Zhuhai Interventional Medical Center, Zhuhai Hospital Affiliated with Jinan University (Zhuhai People's Hospital), Zhuhai, China.
Zhuhai Engineering Technology Research Center of Intelligent Medical Imaging, Zhuhai Hospital Affiliated with Jinan University (Zhuhai People's Hospital), Zhuhai, China.
Liver Int. 2024 Feb;44(2):472-482. doi: 10.1111/liv.15790. Epub 2023 Nov 27.
The transjugular intrahepatic portosystemic shunt has controversial survival benefits; thus, patient screening should be performed preoperatively. In this study, we aimed to develop a model to predict post-transjugular intrahepatic portosystemic shunt mortality to aid clinical decision making.
A total of 811 patients undergoing transjugular intrahepatic portosystemic shunt from five hospitals were divided into the training and external validation data sets. A modified prediction model of post-transjugular intrahepatic portosystemic shunt mortality (Model ) was built after performing logistic regression. To verify the improved performance of Model , we compared it with seven previous models, both in discrimination and calibration. Furthermore, patients were stratified into low-, medium-, high- and extremely high-risk subgroups.
Model demonstrated a satisfying predictive efficiency in both discrimination and calibration, with an area under the curve of .875 in the training set and .852 in the validation set. Compared to previous models (ALBI, BILI-PLT, MELD-Na, MOTS, FIPS, MELD, CLIF-C AD), Model showed superior performance in discrimination by statistical difference in the Delong test, net reclassification improvement and integrated discrimination improvement (all p < .050). Similar results were observed in calibration. Low-, medium-, high- and extremely high-risk groups were defined by scores of ≤160, 160-180, 180-200 and >200, respectively. To facilitate future clinical application, we also built an applet for Model .
We successfully developed a predictive model with improved performance to assist in decision making for transjugular intrahepatic portosystemic shunt according to survival benefits.
经颈静脉肝内门体分流术的生存获益存在争议；因此，术前应进行患者筛选。本研究旨在建立一种预测经颈静脉肝内门体分流术后死亡率的模型，以辅助临床决策。
本研究纳入了来自五家医院的 811 例行经颈静脉肝内门体分流术的患者，将其分为训练集和外部验证数据集。通过逻辑回归构建了改良的经颈静脉肝内门体分流术后死亡率预测模型（模型）。为了验证模型性能的改善，我们在判别和校准方面将其与七个之前的模型进行了比较。此外，我们还将患者分层为低危、中危、高危和极高危亚组。
模型在判别和校准方面均表现出良好的预测效率，在训练集和验证集的曲线下面积分别为 0.875 和 0.852。与之前的模型（ALBI、BILI-PLT、MELD-Na、MOTS、FIPS、MELD、CLIF-C AD）相比，模型在判别方面表现出更好的性能，通过 Delong 检验、净重新分类改善和综合判别改善的统计学差异（均 P < 0.050）。校准方面也观察到了类似的结果。低危、中危、高危和极高危组的评分分别为≤160、160-180、180-200 和>200。为了便于未来的临床应用，我们还为模型构建了一个小程序。
我们成功开发了一种具有改进性能的预测模型，以根据生存获益辅助经颈静脉肝内门体分流术的决策。
