Early economic evaluation of a hypothetical perfect test for predicting the effectiveness of implantable pacemaker-defibrillator devices (CRT-D) in patients with heart failure

Objectives: Cardiac resynchronization therapy (CRT) either via a pacing device (CRT-P) or a pacemaker-defibrillator device (CRT-D) is considered an effective treatment for patients with congestive heart failure (CHF) and disturbances in heart rhythm (arrhythmias) having New York Heart Association (NYHA) class II, III and IV symptoms. However, due to the large numbers of patients, which do not get additional benefits from CRT-D, and also due to large costs of implementation and follow-up this may not always be the most cost-effective alternative. In fact, economic evaluations have shown that incremental cost-effectiveness ratios (ICERs) of CRT-D may be substantially higher than for comparators. A recent study demonstrated that certain biomarkers may in fact reflect the increased susceptibility to SCD in patients with HF and this may further contribute to increase cost-effectiveness of the CRT-D interventions. The objective of this study was to explore the cost-effectiveness of a hypothetical perfect biomarker for risk assessment and subsequent treatment decision in implanting CRT-Ds in heart failure patients who comply with the current clinical guidelines and assess the societal value (headroom) of such test. Methods: The study uses a decision analytical model. Results: The use of a hypothetical perfect biomarker for implanting CRT-Ds in heart failure patients is a cost-effective healthcare intervention. The headroom (societal willingness to pay multiplied by incremental quality-adjusted life years) available for the hypothetical perfect biomarker ranged from € 1,530 to € 6,120 depending on the willingness to pay threshold. Conclusions: The use of a hypothetical perfect biomarker for implanting CRT-D is cost effective. Substantial cost can be saved by a better identification of patients with high-risk for SCD and for whom implantation of CRT-Ds reduces risks of death. However, further research of risk stratifying biomarkers test accuracy is needed to support and strengthen the results of this modeling study