A Global Comparison of Liver Transplant Drug Pricing: US Versus Other G7 Countries and Australia
Bibliographic record
Abstract
Background: A major contributor to increased healthcare spending in the United States is drug pricing, as US drug prices are nearly 3× higher than those in other countries. This cross-sectional study aimed to investigate current global price differences in liver transplant medications and provide potential cost savings for Medicare Part D if international reference pricing was adopted. Methods: Publicly available drug formularies for Canada, the United Kingdom, Japan, France, Germany, Italy, and Australia were used to collect 2024 prices for 8 commonly used liver transplant medications (mycophenolate mofetil, mycophenolate sodium, sirolimus, tacrolimus, Advagraf, Envarsus, everolimus, and cyclosporine). US prices were obtained from UptoDate's 2024 listed representative average wholesale prices and Medicare Part D's drug prices from 2022. Results: The average US wholesale price and Medicare spend for originator liver transplant medications were 4.1× and 6.8×, respectively, the average originator prices in G7 countries and Australia. Adopting the average global originator drug price per dose may lead to an estimated $26 141 463 in cost savings per year to Medicare. The average US wholesale price and Medicare spend for generic liver transplant medications were 2.76× and 3.75×, respectively, the global average generic prices. Adopting the average global generic drug price per dose may lead to an estimated $363 538 474 in cost savings per year to Medicare. Conclusions: This study demonstrates the significantly greater financial burden that liver transplant patients in the United States face compared with liver transplant patients in 7 other major industrial countries. Future adoption of international reference pricing may help bridge this pricing disparity.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".