment and survival among Medicaid-insured women in Ohio, accounting for the timing of enrollment in Medicaid relative to their cancer diagnosis and post-expansion heterogeneous Medicaid eligibility criteria, thus addressing important limitations in previous studies. METHODS: Using 2011-2017 Ohio Cancer Incidence Surveillance System data linked with Medicaid claims data, we identified women aged 18 to 64 years diagnosed with local-stage or regional-stage breast cancer (n=876 and n=1,957 pre-expansion and post-expansion, respectively). We accounted for women's timing of enrollment in Medicaid relative to their cancer diagnosis, and flagged women post-expansion as Affordable Care Act (ACA) versus non-ACA, based on their income eligibility threshold. Study outcomes included standard treatment based on cancer stage and receipt of lumpectomy, mastectomy, chemotherapy, radiation, hormonal treatment, and/or treatment for HER2-positive tumors; time to treatment initiation (TTI); and overall survival. We conducted multivariable robust Poisson and Cox proportional hazards regression analysis to evaluate the independent associations between Medicaid expansion and our outcomes of interest, adjusting for patient-level and area-level characteristics. RESULTS: Receipt of standard treatment increased from 52.6% pre-expansion to 61.0% post-expansion (63.0% and 59.9% post-expansion in the ACA and non-ACA groups, respectively). Adjusting for potential confounders, including timing of enrollment in Medicaid, being diagnosed in the post-expansion period was associated with a higher probability of receiving standard treatment (adjusted risk ratio, 1.14 [95% CI, 1.06-1.22]) and shorter TTI (adjusted hazard ratio, 1.14 [95% CI, 1.04-1.24]), but not with survival benefits (adjusted hazard ratio, 1.00 [0.80-1.26]). CONCLUSIONS: Medicaid expansion in Ohio was associated with improvements in receipt of standard treatment of breast cancer and shorter TTI but not with improved survival outcomes. Future studies should elucidate the mechanisms at play.

Comparing the use of aggressive end-of life care among frail and non-frail patients with cancer using a claims-based frailty index.

INTRODUCTION: Despite mounting consensus that end-of-life (EOL) care for patients with cancer should focus on improving quality of life, many patients continue to receive aggressive, disease-oriented treatment until death. Within this group, patients with increased frailty may be at higher risk of adverse treatment-related outcomes. We therefore examined the relationship between degree of frailty and receipt of aggressive EOL care among Medicare-insured patients with cancer in Ohio. MATERIALS AND METHODS: From the Ohio Cancer Incidence Surveillance System (OCISS) linked with Medicare claims, we identified patients diagnosed with breast, colorectal, lung, or prostate cancer who died between 2012 and 2016. Frailty was operationalized using a validated claims-based frailty index. Six quality indicators reflecting receipt of aggressive EOL care were identified from claims: (1) any cancer-directed treatment, (2) >1 emergency department (ED) visit, (3) >1 hospital admission, (4) any intensive care unit (ICU) admission in the last 30 days of life, (5) entry to hospice in the last three days of life, and (6) in-hospital mortality. Multivariable logistic regression analysis was performed to control for demographic factors, Medicare and Medicaid dual enrollment, and cancer type and stage in the relationship between frailty and aggressive EOL care. RESULTS: Overall, 31,465 patients met selection criteria. Patients with moderate/severe frailty were less likely than non-/pre-frail patients to receive any aggressive EOL care (adjusted odds ratio [aOR] 0.92 [95% confidence interval 0.86-0.99]). This group was also less likely to undergo cancer-directed treatment in their last 30 days or to enter hospice in their last three days. Increasing frailty was associated with lower odds of admission to the ICU in the last 30 days of life (mild frailty: aOR 0.88 [0.83-0.94]; moderate/severe frailty: aOR 0.85 [0.78-0.92]) or of dying in-hospital (mild frailty: 0.85 [0.79-0.91]; moderate/severe frailty: aOR 0.74 [0.67-0.82]), but higher odds of having >1 ED visit in the last 30 days of life (mild frailty: aOR 1.43 [1.32-1.53]; moderate/severe frailty: aOR 1.61 [1.47-1.77]). DISCUSSION: These findings suggest the need for more explicit discussion of emergency care seeking for patients with cancer at the end of life.

