Early Warning Models to Estimate the 30-Day Mortality Risk After Stent Placement for Patients with Malignant Biliary Obstruction

Purpose To develop, validate, and compare early warning models of the 30-day mortality risk for patients with malignant biliary obstruction (MBO) undergoing percutaneous transhepatic biliary stent placement (PTBS). Materials and Methods Between January 2013 and October 2018, this multicenter retrosp...

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Bibliographic Details
Published in:Cardiovascular and interventional radiology 2019-12, Vol.42 (12), p.1751-1759
Main Authors: Zhou, Hai-Feng, Lu, Jian, Zhu, Hai-Dong, Guo, Jin-He, Huang, Ming, Ji, Jian-Song, Lv, Wei-Fu, Li, Yu-Liang, Xu, Hao, Chen, Li, Zhu, Guang-Yu, Teng, Gao-Jun
Format: Article
Language:English
Subjects:
ACCURACY
Aged
Aged, 80 and over
Artificial neural networks
Biliary
BILIARY TRACT
Biliary Tract - pathology
Biliary Tract Neoplasms - complications
Biliary Tract Neoplasms - mortality
Cardiology
Cholestasis - etiology
Cholestasis - mortality
Cholestasis - surgery
Clinical Investigation
Female
Humans
Imaging
Implants
Male
Medicine
Medicine & Public Health
Middle Aged
Model accuracy
Models, Statistical
MORTALITY
NEOPLASMS
NEURAL NETWORKS
Nuclear Medicine
Pancreatic Neoplasms - complications
Pancreatic Neoplasms - mortality
PATIENTS
Performance prediction
Placement
Radiology
RADIOLOGY AND NUCLEAR MEDICINE
Reclassification
Reproducibility of Results
Retrospective Studies
Risk
Risk Assessment
SENSITIVITY
SPECIFICITY
Stents
Surgical implants
TRAINING
Ultrasound
VALIDATION
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Summary:Purpose To develop, validate, and compare early warning models of the 30-day mortality risk for patients with malignant biliary obstruction (MBO) undergoing percutaneous transhepatic biliary stent placement (PTBS). Materials and Methods Between January 2013 and October 2018, this multicenter retrospective study included 299 patients with MBOs who underwent PTBS. The training set consisted of 166 patients from four cohorts, and another two independent cohorts were allocated as external validation sets A and B with 75 patients and 58 patients, respectively. A logistic model and an artificial neural network (ANN) model were developed to predict the risk of 30-day mortality after PTBS. The predictive performance of these two models was validated internally and externally. Results The ANN model had higher values of area under the curve than the logistic model in the training set (0.819 vs 0.797), especially in the validation sets A (0.802 vs 0.714) and B (0.732 vs 0.568). Both models had high accuracy in the three sets (75.9–83.1%). Along with a high specificity, the ANN model improved the sensitivity. The net reclassification improvement and integrated discrimination improvement also demonstrated that the ANN model led to improvements in predictive ability compared with the logistic model. Conclusions Early warning models were proposed to predict the risk of 30-day mortality after PTBS in patients with MBO. The ANN model has higher accuracy and better generalizability than the logistic model.
ISSN:0174-1551
1432-086X
DOI:10.1007/s00270-019-02331-5