The cost-effectiveness of basiliximab induction in "old-to-old" kidney transplant programs: Bayesian estimation, simulation, and uncertainty analysis.
INTRODUCTION: Markov models are employed in economic analyses to evaluate all possible expectations in a dilemna. The introduction of a new clinical protocol (Basiliximab induction with calcineurin-sparing protocols) for a group of kidney transplant recipients receiving organs from marginal donors was validated with a Markov simulation model, demonstrating the usefulness of combining simulation with Bayesian estimation methods for analysis of cost-effectiveness data collected alongside a clinical trial. We sought to determine whether calcineurin-sparing protocols using anti-interleukin-2/antibody induction (Simulect) would show a beneficial effect on initial kidney function and reduce transplantation costs upon admission, clinical incidences, graft function, and complications during the first month after transplant. PATIENTS AND METHODS: A Markov Chain Monte Carlo (MCMC) was used to estimate a system of generalized linear models relating costs and outcomes to a kidney transplant process affected by treatment under alternative therapies. The Markov simulation model was established following three chains: a calcineurin-free regimen with Basiliximab induction (chain A); a calcineurin-sparing protocol with Basiliximab induction (chain B); and a conventional immunosuppressive regimen (chain C). The MCMC draws were used as parameters in simulations that yielded inferences about the relative cost-effectiveness of the novel therapy under a variety of scenarios. After designing the Markov chain and cohorts, 31 patients from the "old-to-old" program were assigned; eight to chain A; eight to chain B; and 15 to chain C. A year after transplantation a cost-benefit study was performed guided by the three branches of the Markov model. RESULTS: The Markov model showed a benefit of induction therapies in elderly patients. A cost-benefit model showed that after a year, there was a clear benefit from calcineurin-free plus Basiliximab induction therapies, with a slight benefit from calcineurin-sparing protocols. CONCLUSIONS: Markov models are extremely useful when introducing new clinical therapies. The approach allows flexibility in assessing treatment using various premises and quantifies the global effect of parametric uncertainty on a decision maker's confidence to adopt one therapy over another. In our transplant program, a cost-effective analysis of outcomes in old patients using the Markov model showed a clear benefit of calcineurin-sparing protocols with Basixilimab induction.