Financial Hardship, Healthcare Utilization, and Health Among U.S. Cancer Survivors.

INTRODUCTION: This study examined associations of both medical and nonmedical financial hardships with healthcare utilization and self-rated health among cancer survivors. METHODS: The National Health Interview Survey (2013-2017) was used to identify cancer survivors (aged 18-64 years: n=4,939; aged ≥65 years: n=6,972). A total of 4 levels of medical financial hardship intensities were created with measures from material, psychological, and behavioral domains. A total of 5 levels of nonmedical financial hardship intensities were created with measures in food insecurity and worry about other economic needs (e.g., housing expenses). Generalized ordinal logistic regression examined associations between medical and nonmedical financial hardship intensities and emergency department visits, use of preventive services and cancer screenings, and self-rated health. All analyses were performed in 2019. RESULTS: In adjusted analyses, cancer survivors with higher medical financial hardship intensity (Level 4 vs Level 1; aged 18-64 years: 42% vs 26.2%, p<0.001; aged ≥65 years: 37.6% vs 24.3%, p=0.001) and higher nonmedical financial hardship intensity (Level 5 vs Level 1; aged 18-64 years: 37.2% vs 27.9%, p=0.011) had more emergency department visits. Moreover, cancer survivors with higher medical financial hardship intensity had lower influenza vaccine (Level 4 vs Level 1; aged 18-64 years: 45.6% vs 52.5%, p=0.036; aged ≥65 years: 64.6% vs 75.6%, p=0.008) and lower breast cancer screening levels (Level 4 vs Level 1; 46.8% vs 61.2%, p=0.001). Similar patterns were found between higher financial hardship intensities and worse self-rated health. CONCLUSIONS: Higher medical and nonmedical financial hardships are independently associated with more emergency department visits, lower receipt of some preventive services, and worse self-rated health in cancer survivors. With growing healthcare costs, unmet medical and nonmedical financial needs may worsen health disparities among cancer survivors.

Patient-Provider Discussions About Out-of-Pocket Costs of Cancer Care in the U.S.

INTRODUCTION: Despite the importance of cost-related discussions in cancer care, little is known about the prevalence or drivers of these discussions in clinical practice. This study estimates the prevalence and examines the correlates of cancer survivors' discussions about out-of-pocket costs of cancer care with providers. METHODS: The 2016 and 2017 Medical Expenditure Panel Survey Experiences with Cancer Surveys were used to identify 1,550 survivors who responded to the question on discussion about out-of-pocket costs of cancer care. Multivariable multinomial logistic regression examined the correlates of discussions about out-of-pocket costs. Analyses were performed in 2019. RESULTS: Approximately one quarter of cancer survivors reported having discussed the out-of-pocket costs of cancer care. In multivariable analyses, respondents in the following categories were less likely to report no cost discussion than any cost discussion: black non-Hispanic/other race (RRR=0.67, 95% CI=0.45, 0.98; white non-Hispanic race as reference), no health insurance at diagnosis (RRR=0.51, 95% CI=0.27, 0.95; private health insurance as reference), and any experience of financial hardship (RRR=0.48, 95% CI=0.35, 0.66; no financial hardship as reference). CONCLUSIONS: Patient-reported discussions about out-of-pocket costs for cancer care are infrequent in the U.S. The findings highlight the needs to improve the understanding of the barriers and facilitators for effective discussions about out-of-pocket costs of cancer care.

Worry About Daily Financial Needs and Food Insecurity Among Cancer Survivors in the United States.

