Surrogate endpoints for overall survival in advanced hepatocellular carcinoma: A meta-analysis.
Bibliographic record
Abstract
563 Background: Recent advances in systemic therapies have resulted in improved overall survivals (OS) for patients with advanced hepatocellular carcinoma (aHCC). The most commonly utilized primary endpoint for phase III trials in aHCC is OS. A robust surrogate endpoint (SEP) can reduce time and financial costs of future trials and accelerate regulatory approvals of new therapies. We conducted a literature-based meta-analysis to evaluate SEPs for OS in aHCC. Methods: Randomized controlled trials evaluating systemic therapies in aHCC published 2007 - 2023 were identified through a systemic literature search of Cochrane and Medline databases as well as of abstracts presented at ASCO and ESMO meetings. Hazard ratios (HR) for OS and progression-free survival (PFS) and time to progression (TTP) were extracted. ΔORR was calculated as the difference in overall response rates (ORR) between control and experimental arms. Pearson correlation and mixed-effects meta-regression analyses were performed. Surrogate threshold effect (STE) was determined for each comparison when possible. A p < 0.05 was considered to be statistically significant. Results: 26 trials were identified in the first-line setting with 14,827 patients and 11 trials in the subsequent-line setting with 5,316 patients. In first-line trials, immunotherapy (IO) is associated with higher ORR than other agents (p=0.003). There are statistically significant correlations between HRs of PFS/TTP/ΔORR and OS (Table). The relationship between HR-PFS and HR-OS persists in trials with or without IO, but only in trials enrolling < 30% patients of non-viral aetiologies. In subsequent-line trials, there are statistically significant correlations between HRs of PFS/TTP and OS (Table). STE for HR PFS is 0.68 and 0.87 respectively for 1st and subsequent line trials. Conclusions: There are moderate to strong correlations between PFS and OS in aHCC in first-line and subsequent line trials. STE for HR-PFS of 0.68 in first-line and 0.87 in subsequent-line settings can guide sample size calculation in future clinical trials. [Table: see text]
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.037 | 0.039 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.014 | 0.082 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".