Effectiveness of b/tsDMARDs Including Ixekizumab Per Line of Therapy and Concomitant csDMARDs Use in Psoriatic Arthritis: Real-World Data from a Prospective Observational Study
Bibliographic record
Abstract
Objectives Treatment (tx) guidelines for psoriatic arthritis (PsA) recommend biologic disease-modifying antirheumatic drugs (bDMARDs) or targeted synthetic (ts) DMARDs after inadequate response to conventional synthetic DMARDs (csDMARDs).[1] In clinical studies, ixekizumab (IXE) has shown efficacy in patients (pts) with PsA who were bDMARD-naïve,[2] tumor necrosis factor inhibitor (TNFi)-experienced,[3] and with and without concomitant csDMARDs. Data from real-world studies is limited. This interim analysis reports the effectiveness of IXE and other b/tsDMARDs in b/tsDMARD-naïve (naïve) and -experienced (exp) pts as well as in monotherapy (mono) and in combination (combo) with any csDMARD at 12 months (M) in real-world setting. Methods In the PRO-SPIRIT study, pts with PsA who initiated or switched to new b/tsDMARDs were evaluated in 5 European countries, and Canada. Pts were categorized by prior b/tsDMARD tx and concomitant csDMARD use at baseline (BL), respectively. Descriptive data for the analysis population at 12 M are presented. Mixed models for repeated measures (MMRM) were used to assess change from BL (CFB). Missing data was handled using multiple imputation. Results Of 1192* pts, TNF inhibitors (TNFi) (68.6%) and secukinumab (SEC) group (33.5%) had the highest proportion of naïve pts, whereas TNFi (53.5%) and JAKi (46.8%) had the highest proportion of combo pts (Table). At 12 M, similar mean CFB was observed in pts treated with IXE for clinical Disease Activity in Psoriatic Arthritis (cDAPSA) in the naïve (−13.6), exp (−12.1), mono (−12.3), and combo (−12.4) subgroups (subsequently reported in that order, herein); as well as for body surface area (BSA) (−5.0), (−3.6) (−4.4) and (−3.9). Similar trends were observed in tender joint counts and swollen joint counts. However, mean CFB in cDAPSA was lower in exp versus (vs) naïve pts treated with SEC (−8.9 vs −12.8), IL-12/23i (−7.4 vs −16.2) and IL-23i (−10.1 vs −17.2) and lower in mono vs combo in TNFi (−12.5 vs −15.2) and IL-23i (−11.0 vs −12.6). Mean CFB in BSA was lower in exp vs naïve pts treated with TNFi (−2.8 vs −5.4), and IL-23i (−2.0 vs −5.3). Table: BL characteristics for patients categorized by b/tsDMARD-naive, -experienced, monotherapy, and combination with csDMARDs Conclusion In real-world setting, IXE demonstrated similar effectiveness on joints and skin regardless of therapy line and concomitant csDMARDs, confirming findings from IXE clinical trials2,3. Other treatments showed less consistent results either in exp vs naïve pts (SEC, IL-12/23i, IL-23i) or in mono vs combo therapy (TNFi, IL-23i). [1.] Gossec L. Ann Rheum Dis 2020;79:700-12. [2.] Nash P. Lancet 2017;389:2317-27. [3.] Mease P. Ann Rheum Dis 2017;76:79-87.
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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 | 0.006 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".