Association of Major Adverse Financial Events and Later-Stage Cancer Diagnosis in the United States.

PURPOSE: This study assessed the prevalence of specific major adverse financial events (AFEs)-bankruptcies, liens, and evictions-before a cancer diagnosis and their association with later-stage cancer at diagnosis. METHODS: Patients age 20-69 years diagnosed with cancer during 2014-2015 were identified from the Seattle, Louisiana, and Georgia SEER population-based cancer registries. Registry data were linked with LexisNexis consumer data to identify patients with a history of court-documented AFEs before cancer diagnosis. The association of AFEs and later-stage cancer diagnoses (stages III/IV) was assessed using separate sex-specific multivariable logistic regression. RESULTS: Among 101,649 patients with cancer linked to LexisNexis data, 36,791 (36.2%) had a major AFE reported before diagnosis. The mean and median timing of the AFE closest to diagnosis were 93 and 77 months, respectively. AFEs were most common among non-Hispanic Black, unmarried, and low-income patients. Individuals with previous AFEs were more likely to be diagnosed with later-stage cancer than individuals with no AFE (males-odds ratio [OR], 1.09 [95% CI, 1.03 to 1.14]; P < .001; females-OR, 1.18 [95% CI, 1.13 to 1.24]; P < .0001) after adjusting for age, race, marital status, income, registry, and cancer type. Associations between AFEs prediagnosis and later-stage disease did not vary by AFE timing. CONCLUSION: One third of newly diagnosed patients with cancer had a major AFE before their diagnosis. Patients with AFEs were more likely to have later-stage diagnosis, even accounting for traditional measures of socioeconomic status that influence the stage at diagnosis. The prevalence of prediagnosis AFEs underscores financial vulnerability of patients with cancer before their diagnosis, before any subsequent financial burden associated with cancer treatment.

Do Contemporary Cancer Survivors Experience Better Quality of Life? Evaluating a Decade of SEER Medicare Health Outcomes Survey Data.

BACKGROUND: A cancer diagnosis may have deleterious effects on health-related quality of life (HRQOL) as adults age. This study examined differences in HRQOL between cancer and matched noncancer Medicare beneficiaries over 65, within and across two time periods. METHODS: We used novel matching methods on data from the Surveillance, Epidemiology and End Results (SEER)-Medicare Health Outcomes Survey (MHOS) data resource. We matched SEER-MHOS respondents with cancer from a recent period (2015-2019) to respondents with cancer from an earlier period (2008-2012). We then matched these two cohorts, without replacement, to contemporary cohorts without cancer diagnoses. We estimated Veteran's RAND 12-Item Short Form Survey Physical Component Summary (PCS) and Mental Component Summary (MCS) scores for all cohorts. RESULTS: Our analysis found significantly higher mean MCS scores in the recent period for those with cancer relative to the recent noncancer control group. Breast and lung cancer presented positive and statistically significant trends. We found statistically insignificant differences in PCS scores between the two time periods. No cancer sites had different PCS scores over time compared with the comparison group. CONCLUSIONS: Mental health for those with cancer improved more between 2008 and 2019 than a matched noncancer comparison group. Physical health remained stable across time. These findings highlight the importance of including a matched noncancer group when evaluating HRQOL outcomes. IMPACT: SEER-MHOS respondents with cancer report stable PCS scores across 15 years of data and higher MCS scores relative to noncancer controls.

Accuracy of Cancer Registry Primary Payer Information and Implications for Policy Research.

