VKORC1 and CYP2C9 genotype and patient characteristics explain a large proportion of the variability in warfarin dose requirement among children
Bibliographic record
Abstract
Although genetic and environmental factors explain approximately half of the interindividual variability in warfarin dose requirement in adults, there is limited information available in children. In a cross-sectional study of anticoagulated children from 5 tertiary care centers, 120 children with a stable warfarin dose were genotyped for VKORC1 (-1639G > A; rs9923231), CYP2C9 (*2 and *3 alleles; rs1799853 and rs1057910), and CYP4F2 (V433M; rs2108622) polymorphisms. Clinical and demographic features were recorded. Multiple regression analysis of the data showed that, although CYP4F2 made no contribution to the dose model, 72.4% of the variability in warfarin dose requirement is attributed to by patient height, genetic polymorphisms in VKORC1 and CYP2C9, and indication for warfarin. The recently published International Warfarin Pharmacogenetics Consortium pharmacogenetic-based warfarin dosing algorithm (based on data derived from anticoagulated adults) consistently overestimated warfarin dose for our cohort of children. A similar proportion of the interindividual variability in warfarin dose is explained by genetic factors in children compared with adult patients, although height is a greater predictor in children. A pharmacogenomic approach to warfarin dosing has the potential to improve the efficacy and safety of warfarin therapy in children. However, algorithms should be derived from data in children if their potential benefit is to be realized.
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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 | 0.001 | 0.000 |
| 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) | 0.000 | 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".