Interferon β-1a in ulcerative colitis: a placebo controlled, randomised, dose escalating study
Bibliographic record
Abstract
BACKGROUND: and aims: Administration of interferon (IFN)-beta may represent a rational approach to the treatment of ulcerative colitis through its immunomodulatory and anti-inflammatory effects. The present study was performed to evaluate the efficacy and tolerability of IFN-beta-1a. METHODS: Patients (n=18) with moderately active ulcerative colitis were randomised to receive IFN-beta-1a or placebo. IFN-beta-1a was started at a dose of 22 micro g three times a week subcutaneously, and the dose was increased at two week intervals to 44 micro g and then to 88 micro g if no response was observed. The maximum duration of treatment was eight weeks. End points were clinical treatment response, defined as a decrease of at least 3 points from baseline in the ulcerative colitis scoring system (UCSS) symptoms score and induction of endoscopically confirmed remission. RESULTS: Baseline characteristics and disease severity were similar in both groups. Data from 17 patients are included in this report (10 patients in the IFN-beta-1a group and seven patients in the placebo group). Clinical response was achieved in five patients (50%) in the IFN-beta-1a group and in one (14%) in the placebo group (P=0.14). Remission was achieved in three patients in the IFN-beta-1a group and in none in the placebo group (p=0.02). Most adverse reactions associated with IFN-beta-1a were influenza-like symptoms or injection site reactions, and were mild or moderate in severity. CONCLUSIONS: IFN-beta-1a may represent a promising novel treatment approach in 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 | 0.006 | 0.005 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".