BACKGROUND: Cancer registry-based "primary payer at diagnosis" (PPDx) data are commonly used to evaluate the effect of insurance on cancer care outcomes, yet little is known about how well they capture Medicaid or Medicare enrollment. METHODS: We linked the National Cancer Institute's Surveillance, Epidemiology, and End Results registry data to monthly Centers for Medicare and Medicaid Services (CMS) Medicaid and Medicare enrollment records, state-year Medicaid policy, and managed care enrollment. We selected adults aged 19-64 years diagnosed between 2007 and 2011. We used bivariate analyses to compare PPDx to CMS enrollment at diagnosis month and assessed underreporting rates by patient characteristics and state-year policy. RESULTS: PPDx reported 7.8% Medicare and 10.1% Medicaid, whereas CMS enrollment indicated 5.5% Medicare, 10.4% Medicaid, and 3.4% dual Medicare-Medicaid (N = 896,031). Positive predictive values for PPDx assignment to Medicaid and Medicare were 65.3% and 75.4%, with false negative rates of 52.0% and 33.8%, respectively. Medicaid underreporting was higher in low (56.5%) versus high (50.8%) poverty areas, for males (56.1%) versus females (48.9%), for Medicaid poverty expansion or waiver enrolled (63.8%) versus cash assistance-related eligibility (47.3%), and in states with large managed care enrollment (all P < 0.001). If Medicaid and Medicare enrollment data were used to edit PPDx, 12.0% of persons would switch primary payer assignment. CONCLUSIONS: Registry-reported PPDx fails to fully capture Medicaid and Medicare enrollment, which may result in biased estimates of insurance-related policy impacts. Enhancement with objective enrollment data could reduce measurement error and bias in estimates necessary to support policy assessment.

The COVID-19 Pandemic and In-Person Visit Rate Disruptions Among Patients With Hematologic Neoplasms in the US in 2020 to 2021.

Importance: The COVID-19 pandemic has led to a reduction in routine in-person medical care; however, it is unknown whether there have been any changes in visit rates among patients with hematologic neoplasms. Objective: To examine associations between the COVID-19 pandemic and in-person visits and telemedicine use among patients undergoing active treatment for hematologic neoplasms. Design, Setting, and Participants: Data for this retrospective observational cohort study were obtained from a nationwide electronic health record-derived, deidentified database. Data for patients with hematologic neoplasms who had received at least 1 systemic line of therapy between March 1, 2016, and February 28, 2021, were included. Treatments were categorized into 3 types: oral therapy, outpatient infusions, and inpatient infusions. The data cutoff date was April 30, 2021, when study analyses were conducted. Main Outcomes and Measures: Monthly visit rates were calculated as the number of documented visits (telemedicine or in-person) per active patient per 30-day period. We used time-series forecasting methods on prepandemic data (March 2016 to February 2020) to estimate expected rates between March 1, 2020, and February 28, 2021 (if the pandemic had not occurred). Results: This study included data for 24 261 patients, with a median age of 68 years (IQR, 60-75 years). A total of 6737 patients received oral therapy, 15 314 received outpatient infusions, and 8316 received inpatient infusions. More than half of patients were men (14 370 [58%]) and non-Hispanic White (16 309 [66%]). Early pandemic months (March to May 2020) demonstrated a significant 21% reduction (95% prediction interval [PI], 12%-27%) in in-person visit rates averaged across oral therapy and outpatient infusions. Reductions in in-person visit rates were also significant for all treatment types for multiple myeloma (oral therapy: 29% reduction; 95% PI, 21%-36%; P = .001; outpatient infusions: 11% reduction; 95% PI, 4%-17%; P = .002; inpatient infusions: 55% reduction; 95% PI, 27%-67%; P = .005), for oral therapy for chronic lymphocytic leukemia (28% reduction; 95% PI, 12%-39%; P = .003), and for outpatient infusions for mantle cell lymphoma (38% reduction; 95% PI, 6%-54%; P = .003) and chronic lymphocytic leukemia (20% reduction; 95% PI, 6%-31%; P = .002). Telemedicine visit rates were highest for patients receiving oral therapy, with greater use in the early pandemic months and a subsequent decrease in later months. Conclusions and Relevance: In this cohort study of patients with hematologic neoplasms, documented in-person visit rates for those receiving oral therapy and outpatient infusions significantly decreased during the early pandemic months but returned to close to projected rates in the later half of 2020. There were no statistically significant reductions in the overall in-person visit rate for patients receiving inpatient infusions. There was higher telemedicine use in the early pandemic months, followed by a decline, but use was persistent in the later half of 2020. Further studies are needed to ascertain associations between the COVID-19 pandemic and subsequent cancer outcomes and the evolution of telemedicine use for care delivery.

