J Cancer 2022; 13(6):1914-1922. doi:10.7150/jca.69548 This issue

Research Paper

Dynamic Nomogram for Predicting Macrovascular Invasion of Patients with Unresectable Hepatocellular Carcinoma after Transarterial Chemoembolization

Huiwen Yan*, Xinhui Wang*, Dongdong Zhou, Peng Wang, Zhiyun Yang

Center of Integrative Medicine, Beijing Ditan Hospital, Capital Medical University, Beijing 100015, China.
*These authors contributed equally to this work.

This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/). See http://ivyspring.com/terms for full terms and conditions.
Yan H, Wang X, Zhou D, Wang P, Yang Z. Dynamic Nomogram for Predicting Macrovascular Invasion of Patients with Unresectable Hepatocellular Carcinoma after Transarterial Chemoembolization. J Cancer 2022; 13(6):1914-1922. doi:10.7150/jca.69548. Available from https://www.jcancer.org/v13p1914.htm

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Graphic abstract

Background: The purpose of our dynamic nomogram is to help clinical select hepatocellular carcinoma (HCC) patients with transarterial chemoembolization (TACE) treatment advantages.

Methods: In total, 1,135 patients with HCC admitted to the Beijing Ditan Hospital of Capital Medical University were enrolled in this study. We used a 7:3 random splits between a training set (n=796) and a validation set (n=339). The dynamic nomogram was established by multiple logistic regression and evaluated by the C-indices. We generated calibration plots, decision analysis curve and a clinical impact curve to assess the clinical usefulness of the nomogram. Macrovascular invasion (MVI) incidence curves were constructed using the Kaplan-Meier method and compared by the log-rank test.

Results: Multivariate logistic regression analysis identified six risk factors independently associated with MVI: BCLC staging B vs 0-A (hazard ratio (HR): 2.350, 95% confidence interval (CI): 1.222-4.531; P = 0.010) and staging C vs 0-A (HR: 3.652, 95% CI: 1.212-11.184; P = 0.022), treatment -TACE (HR: 2.693, 95%CI: 1.824-3.987; P < 0.001), tumour size ≥3cm (HR: 2.239, 95%CI: 1.452-3.459; P < 0.001), ɣ-GGT ≥60 (HR: 1.685, 95%CI: 1.100-2.579; P = 0.016), AFP ≥400 (HR: 2.681, 95%CI: 1.692-4.248; P < 0.001) and CRP ≥5 (HR: 3.560, 95%CI: 2.361-5.388; P < 0.001). The C-indices was 0.817 and 0.829 in the training and validation sets, respectively. The calibration curves showed good agreement between the predicted probability and the actual probability by the dynamic nomogram.

Conclusions: Our study developed and validated a dynamic nomogram including BCLC staging, treatment modality, tumour size, and three laboratory parameters (ɣ-GGT, AFP and CRP). It has good discrimination and accuracy, and provides a simple and reliable basis for clinical decision-making.

Keywords: Hepatocellular carcinoma, Macrovascular invasion, Transarterial chemoembolization, Dynamic Nomogram