Development and validation of a nomogram combining hematological and imaging features for preoperative prediction of microvascular invasion in hepatocellular carcinoma patients

Qiang Zhou; Chenhao Zhou; Yirui Yin; Wanyong Chen; Chunxiao Liu; Manar Atyah; Jialei Weng; Yinghao Shen; Yong Yi; Ning Ren

doi:10.21037/atm-20-4695

Development and validation of a nomogram combining hematological and imaging features for preoperative prediction of microvascular invasion in hepatocellular carcinoma patients

Ann Transl Med. 2021 Mar;9(5):402. doi: 10.21037/atm-20-4695.

Authors

Qiang Zhou¹, Chenhao Zhou^{1

2}, Yirui Yin^{1

3}, Wanyong Chen⁴, Chunxiao Liu², Manar Atyah¹, Jialei Weng¹, Yinghao Shen¹, Yong Yi¹, Ning Ren^{1

4}

Affiliations

¹ Department of Liver Surgery, Liver Cancer Institute, Zhongshan Hospital, and Key Laboratory of Carcinogenesis and Cancer Invasion (Ministry of Education), Fudan University, Shanghai, China.
² Department of Molecular and Cellular Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA.
³ Department of Liver Surgery, Xiamen Branch, Zhongshan Hospital, Fudan University, Xiamen, China.
⁴ Institute of Fudan Minhang Academic Health System, and Key Laboratory of Whole-period Monitoring and Precise Intervention of Digestive Cancer (SMHC), Minhang Hospital & AHS, Fudan University, Shanghai, China.

Abstract

Background: Microvascular invasion (MVI) is a significant hazard factor that influences the recurrence and survival of hepatocellular carcinoma (HCC) patients after undergoing hepatectomy. This study aimed to develop and validate a nomogram that combines hematological and imaging features of HCC patients to preoperatively predict MVI, and investigate the effect of wide resection margin (≥1 cm) on the prognosis of MVI-positive HCC patients.

Methods: A total of 709 HCC patients who underwent hepatectomy at the Liver Cancer Institute of Zhongshan Hospital, Fudan University between June 1, 2015 and December 30, 2016 were included in this study and divided into training (496 patients) and validation cohort (213 patients). Least absolute shrinkage and selection operator (Lasso) regression and multivariable logistic regression were used for variables' selection and development of the predictive model. The model was presented as a nomogram, and its performance was assessed in terms of discrimination, calibration and clinical usefulness.

Results: Independent prognostic factors such as alkaline phosphatase (ALP, >125 U/L), alpha-fetoprotein (AFP, within 20-400 or >400 ng/mL), protein induced by vitamin K absence-II (PVIKA-II, within 40-400 or >400 mAU/mL), tumor number, diameter, pseudo-capsule, tumor growth pattern and intratumor hemorrhage were incorporated in the nomogram. The model showed good discrimination and calibration, with a concordance index (0.82, 95% CI, 0.782-0.857) in the training cohort and C-index (0.80, 95% CI, 0.772-0.837) in the validation cohort. Decision curve analysis (DCA) also showed that this model is clinically useful. Moreover, HCC patients with wide resection margin had a significantly lower 3-year recurrence rate than those with narrower resection margin (0.5-1 cm).

Conclusions: This study presents an optimal model for preoperative prediction of MVI and shows that wide resection margin for MVI-positive HCC patients has a better prognosis. This model can help surgeons choose the best treatment options for HCC patients before and after the operation.

Keywords: Hepatocellular carcinoma (HCC); disease-free survival (DFS); microvascular invasion (MVI); nomogram; prediction.