In A Survey, Marked Inconsistency In How Oncologists Judged Value Of High-Cost Cancer Drugs In Relation To Gains In Survival
Bibliographic record
Abstract
Amid calls for physicians to become better stewards of the nation's health care resources, it is important to gain insight into how physicians think about the cost-effectiveness of new treatments. Expensive new cancer treatments that can extend life raise questions about whether physicians are prepared to make "value for money" trade-offs when treating patients. We asked oncologists in the United States and Canada how much benefit, in additional months of life expectancy, a new drug would need to provide to justify its cost and warrant its use in an individual patient. The majority of oncologists agreed that a new cancer treatment that might add a year to a patient's life would be worthwhile if the cost was less than $100,000. But when given a hypothetical case of an individual patient to review, the oncologists also endorsed a hypothetical drug whose cost might be as high as $250,000 per life-year gained. The results show that oncologists are not consistent in deciding how many months an expensive new therapy should extend a person's life before the cost of therapy is justified. Moreover, the benefit that oncologists demand from new treatments in terms of length of survival does not necessarily increase according to the price of the treatment. The findings suggest that policy makers should find ways to improve how physicians are educated on the use of cost-effectiveness information and to influence physician decision making through clinical guidelines that incorporate cost-effectiveness information.
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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 | 0.053 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".