Treatment preferences of patients with early rheumatoid arthritis: a discrete-choice experiment

Abstract

On average, patients with ERA were risk tolerant, but important differences in preferences were identified. In particular, a subgroup of patients may prefer to avoid treatments with a possible increased risk of cancer/infection if other effective options are available.

A Bayesian model that jointly considers comparative effectiveness research and patients’ preferences may help inform GRADE recommendations: an application to rheumatoid arthritis treatment recommendations

“…Our study has limitations. Patients' preferences were derived from a relatively small sample of patients (n 5 152) and preferences were not measured at the time of the treatment decision [13]. A network meta-analysis requires certain assumptions that may not be valid, but the same approach could be applied to any evidence summary, including a single trial or traditional meta-analysis [29].…”

“…Patients' preferences were derived from a DCE, which we conducted with a sample of 152 adult patients with early RA (!2 years since diagnosis) [13]. For this study, we reanalyzed the DCE using a hierarchical Bayesian model, which has the advantage of allowing the modeling of individual patients' preferences.…”

“…These attributes included the outcomes from the NMA, as well as other important considerations that differed between the treatment options (dosing, rare risks). By analyzing patients' responses, we found that, on average, patients were risk tolerant [13]. Simply considering average preferences, however, ignores differences that may exist between patients.…”

“…In a separate study, we have recently measured patients' preferences for these trade-offs using a discrete-choice experiment (DCE) [13]. In this study, adult patients with early rheumatoid arthritis (ERA; !2 years disease duration) completed 13 different choice tasks where they chose between one of three different hypothetical treatment options that differed in terms of their attributes.…”

What do Australian patients with inflammatory arthritis value in treatment? A discrete choice experiment

“…Since then, they have been extended through theory and modelling and are frequently used to understand preferences [6][7][8]. DCE are commonly used in experiments assessing patient preferences for different treatments and have been used in several therapeutic areas including arthritis [5,[9][10][11][12][13][14][15]. Using data from the DCE component, a restricted latent class model (LCM) can be estimated [16].…”