Validation of the Functional Assessment of Chronic Illness Therapy-Fatigue Scale in Patients with Moderately to Severely Active Systemic Lupus Erythematosus, Participating in a Clinical Trial
Bibliographic record
Abstract
OBJECTIVE: Fatigue is a common symptom of systemic lupus erythematosus (SLE). Our objective was to validate the 13-item Functional Assessment of Chronic Illness Therapy (FACIT)-Fatigue scale in patients with SLE. METHODS: The FACIT-Fatigue, Medical Outcomes Study Short-Form-36 (SF-36) questionnaire, Brief Pain Inventory (BPI), and Patient Global Assessment Visual Analog Scale (Patient-GA) were completed at baseline and at Weeks 12, 24, and 52 by patients with moderately to severely active extrarenal SLE. The patients were participating in a rituximab clinical trial. The British Isles Lupus Assessment Group (BILAG) disease activity index and the Physician Global Assessment Visual Analog Scale (Physician-GA) were completed by physicians at the same visits. RESULTS: At baseline, 254 patients completed the FACIT-Fatigue scale. Cronbach's α was > 0.95 at all visits. In cross-sectional analyses, FACIT-Fatigue scores differentiated between groups defined by BILAG General domain ratings. FACIT-Fatigue had moderate-high correlations (r = 0.5-0.8) with SF-36, BPI, and Patient-GA, but poor correlations with BILAG total score and Physician-GA (r = 0.1-0.3). At Weeks 12, 24, and 52, mean FACIT-Fatigue scale improvement was higher in patients who improved versus those who remained unchanged on the BILAG General domain. FACIT-Fatigue scale scores remained stable for patients with worsened BILAG General domain ratings compared to baseline. Distribution and anchor-based estimates suggested a minimally important difference (MID) range of 3-6 points. CONCLUSION: The FACIT-Fatigue scale is a valid and responsive measure of fatigue in patients with SLE. MID in this SLE sample is similar to that derived previously in other populations. Since few patients experienced worsening BILAG General and Musculoskeletal domains in this study, further research is warranted to evaluate the responsiveness of FACIT-Fatigue to worsening of these domains.
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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 | 0.022 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".