US Cancer Detection Decreased Nearly 9 Percent During The First Year Of The COVID-19 Pandemic.

We investigated the impact of the COVID-19 pandemic on cancer detection, using data from the Surveillance, Epidemiology, and End Results Program, which recently released data through the first year of the pandemic (2020). Across all cancer sites, cancer incidence fell by 8.7 percent. The most common cancers that experienced the largest disruptions were lung and bronchus, melanoma of the skin, and thyroid cancer.

Individual-level home values and cancer mortality in a statewide registry.

BACKGROUND: Prior work assessing disparities in cancer outcomes has relied on regional socioeconomic metrics. These metrics average data across many individuals, resulting in a loss of granularity and confounding with other regional factors. METHODS: Using patients' addresses at the time of diagnosis from the Ohio Cancer Incidence Surveillance System, we retrieved individual home price estimates from an online real estate marketplace. This individual-level estimate was compared with the Area Deprivation Index (ADI) at the census block group level. Multivariable Cox proportional hazards models were used to determine the relationship between home price estimates and all-cause and cancer-specific mortality. RESULTS: A total of 667 277 patients in Ohio Cancer Incidence Surveillance System were linked to individual home prices across 16 cancers. Increasing home prices, adjusted for age, stage at diagnosis, and ADI, were associated with a decrease in the hazard of all-cause and cancer-specific mortality (hazard ratio [HR] = 0.92, 95% confidence interval [CI] = 0.92 to 0.93, and HR = 0.95, 95% CI = 0.94 to 0.95, respectively). Following a cancer diagnosis, individuals with home prices 2 standard deviations above the mean had an estimated 10-year survival probability (7.8%, 95% CI = 7.2% to 8.3%) higher than those with home prices 2 standard deviations below the mean. The association between home price and mortality was substantially more prominent for patients living in less deprived census block groups (Pinteraction < .001) than for those living in more deprived census block groups. CONCLUSION: Higher individual home prices were associated with improved all-cause and cancer-specific mortality, even after accounting for regional measures of deprivation.

Incorporating Effects of Time Accrued on the Waiting List into Lung Transplantation Survival Models.

Rationale: U.S. lung transplant mortality risk models do not account for patients' disease progression as time accrues between mandated clinical parameter updates. Objectives: To investigate the effects of accrued waitlist (WL) time on mortality in lung transplant candidates and recipients beyond those expressed by worsening clinical status and to present a new framework for conceptualizing mortality risk in end-stage lung disease. Methods: Using Scientific Registry of Transplant Recipients data (2015-2020, N = 12,616), we modeled transitions among multiple clinical states over time: WL, posttransplant, and death. Using cause-specific and ordinary Cox regression to estimate trajectories of composite 1-year mortality risk as a function of time from waitlisting to transplantation, we quantified the predictive accuracy of these estimates. We compared multistate model-derived candidate rankings against composite allocation score (CAS) rankings. Measurements and Main Results: There were 11.5% of candidates whose predicted 1-year mortality risk increased by >10% by day 30 on the WL. The multistate model ascribed lower numerical rankings (i.e., higher priority) than CAS for those who died while on the WL (multistate mean; median [interquartile range] ranking at death, 227; 154 [57-334]; CAS median [interquartile range] ranking at death, 329; 162 [11-668]). Patients with interstitial lung disease were more likely to have increasing risk trajectories as a function of time accrued on the WL compared with other lung diagnoses. Conclusions: Incorporating the effects of time accrued on the WL for lung transplant candidates and recipients in donor lung allocation systems may improve the survival of patients with end-stage lung diseases on the individual and population levels.

Accounting for Medicaid expansion and regional policy and programs to advance equity in cancer prevention in the United States.

