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.

Use of pembrolizumab among older adults with cancer in the United States, before and after FDA approval of its tumor-agnostic indication.

INTRODUCTION: Pembrolizumab, an anticancer immunotherapy agent, has received multiple approvals since its first approval by the U.S. Food and Drug Administration (FDA) in 2014. Limited data exist on its real-world use and shifts post tumor-agnostic approval in 2017 for the treatment of patients with any microsatellite instability-high/mismatch repair deficient (MSI-H/dMMR) solid tumors. This study analyzes pembrolizumab's pre and post-tumor-agnostic approval use among older U.S. adults, revealing its evolving role in oncology practice. METHODS: Using the Surveillance, Epidemiology and End Results (SEER)-Medicare data (2014-2019), we examined the cancer sites of pembrolizumab recipients before and after tumor-agnostic approval. Cancer sites were classified based on the timing of site-specific approvals (before/after tumor-agnostic approval) or no site-specific approval, and inclusion in MSI-H/dMMR clinical trials. RESULTS: The total number of pembrolizumab recipients increased from 4221 in the pre-agnostic period to 20 479 in the post-agnostic period. Pembrolizumab was used for a broad range of cancer types, including cancers that had no FDA-approved site-specific indications at the time of use (25.8% in pre- and 24.6% in post-agnostic periods). The proportion of pembrolizumab recipients receiving pembrolizumab for cancers with site-specific approvals before tumor-agnostic approval decreased from 77.3% to 70.8%. The proportion of pembrolizumab recipients receiving pembrolizumab for cancers that gained site-specific approvals following tumor-agnostic approval almost doubled (6.8% to 13.0%). The proportion of pembrolizumab recipients with cancers included in MSI-H/dMMR trials also doubled (12.3% to 25.5%) following tumor-agnostic approval. CONCLUSIONS: Pembrolizumab use has expanded over time among older adults with cancer, extending beyond those with FDA-approved site-specific indications.

Evaluation of the Completeness of Managed Care Data to Identify Cancer Diagnoses and Treatments for Patients in the SEER-Medicare Data.

BACKGROUND: The utility of codes on Medicare Advantage (MA) data to capture cancer diagnoses and treatment for cancer patients is unknown. OBJECTIVE: This study compared cancer diagnoses and treatments on MA encounter data (MA data) with the Surveillance, Epidemiology, and End-Results (SEER) data. SUBJECTS: Subjects were patients enrolled in either MA or Medicare fee-for-service (MFFS) when diagnosed with incident breast, colorectal, prostate, or lung cancer, 2015-2017, in a SEER cancer registry. MEASURES: MA data, from 2 months before to 12 months following SEER diagnosis, were reviewed to identify cancer diagnoses, surgery, chemotherapy, and radiotherapy (RT). MA data were compared with SEER to determine their sensitivity to capture cancer diagnoses and sensitivity/specificity to identify surgeries. The agreement between SEER and Medicare data regarding receipt of chemotherapy and RT was measured by Kappa statistics. A similar comparison to SEER diagnoses/treatments was made using MFFS claims to provide context for the SEER-MA comparison. RESULTS: The study included 186,449 patients, 38% in MA. MA data had 92%+ sensitivity to identify SEER cancer diagnosis and 90%+ sensitivity for cancer surgery. Specificity for surgery was >84%, except for breast cancer (52%). Kappa statistics for agreement between SEER and MA data regarding chemotherapy varied by cancer, 0.61-0.82, and for receipt of RT exceeded 0.75 for all cancers. Results observed for MFFS claims were similar to those in MA data. CONCLUSION: For 4 common cancers, MA data included most cancer diagnoses and general types of cancer treatment reported in the SEER data. More research is needed to assess additional cancers and detailed treatments.

Workforce Caring for Cancer Survivors in the United States: Estimates and Projections of Use.

