In the Dapagliflozin and Prevention of Adverse Outcomes in Heart Failure (DAPA-HF) trial, dapagliflozin was shown to reduce cardiovascular mortality and hospitalizations due to heart failure while improving patient-reported health status. However, the cost-effectiveness of adding dapagliflozin therapy to standard of care (SOC) is unknown.
To estimate the cost-effectiveness of dapagliflozin therapy among patients with chronic heart failure with reduced ejection fraction (HFrEF).
This Markov cohort cost-effectiveness model used estimates of therapy effectiveness, transition probabilities, and utilities from the DAPA-HF trial and other published literature. Costs were derived from published sources. Patients with HFrEF included subgroups based on diabetes status and health status impairment due to heart failure. We compiled parameters from the literature including DAPA-HF, on which our model is based, and many other sources from December 2019 to February 27, 2021. We performed our analysis in February 2021.
Dapagliflozin or SOC.
Hospitalizations for heart failure, life-years, quality-adjusted life-years (QALYs), costs, and the cost per QALY gained (incremental cost-effectiveness ratio).
In the model, dapagliflozin therapy yielded a mean of 0.78 additional life-years and 0.46 additional QALYs compared with SOC at an incremental cost of $38 212, resulting in a cost per QALY gained of $83 650. The cost per QALY was similar for patients with or without diabetes and for patients with mild or moderate impairment of health status due to heart failure. The cost-effectiveness was most sensitive to estimates of the effect on mortality and duration of therapy effectiveness. If the cost of dapagliflozin decreased from $474 to $270 (43% decline), the cost per QALY gained would drop below $50 000.
These findings suggest that dapagliflozin provides intermediate value compared with SOC, based on American College of Cardiology/American Heart Association benchmarks. Additional data regarding the magnitude of mortality reduction would improve the precision of cost-effectiveness estimates.