BACKGROUND: Many studies compare state-level outcomes to estimate changes attributable to Medicaid expansion. However, it is imperative to conduct more granular, demographic-level analyses to inform current efforts on cancer prevention among low-income adults. Therefore, the authors compared the volume of patients with cancer and disease stage at diagnosis in Ohio, which expanded its Medicaid coverage in 2014, with those in Georgia, a nonexpansion state, by cancer site and health insurance status. METHODS: The authors used state cancer registries from 2010 to 2017 to identify adults younger than 64 years who had incident female breast cancer, cervical cancer, or colorectal cancer. Multivariable Poisson regression was conducted by cancer type, health insurance, and state to examine the risk of late-stage disease, adjusting for individual-level and area-level covariates. A difference-in-differences framework was then used to estimate the differences in risks of late-stage diagnosis in Ohio versus Georgia. RESULTS: In Ohio, the largest increase in all three cancer types was observed in the Medicaid group after Medicaid expansion. In addition, significantly reduced risks of late-stage disease were observed among patients with breast cancer on Medicaid in Ohio by approximately 7% and among patients with colorectal cancer on Medicaid in Ohio and Georgia after expansion by approximately 6%. Notably, the authors observed significantly reduced risks of late-stage diagnosis among all patients with colorectal cancer in Georgia after expansion. CONCLUSIONS: More early stage cancers in the Medicaid-insured and/or uninsured groups after expansion suggest that the reduced cancer burden in these vulnerable population subgroups may be attributed to Medicaid expansion. Heterogeneous risks of late-stage disease by cancer type highlight the need for comprehensive evaluation frameworks, including local cancer prevention efforts and federal health policy reforms. PLAIN LANGUAGE SUMMARY: This study looked at how Medicaid expansion affected cancer diagnosis and treatment in two states, Ohio and Georgia. The researchers found that, after Ohio expanded their Medicaid program, there were more patients with cancer among low-income adults on Medicaid. The study also found that, among people on Medicaid, there were lower rates of advanced cancer at the time of diagnosis for breast cancer and colon cancer in Ohio and for colon cancer in Georgia. These findings suggest that Medicaid expansion may be effective in reducing the cancer burden among low-income adults.

Aggressive end-of-life care across gradients of cognitive impairment in nursing home patients with metastatic cancer.

BACKGROUND: Studies examining end-of-life (EOL) care in older cancer patients are scarce, and prior studies have not accounted for gradients of cognitive impairment (COG-I). We examine EOL care patterns across COG-I gradients, hypothesizing that greater COG-I severity is associated with lower odds of receiving aggressive EOL care. METHODS: Using data from the linked Surveillance Epidemiology and End Results (SEER) -Medicare -Minimum Data Set (MDS) 3.0, we identified patients with nursing facility stays (NFS) and who died with metastatic cancer from 2013 to 2017. Markers of aggressive EOL care were: cancer-directed treatment, intensive care unit admission, >1 emergency department visit, or >1 hospitalization in the last 30 days of life, hospice enrollment in the last 3 days of life, and in-hospital death. In addition to descriptive analysis, we conducted multivariable logistic regression analysis to evaluate the independent association between COG-I severity and receipt of aggressive EOL care. RESULTS: Of the 40,833 patients in our study population, 49.2% were cognitively intact; 24.4% had mild COG-I; 19.7% had moderate COG-I; and 6.7% had severe COG-I. The percent of patients who received aggressive EOL care was 62.6% and 74.2% among those who were cognitively intact and those with severe COG-I, respectively. Compared with cognitively intact patients, those with severe COG-I had 86% higher odds of receiving any type of aggressive EOL care (adjusted odds ratio (aOR): 1.86 (95% confidence interval: 1.70-2.04)), which were primarily associated with higher odds of in-hospital death. The odds of in-hospital death associated with severe COG-I were higher among those with short- than with long-term stays (aOR:2.58 (2.35-2.84) and aOR:1.40 (1.17-1.67), respectively). CONCLUSIONS: Contrary to our hypothesis, aggressive EOL care in older metastatic cancer patients with NFS was highest among those suffering severe COG-I. These findings can inform the development of interventions to help reduce aggressive EOL care in this patient population.

Variation in KRAS/NRAS/BRAF-Mutation Status by Age, Sex, and Race/Ethnicity Among a Large Cohort of Patients with Metastatic Colorectal Cancer (mCRC).