BACKGROUND: This study aims to quantify the extent and diversity of the cancer care workforce, beyond medical oncologists, to inform future demand because the number of cancer survivors is expected to grow in the United States. METHODS: Surveillance, Epidemiology, and End Results-Medicare data were used to evaluate health-care use of cancer survivors diagnosed between 2000 and 2014, enrolled in fee-for-service Medicare Parts A and B, and 65 years or older in 2008-2015. We calculated percentage of cancer survivors who saw each clinician specialty and their average annual number of visits in each phase of care. We projected the national number of individuals receiving care and number of annual visits by clinician specialty and phase of care through 2040. RESULTS: Cancer survivors had higher care use in the first year after diagnosis and last year of life phases. During the initial year after cancer diagnosis, most survivors were seen for cancer-related care by a medical oncologist (59.1%), primary care provider (55.9%), and/or other cancer-treating physicians (42.2%). The percentage of survivors with cancer-related visits to each specialty declined after the first year after diagnosis, plateauing after year 6-7. However, at 10 or more years after diagnosis, approximately 20% of cancer survivors had visits to medical oncologists and an average of 4 visits a year. CONCLUSIONS: Cancer survivors had higher care use in the first year after diagnosis and last year of life. High levels of care use across specialties in all phases of care have important implications for models of survivorship care coordination and workforce planning.

Population-Based Cancer Survival in Canada and the United States by Socioeconomic Status: Findings from the CONCORD-2 Study.

Background: Population-based cancer survival provides insight into the effectiveness of health systems to care for all residents with cancer, including those in marginalized groups. Methods: Using CONCORD-2 data, we estimated 5-year net survival among patients diagnosed 2004-2009 with one of 10 common cancers, and children diagnosed with acute lymphoblastic leukemia (ALL), by socioeconomic status (SES) quintile, age (0-14, 15-64, ≥65 years), and country (Canada or United States). Results: In the lowest SES quintile, survival was higher among younger Canadian adults diagnosed with liver (23% vs 15%) and cervical (78% vs 68%) cancers and with leukemia (62% vs 56%), including children diagnosed with ALL (92% vs 86%); and higher among older Americans diagnosed with colon (62% vs 56%), female breast (87% vs 80%), and prostate (97% vs 85%) cancers. In the highest SES quintile, survival was higher among younger Americans diagnosed with stomach cancer (33% vs 27%) and younger Canadians diagnosed with liver cancer (31% vs 23%); and higher among older Americans diagnosed with stomach (27% vs 22%) and prostate (99% vs 92%) cancers. Conclusions: Among younger Canadian cancer patients in the lowest SES group, greater access to health care may have resulted in higher cancer survival, while higher screening prevalence and access to health insurance (Medicare) among older Americans during the period of this study may have resulted in higher survival for some screen-detected cancers. Higher survival in the highest SES group for stomach and liver may relate to treatment differences. Survival differences by age and SES between Canada and the United States may help inform cancer control strategies.

Machine Learning Methods to Identify Missed Cases of Bladder Cancer in Population-Based Registries.

PURPOSE: Population-based cancer incidence rates of bladder cancer may be underestimated. Accurate estimates are needed for understanding the burden of bladder cancer in the United States. We developed and evaluated the feasibility of a machine learning-based classifier to identify bladder cancer cases missed by cancer registries, and estimated the rate of bladder cancer cases potentially missed. METHODS: Data were from population-based cohort of 37,940 bladder cancer cases 65 years of age and older in the SEER cancer registries linked with Medicare claims (2007-2013). Cases with other urologic cancers, abdominal cancers, and unrelated cancers were included as control groups. A cohort of cancer-free controls was also selected using the Medicare 5% random sample. We used five supervised machine learning methods: classification and regression trees, random forest, logic regression, support vector machines, and logistic regression, for predicting bladder cancer. RESULTS: Registry linkages yielded 37,940 bladder cancer cases and 766,303 cancer-free controls. Using health insurance claims, classification and regression trees distinguished bladder cancer cases from noncancer controls with very high accuracy (95%). Bacille Calmette-Guerin, cystectomy, and mitomycin were the most important predictors for identifying bladder cancer. From 2007 to 2013, we estimated that up to 3,300 bladder cancer cases in the United States may have been missed by the SEER registries. This would result in an average of 3.5% increase in the reported incidence rate. CONCLUSION: SEER cancer registries may potentially miss bladder cancer cases during routine reporting. These missed cases can be identified leveraging Medicare claims and data analytics, leading to more accurate estimates of bladder cancer incidence.

Medical Care Costs Associated with Cancer Survivorship in the United States.

