背景:门脉高压(PHT),主要由肝硬化引起,表现出影响患者生存的严重症状。尽管经颈静脉肝内门体分流术(TIPS)是治疗PHT的关键干预措施,它有肝性脑病等风险,从而影响患者生存预后。据我们所知,PHT患者TIPS后生存的现有预后模型未能解释各种预后因素对结局的相互作用和共同影响.因此,创新建模方法的发展对于解决这一限制至关重要。
目的:开发并验证基于贝叶斯网络(BN)的生存预测模型,用于肝硬化诱导的PHT患者经历TIPS。
方法:回顾性分析2015年1月至2022年5月在重庆医科大学附属第二医院行TIPS手术的393例肝硬化PHT患者的临床资料。使用Cox和最小绝对收缩和选择算子回归方法选择变量,建立并评估了基于BN的模型,以预测接受TIPS手术的PHT患者的生存率。
结果:变量选择揭示了以下是影响生存的关键因素:年龄,腹水,高血压,提示的指示,术后门静脉压力(PVP后),天冬氨酸转氨酶,碱性磷酸酶,总胆红素,前白蛋白,Child-Pugh年级,和终末期肝病模型(MELD)评分。根据上述变量,构建了基于BN的2年生存预后预测模型,确定了以下与生存时间直接相关的因素:年龄,腹水,提示的指示,并发高血压,post-PVP,Child-Pugh年级,和MELD得分。贝叶斯信息标准为3589.04,10倍交叉验证表明平均对数似然损失为5.55,标准偏差为0.16。模型的准确性,精度,召回,F1评分分别为0.90、0.92、0.97和0.95,接收器工作特性曲线下的面积为0.72。
结论:本研究成功开发了基于BN的生存预测模型,具有良好的预测能力。它为接受TIPS手术的PHT患者的治疗策略和预后评估提供了有价值的见解。
BACKGROUND: Portal hypertension (PHT), primarily induced by cirrhosis, manifests severe symptoms impacting patient survival. Although transjugular intrahepatic portosystemic shunt (TIPS) is a critical intervention for managing PHT, it carries risks like hepatic encephalopathy, thus affecting patient survival prognosis. To our knowledge, existing prognostic models for post-TIPS survival in patients with PHT fail to account for the interplay among and collective impact of various prognostic factors on outcomes. Consequently, the development of an innovative modeling approach is essential to address this limitation.
OBJECTIVE: To develop and validate a Bayesian network (BN)-based survival prediction model for patients with cirrhosis-induced PHT having undergone TIPS.
METHODS: The clinical data of 393 patients with cirrhosis-induced PHT who underwent TIPS surgery at the Second Affiliated Hospital of Chongqing Medical University between January 2015 and May 2022 were retrospectively analyzed. Variables were selected using Cox and least absolute shrinkage and selection operator regression methods, and a BN-based model was established and evaluated to predict survival in patients having undergone TIPS surgery for PHT.
RESULTS: Variable selection revealed the following as key factors impacting survival: age, ascites, hypertension, indications for TIPS, postoperative portal vein pressure (post-PVP), aspartate aminotransferase, alkaline phosphatase, total bilirubin, prealbumin, the Child-Pugh grade, and the model for end-stage liver disease (MELD) score. Based on the above-mentioned variables, a BN-based 2-year survival prognostic prediction model was constructed, which identified the following factors to be directly linked to the survival time: age, ascites, indications for TIPS, concurrent hypertension, post-PVP, the Child-Pugh grade, and the MELD score. The Bayesian information criterion was 3589.04, and 10-fold cross-validation indicated an average log-likelihood loss of 5.55 with a standard deviation of 0.16. The model\'s accuracy, precision, recall, and F1 score were 0.90, 0.92, 0.97, and 0.95 respectively, with the area under the receiver operating characteristic curve being 0.72.
CONCLUSIONS: This study successfully developed a BN-based survival prediction model with good predictive capabilities. It offers valuable insights for treatment strategies and prognostic evaluations in patients having undergone TIPS surgery for PHT.