"It's just not easy to understand": A mixed methods study of health insurance literacy and insurance plan decision-making in cancer survivors.

BACKGROUND: Understanding cancer survivors' health insurance decision-making is needed to improve insurance choice, potentially resulting in reduced financial hardship. METHODS: This explanatory mixed methods study assessed health insurance decision-making in cancer survivors. Health Insurance Literacy Measure (HILM) captured HIL. Quantitative eye-tracking data collected from two simulated health insurance plan choice sets gauged dwell time (seconds), or interest, in benefits. Dwell time differences by HIL were estimated using adjusted linear models. Qualitative interviews explored survivors' insurance decision-making choices. RESULTS: Cancer survivors (N = 80; 38% breast cancer) had a median age of 43 at diagnosis (IQR 34-52). When comparing traditional and high-deductible health plans, survivors were most interested in drug costs (median dwell time 58 s, IQR 34-109). When comparing health maintenance organization and preferred provider organization plans, survivors were most interested in test/imaging costs (40s, IQR 14-67). Survivors with low versus high HIL had more interest in deductible (ß = 19 s, 95% CI 2-38) and hospitalization costs (ß = 14 s, 95% CI 1-27) in adjusted models. Survivors with low versus high HIL more often ranked out-of-pocket (OOP) maximums and coinsurance as the most important and confusing benefits, respectively. Interviews (n = 20) revealed survivors felt alone "to do their own research" about insurance choices. OOP maximums were cited as the deciding factor since it is "how much money is going to be taken out of my pocket." Coinsurance was considered "rather than a benefit, it's a hindrance." CONCLUSION: Interventions to aid in health insurance understanding and choice are needed to optimize plan choice and potentially reduce cancer-related financial hardship.

End-of-life care trajectories among older adults with lung cancer.

INTRODUCTION: Medicare decedents with cancer often receive intensive care during the last month of life; however, little information exists on longer end-of-life care trajectories. MATERIALS AND METHODS: Using SEER-Medicare data, we selected older adults diagnosed with lung cancer between 2008 and 2013 who survived at least six months and died between 2008 and 2014. Each month we assessed claims to assign care categories ordered by intensity as follows: full-month inpatient/skilled nursing facility > cancer-directed therapy (CDT) only > concurrent CDT and symptom management and supportive care services (SMSCS) > SMSCS only > full-month hospice. We assigned each decedent to one of six trajectories: stable hospice, stable SMSCS, stable CDT with or without concurrent SMSCS, decreasing intensity, increasing intensity, and mixed. Multinomial logistic regression estimated associations between socio-demographics, calendar year, and area hospice use rates with end-of-life trajectory. RESULTS: The sample (N = 24,342) was predominantly aged ≥75 years (59.4%) and non-Hispanic White (80.5%); 19.1% lived in healthcare referral regions where ≤50% of cancer decedents received hospice care. Overall, 6.5% were continuously hospice enrolled, 25.6% received SMSCS only, and 29.4% experienced decreasing intensity; 3.9% received CDT or concurrent care, while 8.7% experienced an increase in intensity. Higher healthcare referral region hospice rates were associated with decreasing end-of-life intensity; Black, non-Hispanic decedents had a higher risk of increasing intensity and mixed patterns. DISCUSSION: Among older decedents with lung cancer, 62% had six-month end-of-life trajectories indicating low or decreasing intensity, but few received persistent CDT. Demographic characteristics, including race/ethnicity, and contextual measures, including area hospice use patterns, were associated with end-of-life trajectory.

Cost-Related Medication Nonadherence and Patient Cost Responsibility for Rural and Urban Cancer Survivors.