BACKGROUND: Racial/ethnic disparities in metastatic colorectal cancer (mCRC) survival are well documented as is the impact that tumor mutation of KRAS and BRAF has on prognosis. It has been suggested that frequency differences of KRAS- and BRAF-mutated tumors may partially explain this disparity. Demographic differences in mutation frequency are not well established nor whether mutation and microsatellite instability (MSI) differentially impact survival among groups. METHODS: Using data for 11,117 patients diagnosed with de-novo mCRC from an electronic health record-derived database we estimated adjusted odds ratios (aOR) to characterize the association between demographics and MSI and KRAS/NRAS/BRAF-mutation status. Stratified Cox models were used to identify differences in overall survival (OS), adjusting for treatment and demographics. RESULTS: Being female, compared to male, (aORKRAS:1.33 (1.23-1.44); aORBRAF:1.84 (1.56-2.16)), and non-Hispanic Black race (NHB), compared to non-Hispanic White (NHW) (aORKRAS:1.62 (1.42-1.85); aORBRAF: 0.55 (0.38-0.77)) were associated with KRAS- or BRAF-mutant tumors. MSI prevalence was similar across race/ethnicity but higher in women. BRAF-mutant tumors were associated with poorer prognosis overall, especially among non-white patients. Among patients who had KRAS/NRAS/BRAF-WT tumors we observed no difference in OS by race or MSI. Among patients with KRAS-mutant tumors, Hispanic patients had more favorable prognosis adjusted hazards ratio (aHR) = 0.76 (0.65-0.89)) than their NHW counterparts. Among those with BRAF-mutant tumors, NHB patients had poorer prognosis than NHW patients (aHR:1.78 (1.08-2.93)). CONCLUSION: MSI and frequency of KRAS and BRAF mutations differed by demographics. Racial/ethnic disparities in OS differed by mutation. Future studies should explore biological and/or social determinants underlying these differences.

Cancer burden in women with HIV on Medicaid: A nationwide analysis.

BACKGROUND: Cancer is the leading cause of death in people living with HIV. In the United States, nearly 1 in 4 people living with HIV are women, more than half of whom rely on Medicaid for healthcare coverage. OBJECTIVE: The objective of this study is to evaluate the cancer burden of women living with HIV on Medicaid. DESIGN: We conducted a cross-sectional study of women 18-64 years of age enrolled in Medicaid during 2012, using data from Medicaid Analytic eXtract files. METHODS: Using International Classification of Diseases, Ninth Revision, Clinical Modification diagnosis codes, we identified women living with HIV (n = 72,508) and women without HIV (n = 17,353,963), flagging the presence of 15 types of cancer and differentiating between AIDS-defining cancers and non-AIDS-defining cancers. We obtained adjusted prevalence ratios and 95% confidence intervals for each cancer and for all cancers combined, using multivariable log-binomial models, and additionally stratifying by age and race/ethnicity. RESULTS: The highest adjusted prevalence ratios were observed for Kaposi's sarcoma (81.79 (95% confidence interval: 57.11-117.22)) and non-Hodgkin's lymphoma (27.69 (21.67-35.39)). The adjusted prevalence ratios for anal and cervical cancer, both of which were human papillomavirus-associated cancers, were 19.31 (17.33-21.51) and 4.20 (3.90-4.52), respectively. Among women living with HIV, the adjusted prevalence ratio for all cancer types combined was about two-fold higher (1.99 (1.86-2.14)) in women 45-64 years of age than in women 18-44 years of age. For non-AIDS-defining cancers but not for AIDS-defining cancers, the adjusted prevalence ratios were higher in older than in younger women. There was no significant difference in the adjusted prevalence ratios for all cancer types combined in the race/ethnicity-stratified analyses of the women living with HIV cohort. However, in cancer type-specific sub-analyses, differences in adjusted prevalence ratios between Hispanic versus non-Hispanic women were observed. For example, the adjusted prevalence ratio for Hispanic women for non-Hodgkin's lymphoma was 2.00 (1.30-3.07) and 0.73 (0.58-0.92), respectively, for breast cancer. CONCLUSION: Compared to their counterparts without HIV, women living with HIV on Medicaid have excess prevalence of cervical and anal cancers, both of which are human papillomavirus related, as well as Kaposi's sarcoma and lymphoma. Older age is also associated with increased burden of non-AIDS-defining cancers in women living with HIV. Our findings emphasize the need for not only cancer screening among women living with HIV but also for efforts to increase human papillomavirus vaccination among all eligible individuals.

