Effect of bimekizumab on symptoms and impact of disease in patients with psoriatic arthritis over 3 years: results from BE ACTIVE
Bibliographic record
Abstract
OBJECTIVES: Evaluate effects of long-term bimekizumab treatment on patient-reported outcome (PRO) measures, symptoms and the impact of PsA on patients. METHODS: Patients with active PsA were enrolled into BE ACTIVE, a 48-week randomised controlled trial (NCT02969525). After Week 48, patients could enter a 104-week open-label extension (NCT03347110), receiving bimekizumab 160 mg every four weeks. PRO measures assessed included arthritis pain visual analogue scale (VAS), PsA Impact of Disease (PsAID)-9, 36-Item Short Form Survey (SF-36) and HAQ-Disability Index (HAQ-DI). Results were analysed as mean (S.E.M.) changes from baseline (CfB) from Week 0 to the end of the open-label extension (3 years) and as percentage of patients reaching patient-acceptable symptom state (PASS) for global impact (PsAID-9 total score ≤4) and normal function (HAQ-DI total score <0.5). Non-responder imputation was applied to missing binary outcomes. RESULTS: In 206 patients (mean age 49.3 years, 51.0% male), completion rate was high; 161 (78.2%) patients completed Week 152. Bimekizumab treatment was associated with long-term sustained improvements in pain [arthritis pain VAS CfB; Week 48: -29.9 (1.9); Week 152: -32.0 (1.9)] and fatigue [PsAID-9 fatigue CfB; -2.4 (0.2); -2.7 (0.2)]. High percentages of patients achieved acceptable symptom state (PsAID-9 PASS: 75.2%; 65.0%) and normalised function (HAQ-DI <0.5: 49.0%; 46.1%). Improvements in patient global assessment and SF-36 Physical Component Summary were also sustained. CONCLUSIONS: Bimekizumab treatment was associated with long-term sustained improvements in pain and fatigue, reducing overall impact of PsA on patients. Physical function and quality of life improved up to 3 years. TRIAL REGISTRATION: ClinicalTrials.gov, https://clinicaltrials.gov, NCT02969525, NCT03347110.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".