End-of-Life Health-Care Cost of Patients With Lung Cancer: A Retrospective Study

Dynamic Prediction of Near-Term Overall Survival in Patients with Advanced NSCLC Based on Real-World Data

Simple Summary

Patients near the end of life often receive aggressive care, which may be of low value. For patients with advanced cancers, it is standard clinical practice to estimate the prognosis to inform treatment decisions and improve end-of-life care. However, clinical estimates of prognosis may be imprecise and rapidly become out-of-date if clinical factors that evolve over time are not incorporated. Patient prognosis is commonly estimated based on a clinician’s subjective assessment of patient reserve, such as performance status. We propose a spline-smoothed landmarking approach to dynamically estimate survival probabilities based on objective, evolving patient features. The proposed method allows predictions at any time during the patient disease course and demonstrates dramatically improved prediction accuracy compared to methods using clinical features at a fixed time. The proposed approaches can assist clinicians and patients in appropriately regulating treatments to improve outcomes and quality of life.

Abstract

Patients with terminal cancers commonly receive aggressive and sub-optimal treatment near the end of life, which may not be beneficial in terms of duration or quality of life. To improve end-of-life care, it is essential to develop methods that can accurately predict the short-term risk of death. However, most prediction models for patients with cancer are static in the sense that they only use patient features at a fixed time. We proposed a dynamic prediction model (DPM) that can incorporate time-dependent predictors. We apply this method to patients with advanced non-small-cell lung cancer from a real-world database. Inverse probability of censoring weighted AUC with bootstrap inference was used to compare predictions among models. We found that increasing ECOG performance status and decreasing albumin had negative prognostic associations with overall survival (OS). Moreover, the negative prognostic implications strengthened over the patient disease course. DPMs using both time-independent and time-dependent predictors substantially improved short-term prediction accuracy compared to Cox models using only predictors at a fixed time. The proposed model can be broadly applied for prediction based on longitudinal data, including an estimation of the dynamic effects of time-dependent features on OS and updating predictions at any follow-up time.

Economic burden of lung cancer in Turkey: a cost of illness study from payer perspective

BACKGROUND

This study was designed to estimate economic burden of lung cancer in Turkey from payer perspective based on expert panel opinion on practice patterns in clinical practice.

METHODS

In this cost of illness study, direct medical cost was calculated based on cost items related to outpatient visits, laboratory and radiological tests, hospitalizations/interventions, drug treatment, adverse events and metastasis. Indirect cost was calculated based on lost productivity due to early retirement, morbidity and premature death resulting from the illness, the value of lost productivity due to time spent by family caregivers and cost of formal caregivers.

RESULTS

Cost analysis revealed the total per patient annual direct medical cost for small cell lung cancer to be €8772), for non-small-cell lung cancer to be €10,167. Total annual direct medical cost was €497.9 million, total annual indirect medical cost was €1.1 billion and total economic burden of lung cancer was €1.6 billion. Hospitalization/interventions (41%) and indirect costs (68.6%) were the major cost drivers for total direct costs and the overall economic burden of lung cancer, respectively.

CONCLUSIONS

Our findings indicate per patient direct medical costs of small cell lung cancer and non-small-cell lung cancer to be substantial and comparable, indicating the substantial economic burden of lung cancer in terms of both direct and indirect costs. Our findings indicate that hospitalization/interventions cost item and indirect costs were the major cost drivers for total direct costs and the overall economic burden of lung cancer, respectively. Our findings emphasize the potential role of improved cancer prevention and early diagnosis strategies, by enabling cost savings related to drug treatment and metastasis management cost items, in sustainability of cancer treatments.

End-of-life cost for lung cancer patients in Greece: a hospital-based retrospective study

Objective: The aim of the present study was to estimate the cost of treating patients with lung cancer at their end-of-life (EOL) phase of care in Greece. Materials & methods: A hospital-based retrospective study was conducted in the Oncology Unit of 'Sotiria' Hospital, in Athens, Greece. All lung cancer patients who died between 1 January 2015 and 31 December 2018 with at least 6 months follow-up were enrolled in the study. Healthcare resource utilization data, including inpatient and outpatient ones, during the last 6 months before death was extracted from a registry kept in the unit. This data were combined with the corresponding local unit costs to calculate the 6, 3 and 1-month EOL cost in €2019 values. Results: A total of 122 patients met the inclusion criteria. The mean (standard deviation) age at diagnosis was 67.8 (8.9) years with 78.7% of patients being male and 55.0% diagnosed at stage IV. About 52.5% of patients had been diagnosed with adenocarcinoma, 28.7% with squamous non-small-cell lung cancer types and 18.9% with small-cell-lung cancer. The median overall survival of these patients was 10.8 months. During the EOL periods, the mean cost/patient in the last 6, 3 and 1 month were €7665, €3351 and €1009, respectively. Pharmaceutical cost was the key driver of the total cost (75% of the total 6-month) followed by radiation therapy (16.2%). The median EOL 6-month cost was marginally statistically significantly higher among patients with adenocarcinoma (€9031) compared with squamous (€6606) and to small-cell-lung cancer (€5474). Conclusion: The findings of the present study indicate that lung cancer treatment incurs high costs in Greece, mainly attributed to pharmaceutical expenses, even at the EOL phase.