PURPOSE: The relationship between out-of-pocket spending and cost-related medication nonadherence among older rural- and urban-dwelling cancer survivors is not well understood. METHODS: This retrospective cohort study used the Surveillance, Epidemiology, and End Results Program, Medicare claims, and the Consumer Assessment of Healthcare Providers and Systems survey linked data resource linked data (2007-2015) to investigate the relationship between cancer survivors' cost responsibility in the year before and after report of delaying or not filling a prescription medication because of cost in the past 6 months (cost-related medication nonadherence). Secondary exposures and outcomes included Medicare spending and utilization. Generalized linear models assessed bidirectional relationships between cost-related medication nonadherence, spending, and utilization. Effects of residence were assessed via interaction terms. RESULTS: Of 6,591 older cancer survivors, 13% reported cost-related medication nonadherence. Survivors were a median 8 years (interquartile range, 4.5-12.5 years) from their cancer diagnosis, 15% were dually Medicare/Medicaid-eligible, and prostate (40%) and breast (32%) cancer survivors were most prevalent. With every $500 USD increase in patient cost responsibility, risk of cost-related medication nonadherence increased by 3% (risk ratio, 1.03; 95% CI, 1.02 to 1.04). After report of cost-related medication nonadherence, patient cost responsibility was 22% higher (95% CI, 1.11 to 1.32) compared with those not reporting nonadherence, amounting to $523 USD (95% CI, $430 USD to $630 USD). Medicare spending and utilization were also higher before and after report of cost-related nonadherence versus none. For survivors residing in rural (18%) and urban (82%) areas, residence did not modify adherence or cost outcomes. CONCLUSION: A bidirectional relationship exists between patient cost responsibility and cost-related medication nonadherence. Interventions reducing urban- and rural-dwelling survivor health care costs and cost-related adherence barriers are needed.

Research on the Economics of Cancer-Related Health Care: An Overview of the Review Literature.

We reviewed current literature reviews regarding economics of cancer-related health care to identify focus areas and gaps. We searched PubMed for systematic and other reviews with the Medical Subject Headings "neoplasms" and "economics" published between January 1, 2010, and April 1, 2020, identifying 164 reviews. Review characteristics were abstracted and described. The majority (70.7%) of reviews focused on cost-effectiveness or cost-utility analyses. Few reviews addressed other types of cancer health economic studies. More than two-thirds of the reviews examined cancer treatments, followed by screening (15.9%) and survivorship or end-of-life (13.4%). The plurality of reviews (28.7%) cut across cancer site, followed by breast (20.7%), colorectal (11.6%), and gynecologic (8.5%) cancers. Specific topics addressed cancer screening modalities, novel therapies, pain management, or exercise interventions during survivorship. The results indicate that reviews do not regularly cover other phases of care or topics including financial hardship, policy, and measurement and methods.

Cancer Survivorship and Supportive Care Economics Research: Current Challenges and Next Steps.

BACKGROUND: Rapid growth in the number of cancer survivors raises numerous questions about health and economic outcomes among survivors along with their families, caregivers, and employers. Health economics theory and methods can contribute to many open questions to improve survivorship. METHODS: In this paper, we review key areas where more research is needed and describe strategies for improving data infrastructure, research funding, and capacity building to strengthen survivorship health economics research. CONCLUSIONS: Health economics has broadened an understanding of key supply- and demand-side factors that promote cancer survivorship. To ensure necessary research in survivorship health economics moving forward, we recommend dedicated funding, inclusion of health economics outcomes in primary data collection, and investments in secondary data sets.

Telehealth Availability and Use of Related Technologies Among Medicare-Enrolled Cancer Survivors: Cross-sectional Findings From the Onset of the COVID-19 Pandemic.

