A Novel Nomogram for the Preoperative Prediction of Edmondson-Steiner Grade III-IV in Hepatocellular Carcinoma Patients

Zheyu Zhou; Shuya Cao; Chaobo Chen; Jun Chen; Xiaoliang Xu; Yang Liu; Qiaoyu Liu; Ke Wang; Bing Han; Yin Yin

doi:10.2147/JHC.S417878

A Novel Nomogram for the Preoperative Prediction of Edmondson-Steiner Grade III-IV in Hepatocellular Carcinoma Patients

J Hepatocell Carcinoma. 2023 Aug 23:10:1399-1409. doi: 10.2147/JHC.S417878. eCollection 2023.

Authors

Zheyu Zhou^#¹, Shuya Cao^#², Chaobo Chen^#^{3

4}, Jun Chen⁵, Xiaoliang Xu⁶, Yang Liu⁴, Qiaoyu Liu⁶, Ke Wang², Bing Han⁴, Yin Yin⁶

Affiliations

¹ Department of General Surgery, Nanjing Drum Tower Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Graduate School of Peking Union Medical College, Nanjing, 210008, People's Republic of China.
² Hepatobiliary Center, The First Affiliated Hospital of Nanjing Medical University; Key Laboratory of Liver Transplantation, Chinese Academy of Medical Science; NHC Key Laboratory of Living Donor Liver Transplantation (Nanjing Medical University), Nanjing, 210029, People's Republic of China.
³ Department of General Surgery, Xishan People's Hospital of Wuxi City, Wuxi, 214105, People's Republic of China.
⁴ Department of Hepatobiliary and Transplantation Surgery, The Affiliated Drum Tower Hospital of Nanjing University Medical School, Nanjing, 210008, People's Republic of China.
⁵ Department of Pathology, The Affiliated Drum Tower Hospital of Nanjing University Medical School, Nanjing, 210008, People's Republic of China.
⁶ Department of General Surgery, The First Affiliated Hospital of Anhui Medical University, Hefei, 230022, People's Republic of China.

^# Contributed equally.

Abstract

Background: Edmondson-Steiner (E-S) grade is a pathological indicator of the degree of hepatocellular carcinoma (HCC) differentiation, and E-S grade III-IV is a poor prognostic factor for HCC patients. Predicting poorly differentiated HCC has essential significance for clinical decision-making. Although some studies have developed predictive models based on magnetic resonance imaging (MRI) and radiomics, radiomic features that require specific software for analysis are impractical for clinical work. This study aims to develop a novel and user-friendly nomogram model to predict E-S grade III-IV.

Patients and methods: Medical data on patients meeting the inclusion criteria were obtained from the Nanjing Drum Tower Hospital HCC database (January 2020 to December 2022). Univariate analysis was used to screen for risk factors associated with E-S grade III-IV. A novel nomogram was established based on the subsequent multivariate logistic regression analysis. The performance of the established model was evaluated through diagnostic ability, calibration, and clinical benefits.

Results: Overall, 240 HCC patients were included in this study. Among them, 103 were highly differentiated (E-S grade I-II) HCC and 137 were poorly differentiated (E-S grade III-IV) HCC. A nomogram model that integrated alpha-fetoprotein (AFP), des-γ-carboxy prothrombin (DCP), hepatitis B virus surface antigen (HBsAg), hepatitis C virus antibodies (HCVAb), aspartate aminotransferase to lymphocyte ratio index (ALRI), and macrovascular invasion was established. The novel model had a good diagnostic performance with an area under the curve (AUC) value of 0.763. Meanwhile, the model had a diagnostic accuracy of 72.5%, a sensitivity of 78.1%, and a specificity of 65.1%. The calibration curve showed good calibration of the nomogram model (mean absolute error = 0.043), and the decision curve analysis (DCA) demonstrated that the clinical benefit was provided.

Conclusion: Our developed nomogram model could successfully predict E-S grade III-IV in HCC patients, which may be helpful in clinical decision-making.

Keywords: Edmondson-Steiner grade; hepatocellular carcinoma; nomogram; prediction.

Grants and funding

This research was funded by the Anhui Provincial Key Research and Development Project (202204295107020032), the National Natural Science Youth Foundation of China (81902415, 82103135, and 82101850), and the Natural Science Youth Foundation of Jiangsu Province (BK20190116).