BACKGROUND: A cancer diagnosis can impose substantial medical financial burden on individuals and may limit their ability to work. However, less is known about worry for nonmedical financial needs and food insecurity among cancer survivors. METHODS: The National Health Interview Survey (2013-2017) was used to identify cancer survivors (age 18-39 years, n=771; age 40-64 years, n=4,269; age ≥65 years, n=7,101) and individuals without a cancer history (age 18-39 years, n=53,262; age 40-64 years, n=60,141; age ≥65 years, n=30,261). For both cancer survivors and the noncancer group, adjusted proportions were generated for (1) financial worry ("very/moderately/not worried") about retirement, standard of living, monthly bills, and housing costs; and (2) food insecurity ("often/sometimes/not true") regarding whether food would run out, the fact that food bought did not last, and the inability to afford balanced meals. Further adjusted analyses examined intensity measures ("severe/moderate/minor or none") of financial worry and food insecurity among cancer survivors only. RESULTS: Compared with individuals without a cancer history, cancer survivors aged 18 to 39 years reported consistently higher "very worried" levels regarding retirement (25.5% vs 16.9%; P<.001), standard of living (20.4% vs 12.9%; P<.001), monthly bills (14.9% vs 10.3%; P=.002), and housing costs (13.6% vs 8.9%; P=.001); and higher "often true" levels regarding worry about food running out (7.9% vs 4.6%; P=.004), food not lasting (7.6% vs 3.3%; P=.003), and being unable to afford balanced meals (6.3% vs 3.4%; P=.007). Findings were not as consistent for cancer survivors aged 40 to 64 years. In contrast, results were generally similar for adults aged ≥65 years with/without a cancer history. Among cancer survivors, 57.6% (age 18-39 years; P<.001), 51.9% (age 40-64 years; P<.001), and 23.8% (age ≥65 years; referent) reported severe/moderate financial worry intensity, and 27.0% (age 18-39 years; P<.001), 14.8% (age 40-64 years; P<.001), and 6.3% (age ≥65 years; referent) experienced severe/moderate food insecurity intensity. Lower income and higher comorbidities were generally associated with greater intensities of financial worry and food insecurity in all 3 age groups. CONCLUSIONS: Younger cancer survivors experience greater financial worry and food insecurity. In addition to coping with medical costs, cancer survivors with low income and multiple comorbidities struggle to pay for daily living needs, such as food, housing, and monthly bills.

Factors Associated With Oncologist Discussions of the Costs of Genomic Testing and Related Treatments.

BACKGROUND: Use of genomic testing is increasing in the United States. Testing can be expensive, and not all tests and related treatments are covered by health insurance. Little is known about how often oncologists discuss costs of testing and treatment or about the factors associated with those discussions. METHODS: We identified 1220 oncologists who reported discussing genomic testing with their cancer patients from the 2017 National Survey of Precision Medicine in Cancer Treatment. Multivariable polytomous logistic regression analyses were used to assess associations between oncologist and practice characteristics and the frequency of cost discussions. All statistical tests were two-sided. RESULTS: Among oncologists who discussed genomic testing with patients, 50.0% reported often discussing the likely costs of testing and related treatments, 26.3% reported sometimes discussing costs, and 23.7% reported never or rarely discussing costs. In adjusted analyses, oncologists with training in genomic testing or working in practices with electronic medical record alerts for genomic tests were more likely to have cost discussions sometimes (odds ratio [OR] = 2.09, 95% confidence interval [CI] = 1.19 to 3.69) or often (OR = 2.22, 95% CI = 1.30 to 3.79), respectively, compared to rarely or never. Other factors statistically significantly associated with more frequent cost discussions included treating solid tumors (rather than only hematological cancers), using next-generation sequencing gene panel tests, having higher patient volume, and working in practices with higher percentages of patients insured by Medicaid, or self-paid or uninsured. CONCLUSIONS: Interventions targeting modifiable oncologist and practice factors, such as training in genomic testing and use of electronic medical record alerts, may help improve cost discussions about genomic testing and related treatments.

Cancer History, Health Insurance Coverage, and Cost-Related Medication Nonadherence and Medication Cost-Coping Strategies in the United States.

