ORIGINAL RESEARCH article
Front. Med.
Sec. Hepatobiliary Diseases
Development and Validation of a Prediction Model for Invasive Syndrome in Liver Abscess Patients Based on LASSO Regression: A Multi-center Retrospective Cohort Study in China
Provisionally accepted
Dian-Dian Hao1
Guang-Zhao Shao2
Xiu-Li Wang2Chang-Cheng Zhao3Jia-Lin Du1Hui Wang1Yu-Lin Ren1Yu-Ze Song1
Xiao-Yu Wen1*- 1Department of Gastroenterology, The First Hospital of Jilin University, Changchun, Jilin, China
- 2Department of Hepatobiliary and Pancreatic Surgery, First Hospital of Jilin University, Changchun, China
- 3Department of General Surgery, Yanshi People's Hospital, Luoyang, Henan, 471900, China., Luoyang, China
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Backgrounds: Patients with liver abscess are at high risk of developing invasive K. pneumoniae liver abscess syndrome (IKPLAS), which can worsen survival and quality of life. Early identification of high-risk patients is crucial. This study aimed to identify risk factors for IKPLAS and develop a predictive model to guide early intervention. Methods: We retrospectively collected data from 1,762 liver abscess patients at the First Hospital of Jilin University between 2015 and 2024. Patients were randomly divided into a training set and an internal validation set at a 7:3 ratio, and 203 patients from another hospital served as an external validation cohort. The SMOTE algorithm was applied to address data imbalance. Independent risk factors were identified using LASSO and logistic regression analyses, and the performance of different models was compared. Ultimately, a LASSO-based logistic regression model was used to construct a predictive nomogram. Model performance was comprehensively evaluated using the area under the receiver operating characteristic curve (AUC), decision curve analysis (DCA), clinical impact curve (CIC), and calibration curve. An online risk calculator was also developed for clinical use. Results: Among 1,965 patients (1,304 males, 661 females; mean age 58.96±13.07 years), 548 (28.9%) developed IKPLAS. Independent risk factors included CRP (OR=1.005, 95% CI: 1.003–1.007), PLT (OR=0.995, 95% CI: 0.994–0.997), Prior biliary disease (OR=1.137, 95% CI: 1.025–2.571), Fever (OR=2.196, 95% CI: 1.292– 3.824), Pleural effusion (OR=7.355, 95% CI: 4.883–14.761), Ascites (OR=8.786, 95% CI: 5.141–9.342), Broth culture (OR=2.264, 95% CI: 1.186–3.371), DM (OR=2.516, 95% CI: 1.757–3.63), and TBIL (OR=1.006, 95% CI: 1.002–1.010). The nomogram achieved AUCs of 0.960, 0.920, and 0.892 in the training, internal, and external
Keywords: Liver Abscess, Invasive syndrome, multicenter, predictive model, web-based calculator
Received: 08 Feb 2025; Accepted: 17 Nov 2025.
Copyright: © 2025 Hao, Shao, Wang, Zhao, Du, Wang, Ren, Song and Wen. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Xiao-Yu Wen, xywen@jlu.edu.cn
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