Cost-effectiveness of adding quizartinib to induction chemotherapy for patients with <i>FLT3-</i> mutant acute myeloid leukemia
Bibliographic record
Abstract
The FLT3 inhibitor quizartinib has been shown to improve overall survival when added to intensive induction chemotherapy (“7 + 3”) in patients 18-75 years old with newly diagnosed AML harboring a FLT3-ITD mutation. However, the health economic implications of this approval are unknown. We evaluated the cost-effectiveness of quizartinib using a partitioned survival analysis model. One-way and probabilistic sensitivity analyses were conducted. In the base case scenario, the addition of quizartinib to 7 + 3 resulted in incremental costs of $289,932 compared with 7 + 3 alone. With an incremental gain of 0.84 quality-adjusted life years (QALYs) with quizartinib + 7 + 3 induction vs. 7 + 3 alone, the incremental cost-effectiveness ratio for the addition of quizartinib to standard 7 + 3 was $344,039/QALY. Only an 87% reduction in the average wholesale price of quizartinib or omitting quizartinib continuation therapy after completion of consolidation therapy and allogeneic hematopoietic cell transplant would make quizartinib a cost-effective option.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.004 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".