Rasburicase Real-World Usage for the Prevention and Treatment of Tumor Lysis Syndrome in Adults and Children
Bibliographic record
Abstract
BACKGROUND: Rasburicase is used to prevent and treat tumor lysis syndrome (TLS) by breaking down uric acid. Administration methods vary, including fixed, weight-based (0.15-0.2 mg/kg), single and multiple doses. Our primary objective is to describe rasburicase use in both adults and children for TLS prevention and treatment. Secondary objectives are to describe the efficacy and safety of different regimens inventoried. Exploratory objective is to estimate savings associated with use of a single fixed dose. METHODS: Retrospective descriptive study conducted among patients who received rasburicase for TLS prevention or treatment between January 2014 and April 2024 in 3 oncology services of the Hospital Center. RESULTS: A total of 133 adults and 60 children were included, of which 42.9% and 5.0%, respectively, presented biochemical TLS pre-rasburicase. A single 6 mg dose was administered in 86.5% of adults and 21.7% of children. Multiple daily doses were used in 24.8% of adults and 76.7% of children. Few adults (1.5%) received weight-based doses, contrary to children (76.7%). Normalized uric acid (< 476 μmol/L) was observed in 97.9% of patients 24 hours after a first dose, with no serious adverse events. Estimated savings were 86 542.92 CA$ if all patients included (n = 193) received a single 0.15 mg/kg dose, capped at 6 mg. CONCLUSION AND RELEVANCE: In the adult and pediatric population, a single rasburicase dose of 0.15 to 0.2 mg/kg, capped at 6 mg, represents an effective, safe, and more cost-effective option for both the prevention and treatment of TLS. Further studies are warranted to compare single versus multiple dosing in pediatric populations and to identify potential risk factors for nonresponders.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".