UCL Institute for Liver & Digestive Health, London, UK
UCL Institute for Liver & Digestive Health, London, UK.
BMJ Open Gastroenterol. 2024 Aug 25;11(1):e001430. doi: 10.1136/bmjgast-2024-001430.
The transition from compensated to decompensated cirrhosis is crucial, drastically reducing prognosis from a median survival of over 10 years to 2 years. There is currently an unmet need to accurately predict decompensation. We systematically reviewed and meta-analysed data regarding biomarker use to predict decompensation in individuals with compensated cirrhosis.
PubMed and EMBASE database searches were conducted for all studies from inception until February 2024. The study was carried out according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. The Quality of Prognosis Studies framework was used to assess the risk of bias. The meta-analysis was conducted with a random effects model using STATA software.
Of the 652 studies initially identified, 63 studies (n=31 438 patients) were included in the final review, examining 49 biomarkers. 25 studies (40%) were prospective with the majority of studies looking at all-cause decompensation (90%). The most well-studied biomarkers were platelets (n=17), Model for End-Stage Liver Disease (n=17) and albumin (n=16). A meta-analysis revealed elevated international normalised ratio was the strongest predictor of decompensation, followed by decreased albumin. However, high statistical heterogeneity was noted (l result of 96.3%). Furthermore, 21 studies were assessed as having a low risk of bias (34%), 26 (41%) moderate risk and 16 (25%) high risk.
This review highlights key biomarkers that should potentially be incorporated into future scoring systems to predict decompensation. However, future biomarker studies should be conducted with rigorous and standardised methodology to ensure robust and comparable data.
从代偿性肝硬化向失代偿性肝硬化的转变至关重要，这使得预后从中位生存期超过 10 年急剧下降至 2 年。目前迫切需要准确预测失代偿。我们系统地回顾和荟萃分析了关于生物标志物用于预测代偿性肝硬化患者失代偿的数据。
从建库至 2024 年 2 月，我们在 PubMed 和 EMBASE 数据库中搜索了所有研究。研究按照系统评价和荟萃分析报告的首选条目进行。使用预后研究质量框架评估偏倚风险。荟萃分析采用 STATA 软件的随机效应模型进行。
最初确定的 652 项研究中，有 63 项研究（n=31438 例患者）最终纳入综述，共涉及 49 种生物标志物。25 项研究（40%）为前瞻性，大多数研究着眼于全因失代偿（90%）。研究最多的生物标志物是血小板（n=17）、终末期肝病模型（n=17）和白蛋白（n=16）。荟萃分析显示，国际标准化比值升高是失代偿的最强预测因子，其次是白蛋白减少。然而，注意到高度统计异质性（I ² 结果为 96.3%）。此外，21 项研究被评估为低偏倚风险（34%），26 项研究（41%）为中度风险，16 项研究（25%）为高风险。
本综述强调了一些关键的生物标志物，这些标志物可能需要纳入未来的评分系统以预测失代偿。然而，未来的生物标志物研究应采用严格和标准化的方法，以确保可靠和可比的数据。