Association of Socioeconomic Position With Racial and Ethnic Disparities in Survival After Lung Transplant.

Importance: A recent National Academies of Sciences, Engineering, and Medicine study found that transplant outcomes varied greatly based on multiple factors, including race, ethnicity, and geographic location. They proposed a number of recommendations including studying opportunities to improve equity in organ allocation. Objective: To evaluate the role of donor and recipient socioeconomic position and region as a mediator of observed racial and ethnic differences in posttransplant survival. Design, Setting, and Participants: This cohort study included lung transplant donors and recipients with race and ethnicity information and a zip code tabulation area-defined area deprivation index (ADI) from September 1, 2011, to September 1, 2021, whose data were in the US transplant registry. Data were analyzed from June to December 2022. Exposures: Race, neighborhood disadvantage, and region of donors and recipients. Main Outcomes and Measures: Univariable and multivariable Cox proportional hazards regression were used to study the association of donor and recipient race with ADI on posttransplant survival. Kaplan-Meier method estimation was performed by donor and recipient ADI. Generalized linear models by race were fit, and mediation analysis was performed. Bayesian conditional autoregressive Poisson rate models (1, state-level spatial random effects; 2, model 1 with fixed effects for race and ethnicity, 3; model 2 excluding region; and 4: model 1 with fixed effects for US region) were used to characterize variation in posttransplant mortality and compared using ratios of mortality rates to the national average. Results: Overall, 19 504 lung transplant donors (median [IQR] age, 33 [23-46] years; 3117 [16.0%] Hispanic individuals, 3667 [18.8%] non-Hispanic Black individuals, and 11 935 [61.2%] non-Hispanic White individuals) and recipients (median [IQR] age, 60 [51-66] years; 1716 [8.8%] Hispanic individuals, 1861 [9.5%] non-Hispanic Black individuals, and 15 375 [78.8%] non-Hispanic White individuals) were included. ADI did not mediate the difference in posttransplant survival between non-Hispanic Black and non-Hispanic White recipients; it mediated only 4.1% of the survival difference between non-Hispanic Black and Hispanic recipients. Spatial analysis revealed the increased risk of posttransplant death among non-Hispanic Black recipients may be associated with region of residence. Conclusions and Relevance: In this cohort study of lung transplant donors and recipients, socioeconomic position and region of residence did not explain most of the difference in posttransplant outcomes among racial and ethnic groups, which may be due to the highly selected nature of the pretransplant population. Further research should evaluate other potentially mediating effects contributing to inequity in posttransplant survival.

Geographic Variation and Risk Factor Association of Early Versus Late Onset Colorectal Cancer.

The proportion of patients diagnosed with colorectal cancer (CRC) at age < 50 (early-onset CRC, or EOCRC) has steadily increased over the past three decades relative to the proportion of patients diagnosed at age ≥ 50 (late-onset CRC, or LOCRC), despite the reduction in CRC incidence overall. An important gap in the literature is whether EOCRC shares the same community-level risk factors as LOCRC. Thus, we sought to (1) identify disparities in the incidence rates of EOCRC and LOCRC using geospatial analysis and (2) compare the importance of community-level risk factors (racial/ethnic, health status, behavioral, clinical care, physical environmental, and socioeconomic status risk factors) in the prediction of EOCRC and LOCRC incidence rates using a random forest machine learning approach. The incidence data came from the Surveillance, Epidemiology, and End Results program (years 2000-2019). The geospatial analysis revealed large geographic variations in EOCRC and LOCRC incidence rates. For example, some regions had relatively low LOCRC and high EOCRC rates (e.g., Georgia and eastern Texas) while others had relatively high LOCRC and low EOCRC rates (e.g., Iowa and New Jersey). The random forest analysis revealed that the importance of community-level risk factors most predictive of EOCRC versus LOCRC incidence rates differed meaningfully. For example, diabetes prevalence was the most important risk factor in predicting EOCRC incidence rate, but it was a less important risk factor of LOCRC incidence rate; physical inactivity was the most important risk factor in predicting LOCRC incidence rate, but it was the fourth most important predictor for EOCRC incidence rate. Thus, our community-level analysis demonstrates the geographic variation in EOCRC burden and the distinctive set of risk factors most predictive of EOCRC.

