Cost-minimization analysis of treprostinil vs. epoprostenol as an alternate to oral therapy non-responders for the treatment of pulmonary arterial hypertension
Bibliographic record
Abstract
INTRODUCTION: Idiopathic pulmonary arterial hypertension (IPAH) is associated with substantial morbidity and mortality. Treprostinil was compared to epoprostenol for the economic impact of treating IPAH patients who failed or were not candidates for bosentan. METHODS: The model was a cost-minimization analysis, assuming clinical equivalence was achieved by proper dosing of both drugs, in terms of survival and surrogate measures. Two theoretical cohorts of 270 patients were treated with subcutaneous treprostinil and intravenous epoprostenol, and were evaluated over 3 years using a spreadsheet model. Annual survival rates were estimated for the cohorts so that at endpoint 114 (42%) patients survived in both groups. The model utilized resource valuation data for medication and supply costs from Medicare; hospital, consultation, surgical, and diagnostic procedural fees from North Carolina hospitals; and costs to treat adverse events from published sources. Costs were obtained from standard lists and were presented as 2003 US dollars, discounted at 3%. Sensitivity analyses were performed testing all model uncertainties. RESULTS: In the base case analysis, treprostinil demonstrated savings of 22,701 US dollars and 37,433 US dollars per patient over 1- and 3-year time horizons, respectively. The greatest savings came from reduced or minimal hospitalizations attributed to the dose titration and treatment of adverse events, such as sepsis, associated with epoprostenol and its delivery system. Probabilistic sensitivity analyses resulted in average 3-year cost-savings of 41,051 US dollars (Standard Deviation = 13,902 US dollars) per patient. CONCLUSIONS: By initiating and continuing treatment with treprostinil over a 3-year period, the economic burden associated with IPAH may be reduced compared to treatment with epoprostenol. The greatest saving with treprostinil was attributed to decreased sepsis.
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".