P97 Busulfan/sulfolane metabolic ratio on the third day of conditioning may predict the event-free survival in children receiving busulfan based conditioning prior to hematopoietic stem-cell transplantation
Bibliographic record
Abstract
Background Busulfan (Bu) is widely used as a component of myeloablative conditioning regimen before hematopoietic stem cell transplantation (HSCT) in children. Obtaining the ratio of Bu to its metabolite sulfolane i.e. metabolic ratio (MR) may serve as an indicator of Bu GSH conjugating capacity of an individual. Objective To evaluate the utility of Bu MR to predict EFS in children undergoing allogeneic HSCT. Methods Two different cohorts with children receiving Bu in four times daily (QID, n=44) and once daily doses (QD, n=13) at St. Justine’s Hospital, Montreal were studied. Bu and Su levels were measured on day 3 of the conditioning regimen at the end of infusion (dose 9 in QID or dose 3 in QD dosing). EFS was defined from the time of transplant until death, relapse, or rejection, whichever occurred first. A receiver-operator characteristic curve (ROC) of Bu MRs was analyzed in relation to EFS. Cutoff values were defined based on the Youden´s J statistic. Results Twenty-two males and 22 females aged from 0.1 to 19.9 years (mean±SD: 7.2 ± 5.7) from Bu QID cohort had the mean MR of 5.9 (SD: 3.2). A cut off value of 4.9 in MR was chosen in ROC analysis in this cohort, with better sensitivity (71%) and specificity (70%) for EFS prediction (p=0.01, AUC= 0.7 (95% CI= 0.6–0.8). In QD cohort nine females, and four males aged between 0.4 and 15.8 years (6.7±5.1) had the mean MR of 29.3 (SD: 16.6). In ROC analysis, a cut off value of 25.06 was chosen with better sensitivity (100%) and specificity (100%) for EFS prediction (p=0.003; AUC=1.0). Conclusion The Bu MR on day 3 above 4.973 and 25.06 were associated with worse EFS in children undergoing HSCT and received Bu in QID and QD dosing schedules, respectively. Disclosure(s) Nothing to disclose
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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 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".