ArticleFrontiers in oncology2026
Prognostic model for predicting recurrence-free survival in HBV-related hepatocellular carcinoma patients after combined treatment: a multicenter study.
Article in Frontiers in oncology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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.
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
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Introduction: Hepatocellular carcinoma (HCC) is a lethal malignancy, with hepatitis B virus (HBV) infection as its leading cause in China. Transarterial chemoembolization (TACE) combined with radiofrequency ablation (RFA) treatment was gradually applied in clinic, but the lack of targeted prognostic tools for this cohort remains a critical issue. This multicenter study aimed to develop a prognostic model for recurrence-free survival (RFS) in HBV-related HCC patients after the combined treatment. Methods: A total of 604 patients from two hospitals were enrolled; 502 (Beijing You'an Hospital) formed the training/internal validation cohort (7:3 split), and 102 (Beijing Ditan Hospital) served as the external validation cohort. Baseline clinical, tumor, and laboratory data were collected. LASSO regression and random survival forest were used for variable screening, followed by multivariate Cox regression to identify independent predictors. The model was visualized as a nomogram, evaluated via Kaplan-Meier survival curves, receiver operating characteristic (ROC) curves, and decision curve analysis (DCA). Results: Age, tumor number, tumor size, gamma-glutamyl transferase (GGT), and total bilirubin (TBIL) were identified as independent RFS factors. The nomogram developed based on the five factors exhibited good discriminative ability: AUC values for 1-, 3-, 5-year RFS were 0.759, 0.777, 0.783 (training cohort), 0.708, 0.751, 0.714 (internal validation cohort), and 0.701, 0.708, 0.751 (external validation cohort). Kaplan-Meier curves confirmed significant RFS differences between high/low-risk groups (all P<0.001), and DCA demonstrated positive net clinical benefit. Conclusion: This study successfully developed a well-performed nomogram model to predict 1-, 3-, and 5-year RFS in HBV-related HCC patients following TACE combined with RFA.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.