糖尿病患者代谢功能障碍相关脂肪变性肝病相关晚期纤维化筛查:一项前瞻性多中心研究

IF 16.6
Diabetes care Pub Date : 2025-06-01 DOI:10.2337/dc24-2075
Cyrielle Caussy, Bruno Vergès, Damien Leleu, Laurence Duvillard, Fabien Subtil, Amna Abichou-Klich, Valérie Hervieu, Laurent Milot, Bérénice Ségrestin, Sylvie Bin, Alexia Rouland, Dominique Delaunay, Pierre Morcel, Samy Hadjadj, Claire Primot, Jean-Michel Petit, Sybil Charrière, Philippe Moulin, Massimo Levrero, Bertrand Cariou, Emmanuel Disse
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引用次数: 0

摘要

目的:糖尿病学推荐筛查代谢功能障碍相关脂肪变性肝病(MASLD)导致的晚期纤维化(AF)。本研究旨在比较无创检测(NITs)与两步算法在检测需要转诊给肝病学家的房颤高风险患者方面的表现。研究设计和方法:我们对一项前瞻性多中心研究进行了计划中的中期分析,该研究纳入了2型糖尿病和/或肥胖和MASLD患者,并进行了全面的肝脏评估,包括基于血液的NITs、振动控制瞬态弹性成像(VCTE)和二维剪切波弹性成像(2D-SWE)。根据可用性,通过肝活检、磁共振弹性成像或VCTE≥12 kPa的综合标准确定房颤风险分层。结果:654例患者中(2型糖尿病87%,男性56%,肥胖74%),房颤中高危17.6%,高危9.3%。NITs检测房颤高风险的经验受者工作特征曲线下面积为:纤维化-4 (FIB-4)评分为0.78 (95% CI 0.72 ~ 0.84);FibroMeter, 0.74 (0.66-0.83);Fibrotest, 0.78 (0.72-0.85);增强肝纤维化(ELF)试验,0.82 (0.76-0.87);SWE为0.84(0.78 ~ 0.89)。FIB-4评分/VCTE算法在转诊房颤中/高风险患者到肝病专科治疗方面表现出良好的诊断效果。另一种FIB-4评分/ELF测试策略显示出较高的负预测值(NPV;88-89%)和较低的阳性预测值(PPV;39-46%),阈值为9.8。FIB-4评分/2D-SWE策略的NPV为91%,PPV为58-62%。年龄适应FIB-4评分阈值导致所有算法的npv和ppv均较低。结论:FIB-4评分/VCTE算法具有良好的诊断性能,可用于糖尿病常规筛查。使用9.8的适应性低阈值的极低频测试可以作为VCTE的替代方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Screening for Metabolic Dysfunction-Associated Steatotic Liver Disease-Related Advanced Fibrosis in Diabetology: A Prospective Multicenter Study.

Objective: Screening for advanced fibrosis (AF) resulting from metabolic dysfunction-associated steatotic liver disease (MASLD) is recommended in diabetology. This study aimed to compare the performance of noninvasive tests (NITs) with that of two-step algorithms for detecting patients at high risk of AF requiring referral to hepatologists.

Research design and methods: We conducted a planned interim analysis of a prospective multicenter study including participants with type 2 diabetes and/or obesity and MASLD with comprehensive liver assessment comprising blood-based NITs, vibration-controlled transient elastography (VCTE), and two-dimensional shear-wave elastography (2D-SWE). AF risk stratification was determined by a composite criterion of liver biopsy, magnetic resonance elastography, or VCTE ≥12 kPa depending on availability.

Results: Of 654 patients (87% with type 2 diabetes, 56% male, 74% with obesity), 17.6% had an intermediate/high risk of AF, and 9.3% had a high risk of AF. The area under the empirical receiver operating characteristic curves of NITs for detection of high risk of AF were as follows: fibrosis-4 index (FIB-4) score, 0.78 (95% CI 0.72-0.84); FibroMeter, 0.74 (0.66-0.83); FibroTest, 0.78 (0.72-0.85); Enhanced Liver Fibrosis (ELF) test, 0.82 (0.76-0.87); and SWE, 0.84 (0.78-0.89). Algorithms with FIB-4 score/VCTE showed good diagnostic performance for referral of patients at intermediate/high risk of AF to specialized care in hepatology. An alternative FIB-4 score/ELF test strategy showed a high negative predictive value (NPV; 88-89%) and a lower positive predictive value (PPV; 39-46%) at a threshold of 9.8. The FIB-4 score/2D-SWE strategy had an NPV of 91% and a PPV of 58-62%. The age-adapted FIB-4 score threshold resulted in lower NPVs and PPVs in all algorithms.

Conclusions: The FIB-4 score/VCTE algorithm showed excellent diagnostic performance, demonstrating its applicability for routine screening in diabetology. The ELF test using an adapted low threshold at 9.8 may be used as an alternative to VCTE.

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