Modeling and Simulation to Inform Apixaban Dosing in Pediatrics With Acute Lymphoblastic Leukemia or Lymphoblastic Lymphoma Treated With Asparaginase
Bibliographic record
Abstract
Apixaban could be a potential treatment option for the prevention of venous thromboembolism (VTE) in children with acute lymphoblastic leukemia (ALL) or lymphoblastic lymphoma (LL). This analysis describes an updated two-compartment population pharmacokinetic (PPK) model that characterizes the PK variability of apixaban in pediatric patients with ALL or LL treated with asparaginase using PK data from a phase III study (PREVAPIX). Patient type of ALL or LL was found to be a significant covariate on the apparent central volume of distribution (Vc/F) and first-order absorption rate (Ka). Pediatric patients (aged 9 months to < 18 years) with ALL or LL had a 52.4% lower Ka compared with adults; this was 81.1% lower than other pediatric patients (9 months to < 18 years) at risk of VTE. Apixaban Vc/F was estimated to be 43.1% lower in pediatric patients compared with adult patients. The updated PPK model was used to simulate and confirm apixaban fixed-dose by weight-tiered regimen-achieved target exposures in pediatric patients (aged 28 days to < 18 years) with ALL or LL. In addition, a PK/pharmacodynamic (PD) analysis was performed using a linear regression model to characterize the relationship between anti-FXa activity (AXA) and apixaban concentration in pediatric patients with ALL or LL. The characterization of apixaban PK and PK/PD in this analysis contributes to evidence that apixaban could be a potential antithrombotic option in pediatric patients.
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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) | 0.001 | 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 | 0.000 |
| 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".