RESUMEN
Objectives: The aim of this study was to investigate out-of-pocket (OOP) expenditures, indirect costs, and health-related quality of life (HRQoL) associated with the central nervous system (CNS) tumors in Thailand. Materials and Methods: A prospective study of CNS tumor patients who underwent first tumor resection at a tertiary care institution in Thailand was conducted. Patients were interviewed during hospitalization for undergoing first surgery. Within 6 months, they were interviewed once more if the disease continued to progress. Costs collected from a patient perspective and converted to 2019 US dollars. For dealing with these skewed data, a generalized linear model was used to investigate the effects of disease severity (malignancy, progressive disease, Karnofsky performance status score, and histology) and other factors on costs (OOP, informal care, productivity loss, and total costs). P < 0.05 was considered statistical significant for all analysis. Results: Among a total of 123 intracranial CNS tumor patients, there were 83 and 40 patients classified into benign and malignant, respectively. In the first brain surgery, there was no statistical difference in HRQoL between patients with benign and malignant tumors (P = 0.072). However, patients with progressive disease had lower HRQoL mean scores at pre-operative and progressive disease periods were 0.711 (95% confidence interval [CI]: 0.662-0.760) and 0.261 (95% CI: 0.144-0.378), respectively. Indirect expenditures were the primary cost driver, accounting for 73.81% of annual total costs. The total annual costs accounted for 59.81% of the reported patient's income in malignant tumor patients. The progressive disease was the only factor that was significantly increases in all sorts of costs, including the OOP (P = 0.001), the indirect costs (P = 0.013), and the total annual costs (P = 0.001). Conclusion: Although there was no statistical difference in HRQoL and costs between patients with benign and malignant tumor, the total costs accounted for more than half of the reported income in malignant tumor patients. The primary cause of significant increases in all costs categories was disease progression.
RESUMEN
Background Traumatic brain injury (TBI) commonly causes death and disability that can result in productivity loss and economic burden. The health-related quality of life (HRQoL) has been measured in patients suffering from TBI, both in clinical and socioeconomic perspectives. The study aimed to assess the HRQoL in patients following TBI using the European quality of life measure-5 domain-5 level (EQ-5D-5L) questionnaire and develop models for predicting the EQ-5D-5L index score in patients with TBI. Method A cross-sectional study was performed with 193 TBI patients who had completed the EQ-5D-5L questionnaire. The clinical characteristics, Glasgow coma scale (GCS) score, treatment, and Glasgow outcome scale (GOS) were collected. The total data was divided into training data (80%) and testing data (20%); hence, the factors affecting the EQ-5D-5L index scores were used to develop the predictive model with linear and nonlinear regression. The performances of the predictive models were estimated with the adjusted coefficient of determination (R 2 ) and the root mean square error (RMSE). Results A good recovery was found at 96.4%, while 2.1% displayed an unfavorable outcome. Moreover, the mean EQ-5D-5L index scores were 0.91558 (standard deviation [SD] 1.09639). GCS score, pupillary light reflex, surgery, and GOS score significantly correlated with the HRQoL scores. The multiple linear regression model had a high adjusted R 2 of 0.6971 and a low RMSE of 0.06701, while the polynomial regression developed a nonlinear model that had the highest adjusted R 2 of 0.6843 and the lowest RMSE of 0.06748. Conclusions A strong positive correlation between the physician-based outcome as GOS and HRQoL was observed. Furthermore, both the linear and nonlinear regression models were acceptable approaches to predict the HRQoL of patients after TBI. There would be limitations for estimating the HRQoL in unconscious or intubated patients. The HRQoL obtained from the predictive models would be an alternative method to resolve this problem.
