Observational Study
Copyright ©The Author(s) 2023. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Gastrointest Oncol. Aug 15, 2023; 15(8): 1486-1496
Published online Aug 15, 2023. doi: 10.4251/wjgo.v15.i8.1486
Development and application of hepatocellular carcinoma risk prediction model based on clinical characteristics and liver related indexes
Zhi-Jie Liu, Yue Xu, Wen-Xuan Wang, Bin Guo, Guo-Yuan Zhang, Guang-Cheng Luo, Qiang Wang
Zhi-Jie Liu, Department of Clinical Transfusion, Affiliated Hospital of North Sichuan Medical College, Nanchong 637000, Sichuan Province, China
Yue Xu, Bin Guo, Guo-Yuan Zhang, Guang-Cheng Luo, Qiang Wang, Department of Clinical Laboratory, Affiliated Hospital of North Sichuan Medical College, Nanchong 637000, Sichuan Province, China
Wen-Xuan Wang, Department of Radiology, Nanchong Central Hospital, Nanchong 637000, Sichuan Province, China
Author contributions: Luo GC and Wang Q contributed to the conceptualisation and design of this study; Liu ZJ, Xu Y, Wang WX, Guo B, and Zhang GY contributed to the clinical data collection and analysis; Liu ZJ, Xu Y, and Wang WX prepared and wrote the first draft of this manuscript; Wang Q revised the manuscript.
Institutional review board statement: This study was approved by the Ethics Committee of Affiliated Hospital of North Sichuan Medical College and conducted in accordance with the declaration of Helsinki Principles.
Informed consent statement: The informed consent of this study was exempted by the Ethics Committee of Affiliated Hospital of North Sichuan Medical College.
Conflict-of-interest statement: All the authors report no relevant conflicts of interest for this article.
Data sharing statement: Technical appendix, statistical code, and dataset available from the corresponding author at email address. Participants gave informed consent for data sharing.
STROBE statement: The authors have read the STROBE Statement-checklist of items, and the manuscript was prepared and revised according to the STROBE Statement-checklist of items.
Open-Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: https://creativecommons.org/Licenses/by-nc/4.0/
Corresponding author: Qiang Wang, PhD, Research Assistant Professor, Department of Clinical Laboratory, Affiliated Hospital of North Sichuan Medical College, No. 1 Maoyuan South Road, Shunqing District, Nanchong 637000, Sichuan Province, China. wqiang_1981@126.com
Received: February 10, 2023
Peer-review started: February 10, 2023
First decision: May 19, 2023
Revised: May 28, 2023
Accepted: June 25, 2023
Article in press: June 25, 2023
Published online: August 15, 2023
Processing time: 181 Days and 5.6 Hours
Abstract
BACKGROUND

Hepatocellular carcinoma (HCC) is difficult to diagnose with poor therapeutic effect, high recurrence rate and has a low survival rate. The survival of patients with HCC is closely related to the stage of diagnosis. At present, no specific serological indicator or method to predict HCC, early diagnosis of HCC remains a challenge, especially in China, where the situation is more severe.

AIM

To identify risk factors associated with HCC and establish a risk prediction model based on clinical characteristics and liver-related indicators.

METHODS

The clinical data of patients in the Affiliated Hospital of North Sichuan Medical College from 2016 to 2020 were collected, using a retrospective study method. The results of needle biopsy or surgical pathology were used as the grouping criteria for the experimental group and the control group in this study. Based on the time of admission, the cases were divided into training cohort (n = 1739) and validation cohort (n = 467). Using HCC as a dependent variable, the research indicators were incorporated into logistic univariate and multivariate analysis. An HCC risk prediction model, which was called NSMC-HCC model, was then established in training cohort and verified in validation cohort.

RESULTS

Logistic univariate analysis showed that, gender, age, alpha-fetoprotein, and protein induced by vitamin K absence or antagonist-II, gamma-glutamyl transferase, aspartate aminotransferase and hepatitis B surface antigen were risk factors for HCC, alanine aminotransferase, total bilirubin and total bile acid were protective factors for HCC. When the cut-off value of the NSMC-HCC model joint prediction was 0.22, the area under receiver operating characteristic curve (AUC) of NSMC-HCC model in HCC diagnosis was 0.960, with sensitivity 94.40% and specificity 95.35% in training cohort, and AUC was 0.966, with sensitivity 90.00% and specificity 94.20% in validation cohort. In early-stage HCC diagnosis, the AUC of NSMC-HCC model was 0.946, with sensitivity 85.93% and specificity 93.62% in training cohort, and AUC was 0.947, with sensitivity 89.10% and specificity 98.49% in validation cohort.

CONCLUSION

The newly NSMC-HCC model was an effective risk prediction model in HCC and early-stage HCC diagnosis.

Keywords: Hepatocellular carcinoma, Risk prediction model, Logistic regression model, Tumour markers, Metabolic markers, Clinical characteristics

Core Tip: This study identified the risk factors associated with hepatocellular carcinoma (HCC) and further established a risk prediction model based on the clinical characteristics and liver indicators. By evaluating in the training cohort and confirming with the validation cohort, we proved that the proposed model has good sensitivity and specificity in high-risk populations with HCC, with a high accuracy in early-stage HCC diagnosis. In addition, we recommend a risk prediction scale (low to very high risk). This will help clinicians to diagnose HCC earlier and thus improve the prognosis of patients.