Therapeutic Drug Monitoring of Busulfan in Transplantation
Bibliographic record
Abstract
Busulfan is the only agent used in myeloablative regimens for hematopoietic stem cell transplantation for which therapeutic drug monitoring (TDM) has been widely used. Studies of oral busulfan (Bu) indicate wide intrapatient and interpatient variations in pharmacokinetic (PK) behavior, particularly in children. Dose adjustments of oral Bu based on TDM to bring exposures within established therapeutic ranges have been shown to reduce toxicity and improve outcomes. Intravenous (IV) Bu is becoming more widely used and has much more predictable PK. Outcomes with IV Bu appear to be superior to those achieved using oral Bu without TDM. However there is still at least a threefold variation in exposures achieved by the same dose of IV Bu in different individuals and a small proportion of patients will experience toxic exposures with current dosing regimens. Therapeutic monitoring with appropriate dose adjustment is therefore recommended for all patients treated with regimens containing high doses of Bu. Giving IV Bu at a fixed rate to adults will narrow the range of exposures but more work is needed to establish the best dosing regimen to bring as many exposures as possible within the target range. Studies of test dosing of IV Bu show that this strategy is more accurate when test and treatment doses are infused at the same rate. Finally, targeting exposures to the upper end of the therapeutic range may provide a safe approach to exploiting dose-intensity for the treatment of some malignancies.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".