Incidence of Aggressive End-of-Life Care Among Older Adults With Metastatic Cancer Living in Nursing Homes and Community Settings.

Importance: Nearly 10% of the 1.5 million persons residing in nursing homes (NHs) have received or will receive a diagnosis of cancer. Although aggressive end-of-life (EOL) care is common among community-dwelling patients with cancer, little is known about such patterns of care among NH residents with cancer. Objective: To compare markers of aggressive EOL care between older adults with metastatic cancer who are NH residents and their community-dwelling counterparts. Design, Setting, and Participants: This cohort study used the Surveillance, Epidemiology, and End Results database linked with the Medicare database and the Minimum Data Set (including NH clinical assessment data) for deaths occurring from January 1, 2013, to December 31, 2017, among 146 329 older patients with metastatic breast, colorectal, lung, pancreas, or prostate cancer, with a lookback period in claims data through July 1, 2012. Statistical analysis was conducted between March 2021 and September 2022. Exposures: Nursing home status. Main Outcomes and Measures: Markers of aggressive EOL care were cancer-directed treatment, intensive care unit admission, more than 1 emergency department visit or more than 1 hospitalization in the last 30 days of life, hospice enrollment in the last 3 days of life, and in-hospital death. Results: The study population included 146 329 patients 66 years of age or older (mean [SD] age, 78.2 [7.3] years; 51.9% men). Aggressive EOL care was more common among NH residents than community-dwelling residents (63.6% vs 58.3%). Nursing home status was associated with 4% higher odds of receiving aggressive EOL care (adjusted odds ratio [aOR], 1.04 [95% CI, 1.02-1.07]), 6% higher odds of more than 1 hospital admission in the last 30 days of life (aOR, 1.06 [95% CI, 1.02-1.10]), and 61% higher odds of dying in the hospital (aOR, 1.61 [95% CI, 1.57-1.65]). Conversely, NH status was associated with lower odds of receiving cancer-directed treatment (aOR, 0.57 [95% CI, 0.55-0.58]), intensive care unit admission (aOR, 0.82 [95% CI, 0.79-0.84]), or enrollment in hospice in the last 3 days of life (aOR, 0.89 [95% CI, 0.86-0.92]). Conclusions and Relevance: Despite increased emphasis to reduce aggressive EOL care in the past several decades, such care remains common among older persons with metastatic cancer and is slightly more prevalent among NH residents than their community-dwelling counterparts. Multilevel interventions to decrease aggressive EOL care should target the main factors associated with its prevalence, including hospital admissions in the last 30 days of life and in-hospital death.

Understanding Disparities in Receipt of Complex Gastrointestinal Cancer Surgery at a Small Geographic Scale.

