CEUS features-based nomogram for predicting early recurrence (ER) of microvascular invasion-negative hepatocellular carcinoma.
Q, S., Y, L., C, P., Z, W., X, T., S, W., X, Y., P, L., J, Y., & X, Y. (2026). CEUS features-based nomogram for predicting early recurrence (ER) of microvascular invasion-negative hepatocellular carcinoma.. Journal of cancer research and therapeutics. https://doi.org/10.4103/jcrt.jcrt_2174_25
Q S, Y L, C P, Z W, X T, S W, et al. CEUS features-based nomogram for predicting early recurrence (ER) of microvascular invasion-negative hepatocellular carcinoma.. Journal of cancer research and therapeutics. 2026; doi: 10.4103/jcrt.jcrt_2174_25
Q S, Y L, C P, et al. CEUS features-based nomogram for predicting early recurrence (ER) of microvascular invasion-negative hepatocellular carcinoma.[J]. Journal of cancer research and therapeutics. 2026. DOI: 10.4103/jcrt.jcrt_2174_25.
@article{q2026,
author = {Shu Q and Liu Y and Pang C and Wang Z and Tian X and Wang S and Yan X and Liang P and Yu J and Yu X},
title = {CEUS features-based nomogram for predicting early recurrence (ER) of microvascular invasion-negative hepatocellular carcinoma.},
journal = {Journal of cancer research and therapeutics},
year = {2026},
doi = {10.4103/jcrt.jcrt_2174_25},
note = {PMID: 42241168},
}
TY - JOUR AU - Shu Q AU - Liu Y AU - Pang C AU - Wang Z AU - Tian X AU - Wang S AU - Yan X AU - Liang P AU - Yu J AU - Yu X TI - CEUS features-based nomogram for predicting early recurrence (ER) of microvascular invasion-negative hepatocellular carcinoma. T2 - Journal of cancer research and therapeutics PY - 2026 DO - 10.4103/jcrt.jcrt_2174_25 AN - PMID:42241168 ER -
PURPOSE: This study aimed to investigate contrast-enhanced ultrasound (CEUS) and clinical features associated with early recurrence (ER) following surgical resection in patients with microvascular invasion (MVI)-negative hepatocellular carcinoma (HCC), and to establish a nomogram-based predictive model. METHODS: A total of 146 pathologically confirmed MVI-negative HCC patients were retrospectively enrolled between August 2021 and June 2024. Univariable and multivariable Cox regression analyses were performed based on CEUS and clinicopathologic variables to identify predictors and develop a nomogram for 2-year recurrence probability. Model performance and discriminative ability were evaluated using the concordance index (C-index), receiver operating characteristic curve, and decision curve analysis (DCA). RESULTS: Multivariable Cox analysis identified smooth morphology, intra-tumoral artery, glypican-3 expression, and albumin-bilirubin (ALBI) grade as independent predictors of ER (all P < 0.05). A nomogram incorporating CEUS and clinicopathologic variables was constructed and demonstrated a favorable C-index of 0.768 (95% confidence interval [CI], 0.711-0.817). The model showed strong discriminative ability, with an area under the curve of 0.870 (95% CI, 0.805-0.952), and DCA indicated good clinical utility. The derived risk score effectively stratified patients into high-risk and low-risk groups. Patients in the low-risk group exhibited significantly better prognosis compared with those in the high-risk group ( P < 0.001). CONCLUSIONS: This CEUS- and clinicopathology-based prognostic model accurately identifies high-risk MVI-negative HCC patients and may provide valuable information for optimizing surveillance and intervention strategies.