Impact of Split Dosing the First Rituximab Infusion in Patients with High Lymphocyte Count
Bibliographic record
Abstract
The most common adverse reactions to rituximab are infusion-related reactions (IRR). We evaluated the efficacy of split dosing the first rituximab infusion over two days to reduce IRR incidence in patients with hematological cancer and a high lymphocyte count. This is a retrospective observational study conducted in two healthcare centers in Quebec, Canada. The study enrolled patients with white blood cell counts ≥25.0 × 109/L who received their first rituximab dose for hematological cancer between December 2007 and May 2020. One healthcare center used asymmetrical split dosing, while the other used symmetrical split dosing. A total of 183 treatment episodes were collected from 143 patients. Among patients who received a fractionated dosing schedule, 42% developed an IRR from the first rituximab infusion compared with 50% for the standard protocol (adjusted relative risk, 0.89; p = 0.540). No significant difference was observed in IRR severity between either groups. However, 24% of patients who received the asymmetrical protocol developed an IRR compared to 68% for the symmetrical protocol (adjusted relative risk, 0.32; p = 0.003). These results suggest that an asymmetrical split dosing could be effective in reducing the incidence of IRR and is preferable to a symmetrical one.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".