A Multicenter Nominal Group Study to Rank Outcomes Important to Patients, and Their Representation in Existing Composite Outcome Measures for Psoriatic Arthritis
Bibliographic record
Abstract
OBJECTIVE: To rank outcomes identified as important to patients with psoriatic arthritis (PsA) and examine their representation in existing composite measures. METHODS: Seven nominal group technique (NGT) meetings took place at 4 hospital sites. Two sorting rounds were conducted to generate a shortlist of outcomes followed by a group discussion and final ranking. In the final ranking round, patients were given 15 points each and asked to rank their top 5 outcomes from the shortlist. The totals were summed across the 7 NGT groups and were presented as a percentage of the maximum possible priority score. RESULTS: Thirty-one patients took part: 16 men and 15 women; the mean age was 54 years (range 24-77; SD 12.2), the mean disease duration was 10.3 years (range 1-40; SD 9.2), and mean Health Assessment Questionnaire was 1.15 (range 0-2.63; SD 0.7). The highest-ranked outcomes that patients wished to see from treatment were pain with 93 points (20.0%), fatigue 62 (13.3%), physical fitness 33 (7.1%), halting/slowing damage 32 (6.9%), and quality of life/well-being 29 (6.2%). Reviewing existing composite measures for PsA demonstrated that no single measure adequately identifies all these outcomes. CONCLUSION: Pain and fatigue were ranked as the outcomes most important to patients receiving treatment for PsA and are not well represented within existing composite measures. Future work will focus on validating composite measures modified to identify outcomes important to patients.
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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 | 0.027 | 0.048 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".