BACKGROUND: The prevalence of cancer survivorship is increasing. In this study, we provide contemporary population-based estimates and projections of the overall and site-specific cancer-attributable medical care costs in the United States. METHODS: We identified survivors aged ≥65 years diagnosed with cancer between 2000 and 2012 from the Surveillance, Epidemiology, and End Results (SEER)-Medicare database and used 2007 to 2013 claims to estimate costs by cancer site, phases of care, and stage at diagnosis. Annualized average cancer-attributable costs for medical care (Medicare Parts A and B) and oral prescription drugs (Medicare Part D) were estimated by subtracting costs between patients with cancer and matched controls. Costs are reported in 2019 U.S. dollars. We combined phase-specific attributable costs with prevalence projections to estimate national costs from 2015 through 2030. RESULTS: Overall annualized average costs were highest in the end-of-life-cancer death phase, followed by the initial and continuing phases (medical care: $105,500, $41,800, and $5,300 and oral prescription drugs: $4,200, $1,800, $1,100, respectively). There was considerable variation in costs by cancer site and stage. Overall national costs in 2015 were $183 billion and projected to increase 34% to $246 billion by 2030, based only on population growth. CONCLUSIONS: Phase of care cancer-attributable cost estimates by cancer site and stage are key inputs for simulation models and cost-effectiveness analyses. IMPACT: The national cancer-attributed medical care costs in the United States are substantial and projected to increase dramatically by 2030, due to population changes alone, reflecting the rising burden of cancer care among cancer survivors.

Cancer-Attributable Medical Costs for Colorectal Cancer Patients by Phases of Care: What Is the Effect of a Prior Cancer History?

Medical care costing studies have excluded patients with a prior cancer history. This study aims to update methods for estimating medical care costs attributable to cancer and to evaluate the effect of a prior history of cancer on costs for colorectal cancer (CRC) patients. We used Surveillance, Epidemiology, and End Results (SEER)-Medicare data and matched cancer patients to controls without cancer to estimate cancer-attributable costs by phases of care using Medicare 2007-2013 claims. CRC annualized average cancer-attributable costs were $56.0 K, $5.3 K, $92.5 K, and $24.3 K in the initial, continuing, and end-of-life cancer and noncancer death phases, respectively, in 2014 dollars. Costs were higher for patients diagnosed with more advanced stage, younger ages, and nonwhite races. Costs for patients with prior cancers were consistently higher than patients without prior cancers, especially in the continuing (4.9 K vs 7.2 K) and end-of-life noncancer death (22.7 K vs 30.0 K). Our CRC costs improve previous estimates by using more recent data and updated methods.

Estimating Chemotherapy Use Among Patients With a Prior Primary Cancer Diagnosis Using SEER-Medicare Data.

Cancer treatment studies commonly exclude patients with prior primary cancers due to difficulties in ascertaining for which site treatment is intended. Surveillance, Epidemiology, and End Results-Medicare patients 65 years and older diagnosed with an index colon or rectal cancer (CRC) or female breast cancer (BC) between 2004 and 2013 were included. Chemotherapy, defined as "any chemotherapy" and more restrictively as "chemotherapy with confirmatory diagnoses," was ascertained based on claims data within 6 months of index cancer diagnosis by prior cancer history. Any chemotherapy use was slightly lower among patients with a prior cancer (CRC: no prior = 17.4%, prior = 16.1%; BC: no prior = 12.9%, prior = 12.0%). With confirmatory diagnoses required, estimates were lower, especially among patients with a prior cancer (CRC: no prior = 16.8%, prior = 13.6%; BC: no prior = 12.6%, prior = 11.0%). These findings suggest that patients with prior cancers can be included in studies of chemotherapy use; requiring confirmatory diagnoses can increase treatment assignment confidence.

Home Health Use Following a Cancer Diagnosis Among Patients Enrolled in Medicare Advantage and Traditional Medicare: Findings From the Newly Linked SEER-Medicare and Home Health OASIS Data.