BACKGROUND: There has been rapid integration of telehealth into care delivery during the COVID-19 pandemic. However, little is known about technology ownership, internet access and use for communication, and telehealth availability among cancer survivors, particularly those enrolled in Medicare. OBJECTIVE: This study aims to identify sociodemographic associations with technology ownership, internet access and use for communication, and telehealth availability in a population-based sample of Medicare-enrolled cancer survivors. METHODS: Data are from the Medicare Current Beneficiary Survey COVID-19 Summer 2020 Supplement administered between June 10 and July 15, 2020. Analyses were restricted to beneficiaries who reported a prior (nonskin) cancer diagnosis and a usual source of care (N=2044). Dichotomous outcomes included technology ownership, internet access, internet use for communication, and telehealth availability from providers. Sociodemographic correlates included sex, age, race/ethnicity, Medicare/Medicaid dual enrollment, rurality, census region, and self-reported comorbidities. RESULTS: Over half (957/2044, 53%) of cancer survivors reported using the internet for communication purposes, and 62% (1218/2044) reported that their usual provider had telehealth services available. Using the internet for communication purposes was reported less frequently for rural compared to urban survivors (adjusted probability of 28% vs 46%; P<.001) and for Hispanic and Black survivors compared to non-Hispanic White survivors (29%, 31%, and 44%, respectively; all P<.01). Rural survivors reported lower telehealth availability (53% vs 63%; P<.001); no significant differences in telehealth availability were identified by race/ethnicity. CONCLUSIONS: During the COVID-19 pandemic, study findings highlight a complex digital divide among Medicare beneficiaries with a history of cancer related to device ownership necessary for telehealth, internet access and use for communication, and reports of providers having telehealth available. Multilevel approaches are needed to increase equitable telehealth availability and use for cancer survivors. Suggested strategies include increasing broadband internet access to providers and patients in at-risk communities, supporting telehealth implementation among providers that serve populations with known health disparities, raising awareness of providers' available telehealth services among patients, and screening for technology use and provision of telehealth-related technical assistance among older and historically underserved cancer survivors.

Fine-tuning the cardiac O-GlcNAcylation regulatory enzymes governs the functional and structural phenotype of the diabetic heart.

AIMS: The glucose-driven enzymatic modification of myocardial proteins by the sugar moiety, ß-N-acetylglucosamine (O-GlcNAc), is increased in pre-clinical models of diabetes, implicating protein O-GlcNAc modification in diabetes-induced heart failure. Our aim was to specifically examine cardiac manipulation of the two regulatory enzymes of this process on the cardiac phenotype, in the presence and absence of diabetes, utilising cardiac-targeted recombinant-adeno-associated viral-vector-6 (rAAV6)-mediated gene delivery. METHODS AND RESULTS: In human myocardium, total protein O-GlcNAc modification was elevated in diabetic relative to non-diabetic patients, and correlated with left ventricular (LV) dysfunction. The impact of rAAV6-delivered O-GlcNAc transferase (rAAV6-OGT, facilitating protein O-GlcNAcylation), O-GlcNAcase (rAAV6-OGA, facilitating de-O-GlcNAcylation), and empty vector (null) were determined in non-diabetic and diabetic mice. In non-diabetic mice, rAAV6-OGT was sufficient to impair LV diastolic function and induce maladaptive cardiac remodelling, including cardiac fibrosis and increased Myh-7 and Nppa pro-hypertrophic gene expression, recapitulating characteristics of diabetic cardiomyopathy. In contrast, rAAV6-OGA (but not rAAV6-OGT) rescued LV diastolic function and adverse cardiac remodelling in diabetic mice. Molecular insights implicated impaired cardiac PI3K(p110α)-Akt signalling as a potential contributing mechanism to the detrimental consequences of rAAV6-OGT in vivo. In contrast, rAAV6-OGA preserved PI3K(p110α)-Akt signalling in diabetic mouse myocardium in vivo and prevented high glucose-induced impairments in mitochondrial respiration in human cardiomyocytes in vitro. CONCLUSION: Maladaptive protein O-GlcNAc modification is evident in human diabetic myocardium, and is a critical regulator of the diabetic heart phenotype. Selective targeting of cardiac protein O-GlcNAcylation to restore physiological O-GlcNAc balance may represent a novel therapeutic approach for diabetes-induced heart failure.

Practice patterns and real-life outcomes for patients with acute promyelocytic leukemia in the United States.

