Mechanism-Based Approach to the Economic Evaluation of Pharmaceuticals: Pharmacokinetic/Pharmacodynamic/Pharmacoeconomic Analysis of Rituximab for Follicular Lymphoma
Background and Objectives:Background and Objectives: Economic value is an important consideration during all phases of the drug development process. We previously published an article in PharmacoEconomics in which we described a mechanism-based economic modelling approach that incorporates data obtained during phase II clinical studies on the relationships between dose, exposure and response. We now describe case studies of rituximab for the treatment of follicular non-Hodgkin's lymphoma based on this methodology. Abstract: Methods:Methods: We utilized a population pharmacokinetic and pharmacodynamic model linking serum rituximab concentration to progression-free survival, to simulate the effectiveness of rituximab in various clinical contexts. These served as inputs to economic models of follicular lymphoma, based on National Institute for Health and Clinical Excellence (NICE) appraisals, to assess the cost effectiveness of rituximab. Our results were compared with trial-based estimates from the NICE appraisals. In a further analysis, we simulated the results of an ongoing trial to generate predictions of cost effectiveness. Abstract: Results:Results: Our analyses suggest an acceptable degree of concordance between simulation- and trial-based estimates of cost effectiveness. For first-line and maintenance therapy, deviations of £2099 and £1355 per QALY, respectively, from trial-based incremental cost-effectiveness ratio estimates of £8290 and £7721 per QALY gained would not affect reimbursement decisions. The probability of rituximab-containing regimens being cost effective at £20 000 and £30 000 per QALY thresholds was 1 for both first-line and maintenance therapy in both simulated and trial-based analyses. Abstract: Conclusions:Conclusions: Our analyses demonstrate the feasibility of mechanism-based economic analyses, which may have applications during drug development to the following: (i) directing future research based on the cost of reducing uncertainty; (ii) assessing subgroups, dosing schedules and protocol deviations; and (iii) informing strategic research and development and pricing decisions.
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