BACKGROUND: This article describes characteristics of patients receiving home health following an initial cancer diagnosis, comparing those enrolled in Medicare Advantage (MA) and Traditional Medicare (TM), using the newly linked 2010-2014 National Cancer Institute's Surveillance, Epidemiology, and End Results (SEER)-Medicare and home health Outcome and Assessment Information Set (OASIS) data. METHODS: We identified SEER-Medicare beneficiaries with at least one OASIS assessment within 3 months of cancer diagnosis in 2010-2014, and summarized their demographic and clinical characteristics. Demographic and diagnostic data were obtained from the SEER-Medicare data, while further details about cognitive status, mood, function, and medical history were obtained from OASIS. We assessed differences between MA and TM beneficiaries using chi-square tests for independence, t-tests, and Kruskal-Wallis tests. RESUTLS: We identified 104 023 patients who received home health within 3 months of cancer diagnosis: 81 587 enrolled in TM and 22 436 enrolled in MA. TM cancer patients had higher unadjusted rates of home health use than MA patients (16.3% vs 10.3%, P < .001). TM cancer patients receiving home health had more limitations in their cognitive function than their MA counterparts and longer lengths of service (mean = 42.2 days vs 39.4 days, P < .001; median = 27 vs 26 days, interquartile range = 42). CONCLUSION: This study demonstrates the large number of cancer patients in the SEER-Medicare-OASIS data and describes characteristics for TM and MA patients. These newly linked data can be used to assess home health care among older patients with cancer.

Assessment of Oncology Practice Billing Claims for Supplementing Chemotherapy: A Pilot Study in the Georgia SEER Cancer Registry.

BACKGROUND: Chemotherapy information in the population-based cancer registries is underascertained and lacks detail. We conducted a pilot study in the Georgia SEER Cancer Registry (GCR) to investigate the feasibility of supplementing chemotherapy information using billing claims from six private oncology practices (OP). METHODS: To assess cancer patients' representativeness from OP, we compared individuals with invasive first primary cancers diagnosed during 2013-2015 in the GCR (cohort 1) with those who had at least one OP claim in the 12 months after diagnosis (cohort 2). To assess completeness of OP claims to capture chemotherapy (yes or no), we further restricted cohort 2 to patients ages 65 years and older enrolled in fee-for-service Medicare Part A and B from the diagnosis date through 12 months follow-up or to the date of death. With Medicare data serving as the gold standard, sensitivity, specificity, and kappa statistics for the receipt of chemotherapy per OP claims were calculated by demographic and clinical characteristics. RESULTS: Cancer patients seeking care in the OP included in our analysis were not representative of the underlying patient population in the GCR. The practices underrepresented minorities and uninsured while overrepresenting females, persons with high socioeconomic status, patients residing outside the metropolitan Atlanta area, and persons with advance staged disease. The ability of practice claims to identify chemotherapy receipt was moderate (76.1% sensitivity) but varied by demographic and clinical characteristics (76.1-83.0%). CONCLUSIONS: Given the limited ability of OP claims to identify chemotherapy receipt, we suggest analyzing these data for hypothesis generation, but inference should be limited to this patient cohort.

Development and Utility of the Observational Research in Oncology Toolbox: Cancer Medications Enquiry Database-Healthcare Common Procedure Coding System (HCPCS).

PURPOSE: Health-care claims are of increasing utility as a rich, real-world data resource for conducting treatment-related cancer research. However, multiple dynamic coding nomenclatures exist, leading to study variability. To promote increased standardization and reproducibility, the National Cancer Institute (NCI) developed the Cancer Medications Enquiry Database (CanMED)-Healthcare Common Procedure Coding System (HCPCS) within the Observational Research in Oncology Toolbox. METHODS: The CanMED-HCPCS includes codes for oncology medications that a) have a US Food and Drug Administration-approved indication for cancer treatment or treatment-related symptom management; b) are present in National Comprehensive Cancer Network guidelines; or c) carry an orphan drug designation for treatment or management of cancer. Included medications and their HCPCS codes were primarily identified based on Center for Medicare and Medicaid Services annual HCPCS Indices (2012-2018). To demonstrate the utility of the CanMED-HCPCS, use of systemic treatment for stage II-IV colorectal cancer patients included in the Surveillance, Epidemiology, and End Results-Medicare data (2007-2013) was assessed. RESULTS: The CanMED-HCPCS (v2018) includes 332 HCPCS codes for cancer-related medications: chemotherapy (156), immunotherapy (74), hormonal therapy (54), and ancillary therapy (48). Observed treatment trends within the NCI Surveillance, Epidemiology, and End Results-Medicare data were as expected; utilization of each treatment type increased with stage, and immunotherapy was largely confined to use among stage IV patients. CONCLUSION: The CanMED-HCPCS provides a comprehensive resource that can be used by the research community to facilitate systematic identification of medications within claims or electronic health data using the HCPCS nomenclature and greater reproducibility of cancer surveillance and health services research.

