Economic evaluation of arsenic trioxide compared to all‐trans retinoic acid + conventional chemotherapy for treatment of relapsed acute promyelocytic leukemia in Canada
Bibliographic record
Abstract
OBJECTIVES: Acute promyelocytic leukemia (APL) is an uncommon type of acute leukemia characterized by high early mortality. Current first-line treatments include all-trans retinoic acid (ATRA), anthracyclines, and other conventional chemotherapies (CTs). Although APL is generally associated with a good prognosis, about 20% of patients who achieve remission subsequently relapse and are resistant to the previously administrated treatment. The objective of this study was to assess, from a Canadian perspective, the economic impact of arsenic trioxide (ATO) compared to ATRA+CT for treatment of patients with relapsed/refractory APL. METHODS: The cost-effectiveness of ATO compared to ATRA+CT for treating patients with relapsed/refractory APL was assessed over a lifetime horizon using a Markov model. The model considers five health states: induction, second remission, treatment failure or relapse, postfailure, and death. Markov cycle length was 1 month for the first 24 months and 1 yr thereafter. The model also takes into account the incidence of grade 3-4 adverse events reported in clinical trials. Analyses were conducted from a Canadian Ministry of Health (MoH) and a societal perspective. RESULTS: Compared to ATRA+CT, ATO was associated with incremental cost-effectiveness ratios of $ 20,551/quality-adjusted life year (QALY) from a MoH perspective and $ 22,219/QALY from a societal perspective. Results of the probabilistic sensitivity analysis indicated that ATO is a cost-effective strategy in 99.27% and 98.98% of the simulations from a MoH and a societal perspective, respectively. CONCLUSIONS: This economic evaluation demonstrates that ATO is a cost-effective strategy compared to ATRA+CT for treatment of patients with relapsed/refractory APL in Canada.
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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".