Exploratory cost-effectiveness analysis of cardiac resynchronization therapy with systematic device optimization vs. standard (non-systematic) optimization: a multinational economic evaluation

Abstract

Background: Recent studies provide evidence of improved clinical benefits associated with cardiac resynchronization therapy (CRT) optimization. Our analysis explores the cost-effectiveness of systematically optimized (SO, 3 times a year) vs. non-systematically optimized (NSO, less than 3 times a year) CRT, whatever the echo optimization method used (manual or SonR® automatic). A longitudinal cohort model was developed to predict clinical and economic outcomes for SO vs. NSO strategies over 5 years. The analysis was performed from the payer perspective. Data from CLEAR study post-hoc analysis was used with 199 pts with CRT pacemaker (CRT-P). The main economic outcome measure was incremental cost-effectiveness (ICER) expressed as cost per Quality Adjusted Life Years (QALY) gained. To assess the impact of data uncertainty, a sensitivity analysis was performed. The model also predicts outcomes for the two optimization strategies for CRT-D therapy vs. optimal medical treatment (OPT).

Results: At 1 year, ICERs for SO CRT vs. NSO CRT-P range between <euro> 22,226 (Spain) and <euro> 26,977 (Italy). Therefore, on the basis of a Willingness-To-Pay of <euro>30,000 per QALY, the SO method develops into a cost effective strategy from 1 year, onwards. These favorable outcomes are supported by the sensitivity analysis. Systematic optimization of CRT-D might also improve the cost-effectiveness of this device therapy by 27 % to 30 % dependent on the country analyzed, at 5 years.

Conclusions: Our economic evaluation shows promising health economic benefits associated with SO CRT. These preliminary findings need further confirmation.

Fig. 1

Death rate with the value of the average between the actual rate and the upper confidence interval limit in the CLEAR study and CARE-HF study (patients >66 year-old), at 1 year

Fig. 2

One-way sensitivity analysis illustrating the impact of main model variables on the incremental cost-effectiveness ratio for the 5-year follow-up time horizon (healthcare payer perspective, Germany)

Fig. 3

Scatterplot illustrating incremental costs versus incremental benefits (QALYs) for a 1-year, 2-year, and 5-year follow-up time horizon (n = 1,000 simulations, healthcare payer perspective, Germany)

Fig. 4

Cost-effectiveness acceptability curve with results produced for a 1-year, 2-year, and 5-year follow-up time horizon (n = 1,000 simulations, healthcare payer perspective, Germany)