Cost-utility analysis of palliative care in patients with advanced cancer: a retrospective study

Abstract

Background Aging population and other factors have led to a rapid rise in cancer incidence in China. However, under the influence of traditional perception of diseases, deaths and economic factors, many patients who are unresponsive to radical treatment are still adherent to excessive and unnecessary treatment, which may lead to poor quality of life (QoL) and increase unnecessary medical burden. Aim Compare the difference of the quality of life and cost-utility value between patients who received palliative care (PC) and patients who were adherent to conventional anticancer treatment (CAT) and provides empirical evidence of clinical and economic value for hospital-based PC. Methods Chinese Quality of Life Questionnaire (CQLQ) Scale was used to collect advanced cancer patients’ QoL on admission and discharge days. Paired and independent samples’ statistical analysis were used to compare inter- and intra- QoL between PC and CAT group. Delphi and Analytic Hierarchy Process were used to weight QoL scores and converted the QoL to quality-adjusted life years (QALYs). Propensity Score Matching (PSM) for 1:1 was used to compare average hospitalization expenses between two groups. The expense per QALYs was used for Cost-Utility analysis between the two treatments. Results A total of 248 hospitalized patients diagnosed with metastatic disease at stage IV were recruited from West China Fourth Hospital between January 2018 and August 2018, including 128 patients receiving PC and 120 patients receiving CAT. Although both treatments had positive effects on improving QoL for patients, the QoL in the PC group were significantly higher than that in the CAT group (55.90 ± 18.80 vs 24.00 ± 8.60, t = 7.51, p < 0.05). The QALY (days) of pre- and post- treatment increased by 55.9 and 24.0 days in PC and CAT group respectively. Compared average hospitalization expense in 613 pairs of advanced cancer inpatients after PSM 1:1, the per capita expense of PC group was higher (13,743.5 ± 11,574.1 vs 11,689.0 ± 8876.8, t = 3.44, p < 0.05), while each unit of QALYs paid by PC group was only 50% of that paid by those receiving CAT. Conclusions PC played a positive role in improving the QoL for patients diagnosed with advanced cancer and alleviating economic burdens of both patient families and the society from the viewpoint of cost-utility. Our findings imply that PC should be recognized as a proactive care model in China that helps patients with some terminal diseases.

Changes in the treatment rate of patients newly diagnosed with stage IV cancer near the end of life from 2012 to 2017 in Korea

“…Moreover, a recent cost-utility analysis conducted in China suggested that palliative care improved the QoL at EoL and mitigated the economic burden for Chinese patients with advanced cancer [ 24 ]. Integrating the evidence from these studies, early HPC, as well as standard oncology care, should be suggested as a viable option for patients whose cancer is unlikely to be cured or successfully managed owing to its advantages.…”

“…Generally, the main needs of cancer patients at their EoL are multifactorial, ranging from psychiatric care to social support from clinicians and caregivers [8,9]. Moreover, even though aggressive treatment for patients with advanced cancer is relatively affordable under a single-payer healthcare system in the Republic of Korea compared to privatized healthcare systems elsewhere, there are limited data on recent trends in the treatment rate and its differences between sociodemographic and clinical subgroups [6,37].…”

Evaluation of Direct Medical Costs and Associated Factors Within the Last 30 days of Life of Hospitalized Cancer Patients

“…This promotes a better quality of life in end-of-life care for cancer patients in an advanced stage of disease and a reduction of costs related to the use of aggressive measures in end-of-life care. 29 Considering the possibilities of behavioral economics in health, Meeker et al, in 2016, evaluated, in a randomized controlled study, the ability of interventions based on behavioral economic principles to reduce the rate of antibiotic prescription not in accordance with clinical protocols for acute respiratory infections. They identified a reduction of inappropriate prescriptions, improving adherence to protocol.…”

Machine Learning to Allocate Palliative Care Consultations During Cancer Treatment

“…Early consultations with a palliative care (PC) specialist for patients with advanced cancer bring clinically meaningful improvements in symptom management, patient satisfaction, quality of life (QOL), and overall survival, and less aggressive end-of-life interventions, [1][2][3] without increasing costs. 4 ASCO and WHO recommend PC consultations for all patients shortly after a diagnosis of incurable cancer. 5,6 However, these recommendations far exceed available capacity.…”