Targeting axial and peripheral psoriatic arthritis: a retrospective observational study on the clinical relevance of upadacitinib
Bibliographic record
Abstract
OBJECTIVE: To evaluate upadacitinib (UPA) effectiveness on axial and peripheral manifestations of PsA by assessing the proportion of patients achieving low disease activity (LDA) and inactive disease (ID) status for axial involvement, and MDA and DAPSA-defined remission/LDA for peripheral domain. METHODS: This retrospective study included PsA patients from 27 Italian rheumatology centres. Demographic, clinical and outcome data were collected at baseline, 6 and 12 months. Kaplan-Meier curves assessed treatment persistence. Multivariate models identified predictors of discontinuation and outcomes. RESULTS: Among the 425 patients, 282 (66.4%) had peripheral PsA and 143 (33.6%) mixed (peripheral and axial) PsA. The 12-month UPA survival rate was 75.1%, higher in peripheral than mixed PsA (P = 0.039). Fibromyalgia was the strongest predictor of discontinuation (aHR 1.72; 95% CI: 1.08-2.75; P = 0.022). At 12 months, 38.2% of patients achieved ASDAS-LDA and 20.6% reached ASDAS-ID (LUNDEX-adjusted rates were 29.4% and 15.8%, respectively). The crude 12-month MDA rate was 59.9% (47.4% after LUNDEX adjustment). Enthesitis resolved in 80.2% of patients (P < 0.001), and NSAIDs use decreased to 32.9% (P < 0.001). Overall, VAS pain decreased significantly from 71.4 to 40 (mean change -31.4; 95% CI: -42.5 to -33.6; P < 0.0001), with a 44% reduction, well above the minimal clinically important improvement. No major cardiovascular events were reported; most adverse events were mild, including gastrointestinal intolerance (19%), infections (9.5%) and elevated liver enzymes (14.2%). CONCLUSION: Our study confirms UPA effectiveness across PsA domains, with clinically meaningful improvements in axial involvement and pain.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 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) | 0.001 | 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".