Explant-based prognostic models for hepatocellular carcinoma recurrence after liver transplantation: A systematic review and meta-analysis

doi:10.4254/wjh.v17.i9.111126

Advanced Search

BPG is committed to discovery and dissemination of knowledge

Home / Archive / Volume 17, Issue 9

This Article

(45)

(39)

(0)

(7)

(750)

Peer-Review Report of This Article

CrossCheck and Google Search of This Article

Academic Rules and Norms of This Article

Supplementary Materials of This Article

Citation of this article

Corresponding Author of This Article

Research Domain of This Article

Article-Type of This Article

Open-Access Policy of This Article

Times Cited Counts in Google of This Article

Journal Information of This Article

Publication Name

World Journal of Hepatology

ISSN

1948-5182

Publisher of This Article

Baishideng Publishing Group Inc, 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA

Meta-Analysis

World J Hepatol. Sep 27, 2025; 17(9): 111126
Published online Sep 27, 2025. doi: 10.4254/wjh.v17.i9.111126

Full Size Figure Download Figure

Figure 4 Sensitivity and specificity of predicting cancer recurrence score and Decaens. A: Sensitivity; B: Specificity. FN: False negatives; FP: False positive; PCRS: Predicting cancer recurrence score; TP: True positives.

Citation: Christofoli de Barros I, Vanzin Fernandes M, Rodríguez Villafuerte S, Brandão ABM. Explant-based prognostic models for hepatocellular carcinoma recurrence after liver transplantation: A systematic review and meta-analysis. World J Hepatol 2025; 17(9): 111126
URL: https://www.wjgnet.com/1948-5182/full/v17/i9/111126.htm
DOI: https://dx.doi.org/10.4254/wjh.v17.i9.111126

Christofoli de Barros I, Vanzin Fernandes M, Rodríguez Villafuerte S, Brandão ABM. Explant-based prognostic models for hepatocellular carcinoma recurrence after liver transplantation: A systematic review and meta-analysis. World J Hepatol 2025; 17(9): 111126 [PMID: 41024870 DOI: 10.4254/wjh.v17.i9.111126]

All content on this site: Copyright © 1993-2026 Baishideng Publishing Group Inc, its licensors, and contributors. All rights are reserved, including those for text and data mining, AI training, and similar technologies. For all open access content, the relevant licensing terms apply.