Acute promyelocytic leukemia (APL) is associated with a favorable long-term prognosis if appropriate treatment is initiated promptly. Outcomes in clinical trials and population-based registries vary; potential explanations include a delay in treatment and lower adherence to guideline-recommended therapy in real-world practice. We used the Vizient Clinical Data Base to describe demographic characteristics, baseline clinical characteristics, and treatment patterns in patients newly diagnosed with APL during the study period of April 2017 to March 2020. Baseline white blood cell count was used to assign risk status and assess treatment concordance with National Comprehensive Cancer Network guidelines. Logistic regression models examined adjusted associations between patient, hospital, disease characteristics, and adverse outcomes (in-hospital death or discharge to hospice). Among 1464 patients with APL, 205 (14.0%) experienced an adverse outcome. A substantial subset (20.6%) of patients did not receive guideline-concordant regimens. Odds of adverse outcomes increased with failure to receive guideline-concordant treatment (odds ratio [OR], 2.31; 95% confidence interval [CI], 1.43-3.75; P = .001), high-risk disease (OR, 2.48; 95% CI, 1.53-4.00; P < .001), and increasing age (≥60 years: OR, 11.13; 95% CI, 4.55-27.22; P < .001). Higher hospital acute myeloid leukemia (AML) patient volume was associated with lower odds of adverse outcome (OR, 0.44; 95% CI, 0.20-0.99 [for ≤50 vs >200 AML patients per year]; P = .046). In conclusion, in this large database analysis, 14.0% of patients newly diagnosed with APL died or were discharged to hospice. A substantial proportion of patients did not receive guideline-concordant therapy, potentially contributing to adverse outcomes.

Impact of the COVID-19 Pandemic on Treatment Patterns for Patients With Metastatic Solid Cancer in the United States.

BACKGROUND: The COVID-19 pandemic has led to delays in patients seeking care for life-threatening conditions; however, its impact on treatment patterns for patients with metastatic cancer is unknown. We assessed the COVID-19 pandemic's impact on time to treatment initiation (TTI) and treatment selection for patients newly diagnosed with metastatic solid cancer. METHODS: We used an electronic health record-derived longitudinal database curated via technology-enabled abstraction to identify 14 136 US patients newly diagnosed with de novo or recurrent metastatic solid cancer between January 1 and July 31 in 2019 or 2020. Patients received care at approximately 280 predominantly community-based oncology practices. Controlled interrupted time series analyses assessed the impact of the COVID-19 pandemic period (April-July 2020) on TTI, defined as the number of days from metastatic diagnosis to receipt of first-line systemic therapy, and use of myelosuppressive therapy. RESULTS: The adjusted probability of treatment within 30 days of diagnosis was similar across periods (January-March 2019 = 41.7%, 95% confidence interval [CI] = 32.2% to 51.1%; April-July 2019 = 42.6%, 95% CI = 32.4% to 52.7%; January-March 2020 = 44.5%, 95% CI = 30.4% to 58.6%; April-July 2020 = 46.8%, 95% CI= 34.6% to 59.0%; adjusted percentage-point difference-in-differences = 1.4%, 95% CI = -2.7% to 5.5%). Among 5962 patients who received first-line systemic therapy, there was no association between the pandemic period and use of myelosuppressive therapy (adjusted percentage-point difference-in-differences = 1.6%, 95% CI = -2.6% to 5.8%). There was no meaningful effect modification by cancer type, race, or age. CONCLUSIONS: Despite known pandemic-related delays in surveillance and diagnosis, the COVID-19 pandemic did not affect TTI or treatment selection for patients with metastatic solid cancers.

Impact of the COVID-19 pandemic on treatment patterns for US patients with metastatic solid cancer.

