Toward Development of a Fibromyalgia Responder Index and Disease Activity Score: OMERACT Module Update
Bibliographic record
Abstract
Following development of the core domain set for fibromyalgia (FM) in Outcome Measures in Rheumatology Clinical Trials (OMERACT) meetings 7 to 9, the FM working group has progressed toward the development of an FM responder index and a disease activity score based on these domains, utilizing outcome indices of these domains from archived randomized clinical trials in FM. Possible clinical domains that could be included in a responder index and disease activity score include pain, fatigue, sleep disturbance, cognitive dysfunction, mood disturbance, tenderness, stiffness, and functional impairment. Outcome measures for these domains demonstrate good to adequate psychometric properties, although measures of cognitive dysfunction need to be further developed. The approach used in the development of responder indices and disease activity scores for rheumatoid arthritis and ankylosing spondylitis represents heuristic models for our work, but FM is challenging in that there is no clear algorithm of treatment that defines disease activity based on treatment decisions, nor are there objective markers that define thresholds of severity or response to treatment. The process of developing candidate dichotomous responder definitions and continuous quantitative disease activity measures is described, along with participant discussions from OMERACT 10. Final results of this work will be published in a separate report pending completion of analyses.
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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 | 0.047 | 0.065 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.004 |
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".