Evidence map›Paper›PMID 42620506›Full record

SynthesisFrontiers in immunology2026

A dual-level Bayesian network meta-analysis of first-line immunotherapy in advanced hepatocellular carcinoma: strategy-level and regimen-level evidence.

Qiangqiang Zhang, Yanyan Hu, Yuli Ge, Rui Wang

Abstract readNetwork Meta-AnalysisSystematic Review
In one paragraph

Synthesis in Frontiers in immunology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0cells of the map it votes in
0citing papers in PubMed
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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

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0 citing papers in PubMed.

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4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

4 authors.

Qiangqiang ZhangDepartment of Medical Oncology, Jinling Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, China.
Yanyan HuDepartment of Medical Oncology, Jinling Hospital, Nanjing Medical University, Nanjing, China.
Yuli GeDepartment of Medical Oncology, Jinling Clinical Medical College, Nanjing University of Chinese Medicine, Nanjing, China.
Rui WangDepartment of Medical Oncology, Jinling Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Phase III trials of first-line immunotherapy-based combinations for advanced hepatocellular carcinoma (HCC) have yielded heterogeneous results, and head-to-head comparisons remain scarce. We evaluated mechanism-based strategy classes and individual regimens using a dual-level Bayesian network meta-analysis to provide a structured interpretation of the current evidence. Methods: We systematically searched the literature up to December 28, 2025, and identified 15 phase III randomised controlled trials. A dual-level Bayesian network meta-analysis was performed using separate models at the strategy level (PD-(L)1 plus VEGF monoclonal antibody (VEGF(Ab)), PD-(L)1 plus tyrosine kinase inhibitor (TKI), PD-(L)1 plus CTLA-4, and PD-(L)1 monotherapy) and the regimen level. Outcomes included overall survival (OS), progression-free survival (PFS), objective response rate (ORR), and grade ≥3 treatment-related adverse events (TRAEs). Results: Fifteen trials comprising 9,792 patients were included. At the strategy level, PD-(L)1 plus VEGF(Ab) showed the most favourable OS effect versus TKI monotherapy and the highest efficacy-oriented ranking, followed by PD-(L)1 plus CTLA-4 and PD-(L)1 plus TKI. PD-(L)1 plus TKI also improved PFS but was associated with a higher toxicity and discontinuation burden, whereas PD-(L)1 monotherapy showed the most favourable tolerability profile. At the regimen level, atezolizumab plus bevacizumab, sintilimab plus IBI305, camrelizumab plus rivoceranib, and STRIDE showed OS benefit versus sorafenib. Conclusions: In this evidence network, PD-(L)1 plus VEGF(Ab) showed the most efficacy-oriented profile and was supported by relatively consistent regimen-level estimates. However, the clinical interpretation of strategy-level findings differed across classes: PD-(L)1 plus TKI required closer regimen-level assessment because of greater within-class variability and a less favourable toxicity profile, whereas PD-(L)1 plus CTLA-4 and PD-(L)1 monotherapy showed distinct benefit-risk patterns. This dual-level framework complements regimen-centric evidence by distinguishing strategy-level patterns from regimen-level findings and by supporting a structured interpretation of efficacy-toxicity trade-offs in first-line ICI-based therapy for advanced HCC. Systematic Review Registration: https://www.crd.york.ac.uk/PROSPERO/view/CRD420251273309, identifier CRD420251273309.

Indexed as

Antineoplastic Combined Chemotherapy ProtocolsCarcinoma, HepatocellularImmunotherapyLiver NeoplasmsBayes TheoremHumansImmune Checkpoint InhibitorsTreatment OutcomeImmune Checkpoint InhibitorsBayesian network meta-analysisfirst-line treatmenthepatocellular carcinomaimmunotherapy combinationsranking

Identifiers

PMID42620506
PMCPMC13485808

What OpenQuestion holds

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.