Evidence map›Paper›PMID 41552825›Full record

SynthesisFrontiers in pharmacology2025

A network meta-analysis of first-line treatment options for patients with Child-Pugh class B functional hepatocellular carcinoma: comparison of efficacy and safety.

Yu-Xuan Zhang, Jia-Yi Wu, Jun-Yi Wu, Zhen-Xin Zeng, Rong-Jian Pan, Xiang-Ye Ou, Yi-Nan Li, Mao-Lin Yan

Abstract readSystematic Review
In one paragraph

Synthesis in Frontiers in pharmacology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Yu-Xuan ZhangShengli Clinical Medical College of Fujian Medical University, Department of Hepatobiliary Pancreatic Surgery, Fujian Provincial Hospital, Fuzhou University Affiliated Provincial Hospital, Fuzhou, Fujian, China.
Jia-Yi WuShengli Clinical Medical College of Fujian Medical University, Department of Hepatobiliary Pancreatic Surgery, Fujian Provincial Hospital, Fuzhou University Affiliated Provincial Hospital, Fuzhou, Fujian, China.
Jun-Yi WuShengli Clinical Medical College of Fujian Medical University, Department of Hepatobiliary Pancreatic Surgery, Fujian Provincial Hospital, Fuzhou University Affiliated Provincial Hospital, Fuzhou, Fujian, China.
Zhen-Xin ZengShengli Clinical Medical College of Fujian Medical University, Department of Hepatobiliary Pancreatic Surgery, Fujian Provincial Hospital, Fuzhou University Affiliated Provincial Hospital, Fuzhou, Fujian, China.
Rong-Jian PanShengli Clinical Medical College of Fujian Medical University, Department of Hepatobiliary Pancreatic Surgery, Fujian Provincial Hospital, Fuzhou University Affiliated Provincial Hospital, Fuzhou, Fujian, China.
Xiang-Ye OuShengli Clinical Medical College of Fujian Medical University, Department of Hepatobiliary Pancreatic Surgery, Fujian Provincial Hospital, Fuzhou University Affiliated Provincial Hospital, Fuzhou, Fujian, China.
Yi-Nan LiShengli Clinical Medical College of Fujian Medical University, Department of Hepatobiliary Pancreatic Surgery, Fujian Provincial Hospital, Fuzhou University Affiliated Provincial Hospital, Fuzhou, Fujian, China.
Mao-Lin YanShengli Clinical Medical College of Fujian Medical University, Department of Hepatobiliary Pancreatic Surgery, Fujian Provincial Hospital, Fuzhou University Affiliated Provincial Hospital, Fuzhou, Fujian, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Management of patients with advanced hepatocellular carcinoma (HCC) and Child-Pugh class B liver function is challenging owing to compromised hepatic functional reserve, affecting treatment selection and outcomes, as many systemic therapies demonstrate altered pharmacokinetics and increased toxicity in this population. Current treatment guidelines predominantly focus on patients with preserved liver function (Child-Pugh A), creating a critical evidence gap for the optimal management of patients with Child-Pugh B liver function. This network meta-analysis (NMA) evaluated first-line therapies for patients with advanced HCC and Child-Pugh B cirrhosis, addressing current evidence gaps to guide optimal treatment selection for this high-risk population. Methods: The PubMed, Embase, and Cochrane Library databases were searched until 31 October 2024. Randomized controlled trials and prospective cohort studies were included if they involved patients with advanced HCC and Child-Pugh class B liver function, evaluated first-line therapeutic agents, and reported overall survival (OS) and/or progression-free survival (PFS) with 95% confidence intervals. Bayesian NMA was employed to evaluate treatment efficacy and safety. Results: Eleven studies comprising 2,536 patients were included in the NMA. Lenvatinib exhibited the greatest probability of ideal efficacy for OS, while atezolizumab and bevacizumab combination therapy demonstrated the highest likelihood of optimal performance in terms of PFS. The overall incidence of adverse events (AEs) was 68.58%. The predominant grade 3-4 AEs included hypertension, proteinuria, hand-foot syndrome, and abnormal liver function. Conclusion: Atezolizumab and bevacizumab combination therapy demonstrated the optimal net benefit regarding PFS and reduced toxicity, whereas lenvatinib monotherapy exhibited the greatest net benefit in OS but with increased toxicity.

Indexed as

Child-Pugh class Befficacyfirst-linetreatmenthepatocellular carcinomanetwork meta-analysissafety

Identifiers

PMID41552825
PMCPMC12807933

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.