OBJECTIVE: To determine the cost effectiveness of treatment strategies for rheumatoid arthritis patients satisfying the indication for tumor necrosis factor (TNF)-blocking treatment. METHODS: A Markov model study was performed. The following treatment strategies were considered: 1) usual treatment; 2) treatment with leflunomide, in the case of nonresponse after 3 months, switch to usual treatment; 3) TNF-blocking treatment, in the case of nonresponse after 3 months, switch to usual treatment; 4) treatment with leflunomide, in the case of nonresponse, switch to TNF-blocking treatment, in the case of nonresponse to TNF-blocking treatment, switch to usual treatment; 5) TNF-blocking treatment, in the case of nonresponse, switch to leflunomide treatment, in the case of nonresponse to leflunomide, switch to usual treatment. Expected patient-years in the different Markov states, costs, and quality-adjusted life years (QALYs) were compared between the treatment strategies; incremental cost-effectiveness ratios (ICERs) were calculated. RESULTS: Over the 5-year period, the expected effect on disease activity and QALYs was better for treatment strategies that included TNF-blocking treatment than for the other treatment strategies. The greater effectiveness of these treatment strategies reduced medical and nonmedical costs compared with usual treatment by about 16% and 33%, respectively, omitting the costs of medication. When the costs of medication were included, the costs of strategies that started with TNF-blocking treatment were higher than those of the other treatment strategies. Treatment strategy 4 had the most favorable ICER of the treatment strategies that included TNF-blocking treatment: 163,556/QALY compared with usual treatment. CONCLUSION: Among strategies that include TNF-blocking agents, one starting with leflunomide and, in the case of nonresponse, switching to TNF-blocking treatment probably results in the most favorable ratio between incremental costs and effects.
OBJECTIVE: To determine the cost effectiveness of treatment strategies for rheumatoid arthritispatients satisfying the indication for tumor necrosis factor (TNF)-blocking treatment. METHODS: A Markov model study was performed. The following treatment strategies were considered: 1) usual treatment; 2) treatment with leflunomide, in the case of nonresponse after 3 months, switch to usual treatment; 3) TNF-blocking treatment, in the case of nonresponse after 3 months, switch to usual treatment; 4) treatment with leflunomide, in the case of nonresponse, switch to TNF-blocking treatment, in the case of nonresponse to TNF-blocking treatment, switch to usual treatment; 5) TNF-blocking treatment, in the case of nonresponse, switch to leflunomide treatment, in the case of nonresponse to leflunomide, switch to usual treatment. Expected patient-years in the different Markov states, costs, and quality-adjusted life years (QALYs) were compared between the treatment strategies; incremental cost-effectiveness ratios (ICERs) were calculated. RESULTS: Over the 5-year period, the expected effect on disease activity and QALYs was better for treatment strategies that included TNF-blocking treatment than for the other treatment strategies. The greater effectiveness of these treatment strategies reduced medical and nonmedical costs compared with usual treatment by about 16% and 33%, respectively, omitting the costs of medication. When the costs of medication were included, the costs of strategies that started with TNF-blocking treatment were higher than those of the other treatment strategies. Treatment strategy 4 had the most favorable ICER of the treatment strategies that included TNF-blocking treatment: 163,556/QALY compared with usual treatment. CONCLUSION: Among strategies that include TNF-blocking agents, one starting with leflunomide and, in the case of nonresponse, switching to TNF-blocking treatment probably results in the most favorable ratio between incremental costs and effects.
Authors: Christine M Nguyen; Mark Bounthavong; Margaret A S Mendes; Melissa L D Christopher; Josephine N Tran; Rashid Kazerooni; Anthony P Morreale Journal: Pharmacoeconomics Date: 2012-07-01 Impact factor: 4.981