Trends in End-of-Life Resource Utilization and Costs among Prostate Cancer Patients from 2006 to 2015: A Nationwide Population-Based Study

Purpose

The purpose of this study was to evaluate end-of-life resource utilization and costs for prostate cancer patients during the last year of life in Korea.

Materials and Methods

The study used the National Health Information Database (NHIS-2017-4-031) of the Korean National Health Insurance Service. Healthcare claim data for the years 2002 through 2015 were collected from the Korean National Health Insurance System. Among 83,173 prostate cancer patients, we enrolled 18,419 after excluding 1,082 who never claimed for the last year of life.

Results

From 2006 to 2015, there was a 3.2-fold increase the total number of prostate cancer decedents. The average cost of care during the last year of life increased over the 10-year period, from 14,420,000 Korean won to 20,300,000 Korean won, regardless of survival time. The cost of major treatments and medications, other than analgesics, was relatively high. Radiologic tests, opioids, pain control, and rehabilitation costs were relatively low. Multiple regression analysis identified age and living in rural area as negatively associated with prostate cancer care costs, whereas income level and a higher number of comorbidities were positively associated.

Conclusions

Expenditure of prostate cancer care during the last year of life varied according to patient characteristics. Average costs increased every year. However, the results suggest underutilization of support services, likely due to lack of alternative accommodation for terminal prostate cancer patients. Further examination of patterns of utilization of healthcare resources will allow policymakers to take a better approach to reducing the burden of prostate cancer care.

State-Level Disparity in Lung Cancer Survival in the United States

Rationale: The cancer mortality-to-incidence ratio (MIR) can serve as a population-based indicator for cancer care outcomes. In the US, evaluation of lung cancer survival by individual states has not been evaluated. Objective: To assess the association between lung cancer survival by using MIRs and state-level health disparities in the United States. Methods: We calculated 5-year lung cancer MIR averages from 2011 to 2015 using the United States Cancer Statistics (USCS) data. America's Health Rankings (AHR) is a platform using weighted measures in five different categories to calculate annual state health rankings. Five-year averages from 2011 to 2015 of the health uninsured rate and 4-year averages from 2011 to 2014 of health spending per capita were obtained from the U.S. Census Bureau and Centers for Medicare & Medicaid Services. Linear regression analyses were performed to determine the associations between cancer survival value (CSV) = (1 - MIR) × 100% and state health variables. Results: During the study period, the 5-year averages of age-adjusted incidence, mortality rates, and CSVs were 60.3 ± 2.1 per 100,000 population, 43.4 ± 2.1 per 100,000, and 27.9 ± 3.9%, respectively. Among the 50 states, Connecticut had the highest CSV (38.6 ± 1.7%) whereas Nevada had the lowest CSV (18.7 ± 6.5%). Hawaii had the highest health ranking and Mississippi had the lowest ranking in 2016. States with better health rankings, lower health uninsured rates, and higher health spending were significantly associated with higher CSVs (R ² = 0.418, P < 0.001; R ² = 0.352, P < 0.001; R ² = 0.142, P = 0.007, respectively). Conclusions: There are significant differences in lung cancer survival within the United States. Lung cancer survival by using CSV was strongly associated with state health disparities, and it can be an applicable measure to evaluate the state-level health disparities in the United States.

Cost-effectiveness of real-world administration of chemotherapy and add-on Viscum album L. therapy compared to chemotherapy in the treatment of stage IV NSCLC patients

Background

For stage IV lung cancer patients receiving add-on Viscum album L. (VA) treatment an improved overall survival was detected. Information regarding cost-effectiveness (CE) for comparisons between chemotherapy (CTx) and CTx plus additive VA in stage IV lung cancer treatment is limited. The present study assessed the costs and cost-effectiveness of CTx plus VA (V) compared to CTx alone (C) for stage IV non-small cell lung cancer (NSCLC) patients treatment in a hospital in Germany.

Methods

In the observational real-world data study, data from the Network Oncology clinical registry were utilized. Enrolled stage IV lung cancer patients received the respective therapy (C or V) in a certified German Cancer Center. Cost and cost-effectiveness analyses from the hospital’s perspective were investigated on the basis of overall survival (OS) and routine financial controlling data. In addition, the incremental cost-effectiveness ratio (ICER) was calculated. The primary result of the analysis was tested for robustness in a bootstrap-based sensitivity analysis.

Results

118 patients (C: n = 86, V: n = 32) were included in the analysis, mean age 63.8 years, the proportion of male patients was 55.1%. Adjusted hospital’s total mean costs for patients from the C and V group were €16,289, 95%CI: 13,834€-18,744€ (over an adjusted mean OS time of 13.4 months) and €17,992, 95%CI: 13,658–22,326 (over an adjusted mean OS time of 19.1 months), respectively. The costs per additional OS year gained (ICER) with the V-therapy compared to C therapy were €3,586.

Conclusion

The findings of the present study suggest that the combined use of chemotherapy and VA was clinically effective and comparably cost-effective to chemotherapy alone in our analysed patient sample from the hospital’s perspective. Further randomized and prospective cost-effectiveness studies are necessary to complement our findings.