OBJECTIVES: To evaluate the relationship between cancer history and cost-related medication nonadherence (CRN) as well as cost-coping strategies, by health insurance coverage. METHODS: We used the 2013 to 2016 National Health Interview Survey to identify adults aged 18 to 64 years with (n = 3599) and without (n = 56 909) a cancer history. Cost-related changes in medication use included (1) CRN, measured as skipping, taking less, or delaying medication because of cost, and (2) cost-coping strategies, measured as requesting lower cost medication or using alternative therapies to save money. Separate multivariable logistic regressions were used to calculate the adjusted odds ratios (AORs) of CRN and cost-coping strategies associated with cancer history, stratified by insurance. RESULTS: Cancer survivors were more likely than adults without a cancer history to report CRN (AOR 1.26; 95% confidence interval [CI] 1.10-1.43) and cost-coping strategies (AOR 1.10; 95% CI 0.99-1.19). Among the privately insured, the difference in CRN by cancer history was the greatest among those enrolled in high-deductible health plans (HDHPs) without health savings accounts (HSAs) (AOR 1.78; 95% CI 1.30-2.44). Among adults with HDHP and HSA, cancer survivors were less likely to report cost-coping strategies (AOR 0.62; 95% CI 0.42-0.90). Regardless of cancer history, CRN and cost-coping strategies were the highest for those uninsured, enrolled in HDHP without HSA, and without prescription drug coverage under their health plan (all P<.001). CONCLUSIONS: Cancer survivors are prone to CRN and more likely to use cost-coping strategies. Expanding options for health insurance coverage, use of HSAs for those with HDHP, and enhanced prescription drug coverage may effectively address CRN.

A population-based multistate model for diffuse large B-cell lymphoma-specific mortality in older patients.

BACKGROUND: Despite effective therapies, outcomes for diffuse large B-cell lymphoma (DLCBL) remain heterogeneous in older individuals due to comorbid diseases and variations in disease biology. METHODS: Using the Surveillance, Epidemiology, and End Results (SEER)-Medicare database, the authors conducted a multistate survival analysis of 11,780 patients with DLBCL who were aged ≥65 years at the time of diagnosis (2002-2009). Cox proportional hazards models were used to specify the impact of prognostic factors on overall survival and cause-specific deaths, and the Aalen-Johansen estimator was used to project the course of DLBCL over time with or without standard therapy with rituximab, cyclophosphamide, doxorubicin, vincristine, and prednisone (R-CHOP). RESULTS: Advanced age (hazard ratio [HR] for ages 71-75 years: 1.25; HR for ages 76-80 years: 1.46; HR for ages 81-85 years: 1.88; and HR for age ≥86 years: 2.26), DLBCL stage (HR for Ann Arbor stage II: 1.28; HR for stage III: 1.54; and HR for stage IV: 1.95), Charlson Comorbidity Index (CCI) ≥1 (HR for CCI of 1, 1.15; and HR for CCI >1, 1.37), and not being married (HR, 1.12) were associated with an increased risk of DLBCL-specific death. Being female (HR, 0.91) and of higher socioeconomic status (HR, 0.91) were associated with a lower risk of DLBCL-related mortality after therapy. For patients treated with R-CHOP (3610 patients), the risk of death due to DLBCL was 14.0% and 18.6%, respectively, at 2 and 5 years of treatment and plateaued afterward, confirming a 5-year "cure" point while receiving R-CHOP among older patients. CONCLUSIONS: Conducting a survival analysis over a large data set, the current study evaluated competing risks for death within a multistate modeling framework, and identified age, sex, and CCI as risk factors for DLBCL-specific and other causes of death.

Evaluating Lung Cancer Screening Uptake, Outcomes, and Costs in the United States: Challenges With Existing Data and Recommendations for Improvement.

The National Lung Screening Trial (NLST) reported substantial reduction in lung cancer mortality among high-risk individuals screened annually with low-dose helical computed tomography (LDCT). As a result, the US Preventive Services Task Force issued a B recommendation for annual LDCT in high-risk individuals, which requires private insurers to cover it without cost-sharing. The Medicare program also covers LDCT for high-risk beneficiaries without cost-sharing. However, the NLST findings may not be generalizable to the community setting because of differences in patients, providers, and practices participating in the NLST. Thus, examining uptake of LDCT screening in community practice is critical, as is evaluating the immediate and downstream outcomes of screening, including false-positive scans, follow-up examinations and adverse events, costs, stage of disease at diagnosis, and survival. This commentary presents an overview of the landscape of the data resources currently available to evaluate the uptake, outcomes, and costs of LDCT screening in the United States. We describe the strengths and limitations of existing data sources, including administrative databases, surveys, and registries. Thereafter, we provide recommendations for improving the data infrastructure pertaining to three overarching research areas: receipt of guideline-consistent screening and follow-up, weighing benefits and harms of screening, and costs of screening.

Assessing the Effectiveness of Treatment Sequences for Older Patients With High-risk Follicular Lymphoma With a Multistate Model.

