Surrogate Endpoints for Overall Survival in Immune-Oncology Trials of Advanced Gastro-Esophageal Carcinoma
Bibliographic record
Abstract
Background: We aimed to assess whether the Response Evaluation Criteria in Solid Tumors (RECIST)-based objective response rate (ORR), disease control rate (DCR) and progression-free survival (PFS) could serve as surrogate endpoints for overall survival (OS) in immune-oncology (IO) trials of advanced gastro-esophageal (GE) carcinoma. Methods: Randomized controlled trials (RCTs) of IO that reported RECIST-based endpoints and OS in advanced GE carcinoma were screened. Surrogacy of endpoints for OS was assessed based on the correlation between endpoints with OS (arm-level), and between treatment effects on endpoints (trial-level). The correlations were quantified by Pearson correlation coefficient (R). Leave-one-out cross-validation was used to assess the prediction accuracy of surrogate model. Results: Seventeen RCTs (9,657 subjects) with 20 comparisons were included. The correlations between DCR and OS were not strong at arm- (R = 0.80) and trial-levels (R = 0.45), but strong correlations between ORR (R = 0.91), PFS (R = 0.89) and OS at arm-level were observed. Treatment effect on ORR and PFS (both R = 0.71) was moderately correlated with treatment effect on OS. Leave-one-out cross-validation approach further validated the surrogacy of PFS. Our analysis showed that 3-month PFS could reliably predict 6-month OS, 6-month PFS could reliably predict 12-month OS, and 12-month PFS could reliably predict 18-month OS. The conservative minimum threshold effect of HR PFS was 0.73. Conclusions: PFS may be the appropriate surrogate for OS in IO trials of GE carcinoma. A conservative minimum threshold effect of HR PFS ? 0.73 has the potential to predict a significant improvement in OS. World J Oncol. 2022;13(3):126-135 doi: https://doi.org/10.14740/wjon1481
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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 | 0.007 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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 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".