Cost-Effectiveness Analysis of a HMGA2 Prognostic Test for Acute Myeloid Leukemia in a Canadian Setting
Bibliographic record
Abstract
BACKGROUND: Current strategies for risk stratification of patients with acute myeloid leukemia assign approximately 40% of patients to the intermediate-risk group, where uncertainty about optimal therapy still persists. OBJECTIVE: expression, which improves genetic risk stratification in acute myeloid leukemia, and compare this test with the current standard of care in Canada. METHODS: A cost-effectiveness model was developed from the Canadian National Healthcare Service and societal perspective using data from the Quebec Leukemia Cell Bank, published literature, and physician surveys. The model includes a lifetime horizon assessing the HMGA2 test vs. standard of care. RESULTS: The HMGA2 test outperformed the standard of care at all time horizons culminating with estimated improvements of 1.92 and 3.12 months in leukemia-free survival and overall survival, respectively. Costs associated with the HMGA2 test were consistently lower, except diagnostic costs, routine medical costs, and costs related to infections and false positives. From a societal perspective, total lifetime costs were $161,358 CAD and $151,908 CAD with the standard of care and the HMGA2 test, respectively. The incremental quality-adjusted life-year gain was 0.138, which led to dominance over the standard of care. Deterministic sensitivity analyses confirmed the results of the base-case scenario. Probabilistic sensitivity analyses revealed that for a willingness-to-pay threshold of $100,000 CAD, the probability of cost effectiveness was 87.19%. CONCLUSIONS: The HMGA2 test is estimated to improve leukemia-free survival and overall survival outcomes, and yield costs savings from a healthcare system and societal perspective.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| 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".