Evaluation of Busulfan as a Third-Party Immunoassay on a Clinical Chemistry Analyzer
Bibliographic record
Abstract
BACKGROUND: Busulfan is widely used in conditioning regimens to prepare patients for hematopoietic stem cell transplantation. Therapeutic drug monitoring (TDM) is critical due to large inter- and intra-individual variability in busulfan pharmacokinetics, and the risk of adverse consequences of toxicity including hepatic veno-occlusive disease. Busulfan is most commonly measured by liquid chromatography-mass spectrometry (LC-MS/MS), which is not as widely available in clinical laboratories as automated routine clinical chemistry analyzers. The objective was to perform analytical verification of a busulfan immunoassay on the Abbott Alinity c platform. METHODS: The MyCare Oncology busulfan immunoassay was configured as a third-party reagent on the Abbott Alinity c. Imprecision, linearity, sample carryover, and onboard stability of reagent studies were evaluated. The performance of the busulfan immunoassay using the Abbott Alinity c was compared to the Beckman Coulter AU480 using sodium heparinized plasma, as well as to LC-MS/MS using lithium heparinized plasma. RESULTS: The imprecision goal of 8% was met, and linearity within the analytical measurement range of 240 to 1700 ng/mL was verified. Sample carryover was negligible, and the reagents were stable onboard for at least 84 days. The busulfan immunoassay correlated well with LC-MS/MS (slope = 0.949, y-intercept = -7.8 ng/mL, r2 = 0.9935) and the Beckman Coulter AU480 (slope = 1.090, y-intercept = -34.5 ng/mL, r2 = 0.9988). CONCLUSIONS: This study demonstrated successful analytical verification of a busulfan third-party immunoassay on the Abbott Alinity c platform. The ability to perform TDM of busulfan on a routine clinical chemistry analyzer will positively impact turnaround times to improve patient outcomes.
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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 | 0.017 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.001 |
| 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 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".