Calzadilla Bertot Luis, Sòria Anna, Jimenez-Masip Alba, Serra Isabel, Broquetas Teresa, Vergara Mercedes, Rodriguez Adrià, Aracil Carles, El Maimouni Cautar, Muñoz-Martinez Sergio, Carrión Jose A, Pardo Albert, Pericàs Juan M, Graupera Isabel, Adams Leon A
Medical School, University of Western Australia, Nedlands, Western Australia, Australia.
Department of Hepatology, Sir Charles Gairdner Hospital, Nedlands, Western Australia, Australia.
Aliment Pharmacol Ther. 2025 Sep;62(5):526-535. doi: 10.1111/apt.70215. Epub 2025 Jun 10.
BACKGROUND & AIMS: Predicting the risk of hepatic decompensation guides prognostication and therapy; however, it is challenging in patients with cirrhosis due to metabolic dysfunction-associated steatotic liver disease (MASLD). We aimed to improve a previously developed predictive tool of hepatic decompensation in MASLD cirrhosis (ABIDE) by incorporating liver stiffness measurement (LSM).
A multi-centre retrospective cohort of patients with compensated cirrhosis due to MASLD was identified, with decompensation incidence assessed using competing risk regression. The prognostic accuracy of a modified ABIDE model incorporating LSM (ABID-LSM) was assessed using time-dependent AUC (tAUC) and compared with other predictive models.
Out of 388 patients, 273 (70.4%) had available LSM. Hepatic decompensation occurred in 54 (20%) patients during follow-up (median 31 months, range: 20-60). The predictive accuracy at 5 years of ABID-LSM (tAUC 0.80) was better than ABIDE (tAUC 0.75, p = 0.03) and LSM (tAUC 0.63, p < 0.001). The ABID-LSM model calibrated well (slope 0.99) with excellent overall performance (Integrated Brier Score 0.15). A cut-off of 8.1 separated those at high and low risk of hepatic decompensation at 5 years (24% vs. 5%, respectively, sHR = 4.8, p < 0.001). The ABID-LSM model had better predictive ability at 5 years than ALBI, FIB-4, NAFLD Decompensation Risk Score and ANTICIPATE models (all p < 0.001) as well as hepatic vein pressure gradient measurement (tAUC 0.78 vs. 0.71, p < 0.001, n = 60).
The ABID-LSM model has greater accuracy in predicting hepatic decompensation in patients with cirrhosis due to MASLD than existing predictive models. If externally validated, ABID-LSM may identify those who benefit from pharmacotherapy and close monitoring.
预测肝失代偿风险有助于指导预后评估和治疗;然而,对于代谢功能障碍相关脂肪性肝病(MASLD)所致肝硬化患者而言,这具有挑战性。我们旨在通过纳入肝脏硬度测量(LSM)来改进先前开发的MASLD肝硬化肝失代偿预测工具(ABIDE)。
确定一个多中心回顾性队列,纳入因MASLD导致的代偿期肝硬化患者,使用竞争风险回归评估失代偿发生率。使用时间依赖性AUC(tAUC)评估纳入LSM的改良ABIDE模型(ABID-LSM)的预后准确性,并与其他预测模型进行比较。
388例患者中,273例(70.4%)有可用的LSM数据。随访期间54例(20%)患者发生肝失代偿(中位时间31个月,范围:20 - 60个月)。ABID-LSM在5年时的预测准确性(tAUC 0.80)优于ABIDE(tAUC 0.75,p = 0.03)和LSM(tAUC 0.63,p < 0.001)。ABID-LSM模型校准良好(斜率0.99),整体性能优异(综合Brier评分0.15)。截断值为8.1时,可区分5年时肝失代偿高风险和低风险患者(分别为24%和5%,sHR = 4.8,p < 0.001)。ABID-LSM模型在5年时的预测能力优于ALBI、FIB-4、NAFLD失代偿风险评分和ANTICIPATE模型(所有p < 0.