ArticleJournal of hepatocellular carcinoma2022
Noninvasive Imaging Evaluation Based on Computed Tomography of the Efficacy of Initial Transarterial Chemoembolization to Predict Outcome in Patients with Hepatocellular Carcinoma.
Article in Journal of hepatocellular carcinoma, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 3 of them syntheses that pooled it.
What it found
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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.
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.
Who cites it
6 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- Performance of Artificial Intelligence Models in Predicting Responsiveness of Hepatocellular Carcinoma to Transarterial Chemoembolization (TACE): A Systematic Review and Meta-Analysis.Journal of the American College of Radiology : JACR · 2026Pooled it
- Artificial Intelligence and Machine Learning Predicting Transarterial Chemoembolization Outcomes: A Systematic Review.Digestive diseases and sciences · 2025Pooled it
- Radiomics as a tool for prognostic prediction in transarterial chemoembolization for hepatocellular carcinoma: a systematic review and meta-analysis.La Radiologia medica · 2024Pooled it
- All You Need to Know About TACE: A Comprehensive Review of Indications, Techniques, Efficacy, Limits, and Technical Advancement.Journal of clinical medicine · 2025Review
- Radiomics analysis based on contrast-enhanced MRI for predicting short-term efficacy of drug-eluting beads transarterial chemoembolization in hepatocellular carcinoma.Abdominal radiology (New York) · 2024Article
- MRI-based radiomics model and nomogram for predicting the outcome of locoregional treatment in patients with hepatocellular carcinoma.BMC medical imaging · 2023Article
Corrections and comments
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Authors and funding
11 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Purpose: This study aims to develop a new model to more comprehensively and accurately predict the survival of patients with HCC after initial TACE. Patients and Methods: The whole cohort (n = 102) was randomly divided into a training cohort and a validation cohort in the ratio of 8:2. The optimal radiomics signatures were screened using the least absolute shrinkage and selection operator algorithm (LASSO) regression for constructing the radscore to predict overall survival (OS). The C-index (95% confidence interval, CI), calibration curve, and decision curve analysis (DCA) were used to evaluate the performance of the models. The independent risk factors (hazard ratio, HR) for predicting OS were stratified by Kaplan-Meier (K-M) analysis and the Log rank test. Results: The median OS was 439 days (95% CI: 215.795-662.205) in whole cohort, and in the training cohort and validation cohort, the median OS was 552 days (95% CI: 171.172-932.828), 395 days (95% CI: 309.415-480.585), respectively ( Conclusion: Noninvasive imaging has a good prediction performance of survival after initial TACE in patients with HCC. The combined model consisting of post-response and radscore may be able to better predict outcome.
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Registered trials
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