Using the SEER-Medicare Data to Assess Incident Chronic Myeloid Leukemia and Bladder Cancer Cases Missed by Cancer Registries.

The growing use of oral systemic therapies and transition of some cancer treatments to the outpatient setting makes capturing all cancer case patients more difficult. We aim to develop algorithms to identify potentially missed incident case patients and estimate impact on incidence rates. We reviewed claims from SEER-Medicare 5% noncancer control patient sample to identify potentially missed chronic myeloid leukemia (CML) and bladder case patients based on diagnosis codes, cancer-related treatments, and oncology consultations. Observed rates of definite missed CML and definite and probable missed bladder case patients were calculated and the impact of missed case patients of these two cancers on SEER 65+ incidence rates were estimated. From 2008 to 2015, the algorithm estimated 781 definite CML case patients missed, increasing the number by 10.7%. From 2007 to 2015, the algorithm estimated 4629 definite and 5772 probable bladder case patients missed, increasing the number by 3.8% to 8.1%. Our algorithms offer potential methods for identifying missed case patients and validating the completeness of cancer registries.

Patterns of Care and Costs for Older Patients With Colorectal Cancer at the End of Life: Descriptive Study of the United States and Canada.

PURPOSE: End-of-life (EOL) cancer care is costly, with challenges regarding intensity and place of care. We described EOL care and costs for patients with colorectal cancer (CRC) in the United States and the province of Ontario, Canada, to inform better care delivery. METHODS: Patients diagnosed with CRC from 2007 to 2013, who died of any cancer from 2007 to 2013 at age ≥ 66 years, were selected from the US SEER cancer registries linked to Medicare claims (n = 16,565) and the Ontario Cancer Registry linked to administrative health data (n = 6,587). We estimated total and resource-specific costs (2015 US dollars) from public payer perspectives over the last 360 days of life by 30-day periods, by stage at diagnosis (0-II, III, IV). RESULTS: In all months, especially 30 days before death, higher percentages of SEER-Medicare than Ontario patients received chemotherapy (15.7% v 8.0%), and imaging tests (39.4% v 31.1%). A higher percentage of Ontario patients were hospitalized (62.5% v 51.0%), but 43.2% of hospitalized SEER-Medicare patients had intensive care unit (ICU) admissions versus 17.9% of hospitalized Ontario patients. Cost differences between cohorts were greater for patients with stage IV disease. In the last 30 days, mean total costs for patients with stage IV disease were $15,881 (SEER-Medicare) and $12,034 (Ontario) versus $19,354 and $17,312 for stage 0-II. Hospitalization costs were higher for SEER-Medicare patients ($11,180 v $9,434), with lower daily hospital costs in Ontario ($1,067 v $2,004). CONCLUSION: These findings suggest opportunities for reducing chemotherapy and ICU use in the United States and hospitalizations in Ontario.

Geographical, racial and socio-economic variation in life expectancy in the US and their impact on cancer relative survival.

PURPOSE: Despite gains in life expectancy between 1992 to 2012, large disparities in life expectancy continue to exist in the United States between subgroups of the population. This study aimed to develop detailed life tables (LT), accounting for mortality differences by race, geography, and socio-economic status (SES), to more accurately measure relative cancer survival and life expectancy patterns in the United States. METHODS: We estimated an extensive set of County SES-LT by fitting Poisson regression models to deaths and population counts for U.S. counties by age, year, gender, race, ethnicity and county-level SES index. We reported life expectancy patterns and evaluated the impact of the County SES-LT on relative survival using data from the Surveillance Epidemiology and End Results (SEER) Program cancer registries. RESULTS: Between 1992 and 2012, the largest increase in life expectancy was among black men (6.8 years), however there were still large geographical differences. Life expectancy was highest for Asian or Pacific Islanders (API), and lowest for American Indians and Alaskan Natives (AIAN). In 2010, life expectancies by state ranged from 73 to 82 years for white males, 78 to 86 years for white females, 66 to 75 for black males, and 75 to 81 for black females. Comparisons of relative survival using National LT and the new County SES-LT showed that relative survival using County SES-LT improved relative survival estimates for some demographic groups, particularly in low and high SES areas, among Hispanics and AIAN, and among older male cancer patients. Relative survival using County SES-LT was 7.3% and 6.7% survival points closer to cause-specific survival compared to the National LT relative survival for AIAN and Hispanic cancer patients diagnosed between ages 75 and 84 years, respectively. Importantly, the County SES-LT relative survival estimates were higher in lower SES areas and lower in higher SES areas, reducing differences in relative survival comparisons. CONCLUSION: The use of these new socio-economic life tables (County SES-LT) can provide more accurate estimates of relative survival, improve comparisons of relative survival among registries, better illustrate disparities and cancer control efforts, and should be used as default for cancer relative survival using U.S. data.

