Efficacy of Transarterial Chemoembolization Combined with Tyrosine Kinase Inhibitors for Hepatocellular Carcinoma Patients with Portal Vein Tumor Thrombus: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Background: Transarterial chemoembolization (TACE) combined with tyrosine kinase inhibitors (TKIs) may enhance the efficacy of treatment for hepatocellular carcinoma (HCC) with portal vein tumor thrombus (PVTT); however, it remains unclear. We aim to evaluate the efficacy of TACE combined with TKIs. Methods: A thorough literature search was performed on major databases since their inception until October 2022. Based on the eligibility criteria, eight studies (2103 patients) were included. Results: Meta-analysis showed that TACE+sorafenib/apatinib had a better tumor response (objective response rate (ORR): RR = 4.85, 95% CI 2.68−8.75, disease control rate (DCR): RR = 3.23, 95% CI 1.88−5.56), and prolonged OS (HR = 0.50, 95%CI 0.42−0.60, p < 0.00001) than TACE alone. TACE+lenvatinib was stronger than TACE+sorafenib in ORR (60.7% vs. 38.9%) and TTP (HR = 0.61, 95% CI 0.43−0.86), whereas it was similar in DCR (96.4% vs. 96.3%) and OS (HR = 0.70 95% CI 0.46−1.05). Conclusions: TACE plus sorafenib or apatinib was superior to TACE alone for hepatocellular carcinoma with PVTT; no significant advantage was found between TACE+lenvatinib and TACE+sorafenib, although TACE+lenvatinib performed better in terms of ORR and TTP.
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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 | 0.007 | 0.016 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.015 | 0.033 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".