BACKGROUND: Disease progression within < 2 years of initial chemoimmunotherapy and patient age > 60 years have been associated with poor overall survival (OS) in follicular lymphoma (FL). No standard treatment exists for these high-risk patients, and the effectiveness of sequential therapies remains unclear. PATIENTS AND METHODS: We studied the course of FL with first-, second-, and third-line treatment. Using large population-based data, we identified 5234 patients with FL diagnosed in 2000 to 2009. Of these patients, 71% had received second-line therapy < 2 years, and 29% had received no therapy after first-line therapy, with a median OS of < 3 years. Treatment included rituximab, R-CVP (rituximab, cyclophosphamide, vincristine), R-CHOP (rituximab, cyclophosphamide, hydroxydaunorubicin, vincristine), R-Other (other rituximab-containing), and other regimens. The Aalen-Johansen estimator and Cox proportional hazards models were used to quantify the outcomes and assess the effects of the clinical and sociodemographic factors. RESULTS: R-CHOP demonstrated the most favorable 5-year OS among first- (71%), second- (55%), and third-line (61%) therapies. First-line R-CHOP improved OS (hazard ratio [HR], 0.57; 95% confidence interval [CI], 0.50-0.64) and reduced the mortality risks after first-line (HR, 0.60; 95% CI, 0.47-0.77), second-line (HR, 0.40; 95% CI, 0.29-0.53), and third-line (HR, 0.63; 95% CI, 0.53-0.76) treatments. B-symptoms, being married, and histologic grade 1/2 were associated with the use of earlier second-line therapy. Early progression from second- to third-line therapy was associated with poor OS. The repeated use of R-CHOP or R-CVP as first- and second-line treatment yielded high 2-year mortality rates (R-CHOP + R-CHOP, 17.3%; R-CVP + R-CVP, 21.1%). CONCLUSION: Our multistate approach assessed the effect of sequential therapy on the immediate and subsequent treatment-line outcomes. We found that R-CHOP in any line improved OS for patients with high-risk FL.

Medical Financial Hardship among Cancer Survivors in the United States: What Do We Know? What Do We Need to Know?

Rising costs of cancer care have led to increased concerns about medical financial hardship for cancer survivors and their families in the United States. In this commentary, we provide an overview of research describing medical financial hardship and introduce a conceptual framework for identifying risk factors and research gaps at the patient and family, provider and care team, health care system, employer, and state and national policy levels. We then use this framework to highlight measurement and data infrastructure gaps related to hardship, summarize existing interventions to minimize hardship, and identify opportunities for future intervention efforts.

Determinants and Outcomes of Satisfaction With Healthcare Provider Communication Among Cancer Survivors.

Background: Despite the surge of interest in improving provider communication, empirical research is sparse on the determinants and outcomes of cancer survivors' satisfaction with healthcare provider communication. Methods: Longitudinal Medical Expenditure Panel Survey data spanning 2008 through 2014 was used to identify 4,588 respondents who were ever diagnosed with cancer. A composite score was generated by combining 5 measures of satisfaction. We used multivariate logistic regressions and 2-part models to examine the associations between satisfaction ratings and outcomes, including general, mental, and physical health; office visits; and total healthcare, drug, and out-of-pocket expenditures. Results: The study sample comprised 2,257 nonelderly (age 18-64 years) and 2,331 elderly (age ≥65 years) respondents. Among both age groups, higher satisfaction was associated with fewer comorbidities, fewer year 1 office visits, and absence of year 1 emergency department visits. Membership of higher satisfaction tertile in year 1 was associated with better year 2 mental health (tertile 1 [T1]: predictive margin [PM], 27.1%; tertile 2 [T2]: PM, 35.5%; P=.013; tertile 3 [T3]: PM, 37.0%; P=.005) and general health (T1 [ref]: PM, 30.3%; T3: PM, 38.9%; P=.007) among the elderly. Greater satisfaction was associated with fewer year 2 office visits (T1 [ref]: PM, 7.42 visits; T3: PM, 6.26 visits; P=.038) among the nonelderly; and lower year 2 healthcare expenditures (T1 [ref]: PM, $34,071; T3: PM, $26,995; P=.049) among the elderly. Conclusions: We identified potential differences in cancer survivors' needs and expectations of provider communication based on comorbidities and baseline service use. These results emphasize the need for individualized communication strategies for patients with cancer and survivors shaped by their distinct requirements. Our findings of better health, lower service use, and lower expenditures among more satisfied cancer survivors suggest that interventions to improve provider communication could lead to a more efficient use of healthcare resources.

