Daclizumab, a humanised monoclonal antibody to the interleukin 2 receptor (CD25), for the treatment of moderately to severely active ulcerative colitis: a randomised, double blind, placebo controlled, dose ranging trial
Bibliographic record
Abstract
BACKGROUND: An uncontrolled pilot study demonstrated that daclizumab, a humanised monoclonal antibody to the interleukin 2 receptor (CD25), might be effective for the treatment of active ulcerative colitis. METHODS: A randomised, double blind, placebo controlled trial was conducted to evaluate the efficacy of daclizumab induction therapy in patients with active ulcerative colitis. A total of 159 patients with moderate ulcerative colitis were randomised to receive induction therapy with daclizumab 1 mg/kg intravenously at weeks 0 and 4, or 2 mg/kg intravenously at weeks 0, 2, 4, and 6, or placebo. The primary end point was induction of remission at week 8. Remission was defined as a Mayo score of 0 on both endoscopy and rectal bleeding components and a score of 0 or 1 on stool frequency and physician's global assessment components. Response was defined as a decrease from baseline in the Mayo score of at least 3 points. RESULTS: Two per cent of patients receiving daclizumab 1 mg/kg (p = 0.11 v placebo) and 7% of patients receiving 2 mg/kg (p = 0.73) were in remission at week 8, compared with 10% of those who received placebo. Response occurred at week 8 in 25% of patients receiving daclizumab 1 mg/kg (p = 0.04) and in 33% of patients receiving 2 mg/kg (p = 0.30) versus 44% of those receiving placebo. Daclizumab was well tolerated. The most frequently reported adverse events in daclizumab treated patients compared with placebo treated patients were nasopharyngitis (14.6%) and pyrexia (10.7%). CONCLUSION: Patients with moderate ulcerative colitis who are treated with daclizumab are not more likely to be in remission or response at eight weeks than patients treated with placebo.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".