BACKGROUND: The COVID-19 pandemic has led to delays in patients seeking care for life-threatening conditions; however, its impact on treatment patterns for patients with metastatic cancer is unknown. We assessed the COVID-19 pandemic's impact on time to treatment initiation (TTI) and treatment selection for patients newly diagnosed with metastatic solid cancer. METHODS: We used an electronic health record-derived longitudinal database curated via technology-enabled abstraction to identify 14,136 US patients newly diagnosed with de novo or recurrent metastatic solid cancer between January 1 and July 31 in 2019 or 2020. Patients received care at ∼280 predominantly community-based oncology practices. Controlled interrupted time series analyses assessed the impact of the COVID-19 pandemic period (April-July 2020) on TTI, defined as the number of days from metastatic diagnosis to receipt of first-line systemic therapy, and use of myelosuppressive therapy. RESULTS: The adjusted probability of treatment within 30 days of diagnosis [95% confidence interval] was similar across periods: January-March 2019 41.7% [32.2%, 51.1%]; April-July 2019 42.6% [32.4%, 52.7%]; January-March 2020 44.5% [30.4%, 58.6%]; April-July 2020 46.8% [34.6%, 59.0%]; adjusted percentage-point difference-in-differences 1.4% [-2.7%, 5.5%]. Among 5,962 patients who received first-line systemic therapy, there was no association between the pandemic period and use of myelosuppressive therapy (adjusted percentage-point difference-in-differences 1.6% [-2.6%, 5.8%]). There was no meaningful effect modification by cancer type, race, or age. CONCLUSIONS: Despite known pandemic-related delays in surveillance and diagnosis, the COVID-19 pandemic did not impact time to treatment initiation or treatment selection for patients with metastatic solid cancers.

ACA Medicaid expansion association with racial disparity reductions in timely cancer treatment.

OBJECTIVES: Racial disparities in cancer care and outcomes remain a societal challenge. Medicaid expansion through the Affordable Care Act was intended to improve health care access and equity. This study aimed to assess whether state Medicaid expansions were associated with a reduction in racial disparities in timely treatment among patients diagnosed with advanced cancer. STUDY DESIGN: This difference-in-differences study analyzed deidentified electronic health record-derived data. Patients aged 18 to 64 years with advanced or metastatic cancers diagnosed between January 1, 2011, and January 31, 2019, and receiving systemic therapy were included. METHODS: The primary end point was receipt of timely treatment, defined as first-line systemic therapy starting within 30 days after diagnosis of advanced or metastatic disease. Racial disparity was defined as adjusted percentage-point (PP) difference for Black vs White patients, adjusted for age, sex, practice setting, cancer type, stage, insurance marketplace, and area unemployment rate, with time and state fixed effects. RESULTS: The study included 30,310 patients (12.3% Black race). Without Medicaid expansion, Black patients were less likely to receive timely treatment than White patients (43.7% vs 48.4%; adjusted difference, -4.8 PP; P < .001). With Medicaid expansion, this disparity was diminished and lost significance (49.7% vs 50.5%; adjusted difference, -0.8 PP; P = .605). The adjusted difference-in-differences estimate was a 3.9 PP reduction in racial disparity (95% CI, 0.1-7.7 PP; P = .045). CONCLUSIONS: Medicaid expansion was associated with reduced Black-White racial disparities in receipt of timely systemic treatment for patients with advanced or metastatic cancers.

Development and evaluation of a proxy for baseline ECOG PS in advanced non-small cell lung cancer, bladder cancer, and melanoma: An electronic health record study.

PURPOSE: Eastern Cooperative Oncology Group performance status (ECOG PS) is an important predictor for receipt of treatment and overall survival (OS) but is often unreported in routine care. We developed a proxy for baseline ECOG PS using electronic health records (EHRs). METHODS: We analyzed patients who were diagnosed with advanced non-small cell lung cancer (aNSCLC), advanced bladder cancer (aBCa), and advanced melanoma (aMEL) between 2011 and 2018 and had a baseline (reported between diagnosis and treatment) ECOG PS in a real-world database. We used stepwise multivariable logistic regression to model associations between baseline ECOG PS good (<2) versus poor (≥2) and sociodemographic, clinical, and laboratory measures in each cancer type. Predictive accuracy of classifying ECOG PS was assessed. We tested the association between OS and observed and predicted ECOG PS. RESULTS: In total, 20 697 aNSCLC patients, 2627 aBCa patients, and 2558 aMEL patients constituted the study population. Percentage of patients with poor ECOG PS ranged from 15.3% (aMEL) to 28.5% (aNSCLC). Poor ECOG PS was associated with more comorbid conditions, older age, lower body mass index, metastases, and abnormal laboratory indicators. Overall prediction accuracy using a 0.50 cutpoint was 73.3% for NSCLC, 73.8% for aBCa, and 85.4% for aMEL. The association of OS with ECOG PS was consistent between the observed and proxy measures. CONCLUSIONS: In the EHR-derived data, clinical, sociodemographic, and laboratory information were used to assign ECOG PS and enhance the use of real-world data in outcome studies.

