Association of busulfan exposure and outcomes after HCT for patients with an inborn error of immunity
Bibliographic record
Abstract
ABSTRACT: Allogeneic hematopoietic cell transplantation (HCT) is a potentially curative treatment strategy for patients with inborn errors of immunities (IEIs). The objective of this study was to assess the optimal busulfan exposure before allogeneic HCT for patients with an IEI who received an IV busulfan-based conditioning regimen. Patients from 17 international centers were included. The main outcome of interest was event-free survival (EFS). Patients were categorized into 4 IEI subgroups: combined immunodeficiency (CID), severe combined immunodeficiency (SCID), neutrophil disorders, and hemophagocytic lymphohistiocytosis (HLH)-related disorders. Busulfan exposure was calculated by individual centers (area under the curve [AUC]CENTER) and re-estimated using a nonlinear mixed-effects model (NONMEM; exposure defined as AUCNONMEM). Overall, 562 patients were included: 173 (30.8%) with CID, 154 (27.4%) with SCID, 101 (18.0%) with HLH-related disorders, and 134 (23.8%) with neutrophil disorders. The median busulfan AUCNONMEM was 69.0 mg × h/L and correlated poorly with the AUCCENTER (r2 = 0.54). In patients with SCID, HLH-related, and neutrophil disorders with a busulfan AUCNONMEM of 70 to 90 mg × h/L, 2-year EFS was superior to <70 mg × h/L, and >90 mg ×h/L. Full donor chimerism increased with higher busulfan AUCNONMEM, plateauing at 90 mg × h/L. For patients with CID, the optimal AUCNONMEM for donor chimerism was found to be >70 mg × h/L. Improved EFS and higher donor chimerism may be achieved by targeting a cumulative busulfan AUCNONMEM of 80 mg × h/L (range, 70-90). Our study stresses the importance of uniformly using a validated population pharmacokinetic model to estimate AUCNONMEM.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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".