Preferences for preventive treatments for rheumatoid arthritis: discrete choice survey in the UK, Germany and Romania - Simons, Gwenda; Veldwijk, Jorien; Disantostefano, Rachael L.; Englbrecht, Matthias; Radawski, Christine; Bywall, Karin Scholin; Mendez, Larissa Valor; Hauber, Brett; Raza, Karim; Falahee, Marie (Rheumatology, 2022)
Objective To quantify preferences for preventive therapies for rheumatoid arthritis (RA) across three countries. Methods A web-based survey including a discrete choice experiment was administered to adults recruited via survey panels in the UK, Germany and Romania. Participants were asked to assume they were experiencing arthralgia and had a 60% chance of developing RA in the next 2 years and completed 15 choices between no treatment and two hypothetical preventive treatments. Treatments were defined by six attributes (effectiveness, risks and frequency/route of administration) with varying levels. Participants also completed a choice task with fixed profiles reflecting subjective estimates of candidate preventive treatments. Latent class models (LCMs) were conducted and the relative importance of attributes, benefit-risk trade-offs and predicted treatment uptake was subsequently calculated. Results Completed surveys from 2959 participants were included in the analysis. Most participants preferred treatment over no treatment and valued treatment effectiveness to reduce risk more than other attributes. A five-class LCM best fitted the data. Country, perceived risk of RA, health literacy and numeracy predicted class membership probability. Overall, the maximum acceptable risk for a 40% reduction in the chance of getting RA (60% to 20%) was 21.7%, 19.1% and 2.2% for mild side effects, serious infection and serious side effects, respectively. Predicted uptake of profiles reflecting candidate prevention therapies differed across classes. Conclusion Effective preventive pharmacological treatments for RA were acceptable to most participants. The relative importance of treatment attributes and likely uptake of fixed treatment profiles were predicted by participant characteristics.
CRIS-Team WoS Importer:2022-09-16