Psychometric validation of the Psoriasis Symptom Scale, Functional Assessment of Chronic Illness Therapy–Fatigue and <scp>pain‐Visual</scp> Analogue Scale in patients with generalized pustular psoriasis
Bibliographic record
Abstract
BACKGROUND: Generalized pustular psoriasis (GPP) is a rare, chronic, inflammatory skin disease associated with considerable patient burden. The Psoriasis Symptom Scale (PSS), Functional Assessment of Chronic Illness Therapy-Fatigue (FACIT-Fatigue) and pain-Visual Analogue Scale (pain-VAS) are patient-reported outcomes (PROs) that have not yet been validated in patients with GPP. OBJECTIVES: To evaluate the psychometric properties of the PSS, FACIT-Fatigue and pain-VAS using data from Effisayil 1, a randomised trial of spesolimab in patients with moderate-to-severe GPP. METHODS: Inter-item correlations and confirmatory factor analysis (CFA) were performed using Week 1 data. Internal consistency was assessed with Cronbach's α coefficient using baseline and Week 1 data. Test-retest reliability was assessed using intraclass correlation coefficients (ICCs); change data for the GPP Physician Global Assessment total score and pustulation subscore were used to define a stable population. Convergent validity was assessed at baseline and Week 1 using Spearman's rank-order correlations. Known-groups validity was measured by analysis of variance using Week 1 data. Ability to detect change from baseline to Week 1 was evaluated by analysis of covariance. RESULTS: Inter-item and item-to-total correlations were moderate or strong for most PSS and FACIT-Fatigue items. CFA demonstrated the unidimensionality of the PSS and FACIT-Fatigue, with high factor loadings for most items (PSS range, 0.75-0.94; FACIT-Fatigue range, 0.11-0.93) and acceptable fit statistics. Both scores demonstrated internal consistency (Cronbach's α, 0.71 and 0.95, respectively). The PSS, FACIT-Fatigue and pain-VAS demonstrated test-retest reliability (ICCs ≥0.70) and good evidence of convergent validity. Furthermore, the PROs could differentiate between known groups of varying symptom severity (range, p < 0.0001-0.0225) and detect changes in symptom severity from baseline to Week 1 (range, p < 0.0001-0.0002). CONCLUSIONS: Overall, these results support the reliability, validity and ability to detect change of the PSS, FACIT-Fatigue and pain-VAS as PROs in patients with GPP.
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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 | 0.014 | 0.023 |
| 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 | 0.001 |
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".