Objective. To develop a simulation model for analysis of the cost-effective
ness 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 o
n Health Assessment Questionnaire (HAQ) scores. Costs were calculated from
data on resource utilization and patients' work capacity. Utilities (prefer
ence weights for health states) were assessed using the EQ-5D (EuroQol) que
stionnaire. Hypothetical treatment interventions were simulated to illustra
te the model.
Results. The cohort distribution among the 6 Markov states clearly showed t
he progression of the disease over 5 years of followup. Costs increased wit
h increasing severity of the Markov states, and total costs over 5 years we
re 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 functio
nal class II.
Conclusion. The Markov model was able to assess disease progression and cos
ts 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.