POS0950 IRRESPECTIVE OF THE NUMBER OF EROSIONS AT BASELINE, PATIENTS WITH PSORIATIC ARTHRITIS TREATED WITH IXEKIZUMAB SHOW IMPROVED CLINICAL OUTCOMES
Bibliographic record
Abstract
Background: Psoriatic arthritis (PsA) is a chronic and progressive disease characterized by high rates of early joint erosions, which have been associated with impaired quality of life and increased mortality rates. However, the relationship between the number of erosions at baseline (BL) and response to biological disease-modifying antirheumatic drugs (bDMARD) therapy has not been thoroughly investigated. Objectives: In this post-hoc analysis, we assessed the efficacy of placebo (PBO), ixekizumab (IXE) or adalimumab (ADA) on patients (pts) with erosions visible on hand radiographs at BL. Methods: Biologic-naïve pts with PsA (SPIRIT-P1, NCT01695239) were randomly assigned to PBO, IXE 80-mg every 2 weeks (Q2W) or 4 weeks (Q4W) after a 160-mg starting dose, or ADA 40-mg Q2W. Pts were stratified into two groups based on the number of BL erosions (erosion component of the modified total sharp scores ≤4 and >4). At week 24, outcomes analyzed for different baseline erosion score (BES) groups included American College of Rheumatology (ACR) 20%, 50%, 70%, Disease Activity index for PSoriatic Arthritis-Low Disease Activity (DAPSA-LDA), Health Assessment Questionnaire-Disability Index (HAQ-DI) and Minimal Disease Activity-Psoriasis Area Severity Index (MDA-PASI). Missing data were imputed using non-responder imputation (NRI) for categorical, and modified baseline observation carried forward (mBOCF) for continuous outcome variables. Comparisons between PBO and treatment within each BES group used logistic models for categorical, and ANCOVA for continuous outcome variables, adjusting for BL values, disease duration, geographic region, and prior conventional DMARD (cDMARD) experience. Results: 183 pts with BES≤4 and 205 pts with BES>4 at BL were included. At week 24, pts with BES>4 on PBO had worse outcomes across all parameters compared to those with BES≤4. There was significant improvement in DAPSA-LDA response rates in pts treated with IXE regardless of BES, whereas significant response rates were seen in ADA treated pts with BES>4. MDA-PASI response rates were significant in patients treated with IXEQ2W and IXEQ4W who had BES≤4, whereas pts with BES>4 demonstrated a significant response rate with IXEQ2W and ADA. Change from baseline in HAQ-DI was significant for all pts treated with bDMARDS, regardless of BES. Similarly, regardless of BES, significant differences in ACR50 and ACR70 response rates versus PBO were seen for pts treated with bMDARDS. Conclusion: Pts with higher BES in the PBO group experienced worse outcomes. Higher response rates (e.g., ACR50/70) were also harder to achieve in pts with higher BES. Irrespective of BES, IXE treated pts showed greater improvement compared to PBO in the achievement of LDA and functional outcomes. REFERENCES: NIL. Acknowledgements: NIL. Disclosure of Interests: M Elaine Husni M. E. Husni is a consultant for: AbbVie, Amgen, Bristol Myers Squibb, Celgene, Eli Lilly and Company, Janssen, Novartis, and UCB Pharma., Vinod Chandran V. Chandran is a consultant for: AbbVie, Amgen, Bristol Myers Squibb, Celgene, Eli Lilly and Company, Janssen, Novartis, Pfizer, and UCB., V. Chandran has received grant/research support from: AbbVie., Jeffrey Lisse J. Lisse is an employee and shareholder of: Eli Lilly and Company., Rebecca Bolce R. Bolce is an employee and shareholder of: Eli Lilly and Company., Carlos Diaz C. Diaz is an employee and shareholder of: Eli Lilly and Company., Baojin Zhu B. Zhu is an employee and shareholder of: Eli Lilly and Company., Elaine Lui E. Lui is a consultant for: Eli Lilly and Company and Pfizer., Laura C. Coates L. C. Coates is a consultant for: AbbVie, Amgen, Boehringer Ingelheim, Celgene, Eli Lilly and Company, Janssen, Merck Sharp & Dohme, Novartis, Pfizer, Prothena, Sun Pharma, and UCB Pharma., Eli Lilly and Company.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".