A cost effectiveness analysis of thiopurine methyltransferase testing for guiding 6‐mercaptopurine dosing in children with acute lymphoblastic leukemia
Bibliographic record
Abstract
BACKGROUND: An increased understanding of the genetic basis of disease creates a demand for personalized medicine and more genetic testing for diagnosis and treatment. The objective was to assess the incremental cost-effectiveness per life-month gained of thiopurine methyltransferase (TPMT) genotyping to guide doses of 6-mercaptopurine (6-MP) in children with acute lymphoblastic leukemia (ALL) compared to enzymatic testing and standard weight-based dosing. PROCEDURE: A cost-effectiveness analysis was conducted from a health care system perspective comparing costs and consequences over 3 months. Decision analysis was used to evaluate the impact of TPMT tests on preventing myelosuppression and improving survival in ALL patients receiving 6-MP. Direct medical costs included laboratory tests, medications, physician services, pharmacy and inpatient care. Probabilities were derived from published evidence. Survival was measured in life-months. The robustness of the results to variable uncertainty was tested in one-way sensitivity analyses. Probabilistic sensitivity analysis examined the impact of parameter uncertainty and generated confidence intervals around point estimates. RESULTS: Neither of the testing interventions showed a benefit in survival compared to weight-based dosing. Both test strategies were more costly compared to weight-based dosing. Incremental costs per child (95% confidence interval) were $277 ($112, $442) and $298 ($392, $421) for the genotyping and phenotyping strategies, respectively, compared to weight-based dosing. CONCLUSIONS: The present analysis suggests that screening for TPMT mutations using either genotype or enzymatic laboratory tests prior to the administration of 6-MP in pediatric ALL patients is not cost-effective.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.005 |
| 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".