Abstract

OBJECTIVE: To simulate haemophilia A (HA) real-life management and compare the cost of different treatment strategies, both with plasma-derived and recombinant factor VIII (pdFVIII and rFVIII, respectively), from the perspective of the Italian NHS. METHODS: A discrete event (micro-)simulation (DES) model was developed to reproduce every possible HA patient clinical pathway: on-demand (OD) treatment of bleeding, continuous or discontinuous prophylaxis (PRO) with FVIII, inhibitors-tolerance-induction treatment (ITI), surgery in case of severe disability. Patient characteristics, treatment indications and disease evolution were modeled basing on data available in clinical literature in order to represent the actual state of art of HA management. In addition to the baseline scenario, reproducing current HA management, alternative strategies were simulated to explore the impact on the cost borne by the Italian NHS for these patients. Only differential direct sanitary costs were considered in the simulation, with a 3.5% discount rate. RESULTS: Baseline scenario results show difference between patients treated with pdFVIII and those treated with rFVIII: mean lifetime HA patient management cost was estimated at € 1,332,373 with pdFVIII treatment, compared with € 2,013,222 for rFVIII. The saving is due mainly to the lower acquisition cost of pdFVIII. Total medical costs are strongly and positively correlated with HA severity: cost per patient increases from € 86,269 (mild HA) to € 1,509,231 (severe HA) for patients treated with pdFVIII and from € 147,900 to € 2,621,540 in patients treated with rFVIII. All analyses conducted in the study lead to the conclusion that the use of pdFVIII is much less expensive than rFVIII, but therapeutically equivalent. CONCLUSION: Management of HA patients is complex and difficult to optimize; although involving a limited number of patients, lifetime management costs for the Italian NHS are extremely high. The main advantage of this model lies in the capability of estimating the economic impact of different strategic choices and economic/regulatory constraints.

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