Evaluating the American Society of Clinical Oncology (ASCO) and European Society of Medical Oncology (ESMO) value frameworks for Food and Drug Administration (FDA) approved checkpoint inhibitors (CIs).
Bibliographic record
Abstract
6624 Background: Although the development of CIs has led to a dramatic change in the oncology landscape, these agents are associated with significant costs and toxicity. ASCO and ESMO have developed separate frameworks to define the value of emerging cancer treatments in order to encourage cost-effective therapies. We apply these frameworks to trials supporting FDA approvals of CIs and explore the correlation between these two scoring systems. Methods: We searched the FDA database for CIs and indications approved between January 1, 2011 and January 1, 2019. Only randomized phase II/III trials for solid tumors were included. Data on survival, toxicity and quality of life were extracted from the most recent publications by two reviewers independently. A trial showing a substantial benefit was defined as an ASCO score of ≥ 45, or ESMO Grade 4-5 (palliative setting) or Grade A/B (curative setting). Concordance for substantial benefit was assessed using Cohen’s Kappa while Spearman coefficients were used to determine the degree of correlation in individual scores. Results: We identified 40 FDA indications for 7 CIs. Of these, 18 indications based on Phase I/II single-arm trials were excluded. The remaining 22 indications were based on 21 randomized phase II/III trials (3 adjuvant, 18 metastatic). In the palliative setting, 73% and 86% trials showed substantial benefit based on ASCO and ESMO frameworks respectively [median ASCO score: 54.8, interquartile range (IQR) 46.2-64.0; median ESMO score: 5, IQR: 4-5]. 27% of trials were scored intermediate or low benefit by ASCO, while 9% were ineligible for ESMO scoring. Weighted kappa was 0.719 between the two frameworks. Spearman rho was 0.84. All 3 adjuvant trials were assigned ESMO grade A but low benefit with ASCO (median 37.7, IQR 20.5-40.9). Conclusions: In the palliative setting, the majority of trials supporting FDA approved CI indications demonstrated substantial benefit using both ASCO and ESMO frameworks. There was a strong correlation between the two frameworks. However, in the curative setting scores were discordant. The ASCO framework may require further refinement for adjuvant trials.
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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 | 0.245 | 0.458 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.010 |
| Bibliometrics | 0.033 | 0.024 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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; the direct Gemma label and the distilled Codex classifier 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".