Meaningful Change Thresholds for Patient-Reported Outcomes Measurement Information System (PROMIS) Fatigue and Pain Interference Scores in Patients With Rheumatoid Arthritis
Bibliographic record
Abstract
OBJECTIVE: We estimated meaningful change thresholds (MCTs) for Patient-Reported Outcomes Measurement Information System (PROMIS) Fatigue and Pain Interference in rheumatoid arthritis (RA). METHODS: The responsiveness of several patient-reported outcomes (PROs) was assessed among 521 patients with RA in the Arthritis, Rheumatism, and Aging Medical Information Systems (ARAMIS) cohort. PROMIS Fatigue (7-item) and Pain Interference (6-item) short form instruments were administered at baseline, 6 months, and 12 months. Self-reported retrospective changes over the previous 6 months (a lot better/worse, a little better/worse, stayed the same) were obtained at 6 and 12 months' follow-up. We estimated MCTs using the mean change in PROMIS scores for patients who rated their change "a little better" or "a little worse." RESULTS: Baseline fatigue and pain interference scores were near normal (median 54 and 56, respectively). At 6 months, 7.9% of patients reported their fatigue was a little better compared to baseline (mean change [SD]: -2.6 [4.8]) and 22.8% a little worse (1.7 [5.6]). Pain was a little better for 11.5% of patients (-1.9 [6.1]) and a little worse for 24.2% of patients (0.6 [5.7]). At 12 months, results were similar. Thus, the MCT range was 1-2 points for both fatigue and pain interference. Correlations between change scores and retrospective ratings were low (0.13-0.29), indicating possible underestimation of MCT. CONCLUSION: The group-level MCT for PROMIS Fatigue and Pain Interference is roughly 2-3 points and corresponds to a small effect size, which is consistent with earlier work demonstrating an MCT of 2 points for PROMIS Physical Functioning.
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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 | 0.019 | 0.055 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".