Long‐term safety of adalimumab in clinical trials in adult patients with Crohn's disease or ulcerative colitis
Bibliographic record
Abstract
BACKGROUND: Adalimumab is used to treat moderate to severe Crohn's disease (CD) and ulcerative colitis (UC) when conventional therapies fail. AIM: To update long-term adalimumab safety from CD and UC trials; the previous report was CD only, 3160 patients/3402 patient-years (PYs). METHODS: Treatment-emergent adverse events (AEs; first dose to 70 days after last dose/December 31, 2015) in adults in phase 2/3 and 3/3b trials and open-label extensions were coded using Medical Dictionary for Regulatory Activities (MedDRA-v18.1). Rates were assessed as events/100 (E/100 PYs). RESULTS: The database (16 trials; CD, N = 3606; UC, N = 1739) represented 4145 and 3397 PYs of exposure, respectively. For CD, incidences of any AEs with adalimumab were 60.8%-65.1%, depending on dose, and 71.5% with placebo; for UC, the incidences were 53.5%-54.8% and 56.1%, respectively. Rates of any AEs (CD, 605 E/100 PYs; UC, 361 E/100 PYs), serious AEs (CD, 36.1 E/100 PYs; UC, 18.9 E/100 PYs), and malignancies (CD, 1.2 E/100 PYs; UC, 1.0 E/100 PYs) were similar between current and prior analyses. Apparent rate of opportunistic infections was lowered to 0.3 and 0.2 E/100 PYs for CD and UC, respectively, by recent MedDRA changes excluding oral candidiasis and tuberculosis. Standardised incidence ratios for malignancies were similar to the general population (CD, 1.45 [95% CI, 0.90-2.22]; UC, 1.36 [95% CI, 0.84-2.07]). Demyelinating disorders were uncommon (CD, 0.1 E/100 PYs; UC, <0.1 E/100 PYs). CONCLUSIONS: Patients with moderately to severely active Crohn's disease or ulcerative colitis continued to experience acceptable safety with adalimumab, without new safety signals.
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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 | 0.069 | 0.114 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".