Biologic Disease-modifying Antirheumatic Drug (bDMARD)-induced Neutropenia: A Registry from a Retrospective Cohort of Patients with Rheumatic Diseases Treated with 3 Classes of Intravenous bDMARD
Bibliographic record
Abstract
OBJECTIVE: To examine the rate, risks factors, and consequences of neutropenia induced by intravenous (IV) biologic disease-modifying antirheumatic drugs (bDMARD). METHODS: We conducted a retrospective cohort study in 499 patients with rheumatic diseases treated by IV abatacept (ABA), infliximab (IFX), or tocilizumab (TCZ). RESULTS: Rheumatoid arthritis (RA) was the most frequent diagnosis (72%). Fifty-two patients (10.4%) experienced at least 1 episode of neutropenia. No episodes of grade 4 neutropenia were documented. TCZ was more frequently related to neutropenia than ABA or IFX (18.6% vs 3.8% and 2.8%, respectively, p < 0.001). The following factors were identified as predictors of experiencing neutropenia with IV bDMARD: history of neutropenia with methotrexate (MTX; synthetic DMARD; OR 1.56, 95% CI 1.17-7.14), concomitant treatment by MTX (OR 1.21, 95% CI 1.01-2.64), and TCZ treatment (OR 2.72, 95% CI 1.53-9.05). Patients experiencing a TCZ-induced neutropenia did not show a higher risk of severe infections; however, this group had a shorter drug survival (9 mos vs 20 mos, p < 0.02) compared with TCZ patients without neutropenia. CONCLUSION: Among 3 different classes of IV bDMARD, TCZ is associated with the higher risk of neutropenia. No increased frequency of infection episodes was documented in this group.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".