title: Patient preferences for treatment of rheumatoid arthritis.
abstract: OBJECTIVE
  To elicit treatment preferences of patients with rheumatoid arthritis (RA) for disease modifying antirheumatic drugs (DMARDs) with varying risk profiles.
  
  
  METHODS
  Patient values for 16 DMARD characteristics were ascertained using published data about side effects, effectiveness, and cost. Patient preferences were determined by Adaptive Conjoint Analysis, an interactive computer program that predicts preferences by asking patients to make trade-offs between specific treatment characteristics. Simulations were run to derive preferences for four drugs: methotrexate, gold, leflunomide, and etanercept, under different risk-benefit scenarios. Infliximab was not included because it is given with methotrexate, and we did not include preferences for combination therapy. Based on each patient's expressed preferences, and the characteristics of the treatments available at the time of the study, the option that best fitted each patient's perspective was identified.
  
  
  RESULTS
  120 patients (mean age 70 years) were interviewed. For the base case scenario (which assumed the maximum benefits reported in the literature, a low probability of adverse effects, and low equal monthly "co-pays" (out of pocket costs)), 95% of the respondents preferred etanercept over the other treatment options. When all four options were described as being equally effective, 88% continued to prefer etanercept owing to its safer short term adverse effect profile. Increasing etanercept's co-pay to $30.00 decreased the percentage of patients preferring this option to 80%.
  
  
  CONCLUSIONS
  In this study, older patients with RA, when asked to consider trade-offs between specific risk and benefits, preferred etanercept over other treatment options. Preference for etanercept is explained by older patients' risk aversion for drug toxicity.
authors.affiliation: VA Connecticut Healthcare System, West Haven, CT 06516, USA. liana.fraenkel@yale.edu
authors.forename: L
authors.initials: L
authors.lastname: Fraenkel
authors.forename: S T
authors.initials: ST
authors.lastname: Bogardus
authors.forename: J
authors.initials: J
authors.lastname: Concato
authors.forename: D T
authors.initials: DT
authors.lastname: Felson
authors.forename: D R
authors.initials: DR
authors.lastname: Wittink
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D018501:Antirheumatic Agents / Q000009:adverse effects / Q000627:therapeutic use*; D001172:Arthritis, Rheumatoid / Q000188:drug therapy / Q000523:psychology*; D003198:Computer Simulation; D000068800:Etanercept; D005260:Female; D006801:Humans; D007074:Immunoglobulin G / Q000009:adverse effects / Q000627:therapeutic use*; D007555:Isoxazoles / Q000009:adverse effects / Q000627:therapeutic use; D000077339:Leflunomide; D008297:Male; D008727:Methotrexate / Q000009:adverse effects / Q000627:therapeutic use; D008875:Middle Aged; D050607:Organogold Compounds; D017060:Patient Satisfaction; D018124:Receptors, Tumor Necrosis Factor / Q000627:therapeutic use*; D012306:Risk
chemical_list: D018501:Antirheumatic Agents; D007074:Immunoglobulin G; D007555:Isoxazoles; D050607:Organogold Compounds; D018124:Receptors, Tumor Necrosis Factor; D000077339:Leflunomide; D000068800:Etanercept; D008727:Methotrexate