Efficacy and Safety of Lenvatinib versus Atezolizumab Plus Bevacizumab in the Treatment of Unresectable Hepatocellular Carcinoma: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
INTRODUCTION: Hepatocellular carcinoma (HCC), the leading form of primary liver cancer, is strongly associated with liver cirrhosis and major risk factors such as hepatitis B and C, alcohol consumption, obesity, and non-alcoholic fatty liver disease. Despite treatment advancements, survival rates for unresectable HCC remain low. Lenvatinib and the combination of atezolizumab and bevacizumab (ATE/BEV) show promise, but further studies are needed to compare their clinical outcomes. This study aims to assess the efficacy and safety of LEN and ATE/BEV in unresectable HCC patients. METHODS: This research was conducted using the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) strategy. Literature searches were conducted through PubMed, ScienceDirect, Google Scholar, Cochrane Library, SpringerLink, and Ebsco to gather studies on comparing LEN versus ATE/BEV for managing unresectable HCC. The quality assessment was assessed using the Newcastle-Ottawa Scale (NOS). Overall survival (OS), progression-free survival (PFS), objective response rate (ORR), disease control rate (DCR) and treatment-related adverse events (AEs) were evaluated using Review Manager 5.4 and RStudio 2024.04.1. RESULTS: Twelve retrospective studies were included, comprising 6,620 samples. There was no difference in the OS (HR=0.72; 95%CI: 0.44-1.18, p=0.20), PFS (HR=0.90; 95%CI: 0.75-1.07; p=0.23), ORR (OR=1.16; 95%CI:0.86-1.56; p=0.34) and DCR (OR=1.14; 95%CI:0.97-1.34; p=0.12) between groups. Moreover, in viral and non-viral patients group, LEN showed similar OS and PFS compared with ATE/BEV. In terms of safety, LEN exhibited higher incidences of decreased appetite (OR=2.95; 95%CI:1.12-7.79; p=0.03), diarrhea (OR=2.61; 95%CI:2.06-3.32; p<0.00001), fatigue (OR=1.48; 95%CI:1.27-1.73; P<0.00001), hand-foot syndrome (OR=7.73; 95%CI:4.84-12.33; P<0.00001), and showed lower incidences of increased aspartate aminotransferase (OR=0.44; 95%CI:0.28-0.69; p=0.0004) compared to ATE/BEV. Moreover, LEN showed similar AEs in grade ≥ 3 AEs (OR=1.15; 95%CI:0.29-4.55; p=0.84), hypertension (OR=1.39; 95%CI:0.84-2.28; p=0.20), proteinuria (OR=1.10; 95%CI:0.75-1.60; p=0.63) compared to ATE/BEV. CONCLUSION: LEN was found to be non-inferior to ATE/BEV in terms of OS, PFS, ORR, DCR. However, LEN may be associated with a higher incidence of AEs.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.009 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".