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Methods: A Markov Monte Carlo simulation model was developed to assess the cost, survival, quality adjusted survival and cost effectiveness of the nebivolol compared with standard medical therapy over the patient's life time. Health states were defined as stable condition, cardiovascular hospitalisation events, death in hospital, sudden death and death due to other causes, based on monthly cycles. Patients characteristics, time to sudden death, time to hospitalisation with standard medical therapy, the hazard ratios with nebivolol and resource used data were derived from the SENIORS clinical trial. Utility scores for each NYHA class were derived from a large heart failure trial. The economic analysis was conducted from the UK health care perspective including costs of hospitalization, drug cost, cost of treatment for severe adverse effects and GP visit cost. We conducted a fully probabilistic sensitivity analysis for all input values to explore uncertainty derived from the model parameters. Costs and outcomes were discounted at 3.5% annually.
Results: The model predicts that the total cost per patient for Nebivolol group was $18,120 compared with $14,298 for standard medical treatment respectively. The mean life-years were 8.49 and 7.16 and QALYs were 5.69 and 4.80 for Nebivolol and medical standard treatment respectively. The probabilistic sensitivity analysis gave an incremental cost of $3,822 a QALYs score of 0.88 and a life year estimate of 1.32. This gives incremental cost-effectiveness ratios (ICERs) of $4,322 (95% CI $3,975 to $4,731) per QALY gained and $2,888 (95% CI $2,663 to $3,170) per life year gained.
Conclusions: This model based analysis indicates that Nebivolol is highly cost-effective, achieving an incremental cost effectiveness ratio well below a standard benchmark used for resource allocation decisions in elderly people with heart failure, when compared to standard medical therapy.
See more of Concurrent Abstracts D: Technology Assessment
See more of The 28th Annual Meeting of the Society for Medical Decision Making (October 15-18, 2006)