Safety of adalimumab in global clinical trials of patients with Crohn's disease.
Bibliographic record
Abstract
Adalimumab (ADA), a fully human anti-TNF monoclonal antibody, is approved in Europe for treating patients with severely active Crohn's disease (CD) who have had an inadequate response to conventional therapy. All patients with CD participating in the pivotal randomized controlled clinical trials, open-label extensions, and Phase IIIb studies were evaluated for safety at regular intervals. Rates of adverse events (AEs) of interest to physicians prescribing anti-TNF therapy were assessed per 100-patient-years (100-PYs) of ADA exposure. Standardized mortality ratios were calculated using the World Health Organization 2003 age- and sex-matched US mortality data. As of 6 November 2009, the ADA CD clinical trial safety database contained data for 3603 patients (4088-PYs of ADA exposure). Table 1 compares AE rates observed in all clinical trials in CD at the 6 November 2009 cutoff to those from the 15 April 2008 safety update.1 Observed cases of lymphoma2, tuberculosis 3, congestive heart failure2, and demyelinating disease5have not increased since the previous update. The AE rates were comparable to those reported in rheumatoid arthritis trials.2 The calculated standardized mortality ratio in ADA-treated patients with CD, 0.48 (95% confidence interval [CI]: 0.15, 1.12), is lower than the rate of 1.52 (95% CI: 1.32, 1.74) reported in a recent meta-analysis of patients with CD.3
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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 | 0.122 | 0.105 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| 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".