Treosulfan Exposure Predicts Thalassemia‐Free Survival in Patients with Beta Thalassemia Major Undergoing Allogeneic Hematopoietic Cell Transplantation
Bibliographic record
Abstract
A toxicity-reduced conditioning regimen with treosulfan, fludarabine, and thiotepa in patients with high-risk β-thalassemia major has significantly improved hematopoietic stem cell transplantation (HCT) outcomes. However, complications resulting from regimen-related toxicities (RRTs), mixed chimerism, and graft rejection remain a challenge. We evaluated the dose-exposure-response relationship of treosulfan and its active metabolite S, S-EBDM, in a uniform cohort of patients with β-thalassemia major to identify whether therapeutic drug monitoring (TDM) and dose adjustment of treosulfan is feasible. Plasma treosulfan/S, S-EBDM levels were measured in 77 patients using a validated liquid chromatography with tandem mass spectrometry method, and the pharmacokinetic parameters were estimated using nlmixr2. The influence of treosulfan and S, S-EBDM exposure, and GSTA1/NQO1 polymorphisms on graft rejection, RRTs, chimerism status, and 1-year overall survival (OS), and thalassemia-free survival (TFS) were assessed. We observed that treosulfan exposure was lower in patients with graft rejection than those without (1,655 vs. 2,037 mg•h/L, P = 0.07). Pharmacodynamic modeling analysis to identify therapeutic cutoff revealed that treosulfan exposure ≥1,660 mg•hour/L was significantly associated with better 1-year TFS (97% vs. 81%, P = 0.02) and a trend to better 1-year OS (90% vs. 69%, P = 0.07). Further, multivariate analysis adjusting for known pre-HCT risk factors also revealed treosulfan exposure <1,660 mg•h/L (hazard ratio (HR) = 3.23; 95% confidence interval (CI) = 1.12-9.34; P = 0.03) and GSTA1*B variant genotype (HR = 3.75; 95% CI = 1.04-13.47; P = 0.04) to be independent predictors for inferior 1-year TFS. We conclude that lower treosulfan exposure increases the risk of graft rejection and early transplant-related mortality affecting TFS. As no RRTs were observed with increasing treosulfan exposure, TDM-based dose adjustment could be feasible and beneficial.
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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 | 0.000 | 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) | 0.001 | 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 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".