Harmonization of Busulfan Plasma Exposure Unit (BPEU): A Community-Initiated Consensus Statement
Bibliographic record
Abstract
Busulfan therapeutic drug monitoring (TDM) is often used to achieve target plasma exposures. Variability in busulfan plasma exposure units (BPEU) is a potential source for misinterpretation of publications and protocols and is a barrier to data capture by hematopoietic cell transplantation (HCT) registry databases. We sought to harmonize to a single BPEU for international use. Using Delphi consensus methodology, iterative surveys were sent to an increasing number of relevant clinical stakeholders. In survey 1, 14 stakeholders were asked to identify ideal properties of a BPEU. In survey 2, 52 stakeholders were asked (1) to evaluate BPEU candidates according to ideal BPEU properties established by survey 1 and local position statements for TDM and (2) to identify potential facilitators and barriers to adoption of the harmonized BPEU. The most frequently used BPEU identified, in descending order, were area under the curve (AUC) in μM × min, AUC in mg × h/L, concentration at steady state (Css) in ng/mL, AUC in μM × h, and AUC in μg × h/L. All respondents conceptually agreed on the ideal properties of a BPEU and to adopt a harmonized BPEU. Respondents were equally divided between selecting AUC in μM × min versus mg × h/L for harmonization. AUC in mg × h/L was finally selected as the harmonized BPEU, because it satisfied most of the survey-determined ideal properties for the harmonized BPEU and is read easily understood in the clinical practice environment. Furthermore, 10 major professional societies have endorsed AUC in mg × h/L as the harmonized unit for reporting to HCT registry databases and for use in future protocols and publications.
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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 | 0.293 | 0.190 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.005 | 0.007 |
| Open science | 0.008 | 0.015 |
| Research integrity | 0.011 | 0.012 |
| 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".