P185 Long-term efficacy and safety of upadacitinib in patients with psoriatic arthritis refractory to biologic therapies: 2-year results from the phase 3 SELECT-PsA 2 study
Bibliographic record
Abstract
Abstract Background/Aims Upadacitinib (UPA), an oral Janus kinase (JAK) inhibitor, demonstrated efficacy and safety in patients (pts) with psoriatic arthritis (PsA) and prior inadequate response or intolerance to ≥ 1 biologic disease-modifying antirheumatic drug (bDMARD) at week (wk) 56 in the phase 3 SELECT-PsA 2 study. We aimed to evaluate the efficacy and safety of UPA at wk 104 from the ongoing long-term extension of SELECT-PsA 2. Methods Pts were randomized to UPA 15 mg (UPA15), UPA 30 mg (UPA30), or placebo (PBO) for 24 wks; PBO pts were then switched to UPA15 or UPA30. For continuous UPA treatment groups, efficacy endpoints at wk 104 were analyzed using non-responder imputation (NRI) and as observed (AO) (binary endpoints) or mixed-effect model repeated measures (MMRM) and AO (continuous endpoints). Treatment-emergent adverse events (TEAEs) were summarized for pts who received ≥1 dose of study drug using visit-based cut-off at wk 104. Results A total of 641 pts received ≥1 dose of study drug. At wk 104, 38.4% of all patients had discontinued study drug, with the highest discontinuation observed in patients randomized to PBO at baseline (all PBO: 46.7%). The most common reasons for discontinuation were lack of efficacy (UPA15: 12.3%, UPA30: 8.7%, all PBO: 21.7%) and adverse event (UPA15: 10.9%, UPA30: 13.3%, all PBO: 12.7%). The proportion of UPA pts that achieved ACR20/50/70, MDA, PASI75/90/100, and resolution of dactylitis and enthesitis were generally similar, or further improved, with 104 wks of treatment vs 56 wks. Similarly, mean change from baseline in HAQ-DI, patient’s assessment of pain, BASDAI, and ASDAS was improved with UPA treatment. At 104 wks of therapy, clinical responses were largely similar with UPA15 and UPA30. Generally, safety data at wk 104 were consistent with that reported at wk 56. Rates of serious infection, herpes zoster, hepatic disorder, anemia, neutropenia, lymphopenia, and CPK elevation remained numerically higher with UPA30 vs UPA15, while rates of malignancies, MACE, and VTE were similar for both UPA groups. One death was reported with UPA15 (unexplained due to lack of information; however, the patient had recently been diagnosed with ovarian cancer) and two with UPA30 (pancytopenia and COVID-19 pneumonia). Conclusion In PsA pts with prior inadequate response or intolerance to ≥ 1 bDMARD, clinical responses were maintained with UPA15 and UPA30 up to two years of treatment. No new safety signals were identified in this long-term extension. Disclosure P.J. Mease: Consultancies; Consultant of: AbbVie, Amgen, Boehringer Ingelheim, Bristol-Myers Squib, Celgene, Eli Lilly, Galapagos, Genentech, Gilead, GSK, Janssen, Novartis, Pfizer, Sun Pharma, and UCB. Member of speakers’ bureau; Speakers bureau: AbbVie, Amgen, Boehringer Ingelheim, Bristol-Myers Squib, Celgene, Eli Lilly, Galapagos, Genentech, Gilead, GSK, Janssen, Novartis, Pfizer, Sun Pharma, and UCB. Grants/research support; Grant/research support from: AbbVie, Amgen, Boehringer Ingelheim, Bristol-Myers Squib, Celgene, Eli Lilly, Galapagos, Genentech, Gilead, GSK, Janssen, Novartis, Pfizer, Sun Pharma, and UCB. A. Setty: Shareholder/stock ownership; Financial Disclosures: Employee of AbbVie and may hold stock or options. K. Papp: Consultancies; Consultant of: AbbVie, Akros, Allergan, Almirall, Amgen, Arcutis, Avillion, Bausch Health, Boehringer Ingelheim, Bristol-Myers Squibb, Celgene, Dermavant, Dermira, Eli Lilly, Galderma, Genentech/Roche. Member of speakers’ bureau; Speakers bureau: AbbVie, Akros, Allergan, Almirall, Amgen, Bausch Health, Boehringer Ingelheim, Bristol-Myers Squibb, Celgene, Dermavant, Dermira, Eli Lilly, Galderma, Genentech/Roche, Janssen, Kyowa. Grants/research support; Grant/research support from: AbbVie, Akros, Allergan, Almirall, Amgen, Arcutis, Avillion, Bausch Health, Boehringer Ingelheim, Bristol-Myers Squibb, Celgene, Dermavant, Dermira, Eli Lilly, Galderma, G. F. Van den Bosch: Consultancies; Consultant of: AbbVie, Bristol-Myers Squibb, Celgene, Eli Lilly, Galapagos, Gilead, Janssen, Merck, Novartis, Pfizer, and UCB. Member of speakers’ bureau; Speakers bureau: AbbVie, Bristol-Myers Squibb, Celgene, Eli Lilly, Galapagos, Gilead, Janssen, Merck, Novartis, Pfizer, and UCB. S. Tsuji: Consultancies; Consultant of: AbbVie, Eli Lilly, Janssen, Novartis, and UCB. Member of speakers’ bureau; Speakers bureau: AbbVie, Eli Lilly, Janssen, Novartis, and UCB. Grants/research support; Grant/research support from: AbbVie, Eli Lilly, Janssen, Novartis, and UCB. M. Keiserman: Consultancies; Consultant of: AbbVie, Bristol-Myers Squibb, Celgene, Eli Lilly, Janssen, Novartis, Pfizer, Roche, and UCB. Member of speakers’ bureau; Speakers bureau: AbbVie, Bristol Myers Squibb, Celgene, Eli Lilly, Janssen, Novartis, Pfizer, Roche, and UCB. Grants/research support; Grant/research support from: AbbVie, Bristol-Myers Squibb, Celgene, Eli Lilly, Janssen, Novartis, Pfizer, Roche, and UCB. X. Bu: Shareholder/stock ownership; Financial Disclosures: Employee of AbbVie and may hold stock or options. L. Chen: Shareholder/stock ownership; Financial Disclosures: Employee of AbbVie and may hold stock or options. R. Mccaskill: Shareholder/stock ownership; Financial Disclosures: Employee of AbbVie and may hold stock or options. E. Mcdearmon-Blondell: Shareholder/stock ownership; Financial Disclosures: Employee of AbbVie and may hold stock or options. P. Wung: Shareholder/stock ownership; Financial Disclosures: Employee of AbbVie and may hold stock or options. W. Tillett: Consultancies; Consultant of: AbbVie, Amgen, Celgene, Eli Lilly, MSD, Novartis, Pfizer, and UCB. Member of speakers’ bureau; Speakers bureau: AbbVie, Amgen, Celgene, Eli Lilly, Janssen, Novartis, Pfizer, and UCB. Grants/research support; Grant/research support from: AbbVie, Celgene, Eli Lilly, and Janssen.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".