Evidence map›Paper›PMID 41080629›Full record

ArticleJournal of hepatocellular carcinoma2025

Establishing a Survival Time Prediction Model for Patients with Hepatocellular Carcinoma After TACE Based on CT Radiomics: A Multi-Center Study.

Han Yang, Juan Zhao, Yingwei Wang, Diwen Zhu, Junpeng Gu, Weixin Ren

Abstract read
In one paragraph

Article in Journal of hepatocellular carcinoma, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
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

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

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Review
4 · The record

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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

6 authors.

Han Yang *Department of Interventional Radiology, The First Affiliated Hospital of Xinjiang Medical University (Xinjiang Interventional Medicine Clinical Research Center), Xinjiang, Urumqi, 830054, People's Republic of China.
Juan Zhao *Department of Anesthesiology, Sichuan Cancer Hospital & Institute (Sichuan Cancer Center, or Cancer Hospital Affiliated to University of Electronic Scienceand Technology of China), Sichuan, Chengdu, 610041, People's Republic of China.
Yingwei WangDepartment of Radiology, The First Affiliated Hospital of Southwest Medical University, Sichuan, Luzhou, 646000, People's Republic of China.
Diwen ZhuDepartment of Interventional Radiology, The First Affiliated Hospital of Xinjiang Medical University (Xinjiang Interventional Medicine Clinical Research Center), Xinjiang, Urumqi, 830054, People's Republic of China.
Junpeng GuDepartment of Interventional Radiology, The First Affiliated Hospital of Xinjiang Medical University (Xinjiang Interventional Medicine Clinical Research Center), Xinjiang, Urumqi, 830054, People's Republic of China.
Weixin RenDepartment of Interventional Radiology, The First Affiliated Hospital of Xinjiang Medical University (Xinjiang Interventional Medicine Clinical Research Center), Xinjiang, Urumqi, 830054, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: This research constructs a prognostic model for overall survival (OS) in hepatocellular carcinoma (HCC) patients using radiomic features from non-contrast CT scans obtained within 24 hours after transarterial chemoembolization (TACE). Patients and Methods: Patients were retrospectively enrolled from three institutions to form training (n = 112) and validation (n = 56) cohorts from January 2016 to December 2023. All patients underwent a minimum of three TACE treatment sessions. January 2019 served as the cutoff point for dividing the dataset into training and validation cohorts. Univariate and multivariate Cox regression analyses were employed to obtain clinical variables related to OS for constructing the clinical model. The least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression analyses were employed to construct the radiomics model from lipiodol deposits in the target lesions (TL) within 24 hours after the initial TACE, and the clinical-radiomics model was further constructed. Model prediction performance was subsequently assessed by the area under the time-dependent receiver operating characteristic curve (AUC) and calibration curve. Additionally, Kaplan-Meier analysis was used to evaluate the model's value in predicting OS. Results: The clinical-radiomics model predicted OS at 1, 2, and 3 years more accurately than the clinical or radiomics model alone (training group, AUC = 0.787, 0.765 and 0.827, respectively; validation group, AUC = 0.731, 0.713 and 0.798, respectively). The predicted high-risk subgroup based on the clinical-radiomics model had shorter mOS than predicted low-risk subgroup (training group, 16 m vs 37 m, p = 0.0002; validation group 14 m vs 35 m, p<0.0001), enabling risk stratification of various clinical subgroups. Conclusion: The radiomic signature derived from lipiodol within 24 hours post-TACE functions as a prognostic biomarker for OS in HCC patients. The clinical-radiomics model demonstrates robust predictive performance, providing a valuable tool for prognostic evaluation in HCC.

Indexed as

hepatocellular carcinomaoverall survivalradiomicstomographytranscatheter arterial chemoembolizationx-ray computed

Identifiers

PMID41080629
PMCPMC12515015

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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.