Rheumatoid arthritis triple therapy compared with etanercept: difference in infectious and gastrointestinal adverse events
Bibliographic record
Abstract
Objective: The main aim of this study was to examine the differences between triple therapy (T: SSZ and HCQ added to MTX) and etanercept (E) added to MTX with regard to the infectious and gastrointestinal (GI) adverse events (AEs) reported in The Rheumatoid Arthritis Comparison of Active Therapies Trial. Methods: The patients were 353 RA MTX incomplete responders who were randomized to T (n = 178) or E (n = 175). Of these, 88 patients were switched to the alternative treatment from the initial treatment (E or T) at 24 weeks per protocol. Infectious and GI serious AEs (SAEs) and non-serious AEs (NAEs) were reported during 48 and 4 weeks after the intervention period. Generalized linear models were used to estimate the incidence rate ratios (IRRs) of AEs between the two therapies. Results: Patients on E therapy were more likely to have infectious NAEs (IRR = 1.56, 95% CI: 1.11, 2.19). There was a greater number of infectious SAEs that occurred when patients received E than T therapy [12 E (6.9%) vs 4 T (2.2%), P = 0.19]. Pneumonia was the most common infectious SAE for both treatments [6 E (3.4%) and 2 T (1.1%)]. Conversely, patients who were on E were less likely to have GI NAEs than those on T therapy (IRR = 0.62, 95% CI: 0.40, 0.94). The most common GI SAE reported was GI haemorrhage, which occurred among three patients on E (1.7%). Conclusion: This study provides evidence of different likelihoods of infectious and GI AEs associated with two common, equally effective treatments for RA patients who have had incomplete responses to MTX. Trial registration: ClinicalTrials.gov, http://clinicaltrials.gov , NCT00405275.
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".