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Nomogram For Preoperative Prediction Of Microvascular Invasion Risk In Hepatocellular Carcinoma

Authors Deng G, Yao L, Zeng F, Xiao L, Wang Z

Received 17 May 2019

Accepted for publication 10 September 2019

Published 22 October 2019 Volume 2019:11 Pages 9037—9045


Checked for plagiarism Yes

Review by Single-blind

Peer reviewer comments 2

Editor who approved publication: Dr Sanjeev Srivastava

Guangtong Deng,1 Lei Yao,1 Furong Zeng,2 Liang Xiao,1,* Zhiming Wang1,*

1General Surgery Department, Xiangya Hospital, Central South University, Changsha, People’s Republic of China; 2Xiangya School of Medicine, Central South University, Changsha, People’s Republic of China

*These authors contributed equally to this work

Correspondence: Zhiming Wang; Liang Xiao
General Surgery Department, Xiangya Hospital, Central South University, Xiangya Road 87, Changsha 410008, People’s Republic of China
Tel +8618773132682

Objective: To preoperatively predict the microvascular invasion (MVI) risk in hepatocellular carcinoma (HCC) using nomogram.
Methods: A retrospective cohort of 513 patients with HCC hospitalized at Xiangya Hospital between January 2014 and December 2018 was included in the study. Univariate and multivariate analysis was performed to identify the independent risk factors for MVI. Based on the independent risk factors, nomogram was established to preoperatively predict the MVI risk in HCC. The accuracy of nomogram was evaluated by using receiver operating characteristic (ROC) curve, calibration curve and decision curve analysis (DCA).
Results: Tumor size (OR=1.17, 95% CI: 1.11–1.23, p<0.001), preoperative AFP level greater than 155 ng/mL (OR=1.65, 95% CI: 1.13–2.39, p=0.008) and NLR (OR=1.14, 95% CI: 1.00–1.29, p=0.042) were the independent risk factors for MVI. Incorporating these 3 factors, nomogram was established with the concordance index of 0.71 (95% CI, 0.66–0.75) and well-fitted calibration curves. DCA confirmed that using this nomogram added more benefit compared with the measures that treat all patients or treat none patients. At the cutoff value of predicted probability ≥0.44, the model demonstrated sensitivity of 61.64%, specificity of 71.53%, positive predictive value (PPV) of 64.13%, and negative predictive value (NPV) of 69.31%.
Conclusion: Nomogram was established for preoperative prediction of the MVI risk in HCC patients, and better therapeutic choice will be made if it was applied in clinical practice.

Keywords: microvascular invasion, MVI, hepatocellular carcinoma, HCC, preoperative prediction, independent risk factors, nomogram

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