End-of-life patterns of symptom management and cancer-directed care among Medicare beneficiaries with lung cancer: a claims-based analysis.

BACKGROUND: Rather than early hospice enrollment, most Medicare beneficiaries receive "usual care" in the last months of life, outside of the hospice setting. While care intensity during the last weeks of life has been studied extensively, patterns of symptom management services (SMS) and/or cancer-directed therapies (CDT) received over a 6-month end-of-life period have not. METHODS: This retrospective study used the Surveillance, Epidemiology, and End Results (SEER)-Medicare database to identify decedents diagnosed with lung cancer at age ≥ 66 years between January 2007 and December 2013 who survived ≥ 6 months from diagnosis. Medicare claims identified receipt of SMS and/or CDT. We created monthly indicators for care content (SMS-only, CDT-only, or both; otherwise full-month hospice or inpatient/skilled nursing). Multinomial logistic regression estimated associations between sociodemographics and comorbidity, with care content in the final month. RESULTS: Between 6 and 1 months before death, full-month hospice and inpatient/skilled nursing increased; CDT decreased from 31.9 to 18.5%; SMS increased from 86.6 to 97.7%. Relative to full-month hospice, the percentage of patients receiving SMS-only was higher for males, unmarried, younger age, and higher comorbidity; the percentage receiving CDT was also higher for males, unmarried, and younger age, but decreased with increasing comorbidity and over calendar time. CONCLUSION: Among lung cancer decedents observed in the outpatient, nonhospice setting, SMS receipt increased and was nearly universal as death approached. CDT diminished dramatically over the end-of-life period. Associations between sociodemographic characteristics and care setting suggest differences in care preferences or access barriers. Claims represent an important resource for characterizing end-of-life care patterns.

Did quality of life for older cancer survivors improve with the turn of the century in the United States?

OBJECTIVES: Although survival after a cancer diagnosis has improved considerably over the past 20 years, little is known about trends in health-related quality-of-life (HRQOL) for older prostate, breast, and lung cancer survivors. METHODS: Using a population-based registry with longitudinal patient reported outcomes (the National Cancer Institute Surveillance, Epidemiology and End Results database linked to Medicare Health Outcomes Survey), we analyzed Medicare Advantage patients diagnosed with cancer during 1998-2011, who completed surveys regarding HRQOL through 2013. 'Early Era' patients were treated during 1998-2003; 'Late Era' patients were treated during 2006-2011. After propensity score matching, post-diagnosis changes in health utility (HU), Physical Component Summary (PCS) and Mental Component Summary (MCS) scores were calculated and compared between the two eras. RESULT: We identified 208 older patients with prostate, 276 with breast and 76 with lung cancer who were treated in the 'Early Era' and matched to equal numbers in the 'Late Era'. Mean age of patients in early and late era was 72 and 73 years, respectively. The mean post-diagnosis decline in health utility for patients treated in the 'Late Era' was not significantly different from the 'Early Era' for any cancer (Prostate [early vs. late]: -0.06 vs. -0.03, p = .09; Breast: -0.03 vs. -0.04, p = .65; Lung: -0.07 vs. -0.07, p = .95); nor for Physical Component Summary or Mental Component Summary scores. CONCLUSION: Older patients treated for prostate, breast or lung cancer in the later era reported similar outcomes of changes in HRQOL compared to earlier era patients.

A framework for cancer health economics research.

LAY SUMMARY: Cancer has substantial economic impacts for patients, their families and/or caregivers, employers, and the health care system. However, there is only limited understanding of how economic issues can affect access to cancer care services and the receipt of high-quality cancer care. Health economics research in cancer is particularly timely due to the large and increasing number of patients with cancer and cancer survivors, but there are many factors that may create barriers to performing cancer health economics research. This commentary has identified important topics and questions in cancer health economics research and will assist in the development of this critical field.