Retrospective Study
Copyright ©The Author(s) 2022. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Clin Cases. Oct 16, 2022; 10(29): 10467-10477
Published online Oct 16, 2022. doi: 10.12998/wjcc.v10.i29.10467
Development and validation of a prognostic nomogram for decompensated liver cirrhosis
Wang Zhang, Yue Zhang, Qi Liu, Yuan Nie, Xuan Zhu
Wang Zhang, Yue Zhang, Qi Liu, Yuan Nie, Xuan Zhu, Department of Gastroenterology, Jiangxi Clinical Research Center for Gastroenterology, The First Affiliated Hospital of Nanchang University, Nanchang 330006, Jiangxi Province, China
Author contributions: Zhang W and Zhang Y contributed equally to this study; Zhang W designed and wrote the original draft; Zhang Y collected the data and wrote the original draft; Liu Q analyzed the data; Nie Y and Zhu X critically revised the manuscript; All authors have read and approve the final manuscript.
Supported by the National Natural Science Foundation of China, No. 81960120; the “Gan-Po Talent 555” Project of Jiangxi Province, No. GCZ (2012)-1; the Jiangxi Clinical Research Center for Gastroenterology, No. 20201ZDG02007.
Institutional review board statement: Study protocol was approved by the ethics committee of First Affiliated Hospital of Nanchang University (No.2013-1202). The study was performed in accordance with the Declaration of Helsinki.
Conflict-of-interest statement: The authors declare that there are no conflicts of interest.
Data sharing statement: The data that support the findings of this study are available from the corresponding author, Zhu X, upon reasonable request.
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:
Corresponding author: Xuan Zhu, MD, Professor, Department of Gastroenterology, Jiangxi Clinical Research Center for Gastroenterology, The First Affiliated Hospital of Nanchang University, No.17 Yongwaizhengjie Road, Donghu District, Nanchang 330006, Jiangxi Province, China.
Received: May 30, 2022
Peer-review started: May 30, 2022
First decision: August 21, 2022
Revised: August 31, 2022
Accepted: September 9, 2022
Article in press: September 9, 2022
Published online: October 16, 2022
Research background

Decompensated liver cirrhosis (DLC) has high mortality, and there are some limitations when applying the common prognostic scores. Nomograms are widely used as prognostic models for many diseases.

Research motivation

Due to the worse prognosis, the overall survival of DLC has attracted much attention from clinicians. Thus, it is necessary to develop a prognostic model to evaluate the outcome of DLC patients.

Research objectives

This study aimed to develop and validate a novel and simple-to-use prognostic nomogram to assess the prognosis of DLC patients.

Research methods

A total of 493 DLC patients were included in this study and divided into a derivation group (n = 329) and a validation group (n = 164). According to the results of univariate and multivariate Cox regression analyses, a nomogram model was developed to predict the prognosis of DLC.

Research results

The nomogram was developed based on age, mechanical ventilation application, model for end-stage liver disease (MELD) score, mean arterial blood pressure and PaO2/FiO2. The C-indexes, calibration curves and decision curve analysis revealed that the nomogram model is a valid tool.

Research conclusions

We constructed a nomogram model that could accurately predict the prognosis of DLC patients and showed better prognostic performance than the CTP and MELD scores.

Research perspectives

This research established a nomogram that could predict prognosis in DLC patients. In addition, the nomogram was precisely evaluated by internal validation, which may be helpful to clinicians in clinical decision making.