Fatigue numeric rating scale validity, discrimination and responder definition in patients with psoriatic arthritis
Bibliographic record
Abstract
OBJECTIVES: This study assessed the psychometric properties of the fatigue numeric rating scale (NRS) and sought to establish values for clinically meaningful change (responder definition). METHODS: Using disease-specific clinician-reported and patient-reported data from two randomised clinical trials of patients with psoriatic arthritis (PsA), the fatigue NRS was evaluated for test-retest reliability, construct validity and responsiveness. A responder definition was also explored using anchor-based and distribution-based methods. RESULTS: Test-retest reliability analyses supported the reproducibility of the fatigue NRS in patients with PsA (intraclass correlation coefficient=0.829). Mean (SD) values at baseline and week 2 were 5.7 (2.2) and 5.7 (2.4), respectively. Supporting construct validity of the fatigue NRS, moderate-to-large correlations with other assessments measuring similar concepts as measured by Sackett's conventions were demonstrated. Fatigue severity was reduced when the underlying disease activity was improved and reductions remained consistent at week 12 and 24. A 3-point improvement was identified as being optimal for demonstrating a level of clinically meaningful improvement in fatigue NRS after 12-24 weeks of treatment. CONCLUSIONS: Fatigue NRS is a valid and responsive patient-reported outcome instrument for use in patients with PsA. The established psychometric properties from this study support the use of fatigue NRS in clinical trials and in routine clinical practice. Robust validation of reliability for use in routine clinical practice in treating patients with active PsA in less active disease states and other more diverse ethnic groups is needed.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.040 | 0.105 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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".