Speed of clinical improvement in the real‐world setting from patient‐reported Psoriasis Symptoms and Signs Diary: Secondary outcomes from the Psoriasis Study of Health Outcomes through 12 weeks
Bibliographic record
Abstract
BACKGROUND: Rapid skin improvement is a key treatment goal of patients with moderate-to-severe psoriasis (PsO). OBJECTIVES: To compare the speed of clinical improvement of approved biologics on the symptoms and signs of psoriasis assessed by patients using the validated Psoriasis Symptoms and Signs Diary (PSSD) through 12 weeks. METHODS: Psoriasis Study of Health Outcomes (PSoHO) is an international, prospective, non-interventional study that compares the effectiveness of anti-interleukin (IL)-17A biologics versus other biologics, together with pairwise comparisons of ixekizumab versus five individual biologics in patients with PsO. Using the PSSD 7-day recall period, patients assessed the symptoms (itch, skin tightness, burning, stinging and pain) and signs (dryness, cracking, scaling, shedding/flaking, redness and bleeding) of their psoriasis (0-10). Symptom and sign summary scores (0-100) are derived from the average of individual scores. Percentage change in summary scores and proportion of patients with clinically meaningful improvements (CMI) in PSSD summary and individual scores are evaluated weekly. Longitudinal PSSD data are reported as observed with treatment comparisons analysed using mixed model for repeated measures (MMRM) and generalized linear mixed models (GLMM). RESULTS: Across cohorts and treatments, eligible patients (n = 1654) had comparable baseline PSSD scores. From Week 1, the anti-IL-17A cohort achieved significantly larger score improvements in PSSD summary scores and a higher proportion of patients showed CMIs compared to the other biologics cohort through 12 weeks. Lower PSSD scores were associated with a greater proportion of patients reporting their psoriasis as no longer impacting their quality-of-life (DLQI 0,1) and a high level of clinical response (PASI100). Results also indicate a relationship between an early CMI in PSSD score at Week 2 and PASI100 score at Week 12. CONCLUSIONS: Treatment with anti-IL-17A biologics, particularly ixekizumab, resulted in rapid and sustained patient-reported improvements in psoriasis symptoms and signs compared with other biologics in a real-world setting.
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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 | 0.009 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".