Progression free survival (PFS) as a surrogate endpoint for overall survival (OS) in first-line advanced ovarian cancer (AOC) therapy: A Gynecologic Cancer InterGroup individual (GCIG) patient-level (IPD) analysis of multiple randomized trials.
Bibliographic record
Abstract
5576 Background: OS is considered the gold standard endpoint for controlled clinical trials but it requires extended follow-up (median OS > 40 months for first line therapy) and large sample sizes. Our objective was to evaluate whether PFS based on CA125 measurements confirmed by radiological exam or on combined GCIG criteria is a surrogate endpoint for OS in AOC. Methods: Using the meta-analytic approach on trials published after 2000, correlations between PFS and OS at the individual level, and between treatment effects on PFS and on OS at the trial level, were estimated using Kendall’ tau and copula bivariate (R2Copula) models respectively. Criteria for PFS surrogacy required R2Copula ≥ 0.80. Results: We analyzed IPD from 8,973 patients enrolled in 15 randomized first line trials of standard (n = 7), intensification (n = 5) and maintenance (n = 3) chemotherapies or targeted treatments. No heterogeneity in the treatment effects across trials was detected. High correlations were found at the individual level (tau = 0.69) but low correlation at the trial level (R2Copula = 0.03). Sub-group analyses led to similar results. Conclusions: This large IPD meta-analysis did not establish PFS as a surrogate endpoint for OS in first line treatment of AOC, but the analysis was limited by the narrow range of treatment effects observed and post study treatment. Additional trials are being collected that will enable us to refine the sub-groups analyses. Table of results Endpoint / Trial type Trials N (pts) taua R2Copulaa Overall 15 (8973) 0.69 0.03 CA125 confirmed by radiological exam 9 (5126) 0.67 0.16 GCIG criteria 4 (2548) 0.7 0.14 Carbo-Tax as control 9 (5807) 0.72 0.05 Standard or intensification 12 (7703) 0.71 0.10 Maintenance 3 (1270) 0.64 0.14 atau and R2 values range from 0 (no association) to 1 (perfect correlation).
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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 | 0.045 | 0.050 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.031 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".