Grady John, Song Michael, Townsend Whitney, Mahmud Nadim, Tapper Elliot B, Parikh Neehar D
Department of Internal Medicine, University of Michigan, Ann Arbor, Michigan, USA.
Division of Gastroenterology and Hepatology, Department of Internal Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
Hepatol Commun. 2025 Mar 24;9(4). doi: 10.1097/HC9.0000000000000675. eCollection 2025 Apr 1.
Hepatic decompensation carries profound implications for patient quality of life and risk of mortality. We lack comparative data on how noninvasive tools perform in risk stratification for those with compensated cirrhosis. We performed a systematic review to assess the performance of laboratory and transient elastography-based models for predicting hepatic decompensation in patients with compensated cirrhosis.
The following databases were searched by an informationist to identify relevant studies, including adult patients with compensated cirrhosis from inception to August 2023: Medline, Embase, Scopus, Web of Science, and ClinicalTrials.gov. Title and abstract screening followed by full-text review were performed by 2 independent reviewers, and data abstraction was completed using standardized forms. Studies of patients with decompensation at baseline (defined by ascites, variceal bleeding, and HE) or any primary hepatic malignancy were excluded. The primary outcome was hepatic decompensation, as defined above. Pooled HRs were calculated using the common-effect inverse-variance model.
Forty-four full-text studies met the inclusion criteria. Across 52,589 patients, the cumulative incidence of any decompensation was 17.9% over a follow-up time of 111,401 patient years. Pooled risk estimates for all-cause decompensation demonstrated that MELD (HR: 1.08; 95% CI: 1.06-1.10), albumin-bilirubin (HR: 2.13, 95% CI: 1.92-2.36), fibrosis-4 (HR: 1.04, 95% CI: 1.03-1.06), albumin-bilirubin-fibrosis-4 (HR: 1.25, 95% CI: 1.18-1.33), and liver stiffness by transient elastography (HR: 1.04; 95% CI: 1.04-1.05) predict decompensation.
Available blood and imaging-based biomarkers can risk-stratify patients for hepatic decompensation. Changes in albumin-bilirubin appear to have the highest discrimination in predicting decompensation events.
肝失代偿对患者生活质量和死亡风险具有深远影响。对于代偿期肝硬化患者，我们缺乏关于非侵入性工具在风险分层中表现的比较数据。我们进行了一项系统评价，以评估基于实验室检查和瞬时弹性成像的模型在预测代偿期肝硬化患者肝失代偿方面的性能。
由一名信息专家检索以下数据库，以识别相关研究，包括从研究开始至2023年8月的成年代偿期肝硬化患者：医学期刊数据库（Medline）、荷兰医学文摘数据库（Embase）、Scopus数据库、科学引文索引数据库（Web of Science）和美国国立医学图书馆临床试验注册库（ClinicalTrials.gov）。由2名独立评审员进行标题和摘要筛选，随后进行全文评审，并使用标准化表格完成数据提取。排除基线时存在失代偿（定义为腹水、静脉曲张出血和肝性脑病）或任何原发性肝癌的患者研究。主要结局为上述定义的肝失代偿。使用固定效应逆方差模型计算合并风险比（HR）。
44项全文研究符合纳入标准。在52589例患者中，在111401患者年的随访时间内，任何失代偿的累积发生率为17.9%。全因失代偿的合并风险估计表明，终末期肝病模型（MELD）（HR：1.08；95%置信区间：1.06 - 1.10）、白蛋白-胆红素比值（HR：2.13，95%置信区间：1.92 - 2.36）、纤维化-4指数（HR：1.04，95%置信区间：1.03 - 1.06）、白蛋白-胆红素-纤维化-4指数（HR：1.25，95%置信区间：1.18 - 1.33）以及瞬时弹性成像测定的肝脏硬度（HR：1.04；95%置信区间：1.04 - 1.05）可预测失代偿。
现有的血液和影像学生物标志物可对肝失代偿患者进行风险分层。白蛋白-胆红素比值的变化在预测失代偿事件方面似乎具有最高的辨别力。
