Real-world clinical outcomes of patients with moderate-to-severe rheumatoid arthritis initiating upadacitinib in the United Kingdom: final analysis from a prospective observational cohort study (ENDEAVOUR)
Bibliographic record
Abstract
OBJECTIVE: Upadacitinib is recommended by National Institute for Health and Care Excellence in the UK in adults with moderate-to-severe rheumatoid arthritis (RA). This observational study assessed real-world clinical outcomes and patient-reported outcomes (PROs) in patients receiving upadacitinib for 6 months in the UK. METHODS: Patients from 14 centres in whom the decision to initiate upadacitinib had already been made were enrolled. Baseline data were retrospectively collected from patient records. Clinician-reported data were collected at routine clinic visits 3 and 6 months after upadacitinib initiation. Patient-reported data were collected directly from patients using an app (electronic PROs, ePROs). The primary end-point was proportion of patients achieving clinical remission (DAS28 CRP <2.6) after 6 months of upadacitinib. RESULTS: Data are available for 63 patients at all three datapoints and for 53 patients for the primary end-point. At 6 months, 40% (21/53) of patients achieved clinical remission and 21% (11/53) achieved low disease activity. Response was seen at 3 months for all efficacy end-points. ePROs allowed the capture of early patient-reported data which demonstrated clinically important improvements in pain and fatigue within 10 days and other PROs within 2 months. Improvements were also seen in metrics of activity, work and quality of life (QOL). CONCLUSION: Patients in ENDEAVOUR showed similar early effectiveness with upadacitinib to that observed in clinical trials. Use of ePROs demonstrated rapid onset of action and meaningful improvements in QOL providing a potential opportunity to reduce outpatient visits for early responders, thus reducing the burden on rheumatology services.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| 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".