The Cost Effectiveness of Erythropoietin-Stimulating Agents for Treating Anemia in Patients on Dialysis: A Systematic Review
Bibliographic record
Abstract
BACKGROUND: Anemia is a common complication associated with kidney failure and is marked by poor health and increased risk of morbidity and mortality. There are ongoing concerns with the use of Erythropoietin Stimulating Agents (ESAs) to treat anemia in patients with kidney failure on dialysis. Questions as to their benefits, harms and overall effect on quality of life are still relevant today. Our objective was to systematically review studies evaluating the cost-effectiveness of ESAs in patients with kidney failure on dialysis. METHODS: We performed a systematic review of studies determining the cost-effectiveness of ESAs in adult patients on dialysis. Databases, including PubMed, EMBASE, and Cochrane Database of Systematic Reviews, were searched from their establishment until June 2013. Studies that reported an incremental cost-effectiveness ratio of hemoglobin correction strategies based on ESA treatments in comparison to red blood cell transfusions, lower hemoglobin targets, or no ESA treatment were included. RESULTS: Seven studies met inclusion criteria. Reported cost/quality-adjusted life-year (QALY) ratios ranged from USD 931-677,749/QALY across five studies comparing ESAs to red blood cell transfusions. There was heterogeneity in results when considering higher hemoglobin targets, with studies finding higher targets to be both dominant and dominated. Mortality, hospitalization, and utility estimates were major drivers. CONCLUSIONS: There is substantial variability in the estimates of the cost-effectiveness of using ESAs in the dialysis population. New models incorporating recent meta-analyses for estimates of utility, mortality, and hospitalization changes would allow for a more comprehensive answer to this question.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.007 | 0.001 |
| Bibliometrics | 0.000 | 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 | 0.001 |
| 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".