Retrospective Study
Copyright ©The Author(s) 2024. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Gastrointest Oncol. Apr 15, 2024; 16(4): 1213-1226
Published online Apr 15, 2024. doi: 10.4251/wjgo.v16.i4.1213
Predictive model for non-malignant portal vein thrombosis associated with cirrhosis based on inflammatory biomarkers
Guo-Le Nie, Jun Yan, Ying Li, Hong-Long Zhang, Dan-Na Xie, Xing-Wang Zhu, Xun Li
Guo-Le Nie, Hong-Long Zhang, Dan-Na Xie, Xing-Wang Zhu, The First School of Clinical Medicine, Lanzhou University, Lanzhou 730000, Gansu Province, China
Jun Yan, Ying Li, Xun Li, Department of General Surgery, The First Hospital of Lanzhou University, Lanzhou 730000, Gansu Province, China
Author contributions: Nie GL and Zhang HL wrote the first draft of the manuscript; Li Y and Yan J established inclusion and exclusion criteria; Xie DN and Zhu XW conducted literature searches; GL N and Zhang HL performed the data analysis and drew tables and pictures; Li Y, Yan J, and Li X reviewed and provided feedback on various drafts of the manuscript and approved the final manuscript.
Institutional review board statement: This study was approved by the Ethics Committee of the First Hospital of Lanzhou University (LDYYLL2021-286) and was conducted in accordance with the principles of the Declaration of Helsinki.
Informed consent statement: As the study was a retrospective study, the extracted clinical data and laboratory tests were from the electronic case retrieval system of the First Hospital of Lanzhou University. The study was approved by the Ethics Committee of the First Hospital of Lanzhou University (LDYYLL2021-286). The data are a nonymous, and the requirement for informed consent was therefore waived.
Conflict-of-interest statement: The authors reported no financial interests or potential conflicts of interest.
Data sharing statement: Data supporting the findings of this study are available from the author upon 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: https://creativecommons.org/Licenses/by-nc/4.0/
Corresponding author: Xun Li, PhD, Chief Physician, Department of General Surgery, The First Hospital of Lanzhou University, No. 1 Donggang West Road, Chengguan District, Lanzhou 730000, Gansu Province, China. lxdr21@126.com
Received: October 8, 2023
Peer-review started: October 8, 2023
First decision: January 12, 2024
Revised: January 18, 2024
Accepted: February 23, 2024
Article in press: February 23, 2024
Published online: April 15, 2024
Processing time: 185 Days and 22.5 Hours
Abstract
BACKGROUND

Portal vein thrombosis (PVT), a complication of liver cirrhosis, is a major public health concern. PVT prediction is the most effective method for PVT diagnosis and treatment.

AIM

To develop and validate a nomogram and network calculator based on clinical indicators to predict PVT in patients with cirrhosis.

METHODS

Patients with cirrhosis hospitalized between January 2016 and December 2021 at the First Hospital of Lanzhou University were screened and 643 patients with cirrhosis who met the eligibility criteria were retrieved. Following a 1:1 propensity score matching 572 patients with cirrhosis were screened, and relevant clinical data were collected. PVT risk factors were identified using the least absolute shrinkage and selection operator (LASSO) and multivariate logistic regression analysis. Variance inflation factors and correlation matrix plots were used to analyze multicollinearity among the variables. A nomogram was constructed to predict the probability of PVT based on independent risk factors for PVT, and its predictive performance was verified using a receiver operating characteristic curve (ROC), calibration curves, and decision curve analysis (DCA). Finally, a network calculator was constructed based on the nomograms.

RESULTS

This study enrolled 286 cirrhosis patients with PVT and 286 without PVT. LASSO analysis revealed 13 variables as strongly associated with PVT occurrence. Multivariate logistic regression analysis revealed nine indicators as independent PVT risk factors, including etiology, ascites, gastroesophageal varices, platelet count, D-dimer, portal vein diameter, portal vein velocity, aspartate transaminase to neutrophil ratio index, and platelet-to-lymphocyte ratio. LASSO and correlation matrix plot results revealed no significant multicollinearity or correlation among the variables. A nomogram was constructed based on the screened independent risk factors. The nomogram had excellent predictive performance, with an area under the ROC curve of 0.821 and 0.829 in the training and testing groups, respectively. Calibration curves and DCA revealed its good clinical performance. Finally, the optimal cutoff value for the total nomogram score was 0.513. The sensitivity and specificity of the optimal cutoff values were 0.822 and 0.706, respectively.

CONCLUSION

A nomogram for predicting PVT occurrence was successfully developed and validated, and a network calculator was constructed. This can enable clinicians to rapidly and easily identify high PVT risk groups.

Keywords: Portal vein thrombosis; Liver cirrhosis; Nomogram; Inflammatory markers; Aspartate aminotransferase to neutrophil ratio index; Platelet-to-lymphocyte ratio

Core Tip: A nomogram to predict the probability of portal vein thrombosis (PVT) occurrence was successfully developed and validated and further constructed a network calculator. This can help clinicians to quickly and easily identify people at high risk for PVT in cirrhosis and early prevention.