Retrospective Study
Copyright ©The Author(s) 2020. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Gastroenterol. Jun 7, 2020; 26(21): 2839-2851
Published online Jun 7, 2020. doi: 10.3748/wjg.v26.i21.2839
Non-invasive prediction model for high-risk esophageal varices in the Chinese population
Long-Bao Yang, Jing-Yuan Xu, Xin-Xing Tantai, Hong Li, Cai-Lan Xiao, Cai-Feng Yang, Huan Zhang, Lei Dong, Gang Zhao
Long-Bao Yang, Jing-Yuan Xu, Xin-Xing Tantai, Hong Li, Cai-Lan Xiao, Cai-Feng Yang, Huan Zhang, Lei Dong, Gang Zhao, Department of Gastroenterology, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an 710004, Shaanxi Province, China
Author contributions: All authors helped to perform the research; Dong L and Zhao G completed the project; Xiao CL and Zhang H completed the data collection; Tantai XX, Xu JY, and Yang CF completed the data analysis; Yang LB and Li H completed writing of the article.
Institutional review board statement: This study has been approved by the Ethics Committee of The Second Affiliated Hospital of Xi'an Jiaotong University.
Informed consent statement: This study is a retrospective study; thus, the ethics committee has exempted the informed consent of the patients.
Conflict-of-interest statement: The authors declare that they have no conflict of interest.
Data sharing statement: No additional data are available.
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: http://creativecommons.org/licenses/by-nc/4.0/
Corresponding author: Gang Zhao, MD, PhD, Doctor, Department of Gastroenterology, The Second Affiliated Hospital of Xi'an Jiaotong University, No. 157, Xiwu Road, Xi'an 710004, Shaanxi Province, China. zhaogang799@126.com
Received: December 28, 2019
Peer-review started: December 28, 2019
First decision: January 13, 2020
Revised: March 26, 2020
Accepted: April 21, 2020
Article in press: April 21, 2020
Published online: June 7, 2020
Processing time: 160 Days and 22.2 Hours
Abstract
BACKGROUND

There are two types of esophageal varices (EVs): high-risk EVs (HEVs) and low-risk EVs, and HEVs pose a greater threat to patient life than low-risk EVs. The diagnosis of EVs is mainly conducted by gastroscopy, which can cause discomfort to patients, or by non-invasive prediction models. A number of non-invasive models for predicting EVs have been reported; however, those that are based on the formula for calculation of liver and spleen volume in HEVs have not been reported.

AIM

To establish a non-invasive prediction model based on the formula for liver and spleen volume for predicting HEVs in patients with viral cirrhosis.

METHODS

Data from 86 EV patients with viral cirrhosis were collected. Actual liver and spleen volumes of the patients were determined by computed tomography, and their calculated liver and spleen volumes were calculated by standard formulas. Other imaging and biochemical data were determined. The impact of each parameter on HEVs was analyzed by univariate and multivariate analyses, the data from which were employed to establish a non-invasive prediction model. Then the established prediction model was compared with other previous prediction models. Finally, the discriminating ability, calibration ability, and clinical efficacy of the new model was verified in both the modeling group and the external validation group.

RESULTS

Data from univariate and multivariate analyses indicated that the liver-spleen volume ratio, spleen volume change rate, and aspartate aminotransferase were correlated with HEVs. These indexes were successfully used to establish the non-invasive prediction model. The comparison of the models showed that the established model could better predict HEVs compared with previous models. The discriminating ability, calibration ability, and clinical efficacy of the new model were affirmed.

CONCLUSION

The non-invasive prediction model for predicting HEVs in patients with viral cirrhosis was successfully established. The new model is reliable for predicting HEVs and has clinical applicability.

Keywords: Cirrhosis; High-risk esophageal varices; Non-invasive prediction model; Liver volume; Spleen volume

Core tip: The non-invasive prediction model for predicting high-risk esophageal varices in patients with viral cirrhosis was successfully established based on the standard formula for calculation of liver and spleen volumes. It is a novel model that has not been reported. The model was shown to be better than previous prediction models. The new model had clinical efficacy and the ability to predict high-risk esophageal varices.