MO551A COST-OFFSET ANALYSIS OF THE ROXADUSTAT DIALYSIS-DEPENDENT GLOBAL PHASE 3 PROGRAM: A CANADIAN HEALTHCARE PERSPECTIVE
Bibliographic record
Abstract
Abstract Background and Aims Chronic kidney disease (CKD) is a costly public health issue, which affects 13.4% of the population globally. Anaemia is a common complication in patients with CKD resulting in reduced health-related quality of life and high healthcare costs. The objective of this analysis was to estimate the direct medical care cost offsets of the investigational agent roxadustat for the treatment of anaemia in patients with dialysis-dependent (DD) CKD from a Canadian healthcare perspective. Method Data from the roxadustat global phase 3 program were used to estimate the incidence of rescue therapy or iron supplementation use (i.e. intravenous iron, erythropoiesis-stimulating agents [ESAs] or red blood cell transfusions) and major adverse cardiovascular events (MACE+) for roxadustat compared with ESAs in DD patients with anaemia of CKD. MACE+ included myocardial infarction, stroke, unstable angina requiring hospitalization, congestive heart failure (CHF) requiring hospitalization, cardiovascular death and other death. Published Canadian cost data were used to estimate event costs. Drug acquisition costs for roxadustat and ESAs were not considered. A hypothetical cohort of 10,000 Canadian adult DD patients (90% undergoing haemodialysis, 10% undergoing peritoneal dialysis) with treatable anaemia was modelled to determine net medical care cost offsets annually and cumulatively compared with ESAs over a 4-year time horizon. Results Preliminary results for patients with DD CKD show that, compared with ESAs, roxadustat could produce sizeable net medical care cost offsets resulting from reductions in rescue therapy or iron supplementation use, specifically red blood cell transfusions, and from reductions in MACE+, specifically CHF hospitalizations. For the entire cohort of patients with DD CKD, cumulative medical care cost offsets for roxadustat were an estimated $162,609 for rescue therapy or iron supplementation use and $1,027,070 for MACE+ compared with ESAs. Conclusion This analysis provides evidence that treatment with roxadustat in DD patients with anaemia of CKD could result in considerable medical care cost offsets for roxadustat compared with ESAs.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".