Economic evaluation of programs or interventions in the management of rheumatoid arthritis: defining a consensus-based reference case.
Bibliographic record
Abstract
Improvement in the quality of economic evaluation could be documented as a consequence of international and national standardization efforts. One such effort is the recommendation that all economic evaluations in a given field produce findings in a standard format using a reference case. A reference case-based economic evaluation would adhere to specific settings with regard to outcomes, comparators, modeling techniques, and use of costs to facilitate comparisons among economic evaluations performed with the same objective. In the past, the Outcome Measures in Rheumatology Clinical Trials (OMERACT) consensus conference has successfully developed widely used, consensus-based outcome criteria for clinical improvement in rheumatoid arthritis (RA). Present efforts are being directed at the development of recommendations for the type and format of a reference case economic evaluation for newly developed disease modifying antirheumatic drugs (DMARD). This document discusses 13 important elements that experts considered to be relevant for the development of a reference case recommendation for economic evaluations in RA. We provide the rationale for each element and discuss how each element has been addressed in published economic evaluations of DMARD.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.361 | 0.489 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| Bibliometrics | 0.009 | 0.008 |
| Science and technology studies | 0.003 | 0.007 |
| Scholarly communication | 0.013 | 0.011 |
| Open science | 0.006 | 0.006 |
| Research integrity | 0.011 | 0.008 |
| Insufficient payload (model declined to judge) | 0.003 | 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 source (direct Gemma or distilled Codex), 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".