New Opportunities for Cancer Health Services Research: Linking the SEER-Medicare Data to the Nursing Home Minimum Data Set.

BACKGROUND: The Surveillance, Epidemiology and End Results (SEER)-Medicare data combine clinical information from population-based cancer registries with Medicare claims. These data have been used in many studies to understand cancer screening, treatment, outcomes, and costs. However, until recently, these data included limited information related to the characteristics and outcomes of cancer patients residing in or admitted to nursing homes. OBJECTIVES: To provide an overview of the new linkage between SEER-Medicare data and the Minimum Data Set (MDS), a nursing home resident assessment instrument detailing residents' physical, psychological, and psychosocial functioning as well as any therapies or treatments received. RESEARCH DESIGN: This is a descriptive, retrospective cohort study. SUBJECTS: Persons in SEER-Medicare diagnosed with cancer from 2004 to 2013 were linked to the 2011-2014 MDS, with 17% of SEER-Medicare patients linked to the MDS data. During 2011-2014, we identified 318,617 cancer patients receiving care in a nursing home and 256,947 cancer patients newly admitted to a total of 10,953 nursing homes. Of these patients, approximately two thirds were Medicare fee-for-service beneficiaries. RESULTS: The timing from cancer diagnoses to nursing home admission varied by cancer. In total, 93% of all patients were admitted directly to a nursing home from an acute care hospital. The majority of patients were cognitively intact, 21% reported some level of depression, and 9% had severe functional limitations. CONCLUSIONS: The new SEER-Medicare-MDS dataset provides a valuable resource for understanding the postacute and long-term care experiences of cancer patients receiving care in United States' nursing homes.

Antineoplastic Treatment of Advanced-Stage Non-Small-Cell Lung Cancer: Treatment, Survival, and Spending (2000 to 2011).

Purpose Multiple agents for advanced non-small-cell lung cancer (NSCLC) have been approved in the past decade, but little is known about their use and associated spending and survival. Methods We used SEER-Medicare data for elderly patients with a new diagnosis of advanced-stage NSCLC and were treated with antineoplastic agents between 2000 and 2011 (N = 22,163). We estimated the adjusted percentage of patients who received each agent, days while on treatment, survival, and spending in the 12 months after diagnosis. Results During the 12-year study period, a marked shift in treatment occurred along with a rapid adoption of pemetrexed (39.2%), erlotinib (20.3%), and bevacizumab (18.9%) and a decline in paclitaxel (38.7%), gemcitabine (17.0%), and vinorelbine (5.7%; all P < .05). The average total days on therapy increased by 5 days (from 103 to 108 days). Patients who received bevacizumab, erlotinib, or pemetrexed had the longest treatment durations on average (approximately 146 days v 75 days for those who did not receive these agents). Approximately 44% of patients received antineoplastic agents in the last 30 days of life throughout the study period. Acute inpatient spending declined (from $29,376 to $23,731), whereas outpatient spending increased 23% (from $37,931 to $46,642). Median survival gains of 1.5 months were observed. Conclusion Considerable shifts in the treatment of advanced-stage NSCLC occurred along with modest gains in survival and total Medicare spending. More precise outcome information is needed to inform value-based treatment decisions for advanced-stage NSCLC.

Comorbidity-adjusted life expectancy: a new tool to inform recommendations for optimal screening strategies.

