Comparing the EQ-5D-5L utility index based on value sets of different countries: impact on the interpretation of clinical study results
Why this work is in the frame
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Bibliographic record
Abstract
OBJECTIVE: To compare the country-specific value sets of the EQ-5D-5L utility index and to evaluate the impact on the interpretation of clinical study results. Six country value sets from Canada, England, Japan, Korea, Netherlands and Uruguay were obtained from literature. In addition, ten crosswalk value sets were downloaded from the EuroQol.org website. RESULTS: For each of the 3125 possible health states the difference between the country with the highest index and the country with the lowest index was calculated. The median difference was 0.417 across the health states. When analyzing multinational clinical studies, country-specific value sets should be used to evaluate treatment effects. Additional country-specific analyses are needed.
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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 | 0.093 | 0.040 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it