Effectiveness of 6-month Use of Secukinumab in Patients With Psoriatic Arthritis in the CorEvitas Psoriatic Arthritis/Spondyloarthritis Registry
Bibliographic record
Abstract
OBJECTIVE: To evaluate clinical and patient-reported outcomes (PROs) at 6 months after secukinumab initiation in US patients with psoriatic arthritis (PsA). METHODS: Patients with PsA in the CorEvitas Psoriatic Arthritis/Spondyloarthritis Registry who initiated secukinumab between April 1, 2017, and December 2, 2019, and maintained secukinumab at their 6-month follow-up visit were included. Achievement of minimal disease activity (MDA) among patients not in MDA at initiation; resolution (ie, no evidence) of tender and swollen joint counts, enthesitis, and dactylitis among patients with ≥ 1 of these at initiation; and change in disease activity and PROs were evaluated at 6 months in all patients and in patients who received secukinumab as a first-line biologic. RESULTS: Of the 100 eligible patients included, most (83.0%) were biologic experienced and 17.0% initiated secukinumab as a first-line biologic. At initiation, 75/90 patients (83.3%) with available data were not in MDA; 26/71 (36.6%) with follow-up data achieved MDA at 6 months. Further, 28/68 patients (41.2%) with ≥ 1 tender joint, 24/54 (44.4%) with ≥ 1 swollen joint, 17/28 (60.7%) with enthesitis, and 9/12 (75.0%) with dactylitis at initiation achieved resolution at 6 months. Improvements in clinical manifestations, PRO measures, and work productivity and activity were observed after 6 months among patients with PsA who initiated and maintained secukinumab. CONCLUSION: In this real-world population, patients with PsA who received and maintained secukinumab for 6 months achieved MDA in proportions consistent with clinical trials and demonstrated improvements in clinical manifestations and PROs.
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".