Treatment of Ulcerative Colitis with a Humanized Antibody to the α <sub>4</sub> β <sub>7</sub> Integrin
Bibliographic record
Abstract
BACKGROUND: Selective blockade of interactions between leukocytes and vascular endothelium in the gut is a promising strategy for the treatment of inflammatory bowel diseases. METHODS: We conducted a multicenter, double-blind, placebo-controlled trial of MLN02, a humanized antibody to the alpha4beta7 integrin, in patients with active ulcerative colitis. We randomly assigned 181 patients to receive 0.5 mg of MLN02 per kilogram of body weight, 2.0 mg per kilogram, or an identical-appearing placebo intravenously on day 1 and day 29. Eligible patients also received concomitant mesalamine or no other treatment for colitis. Ulcerative colitis clinical scores and sigmoidoscopic assessments were evaluated six weeks after randomization. RESULTS: Clinical remission rates at week 6 were 33 percent, 32 percent, and 14 percent for the group receiving 0.5 mg of MLN02 per kilogram, the group receiving 2.0 mg per kilogram, and the placebo group, respectively (P=0.03). The corresponding proportions of patients who improved by at least 3 points on the ulcerative colitis clinical score were 66 percent, 53 percent, and 33 percent (P=0.002). Twenty-eight percent of patients receiving 0.5 mg per kilogram and 12 percent of those receiving 2.0 mg per kilogram had endoscopically evident remission, as compared with 8 percent of those receiving placebo (P=0.007). For the minority of patients in whom an MLN02 antibody titer greater than 1:125 developed, incomplete saturation of the alpha4beta7 receptor on circulating lymphocytes was observed and no benefit of treatment was identifiable. CONCLUSIONS: In this short-term study, MLN02 was more effective than placebo for the induction of clinical and endoscopic remission in patients with active ulcerative colitis.
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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 | 0.001 |
| 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) | 0.002 | 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".