Societal preferences for rheumatoid arthritis treatments: evidence from a discrete choice experiment
Bibliographic record
Abstract
OBJECTIVE: There is a concern that cost-effectiveness analysis using quality-adjusted life years does not capture all valuable benefits of treatments. The objective of this study was to determine the value society places on aspects of RA treatment to inform policymaking. METHODS: A discrete choice experiment was administered to a representative sample of the Canadian general population. The discrete choice experiment, developed using focus groups, had seven attributes (route and frequency of administration, chance of benefit, chance of serious and minor side effects, confidence in evidence and life expectancy). A conditional logit regression model was used to estimate the significance and relative importance of attributes in influencing preferences on the quality-adjusted life years scale. RESULTS: Responses from 733 respondents who provided rational responses were analysed. Six attribute levels within four attributes significantly influenced preferences for treatments: a willingness to trade a year of life expectancy over a 10-year period to increase the probability of benefiting from treatment, or two-thirds of a year to reduce minor or serious side effects to the lowest level or improve the confidence in benefit/side-effect estimates. There was also some evidence of a preference for oral drug delivery, though a subgroup analysis suggested this preference was restricted to injection-naive respondents. CONCLUSION: Our results suggest society values the degree of confidence in the estimates of risks and benefits of RA treatments and the route of administration, as well as benefits and side effects. This study provides important evidence to policymakers determining the cost-effectiveness of treatments in arthritis.
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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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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".