Abstract / Summary
Background: Depression is a leading cause of disability worldwide, associated with reduced quality-of-life and significant economic costs. While NICE has recommended first-line pharmacological, psychological and physical interventions for adults with less severe (subthreshold/mild) and more severe (moderate/severe) depression within a shared decision-making framework (NICE 2022), comparative cost-effectiveness has not been established from Irish or Ukrainian perspectives, two countries with different healthcare systems that currently lack national cost-effectiveness evidence. Aim To estimate the comparative cost-effectiveness of first-line depression treatments for adults with less severe and more severe depression from Irish and Ukrainian perspectives, following NICE treatment recommendations. Methods A cost-effectiveness analysis comparing pharmacological, psychological and physical interventions for less severe and more severe depression will be conducted from Irish and Ukrainian perspectives, following CHEERS guidelines, using clinical effectiveness inputs from the network meta-analysis (NMA) underpinning NICE NG222. Two independent models will be developed, one per severity stratum, each parameterised with population-specific inputs, consistent with NICE methods. In Phase 1 (primary outcome, 8–12 weeks), NMA standardised mean differences will be converted to numbers needed to treat (NNT) and combined with activity-based micro-costing to calculate incremental cost-effectiveness ratios as cost per additional patient in remission versus treatment as usual (less severe) or pill placebo (more severe depression). Depression-free days (DFDs) will be reported as a secondary outcome. In Phase 2 (secondary outcome, 2 years), a decision tree linked to a three-state Markov model (remission, depressive episode, death) will estimate cost per quality-adjusted life year (QALY) gained. Phase 2 primary findings will be presented for Ireland, with exploratory analysis for Ukraine. DFDs will be estimated from modelled time in remission. Uncertainty will be characterised through Probabilistic Sensitivity Analysis. Results and expected impact Results will provide policy-relevant economic evidence on first-line depression treatments across two distinct European healthcare systems, supporting evidence-based resource allocation.