Treatment preferences of patients with early rheumatoid arthritis: a discrete-choice experiment
Bibliographic record
Abstract
OBJECTIVE: To quantify the preferences of patients with early RA (ERA) with the benefits and harms of DMARDs. METHODS: We assessed patients' preferences using a discrete-choice experiment, an experimentally designed survey to measure trade-offs. Consecutive adult patients with ERA (<2 years since diagnosis) were presented 13 different sets of three treatment options described by eight attributes (clinical outcomes, risks and dosing regimens) and asked to choose one. From patients' responses we estimated the average importance of each attribute and explored preference heterogeneity through latent-class analysis. RESULTS: A total of 152 patients completed the survey (86% response rate): mean age 52 years, 63% female, disease duration 7.8 months. Treatment benefits (increasing the chance of a major symptom improvement and reducing the chance of serious joint damage) were most important. Of potential adverse events, a small risk of serious infections/possible increased risk of cancer was most important. Patients were willing to accept this risk for a 15% absolute increase in the chance of a major symptom improvement. Patients had an aversion to i.v. therapy, but were relatively indifferent to other dosing regimens. Through latent-class analysis, we identified two patient groups: 54% who were more risk averse, particularly to a possible risk of cancer/infection, and others who were highly benefit-driven. CONCLUSION: 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.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".