Cost-effectiveness of eltrombopag vs intravenous immunoglobulin for the perioperative management of immune thrombocytopenia
Bibliographic record
Abstract
Eltrombopag has been shown to be noninferior to intravenous immunoglobulin (IVIG) for improving perioperative platelet counts in patients with immune thrombocytopenia (ITP) in a randomized trial; thus, cost is an important factor for treatment and policy decisions. We used patient-level data from the trial to conduct a cost-effectiveness analysis comparing perioperative eltrombopag 50 mg daily starting dose, with IVIG 1 or 2 g/kg (according to local practice) from a Canadian public health care payer's perspective over the observation period, from preoperative day 21 to postoperative day 28. Resource utilization data were obtained from the trial data (eltrombopag, n = 38; IVIG, n = 36), and unit costs were collected from the Ontario Schedule of Benefits, Ontario Drug Formulary, and secondary sources. All costs were adjusted to 2020 Canadian dollars. We calculated the incremental cost per patient for all patients randomized. Uncertainty was addressed using nonparametric bootstrapping. The use of perioperative eltrombopag for patients with ITP resulted in a cost-saving of $413 Canadian per patient. Compared with IVIG, the probability of eltrombopag being cost effective was 70% even with no willingness to pay. In a sensitivity analysis based on IVIG dose, we found that with the higher dose of IVIG (2 g/kg), eltrombopag saved $2,714 per patient, whereas with the lower dose of IVIG (1 g/kg), eltrombopag had a higher mean cost of $562 per patient. In summary, based on data from the randomized trial that demonstrated noninferiority, the use of eltrombopag for the management of ITP in the perioperative setting was less costly than IVIG.
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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 | 0.005 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.005 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".