Use of new oral anticoagulants (apixaban, dabigatran and rivaroxaban) for atrial fibrillation is increasing rapidly. The objective of this analysis was to investigate whether or not elimination of decision uncertainty related to the new oral anticoagulants for atrial fibrillation would be cost-effective.
Method:
We developed a decision analytic model, designed as a probabilistic Markov model containing more than 200 different probability distributions and eight health states. Epidemiological input data was gathered from registries. Data on Health Related Quality of Life were based on published EQ-5D data and costs were based on national tariffs.
Efficacy data included the three major randomized controlled trials comparing each of the new oral anticoagulants (apixaban, dabigatran and rivaroxaban) with warfarin. Current efficacy estimates indicate that the new anticoagulants are efficacious on some, but not all, outcomes compared to warfarin. However, no direct evidence comparing any of these new anticoagulants with each other is yet available. To explore the value of reducing decision uncertainty, we conducted expected value of perfect information on parameters (EVPPI) for parameters and groups of parameters. We focused particularly on efficacy, in order to investigate whether new RCT’s with direct comparison on the new oral anticoagulants is worth conducting.
Result:
Expected value of perfect information analyses on groups of parameters (EVPPI) for the group of efficacy parameters was not higher than EVPPI for the other groups of parameters (QALYs, costs, epidemiological data). EVPPI for efficacy data was $ 7 (medium risk patients) and $ 1,300 (high risk patients) per patient, given an assumed threshold value of $100,000 per QALY gained.
Conclusion:
There is added value in conducting more research on the efficacy of new oral anticoagulants for high risk patients. Hence, new randomized controlled trial(s) comparing all of the new oral anticoagulants would probably decrease decision uncertainty, at least for high risk patients. However, better data on QALYs and epidemiological data would have even higher potential for reducing decision uncertainty.