Fixed dosing of alpelisib for children with vascular anomalies: Can we do better?
Bibliographic record
Abstract
Severe forms of vascular malformations (VM) can highly impact patients' quality of life and lead to life-threatening organ dysfunction. Numerous VM are caused by somatic activating mutations in the PI3K/AKT/mTOR signalling pathway. Alpelisib, a PIK3CA inhibitor was recently FDA-approved for paediatric PIK3CA-related overgrowth syndrome (PROS). However, an empiric and fixed dose of 50 mg was selected, irrespective of weight, in the absence of any pharmacokinetic (PK) data. We aim to report novel alpelisib PK data in children to support dosing decisions. Nine patients with severe VM (PROS: n = 4, other VM: n = 5) were included. Mean age was 10.5 years (SD = 5.2 years), and mean weight was 43 kg (SD = 24 kg). AUC on the fixed dose of 50 mg/day was highly variable (mean = 7035 ng*h/mL, SD = 4057, CV = 58%). AUC was correlated with weight. As short- and long-term adverse effects to alpelisib in children are unknown, a dosing based on PK data is urgently needed.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".