Characterizing Autoimmune Disease-associated Diffuse Large B-cell Lymphoma in a SEER-Medicare Cohort.

BACKGROUND: Severe immune dysregulation such as seen in autoimmune (AI) disease is known to act as a significant risk factor for diffuse large B-cell lymphoma (DLBCL). However, little is known about the demographics or clinical outcomes of DLBCL that arises in the setting of AI disease. PATIENTS AND METHODS: We used the Surveillance, Epidemiology, and End Results (SEER) database for patients with a diagnosis from 1999 to 2009 linked to their Medicare claims data through 2011 to characterize the presentation, treatment, and survival patterns in DLBCL patients, including those with rheumatoid arthritis, systemic lupus erythematosus (SLE), Sjögren syndrome, and other B-cell-mediated AI diseases. We examined the baseline clinical characteristics for patients with B-cell-mediated AI disease, plotted the overall survival and lymphoma-related survival (LRS) for these groups, and compared the median survival times. RESULTS: Patients with DLBCL and AI disease were more commonly female. However, patients with DLBCL and rheumatoid arthritis, SLE, Sjögren syndrome, or other B-cell AI diseases did not differ from other DLBCL patients in any other baseline presenting features and received similar first-line treatment. A trend toward decreased LRS was seen in patients with SLE and DLBCL compared with all other groups, but this difference was not statistically significant in this cohort. CONCLUSION: In the present retrospective claims-based cohort of older patients with DLBCL, concomitant AI disease was uncommon and was more likely to occur in female DLBCL patients, which likely reflects the greater incidence of AI disease in women. The possibility of lower LRS for SLE patients should be explored in future studies.

Changing trends of an endemic trauma.

The incidence of severe burn is extremely high in the Low and Middle Income Countries with an estimated 90% of the world incidence of which 50% is in South East Asia. Through an earlier analysis of 11,196 burn admission over 8 years (1993-2000--Phase I) to our burn unit we established the endemic nature of the injury [Ahuja RB, Bhattacharya S. An analysis of 11,196 burn admissions and evaluation of conservative management techniques. Burns 2002;28:555-61]. A continued analysis of 5566 burn admissions over the next 7 years (2001-2007--Phase II) and its comparison with the Phase I reveals a significant change in the epidemiological profile. The average yearly admissions have fallen by 43.14%, from 1399.5 patients in Phase I to 795.14 patients in Phase II. This fall in average yearly admissions is predominant in the age group 16-35 years (52.61% decline) and 36-55 years (46.51% decline). The overall female to male ratio has also changed from 1.26:1 to 0.91:1. However, the overall mean %TBSA burn has reduced only mildly from 49.12% TBSA in Phase I to 44.39% in Phase II. During Phase II there was also a significant decline of 46.93% and 56.25% in the yearly admission of flame and scald burn respectively. Non-intentional incidents still remain the main mode of injury accounting for 87.12% in Phase I and 89.89% in Phase II. But, the yearly admissions of non-intentional burns fell from 1219.25 in Phase I to 714.71 in Phase II, which is a significant drop of 41.38%. Kitchen continues to dominate as the main location for flame incidents, but the yearly admission rate from kitchen accidents dropped from 897.5 patients in Phase I to 368.43 patients in Phase II. At the same time, liquefied petroleum gas (LPG) leaks which accounted for only 0.72% of all kitchen accidents in Phase I rose to 10.74% in Phase II. Another redeeming feature is the reduction in overall mortality from 51.8% in Phase I to 40.20% in Phase II. Interestingly, a very significant negative correlation exists (being significant at 0.01 level--2 tailed) between burn admissions and the yearly per-capita income of Delhi, from 1993 to 2005, to prove that the incidence and profile of burns directly reflects the economic development of the society. We see this as the first long term study from a burn unit of a developing country to directly reflect this association of burn incidence and its changing profile with economic prosperity.