Occurrence of Serious Infection in Patients with Rheumatoid Arthritis Treated with Biologics and Denosumab Observed in a Clinical Setting
Bibliographic record
Abstract
OBJECTIVE: Previous studies combining biologic disease-modifying antirheumatic drugs (bDMARD) to treat rheumatoid arthritis (RA) have shown an increased risk of infection. However, the risk of infection with concurrent use of denosumab, a biologic agent for the treatment of osteoporosis, and a bDMARD remains unclear. Here, we evaluated the incidence of serious and opportunistic infections in patients treated concurrently with denosumab and a bDMARD and patients treated with a bDMARD alone. METHODS: A chart review of patients with RA from 2 Canadian rheumatology practices between July 1, 2010, and July 31, 2014, identified 2 groups of patients: those taking denosumab and a bDMARD concurrently (concurrent group) and those taking only a bDMARD (biologic-alone group). Patients were followed from the time of initiation of denosumab, or a matched index date for the biologic-alone group, to the end of the study or loss to followup. Instances of serious or opportunistic infections were recorded. RESULTS: A total of 308 patients (n = 102 for the concurrent group and n = 206 for the biologic-alone group) were evaluated. Within the concurrent group, 3 serious infection events occurred. Within the biologic-alone group, 4 serious infection events and 1 opportunistic infection event occurred. In both groups, all patients with serious or opportunistic infection recovered, and there were no instances of death during the study period. CONCLUSION: This study demonstrated a low occurrence of serious and opportunistic infections in patients with RA taking bDMARD, including patients with concurrent denosumab use.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".