Economic evaluation of erythropoiesis‐stimulating agents for anemia related to cancer
Bibliographic record
Abstract
BACKGROUND: Erythropoiesis-stimulating agents (ESA) administered to cancer patients with anemia reduce the need for blood transfusions and improve quality-of-life (QOL). Concerns about toxicity have led to more restrictive recommendations for ESA use; however, the incremental costs and benefits of such a strategy are unknown. METHODS: The authors created a decision model to examine the costs and consequences of ESA use in patients with anemia and cancer from the perspective of the Canadian public healthcare system. Model inputs were informed by a recent systematic review. Extensive sensitivity analyses and scenario analysis rigorously assessed QOL benefits and more conservative ESA administration practices (initial hemoglobin [Hb] <10 g/dL, target Hb < or =12 g/dL, and chemotherapy induced anemia only). RESULTS: Compared with supportive transfusions only, conventional ESA treatment was associated with an incremental cost per quality-adjusted life year (QALY) gained of $267,000 during a 15-week time frame. During a 1.3-year time horizon, ESA was associated with higher costs and worse clinical outcomes. In scenarios where multiple assumptions regarding QOL all favored ESA, the lowest incremental cost per QALY gained was $126,000. Analyses simulating the use of ESA in accordance with recently issued guidelines resulted in incremental cost per QALY gained of > $100,000 or ESA being dominated (greater costs with lower benefit) in the majority of the scenarios, although greater variability in the cost-utility ratio was present. CONCLUSIONS: Use of ESA for anemia related to cancer is associated with incremental cost-effectiveness ratios that are not economically attractive, even when used in a conservative fashion recommended by current guidelines.
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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 | 0.009 | 0.033 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".