PGA×BSA: A Measure of Psoriasis Severity Tested in Patients with Active Psoriatic Arthritis and Treated with Certolizumab Pegol
Bibliographic record
Abstract
OBJECTIVE: The product of physician's global assessment and body surface area (PGA×BSA) to assess psoriasis severity has previously been investigated in patients with psoriasis, with the aim of assessing PGA×BSA as an alternative to the time-consuming Psoriasis Area and Severity Index (PASI). Here, we investigate PGA×BSA as an alternative to PASI in patients with psoriatic arthritis (PsA). METHODS: Analyses used data from the double-blind, placebo-controlled, RAPID-PsA trial (NCT01087788) that investigated the efficacy of certolizumab pegol (CZP) in patients with PsA. Outcomes assessed whether the PGA×BSA and PASI results were comparable, and whether these outcomes correlated with one another or with the Dermatology Life Quality Index (DLQI). RESULTS: For CZP-treated patients, both PGA×BSA and PASI demonstrated similar sensitivities to treatment between baseline and Week 24, with mean improvements of 77.4% and 69.0%, respectively. Similar improvements were also seen with placebo (PGA×BSA: 3.2%, PASI: 6.1%). Achievement of 75% response criterion in PGA×BSA and PASI was attained by similar proportions of patients with CZP (PGA×BSA75: 59.0%, PASI75: 61.4%) and placebo (PGA × BSA75: 15.1%, PASI75: 15.1%). Cross tabulations showed high concordance between achievement of response outcomes in PGA×BSA and PASI (79.6-95.2%). Spearman correlations revealed strong correlations between PGA×BSA and PASI at baseline (r = 0.78; n = 225) and percentage improvement to Week 24 (r = 0.85; n = 186). Both outcomes were only moderately correlated with DLQI (r = 0.41-0.50; n = 179-249). CONCLUSION: PGA×BSA is sensitive to changes in skin manifestations in patients with PsA treated with CZP. Further, PGA×BSA correlates strongly with PASI, and achievement of 75% improvement was similar for PGA×BSA and PASI.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".