Evaluating the Economic Burden of Acute Myeloid Leukemia in Canada
Bibliographic record
Abstract
INTRODUCTION: Acute myeloid leukemia (AML) represents a significant burden for patients and their families, and to the healthcare system. This study estimated the total cost of illness associated with newly diagnosed AML patients in Canada. METHODS: The economic burden of AML was estimated using an incidence-based model, analyzing different types of AML cases in Canada. Direct and indirect costs were calculated using scientific literature and Canadian clinical experts' inputs. Patients were categorized depending on their eligibility for intensive chemotherapy (fit and unfit patients) as well as according to age and cytogenetic markers. RESULTS: The total average cost of AML per patient is estimated to be CAD 178,073 with a cost of CAD 210,983 and CAD 145,163 for fit and unfit patients, respectively. The costs related to treatment represent half of the total average cost (52%), followed by hematopoietic stem cell transplant (23%), best supportive care (16%), productivity loss (6%), and wastage (4%). CONCLUSION: For patients with AML, the costs associated with fit patients are higher than unfit patients. Hospitalization and best supportive care costs are key cost drivers for the total costs of fit and unfit patients, respectively. This study highlights that AML is associated with a significant economic burden in Canada.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".