BACKGROUND: Many guidelines recommend considering health status and life expectancy when making cancer screening decisions for elderly persons. OBJECTIVE: To estimate life expectancy for elderly persons without a history of cancer, taking into account comorbid conditions. DESIGN: Population-based cohort study. SETTING: A 5% sample of Medicare beneficiaries in selected geographic areas, including their claims and vital status information. PARTICIPANTS: Medicare beneficiaries aged 66 years or older between 1992 and 2005 without a history of cancer (n = 407 749). MEASUREMENTS: Medicare claims were used to identify comorbid conditions included in the Charlson index. Survival probabilities were estimated by comorbidity group (no, low/medium, and high) and for the 3 most prevalent conditions (diabetes, chronic obstructive pulmonary disease, and congestive heart failure) by using the Cox proportional hazards model. Comorbidity-adjusted life expectancy was calculated based on comparisons of survival models with U.S. life tables. Survival probabilities from the U.S. life tables providing the most similar survival experience to the cohort of interest were used. RESULTS: Persons with higher levels of comorbidity had shorter life expectancies, whereas those with no comorbid conditions, including very elderly persons, had favorable life expectancies relative to an average person of the same chronological age. The estimated life expectancy at age 75 years was approximately 3 years longer for persons with no comorbid conditions and approximately 3 years shorter for those with high comorbidity relative to the average U.S. population. LIMITATIONS: The cohort was limited to Medicare fee-for-service beneficiaries aged 66 years or older living in selected geographic areas. Data from the Surveillance, Epidemiology, and End Results cancer registry and Medicare claims lack information on functional status and severity of comorbidity, which might influence life expectancy in elderly persons. CONCLUSION: Life expectancy varies considerably by comorbidity status in elderly persons. Comorbidity-adjusted life expectancy may help physicians tailor recommendations for stopping or continuing cancer screening for individual patients.

Assessing non-cancer-related health status of US cancer patients: other-cause survival and comorbidity prevalence.

With advances in prevention, screening, and treatment, cancer patients are living longer; hence, non-cancer-related health status will likely play a larger role in determining their life expectancy. In this study, we present a novel method for characterizing non-cancer--related health status of cancer patients using population-based cancer registry data. We assessed non-cancer-related health status in the context of survival from other causes of death and prevalence of comorbidities. Data from the Surveillance, Epidemiology, and End Results program (2000-2006) were used to analyze cancer patients' survival probabilities by cause of death. Other-cause survival was estimated using a left-truncated survival method with the hazard of death due to other causes characterized as a function of age. Surveillance, Epidemiology, and End Results data linked to Medicare claims (1992-2005) were used to quantify comorbidity prevalence. Relative to the US population, survival from a non-cancer-related death was higher for patients diagnosed with early stage breast and prostate cancer but lower for lung cancer patients at all stages. Lung cancer patients had worse comorbidity status than did other cancer patients. The present study represents the first attempt to evaluate the non-cancer-related health status of US cancer patients by cancer site (breast, prostate, colorectal, and lung) and stage. The findings provide insight into non-cancer-related health issues among cancer patients and their risk of dying from other causes.

Development of a prognostic model for six-month mortality in older adults with declining health.

CONTEXT: Estimation of six-month prognosis is essential in hospice referral decisions, but accurate, evidence-based tools to assist in this task are lacking. OBJECTIVES: To develop a new prognostic model, the Patient-Reported Outcome Mortality Prediction Tool (PROMPT), for six-month mortality in community-dwelling elderly patients. METHODS: We used data from the Medicare Health Outcomes Survey linked to vital status information. Respondents were 65 years old or older, with self-reported declining health over the past year (n=21,870), identified from four Medicare Health Outcomes Survey cohorts (1998-2000, 1999-2001, 2000-2002, and 2001-2003). A logistic regression model was derived to predict six-month mortality, using sociodemographic characteristics, comorbidities, and health-related quality of life (HRQOL), ascertained by measures of activities of daily living and the Medical Outcomes Study Short Form-36 Health Survey; k-fold cross-validation was used to evaluate model performance, which was compared with existing prognostic tools. RESULTS: The PROMPT incorporated 11 variables, including four HRQOL domains: general health perceptions, activities of daily living, social functioning, and energy/fatigue. The model demonstrated good discrimination (c-statistic=0.75) and calibration. Overall diagnostic accuracy was superior to existing tools. At cut points of 10%-70%, estimated six-month mortality risk sensitivity and specificity ranged from 0.8% to 83.4% and 51.1% to 99.9%, respectively, and positive likelihood ratios at all mortality risk cut points ≥40% exceeded 5.0. Corresponding positive and negative predictive values were 23.1%-64.1% and 85.3%-94.5%. Over 50% of patients with estimated six-month mortality risk ≥30% died within 12 months. CONCLUSION: The PROMPT, a new prognostic model incorporating HRQOL, demonstrates promising performance and potential value for hospice referral decisions. More work is needed to evaluate the model.