Correlation of Anticancer Drug Prices with Outcomes of Overall Survival and Progression-Free Survival in Clinical Trials in Japan
Bibliographic record
Abstract
Drug pricing methods vary extensively across countries. Japan calculates drug prices using cost accounting and based on the efficacy of similar drugs. This study investigated the relationship between drug prices and their clinical efficacy and usefulness using public information on anticancer drugs reimbursed by the National Health Insurance price listing between January 2009 and March 2020. We investigated drug characteristics, prices, and clinical benefits based on overall survival (OS) and progression-free survival (PFS). Eighty anticancer drugs were approved in Japan during the study period. The largest number (28 drugs, 35.0%) was approved based on PFS, 18 (22.5%) were approved based on OS, and 13 (16.3%) based on the response rate. The mean (±SD) drug price was JPY 88,416.2 (±148,974.7), while the median drug price (with quartiles) was JPY 21,694 (JPY 4855.0-JPY 93,396.8). Drug prices were significantly higher for PFS than for OS, while cost index-the drug price to extend PFS or OS by one day-did not differ significantly between PFS and OS. The relationship between the 46 drugs approved based on OS or PFS and their prices was examined. A correlation was found between drug prices and their clinical usefulness in terms of OS but not PFS.
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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 | 0.012 | 0.073 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".