ArticleRheumatology (Oxford, England)2023
Preferences for preventive treatments for rheumatoid arthritis: discrete choice survey in the UK, Germany and Romania.
Article in Rheumatology (Oxford, England), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
12 citing papers in PubMed, 1 synthesis or guideline pooled it.
- The Evolving Landscape of Discrete Choice Experiments in Health Economics: A Systematic Review.PharmacoEconomics · 2025Pooled it
- Severity or Incidence: Labeling Side-Effect Attributes in Discrete Choice Experiments.The patient · 2026Article
- Patient and First-Degree Relatives Perceptions About Prediction and Prevention of Inflammatory Bowel Disease-A Multinational Survey.United European gastroenterology journal · 2025Article
- What Next for the Science of Patient Preference? Interoperability, Standardization, and Transferability.The patient · 2025Review
- Prevention of Rheumatoid Arthritis in At-Risk Individuals: Current Status and Future Prospects.Drugs · 2024Review
- Research Priorities to Increase Confidence in and Acceptance of Health Preference Research: What Questions Should be Prioritized Now?The patient · 2024Article
- Can the General Public Be a Proxy for an "At-Risk" Group in a Patient Preference Study? A Disease Prevention Example in Rheumatoid Arthritis.Medical decision making : an international journal of the Society for Medical Decision Making · 2024Article
- 'What is my risk really?': a qualitative exploration of preventive interventions among individuals at risk of rheumatoid arthritis.Rheumatology advances in practice · 2024Article
- Rheumatoid arthritis prevention in arthralgia: fantasy or reality?Nature reviews. Rheumatology · 2023Review
- Maximum Acceptable Risk Estimation Based on a Discrete Choice Experiment and a Probabilistic Threshold Technique.The patient · 2023Article
- How can patient preferences be used and communicated in the regulatory evaluation of medicinal products? Findings and recommendations from IMI PREFER and call to action.Frontiers in pharmacology · 2023Article
- Article
Corrections and comments
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Authors and funding
10 authors.
Funding
Abstract
objectiveTo quantify preferences for preventive therapies for rheumatoid arthritis (RA) across three countries.
methodsA 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.
resultsCompleted 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.
conclusionEffective 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.
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