Evidence map›Paper›PMID 42540571›Full record

ArticleArchives of medical science : AMS2026

Predictive factors of improved postoperative results after surgery for patients with hepatocellular carcinoma: a retrospective study.

Maher Hendi, Bin Zhang, Xiu-Jun Cai

Abstract read
In one paragraph

Article in Archives of medical science : AMS, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

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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

3 authors.

Maher HendiDepartment of Surgery, Zhejiang University School of Medicine, Sir Run Run Shaw Hospital, China.
Bin ZhangDepartment of Surgery, Zhejiang University School of Medicine, Sir Run Run Shaw Hospital, China.
Xiu-Jun CaiDepartment of Surgery, Zhejiang University School of Medicine, Sir Run Run Shaw Hospital, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Several clinical studies have demonstrated the benefits of surgery for patients with hepatocellular carcinoma (HCC). The goal of our study was to identify prognostic factors associated with overall survival (OS) and recurrence-free survival (RFS) in patients with HCC and develop nomograms to predict these factors. Material and methods: We retrospectively conducted follow-up evaluations of 176 patients with HCC up to 10 years after their tumors were removed. All of these patients were from a single hospital, and all of the enrolled patients were divided into two groups: those who survived less than 3 years and those who survived more than 3 years. Independent prognostic factors associated with OS and RFS were determined via univariate and multivariate Cox regression model analyses. Two prognostic nomogram models were built on the basis of the data and evaluated via the concordance index (C-index). The calibration curves indicated that the two nomograms performed well over a 5-year period. Additionally, the area under the receiver operating characteristic (ROC) curve and the time-dependent area under the ROC curve (AUC) were determined, and decision curve analyses (DCAs) were conducted. Results: The nomograms successfully discriminated patients with HCC. Prognostic factors for OS and RFS were identified, and nomograms were successfully built. The calibration discrimination was good for both the OS and RFS nomogram prediction models (C-indexes: 0.815 and 0.80, respectively). Our nomograms and calibration curves demonstrated favorable results with strong predictive accuracy and ROC curves, and according to the DCA, our nomogram results showed a greater net clinical benefit. The Kaplan-Meier plots for OS and RFS were generated via the log-rank test, the Conclusions: We established nomogram survival prediction models to predict the prognosis of HCC after invasive treatment and achieved an acceptable level of accuracy in both OS and RFS analyses. These models may be valuable for guiding the selection of clinical treatment strategies and may also facilitate clinical decision making.

Indexed as

hepatocellular carcinomalong-term survivalnomogramoverall survivalprognosisrecurrence-free survival

Identifiers

PMID42540571
PMCPMC13426181

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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.