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Record W4409670273 · doi:10.1016/j.jhepr.2025.101431

Efficacy of atezolizumab plus bevacizumab for unresectable HCC: Systematic review and meta-analysis of real-world evidence

2025· article· en· W4409670273 on OpenAlexaff
Giulia Francesca Manfredi, Claudia Angela Maria Fulgenzi, Ciro Celsa, Bernardo Stefanini, Antonio D’Alessio, Matthias Pinter, B Scheiner, Nichola Awosika, Leonardo Brunetti, Pasquale Lombardi, Charles Latchford, Pei-Chang Lee, Yi‐Hsiang Huang, Andrea Dalbeni, Arndt Vogel, Peter R. Galle, Masatoshi Kudo, Lorenza Rimassa, Hong Jae Chon, Giuseppe Cabibbo, Fabio Piscaglia, Calogero Cammà, Anjana Pillai, Mario Pirisi, Amit G. Singal, David J. Pinato

Bibliographic record

VenueJHEP Reports · 2025
Typearticle
Languageen
FieldMedicine
TopicHepatocellular Carcinoma Treatment and Prognosis
Canadian institutionsPrincess Margaret Cancer Centre
FundersImperial Experimental Cancer Medicine CentreEuropean Association for the Study of the LiverAssociazione Italiana per la Ricerca sul CancroFoundation for Liver ResearchNational Institute for Health and Care ResearchNIHR Imperial Biomedical Research CentreCancer Treatment and Research TrustCancer Research UKWellcome TrustF. Hoffmann-La RocheRoche
KeywordsAtezolizumabBevacizumabMedicineInternal medicineOncologyNivolumabCancerChemotherapy

Abstract

fetched live from OpenAlex

Background & Aims Atezolizumab plus bevacizumab (A+B) is a standard-of-care treatment in unresectable hepatocellular carcinoma (uHCC). Verification of its effectiveness outside clinical trials is an area of unmet need, especially in estimating long-term survival outcomes. Methods We conducted a systematic review and meta-analysis of the MEDLINE, Embase, and Cochrane libraries to evaluate therapy outcomes in patients treated with frontline A+B for uHCC outside trials. Pooled estimates of overall survival (OS) and progression-free survival (PFS) at 6 and 12 months were calculated from individual patient-level data using random-effects analysis. Results Of 2,179 patients selected from 12 cohorts, 80.5% were male, median age was 66 years (IQR 61.6–73.0), 61.6% had advanced-stage hepatocellular carcinoma (HCC), and 83.6% were Child–Pugh (CP) class A. Pooled 6- and 12-month OS was 82% (95% CI: 76–86%; I 2 = 80%) and 65% (95% CI: 60–70%; I 2 = 66%). Median OS of patients with CP-A liver function was 20.9 months (95% CI: 15.7–20.9), consistent with IMbrave150 estimates (19.2 months, 95% CI: 17.0–23.7, p = 0.58). Pooled PFS at 6 and 12 months was 57% (95% CI: 53–61%; I 2 = 49%) and 35% (95% CI: 31–39%, I 2 = 60%). Among patients with longer follow-up, the OS (n = 1,783) and PFS (n = 959) rates were 52% (95% CI: 46–58; I 2 = 90%) and 26% (95% CI: 17–37; I 2 = 91%) at 18 months, respectively. At 24 months, OS (n = 1,556) rate was 39% (95% CI: 31–49; I 2 = 90%) and PFS (n = 732) rate was 25% (95% CI: 12–45; I 2 = 95%). Conclusions The effectiveness of A+B after registration mirrors its efficacy estimates from clinical trial datasets. Long-term survival at 24 months can be achieved in up to 39% of patients with uHCC treated with A+B in routine clinical practice. Impact and implications This study provides real-world evidence supporting the long-term efficacy of atezolizumab plus bevacizumab (A+B) for unresectable hepatocellular carcinoma, showing survival outcomes similar to those achieved in clinical trials. These findings are important for clinicians in supporting A+B as a frontline treatment, particularly for patients with Child–Pugh class A liver function. They also offer valuable insights for policymakers and researchers for optimising treatment strategies for unresectable hepatocellular carcinoma. However, results should be interpreted with caution because of potential variability in patient populations.

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 imitation

Not 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.

metaresearch head score (Codex)0.014
metaresearch head score (Gemma)0.034
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.018
Threshold uncertainty score0.073

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0140.034
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0180.035
Bibliometrics0.0070.006
Science and technology studies0.0000.001
Scholarly communication0.0030.002
Open science0.0020.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.155
GPT teacher head0.367
Teacher spread0.212 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designMeta-analysis
Domainnot available
GenreEmpirical

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".

Quick stats

Citations8
Published2025
Admission routes1
Has abstractyes

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