Abstract

Objectives

Decision-analytic models for Alzheimer’s disease (AD) have been advanced to a discrete-event simulation (DES), in which individual-level modeling of disease progression across continuous severity spectra become feasible. This study aimed to apply DES to perform cost-effectiveness analysis of AD treatment in Thailand.

Methods

A data set of Thai AD patients, representing unique demographic and clinical characteristics, was bootstrapped to generate a baseline cohort of 50 000 patients. Each patient was cloned and assigned to donepezil, galantamine, rivastigmine, memantine, or no treatment. Correlated changes in cognitive and behavioral status over time were developed using patient-level data. Treatment effects were obtained from the most recent network meta-analysis. Treatment persistence; mortality; and predictive equations for functional status, costs (Thai baht in 2017), and quality-adjusted life-year (QALY) were derived from country-specific real-world data.

Results

From a societal perspective, only the prescription of donepezil to AD patients with all disease-severity levels was found to be cost-effective (incremental cost-effectiveness ratio): 138 524 Thai baht/QALY ($4062/QALY)]. Regardless of whether the treatment-stopping rule when the mini-mental state examination score 10 was introduced, providing early treatment with donepezil to mild AD patients further reduced the incremental cost-effectiveness ratio. Extensive sensitivity analyses indicated robust simulation findings.

Conclusions

Discrete-event simulation greatly enhances the real-world representativeness of decision-analytic models for AD. Donepezil is the most cost-effective treatment option for AD in Thailand and is worth being considered for universal financial coverage. Application of DES in heath technology assessment should be encouraged, especially when the validity of the model is questionable with classical modeling methods.