Quality of life and patient‐perceived symptoms in patients with psoriasis undergoing proactive or reactive management with the fixed‐dose combination Cal/BD foam: A <i>post‐hoc</i> analysis of PSO‐LONG
Bibliographic record
Abstract
BACKGROUND: Psoriasis has important physical and psychosocial effects that extend beyond the skin. Understanding the impact of treatment on health-related quality of life (HRQoL) and patient-perceived symptom severity in psoriasis is key to clinical decision-making. OBJECTIVES: This post hoc analysis of the PSO-LONG trial data assessed the impact of long-term proactive or reactive management with fixed-dose combination calcipotriene 50 µg/g and betamethasone dipropionate 0.5 mg/g (Cal/BD) foam on patient-reported outcomes (PROs) in patients with psoriasis vulgaris. METHODS: Five hundred and twenty-one patients from the Phase 3, randomized, double-blind PSO-LONG trial were included. An initial 4-week, open-label phase of fixed-dose combination Cal/BD foam once daily (QD) was followed by a 52-week maintenance phase, at the start of which patients were randomized to a proactive management arm (Cal/BD foam twice weekly) or reactive management arm (vehicle foam twice weekly). Patient-perceived symptom severity and HRQoL were assessed using the Psoriasis Symptom Inventory (PSI), the Dermatology Life Quality Index (DLQI) and the EuroQol-5D for psoriasis (EQ-5D-5L-PSO). RESULTS: Statistically and clinically significant improvements were observed across all PRO measures. The mean difference (standard deviation) from baseline to Week 4 was -8.97 (6.18) for PSI, -6.02 (5.46) for DLQI and 0.11 (0.15) for EQ-5D-5L-PSO scores. During maintenance, patients receiving reactive management had significantly higher DLQI (15% [p = 0.007]) and PSI (15% [p = 0.0128]) and a numerically lower EQ-5D-5L-PSO mean area under the curve score than patients receiving proactive management (1% [p = 0.0842]). CONCLUSIONS: Cal/BD foam significantly improved DLQI, EQ-5D-5L-PSO and PSI scores during the open-label and maintenance phases. Patients assigned to proactive management had significantly better DLQI and PSI scores and numerically better EQ-5D-5L-PSO versus reactive management. Additionally, baseline flare was associated with worse PROs than the start of a relapse, and patients starting a relapse also had worse PROs than patients in remission.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".