A simplified method for busulfan monitoring using dried blood spot in combination with liquid chromatography/tandem mass spectrometry
Bibliographic record
Abstract
RATIONALE: Busulfan (Bu) is an important component of the myeloablative conditioning regimen prior to hematopoietic stem cell transplantation (HSCT) especially in children. Intravenously administered Bu exhibits a therapeutic window phenomenon requiring therapeutic drug monitoring. Analytical methods developed for Bu routine monitoring were aimed at using low volumes of biological fluids and development of simple procedures to facilitate the dosage adjustment. In this report, we describe a simple, rapid method for Bu measurement using dried blood spots (DBS) from only 5 μL of whole blood. METHODS: Bu extracted from DBS with methanol was measured by high-performance liquid chromatography with electrospray ionization and tandem mass spectrometry in multiple reaction monitoring mode using D8-Bu as an internal standard. The method was in-house validated evaluating trueness, repeatability, within-laboratory reproducibility, specificity and the lower limit of quantification (LLOQ). RESULTS: The method was linear in the calibration range of 100-2000 ng mL(-1) (r(2)>0.99) encompassing the therapeutic concentrations of Bu. A good trueness (<14%), precision (<10%), and recovery (100%) were observed during validation of the method with quality controls of 300, 600 and 1400 ng mL(-1). The LLOQ was determined as 50 ng mL(-1) and no matrix or carryover effects were observed. The validated method was applied to measure Bu levels in four children receiving infusion of Bu prior to HSCT. A good correlation was observed between the Bu levels measured by DBS and dried plasma spot (DPS) (r(2) =0.96) and between DPS and the GC/MS method (r(2) =0.92). Bu was found to be stable in DBS up to 6 h at room temperature and for 24 h at 4 °C. CONCLUSIONS: The new DBS method facilitates earlier dosage adjustment during Bu therapy by its specific and simple procedure using 5 μL of whole blood.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.004 |
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".