Higher adalimumab maintenance regimen is more effective than standard dose in anti-TNF experienced Crohn’s disease patients
Bibliographic record
Abstract
BACKGROUND: Many Crohn's disease patients treated with anti-tumor necrosis factor (TNF) therapies suffer from loss of response over time and require dose escalation. The aim of this study was to evaluate the efficacy and safety of treating anti-TNF experienced Crohn's disease patients with higher maintenance regimens of adalimumab. METHODS: In a retrospective observational study, Crohn's disease patients receiving adalimumab were categorized according to their maintenance regimen; 40 mg weekly, 80 mg every other week or greater were defined as a high-dose maintenance regimen and 40 mg every other week was defined as a standard maintenance regimen. The primary outcome was time to treatment failure. RESULTS: Thirty-nine patients were started on high-dose regimens following induction and 40 patients received the standard regimen. According to a Kaplan-Meier survival curve analysis, time to treatment failure was significantly longer in patients in the high-dose group (P = 0.0015). Patients on high-dose adalimumab had a lower treatment failure rate (hazard ratio 0.21; P = 0.0005) when compared to patients on the standard regimen, after adjusting for induction dose and concomitant immunomodulator use. No difference in adverse events was identified between the groups (31 vs. 30%; P = 0.94). CONCLUSION: High-dose maintenance regimens were more effective than the standard adalimumab maintenance protocol with better short and long-term clinical outcomes.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| 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".