Potential approaches for the pricing of cancer medicines across Europe to enhance the sustainability of healthcare systems and the implications
Bibliographic record
Abstract
Introduction: There are growing concerns among European health authorities regarding increasing prices for new cancer medicines, prices not necessarily linked to health gain and the implications for the sustainability of their healthcare systems.Areas covered: Narrative discussion principally among payers and their advisers regarding potential approaches to the pricing of new cancer medicines.Expert opinion: A number of potential pricing approaches are discussed including minimum effectiveness levels for new cancer medicines, managed entry agreements, multicriteria decision analyses (MCDAs), differential/tiered pricing, fair pricing models, amortization models as well as de-linkage models. We are likely to see a growth in alternative pricing deliberations in view of ongoing challenges. These include the considerable number of new oncology medicines in development including new gene therapies, new oncology medicines being launched with uncertainty regarding their value, and continued high prices coupled with the extent of confidential discounts for reimbursement. However, balanced against the need for new cancer medicines. This will lead to greater scrutiny over the prices of patent oncology medicines as more standard medicines lose their patent, calls for greater transparency as well as new models including amortization models. We will be monitoring these developments.
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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 | 0.041 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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; both teacher heads agree on what is shown here.
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".