OBJECTIVE: To develop a simulation model for analysis of the cost-effectiveness of treatments that affect the progression of rheumatoid arthritis (RA). METHODS: The Markov model was developed on the basis of a Swedish cohort of 116 patients with early RA who were followed up for 5 years. The majority of patients had American College of Rheumatology (ACR) functional class II disease, and Markov states indicating disease severity were defined based on Health Assessment Questionnaire (HAQ) scores. Costs were calculated from data on resource utilization and patients' work capacity. Utilities (preference weights for health states) were assessed using the EQ-5D (EuroQol) questionnaire. Hypothetical treatment interventions were simulated to illustrate the model. RESULTS: The cohort distribution among the 6 Markov states clearly showed the progression of the disease over 5 years of followup. Costs increased with increasing severity of the Markov states, and total costs over 5 years were higher for patients who were in more severe Markov states at diagnosis. Utilities correlated well with the Markov states, and the EQ-5D was able to discriminate between patients with different HAQ scores within ACR functional class II. CONCLUSION: The Markov model was able to assess disease progression and costs in RA. The model can therefore be a useful tool in calculating the cost-effectiveness of different interventions aimed at changing the progression of the disease.
OBJECTIVE: To develop a simulation model for analysis of the cost-effectiveness of treatments that affect the progression of rheumatoid arthritis (RA). METHODS: The Markov model was developed on the basis of a Swedish cohort of 116 patients with early RA who were followed up for 5 years. The majority of patients had American College of Rheumatology (ACR) functional class II disease, and Markov states indicating disease severity were defined based on Health Assessment Questionnaire (HAQ) scores. Costs were calculated from data on resource utilization and patients' work capacity. Utilities (preference weights for health states) were assessed using the EQ-5D (EuroQol) questionnaire. Hypothetical treatment interventions were simulated to illustrate the model. RESULTS: The cohort distribution among the 6 Markov states clearly showed the progression of the disease over 5 years of followup. Costs increased with increasing severity of the Markov states, and total costs over 5 years were higher for patients who were in more severe Markov states at diagnosis. Utilities correlated well with the Markov states, and the EQ-5D was able to discriminate between patients with different HAQ scores within ACR functional class II. CONCLUSION: The Markov model was able to assess disease progression and costs in RA. The model can therefore be a useful tool in calculating the cost-effectiveness of different interventions aimed at changing the progression of the disease.
Authors: Peter K Schädlich; Henning Zeidler; Angela Zink; Erika Gromnica-Ihle; Matthias Schneider; Christoph Straub; Josef G Brecht; Eduard Huppertz Journal: Pharmacoeconomics Date: 2005 Impact factor: 4.981