Evaluating Sorafenib (SORA-2) as Second-Line Treatment for Unresectable Hepatocellular Carcinoma: A European Retrospective Multicenter Study
Bibliographic record
Abstract
BACKGROUND/OBJECTIVES: Systemic treatment for unresectable hepatocellular carcinoma (HCC) has rapidly advanced, with immune checkpoint inhibitors now the preferred first-line option. However, with multiple agents available and no established treatment sequence, selecting the most suitable second-line (2L) therapy remains challenging. While sorafenib is frequently chosen for 2L treatment, comprehensive data supporting its use is limited. This study evaluates the effectiveness of sorafenib as 2L therapy and factors influencing outcomes following first-line treatment failure in advanced HCC patients. METHODS: This is a retrospective, multicenter study, including 81 patients with unresectable HCC from 12 European centers who received sorafenib as 2L treatment. Median overall survival (mOS), median progression-free survival (mPFS), radiological response to treatment, and toxicity were evaluated. Univariable and multivariable analyses were performed to identify potential predictors of clinical benefit. RESULTS: In this cohort, some patients were treated with 2L sorafenib mOS for 7.4 months (95% CI: 6.6-13.6) and other patients were treated with mPFS for 3.7 months (95% CI: 3.0-4.8). Multivariable analysis revealed the best median OS for patients with CP A and AFP levels < 400 ng/mL (15.5 months). Adverse events (AE) of grade ≥ 3 were reported in 59.4% of patients. CONCLUSIONS: In this real-world cohort of European patients with unresectable HCC, the outcome of sorafenib treatment in the 2L setting was comparable to that of the other established 2L treatment options in patients with preserved liver function and good performance status. This study contributes to the understanding of the role of sorafenib in the 2L setting and underscores the need for further research to identify predictive factors for response and survival in order to optimize treatment algorithms for advanced HCC.
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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".