OBJECTIVE: To define neighborhood-level disparities in the receipt of complex cancer surgery. BACKGROUND: Little is known about the geographic variation of receipt of surgery among patients with complex gastrointestinal (GI) cancers, especially at a small geographic scale. METHODS: This study included individuals diagnosed with 5 invasive, nonmetastatic, complex GI cancers (esophagus, stomach, pancreas, bile ducts, liver) from the Ohio Cancer Incidence Surveillance System during 2009 and 2018. To preserve patient privacy, we combined US census tracts into the smallest geographic areas that included a minimum number of surgery cases (n=11) using the Max-p-regions method and called these new areas "MaxTracts." Age-adjusted surgery rates were calculated for MaxTracts, and the Hot Spot analysis identified clusters of high and low surgery rates. US Census and CDC PLACES were used to compare neighborhood characteristics between the high- and low-surgery clusters. RESULTS: This study included 33,091 individuals with complex GI cancers located in 1006 MaxTracts throughout Ohio. The proportion in each MaxTract receiving surgery ranged from 20.7% to 92.3% with a median (interquartile range) of 48.9% (42.4-56.3). Low-surgery clusters were mostly in urban cores and the Appalachian region, whereas high-surgery clusters were mostly in suburbs. Low-surgery clusters differed from high-surgery clusters in several ways, including higher rates of poverty (23% vs. 12%), fewer married households (40% vs. 50%), and more tobacco use (25% vs. 19%; all P <0.01). CONCLUSIONS: This improved understanding of neighborhood-level variation in receipt of potentially curative surgery will guide future outreach and community-based interventions to reduce treatment disparities. Similar methods can be used to target other treatment phases and other cancers.

Receipt of Targeted Therapy and Survival Outcomes in Patients With Metastatic Colorectal Cancer.

Importance: Professional society guidelines recommend treating patients with metastatic colorectal cancer with targeted therapies, including epithelial growth factor receptor (EGFR) inhibitors and vascular endothelial growth factor (VEGF) inhibitors, depending on the presence or absence of certain mutations. Since most studies of first-line targeted therapies have been limited by sample size, there is a need for larger studies using data from routine clinical care. Objectives: To identify factors associated with receipt of first-line targeted therapies among patients with metastatic colorectal cancer for whom RAS or BRAF mutation data in the tumor were available and investigate whether targeted therapy is associated with survival. Design, Setting, and Participants: This cohort study used deidentified data from an electronic health record-derived database to include patients from 800 sites of patient care across the US who were diagnosed with de novo metastatic colorectal cancer between January 1, 2013, and March 31, 2020 (n = 9134). Main Outcomes and Measures: Receipt of first-line targeted therapy, categorized as ever having received EGFR inhibitors, VEGF inhibitors, or neither. The secondary outcome was overall survival. Results: The study population included 9134 patients. The median age at diagnosis was 62 years (IQR, 53-71 years), 5019 (54.9%) were male, and 5692 (62.3%) were White. The median follow-up period was 15 months. Overall, 713 patients (7.8%) received EGFR inhibitors and 5081 patients (55.6%) received VEGF inhibitors as part of their first-line treatment. Among patients with RAS wild-type (RAS-WT) tumors, 625 patients (15.5%) received EGFR inhibitors and 2053 patients (50.9%) received VEGF inhibitors. In patients with RAS mutant (RAS-Mut) tumors, 50 patients (1.1%) received EGFR inhibitors and 2682 patients (59.7%) received VEGF inhibitors; among those with BRAF-mutant (BRAF-Mut) tumors, 38 patients (6.3%) received EGFR inhibitors and 346 patients (57.2%) received VEGF inhibitors. More than one-third of the patients (36.6%) received neither EGFR inhibitors nor VEGF inhibitors. Compared with patients younger than age 40 years, those aged 80 years or older had significantly lower odds to receive targeted therapies (EGFR or VEGF inhibitors in patients with RAS-WT tumors: adjusted odds ratio [aOR], 0.53; 95% CI, 0.36-0.79; and VEGF inhibitors in patients with RAS-Mut tumors: aOR, 0.62; 95% CI, 0.42-0.90). Improved survival was associated with EGFR inhibitor therapy in patients with RAS-WT tumors (adjusted hazard ratio [aHR], 0.85; 95% CI, 0.74-0.98). Unlike in clinical trials, however, no survival benefit was noted with use of VEGF inhibitors among patients with RAS-WT (aHR, 1.00; 95% CI, 0.91-1.11) or RAS-Mut (aHR, 1.01; 95% CI, 0.93-1.10) tumors. Conclusions and Relevance: The findings of this study showed mixed results on survival benefits associated with targeted therapy. In addition, given that some of the results differed from those of randomized clinical trials, this study highlights the importance of using data originating from routine clinical care.