Background/aims: Few studies have modeled individual Neuropsychiatric Inventory (NPI) symptom scores for Alzheimer disease (AD) patients and assessed the value of therapeutic interventions that can potentially impact them. The main objective of this study was to evaluate the impact of new AD symptomatic treatments on relevant health economic outcomes via their potential effects on cognition and neuropsychiatric symptoms such as depression, irritability, anxiety, and sleep disorder.
Methods: We enhanced the previously published AHEAD model (Assessment of Health Economics in Alzheimer's Disease) by including new variables and functional relations to capture the NPI's individual neuropsychiatric symptoms in addition to the total NPI score. This update allowed us to study the longitudinal effect of improvements in specific NPI subscale scores and the downstream impact on outcomes such as psychiatric medication use, survival, and institutional placement.
Results: The model base-case results showed that a hypothetical treatment with symptomatic effects on anxiety, depression, and irritability NPI subscales was not cost-effective; however, the treatment's cost-effectiveness was improved once a direct link between NPI subscales and mortality was explored or under relatively stronger treatment effects.
Conclusion: Treatments that influence specific symptoms within the overall NPI have the potential to improve patient outcomes in a cost-effective way. This model is a useful tool for evaluating target product profiles of drugs with effect on NPI symptoms in early stages of development.
Keywords: Alzheimer disease; Economic analysis; Institutionalization; Modeling; Neuropsychiatric Inventory; Psychiatric medication; Symptomatic treatment.