Rheumatoid Arthritis Disease-modifying Antirheumatic Drug Intervention and Utilization Study: Safety and Etanercept Utilization Analyses from the RADIUS 1 and RADIUS 2 Registries
Bibliographic record
Abstract
OBJECTIVE: to report the rates of serious adverse events (SAE), serious infectious events (SIE), and events of medical interest (EMI) in patients receiving etanercept; to identify the risk factors for SAE, SIE, and EMI; and to report time to switching from etanercept therapy, reasons for switching, and time to restarting treatment with etanercept in patients with rheumatoid arthritis (RA) in US clinical practice. METHODS: adults ≥ 18 years of age who fulfilled the 1987 American Rheumatism Association criteria for RA were eligible for enrollment in 2 prospective, 5-year, multicenter, observational registries. RADIUS 1 (Rheumatoid Arthritis DMARD Intervention and Utilization Study) enrolled patients with RA who required a change in treatment [either an addition or a switch of a biologic or nonbiologic disease-modifying antirheumatic drug (DMARD)]. In RADIUS 2, patients with RA were required to start etanercept therapy at entry. Patients were seen at a frequency determined by their rheumatologist. RADIUS 1 and RADIUS 2 were registered under the US National Institutes of Health ClinicalTrials.gov identifiers NCT00116714 and NCT00116727, respectively. RESULTS: in these patients, SAE, SIE, and EMI occurred at rates comparable to those seen in clinical trials. No unexpected safety signals were observed. Rates for SAE, SIE, and EMI in etanercept-treated patients were comparable to rates observed in patients receiving methotrexate monotherapy and did not increase with greater exposure to etanercept therapy. CONCLUSION: the RADIUS registries provide a better understanding of the safety of etanercept in patients with RA in the US practice setting.
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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 | 0.007 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".