Escalation to weekly dosing recaptures response in adalimumab‐treated patients with moderately to severely active ulcerative colitis
Bibliographic record
Abstract
BACKGROUND: Patients with moderately to severely active ulcerative colitis occasionally do not respond to or lose initial response to maintenance dosing of anti-TNF therapy. AIM: To report the efficacy of escalation from every other week (EOW) to weekly adalimumab dosing in patients from the clinical trial ULTRA 2 (NCT00408629), by week 8 response (i.e. response after adalimumab induction therapy). METHODS: Week 52 remission, response, and mucosal healing rates were assessed in ULTRA 2 adalimumab-randomised patients who escalated to weekly dosing. Patients were stratified by week 8 response per partial Mayo score. Kaplan-Meier and logistic regression analyses estimated time to weekly dosing and defined predictors of escalation to weekly dosing, respectively. Adverse events were reported for patients receiving open-label adalimumab. RESULTS: The rate of escalation to weekly dosing was 16.3% (20/123) for week 8 responders and 38.4% (48/125) for week 8 nonresponders. Week 52 remission, response and mucosal healing rates with weekly dosing were 20%, 45%, and 45% for week 8 responders and 2.1%, 25% and 29.2% for nonresponders, respectively (NRI). The median time to weekly dosing was 288 days for week 8 nonresponders and not estimable for responders. Prior anti-TNF use was a significant predictor of escalation to weekly dosing. Treatment-emergent adverse event rates were similar for patients receiving open-label EOW or weekly adalimumab. CONCLUSIONS: Escalation to weekly adalimumab dosing demonstrated clinical benefits for patients who lost response to therapy and may be beneficial for patients not initially responding to induction therapy. No new safety risks were identified with weekly dosing.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| 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) | 0.001 | 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".