A Real-World Evidence Analysis of Associations Among Costs, Quality of Life, and Disease-Severity Indicators of Alzheimer’s Disease in Thailand

Abstract

Background: Although an increase in the burden of Alzheimer's disease (AD) is evident worldwide, knowledge of costs and health-related quality of life (HRQOL) associated with AD in low-and middle-income countries is still lacking.Objectives: This study aimed to collect real-world cost and HRQOL data, and investigate their associations with multiple disease-severity indicators among AD patients in Thailand.Methods: We recruited AD patients aged $60 years accompanied by their caregivers at a university-affiliated tertiary hospital. A one-time structured interview was conducted to collect disease-severity indicators, HRQOL, and caregiving information using standardized tools. The hospital's database was used to retrieve healthcare resource utilization occurred over 6 months preceding the interview date. Costs were annualized and stratified based on cognitive status. Generalized linear models were employed to evaluate determinants of costs and HRQOL.

Do Drug Accessibility and OOP Burden Affect Health-Related Quality of Life of Patients With Chronic Diseases? — EQ-5D-5L Evaluation Evidence From Five Districts in China

“…However, for patients with multimorbidity, the level of education is positively correlated with health effectiveness, indicating that patients with multiple chronic diseases need more knowledge of health management. There is ample evidence for the relationship between income and health-related quality of life (50,51). Our research further concludes that: In China, patients with a monthly income of <1,000 RMB would have lower HRQoL due to poor quality of life such as diet and living conditions.…”

Application of Discrete-Event Simulation in Health Technology Assessment: A Cost-Effectiveness Analysis of Alzheimer’s Disease Treatment Using Real-World Evidence in Thailand

“…10 Simulated individuals with unique demographic and disease characteristics were first generated by bootstrapping from a cohort of 148 Thai AD patients. 11 A description of this cohort was provided in Appendix 7 and Appendix Table 1 in Supplemental Materials found at https://doi.org/10.1016/j.jval.2020.01.010. A total of 5 identical copies of each patient were then created and allocated to different treatment options: (1) 10 mg of oral donepezil once daily, (2) 16 mg of oral galantamine twice daily, (3) transdermal rivastigmine twice daily, (4) 10 mg of oral memantine twice daily, or (5) no AD treatment.…”

“…01.010). 11 The data set captured information on patient age; sex; AD duration; Charlson Comorbidity Index; use of psychotherapeutic agents; MMSE and NPI scores; and caregiver age, sex, and relationship with the patient. These patients had a mean age of 80.1 (range, 60.8-93.5) years and 71.0% were women, representing the current AD population that received diagnosis and treatment, as appropriate, from specialists in Thailand.…”

“…Besides, our study modeled the predictive equation for DAD scores using patient-level data from a cross-sectional study conducted in Thailand. 11 A multivariable generalized linear model with Gaussian distribution and identity link after the modified Park's test 20 was employed to model the equation for DAD. All equations for disease progression are provided in Table 1, showing that the change in NPI scores was influenced by MMSE scores, whereas DAD scores were dependent on both MMSE and NPI scores.…”

“…Patients who discontinued their treatment were assumed to lose all treatment benefits gained from the previous treatment over the following 6 weeks. 22 In addition, the real-world observation of appointment for the next hospital visit among patients with AD in Thailand 11 was used to predict time to hospital visits for all patients in the simulation (see Appendix Table 6 in Supplemental Materials found at https://doi.org/10.1016/j.jval.2020.01.010).…”