Data from Pharmacokinetics of Nilotinib in Pediatric Patients with Philadelphia Chromosome–Positive Chronic Myeloid Leukemia or Acute Lymphoblastic Leukemia
Bibliographic record
Abstract
AbstractPurpose: We investigated nilotinib exposure in pediatric patients with chronic myeloid leukemia (CML) or Philadelphia chromosome–positive (Ph+) acute lymphoblastic leukemia (ALL) resistant to, relapsed on, refractory to, or intolerant of previous treatment. Patients and Methods: Fifteen patients (aged 1–<18 years) with CML resistant to or intolerant of imatinib and/or dasatinib (n = 11) or Ph+ ALL relapsed on or refractory to standard therapy (n = 4) enrolled in this phase I study. Nilotinib (230 mg/m2 twice daily; equivalent to the adult 400-mg twice-daily dose) was administered orally in 12 or 24 cycles of 28 days. The primary objective was to characterize the pharmacokinetics of nilotinib in pediatric patients. Results: The area under the concentration–time curve at steady state was slightly lower in pediatric patients versus adults (14,751.4 vs. 17,102.9 ng/h/mL); the geometric mean ratio (GMR; pediatric:adult) was 0.86 [90% confidence interval (CI), 0.70–1.06]. Body surface area–adjusted systemic clearance was slightly higher in pediatric versus adult patients (GMR, 1.30; 90% CI, 1.04–1.62). Nilotinib was generally well tolerated. The most common adverse events were headache, vomiting, increased blood bilirubin, and rash. Three patients with CML achieved major molecular response, and three with Ph+ ALL achieved complete remission. Conclusions: Nilotinib 230 mg/m2 twice daily in pediatric patients provided a pharmacokinetics and safety profile comparable with the adult reference dose; clinical activity was demonstrated in both CML and Ph+ ALL. This dose is recommended for further evaluation in pediatric patients. The safety profile was consistent with that in adults.
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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 | 0.001 |
| 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".