Adalimumab Safety in Crohnʼs Disease and Rheumatoid Arthritis Clinical Trials, Reduced Mortality in Rheumatoid Arthritis
Bibliographic record
Abstract
Purpose: Evaluate adalimumab safety in clinical trials for rheumatoid arthritis (RA) and Crohn's disease (CD). Methods: Safety data were routinely collected in all adalimumab clinical trials. Rates of serious adverse events (SAE) of interest to physicians prescribing anti-TNF therapy were assessed per 100-patient-years (E/100-PY). Rates in CD clinical trials [4 Phase II/III multicenter RCT trials and an OL extension] and RA clinical trials [the early RA trial excluded, all Phase I-III randomized controlled trials (RCTs), open-label (OL) extensions, and OL Phase IIIb clinical trials] were compared with previously reported rates in adalimumab. Results: As of April 15, 2005, the adalimumab RA clinical trial safety database included data for 10050 patients, representing 12506 PY of adalimumab exposure1. The serious infection rate (5.05/100-PY) was comparable to that reported on August 31, 2002 (4.9/100-PY) and to published reports of anti-TNF naïve RA populations2,3. SAE rates of interest in RA and CD clinical trials are summarized in the table.Table: SAE of Interest (E/100-PY).In adalimumab RA clinical trials, the calculated standardized mortality ratio of 0.64 (95% CI 0.52–0.79) was lower than previously reported for the RA population prior to the advent of anti-TNF therapy4,5. Conclusions: Adalimumab therapy showed consistent safety profiles in clinical trials for RA and CD. SAE rates of interest were generally similar in clinical trials in RA and CD. Evidence suggests a decrease in mortality in adalimumab-treated patients with RA compared with a gender- and age-matched general population. 1 Schiff MH, et al. Ann Rheum Dis 2006;doi:10.1136/ard.2005.043166. 2 Singh G, et al. Arthritis Rheum 1999;42(Suppl):S242. 3 Doran MF, et al. Arthritis Rheum 2002;46:2287–9. 4 Gabriel SE, et al. Arthritis Rheum 2003;48(1):54–58. 5 Wolfe F, et al. Arthritis Rheum 1994;37(4):481–94.
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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 | 0.096 | 0.125 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| 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".