Application of the ASCO Value Framework and ESMO Magnitude of Clinical Benefit Scale to assess the value of abiraterone acetate (AA) and enzalutamide (E) in advanced prostate cancer: clinical value and cost considerations.
Bibliographic record
Abstract
276 Background: AA and E improve overall survival (OS) in metastatic castration resistant prostate cancer (mCRPC). AA also improves OS in metastatic castration sensitive disease (mCSPC). However, concerns exist over the cost implications of earlier treatment versus the clinical benefit gained. We aimed to quantify and compare the clinical value of AA and E and their drug costs in both the mCRPC and mCSPC settings. Methods: We identified 6 randomized Phase 3 trials of AA and E in mCRPC and mCSPC. Net clinical benefit was quantified by the ASCO Value Framework version 2 (range < 180) and ESMO MCBS version 1.1 (range 1-5)—both consider benefits in overall survival, progression free survival, and quality of life, against increase in drug toxicity. A higher score indicates greater value. Incremental cancer drug costs were also calculated, using average wholesale price from the REDBOOK and the trials’ reported duration of treatment. Results: (Table). Conclusions: AA and E administered in early mCSPC do not provide consistent increases in net clinical benefit compared to mCRPC, but they incur exponential cost considerations. Alternatives such as chemotherapy, which may provide similar net clinical benefit at less incremental costs, still warrant major consideration for clinicians and patients. Until more information is available to define the optimal sequencing of AA, E and other available treatment modalities, current cost implications may hinder moving these agents to earlier treatment settings.[Table: see text]
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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 | 0.027 | 0.091 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.004 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".