CLivD评分改变了FIB-4在美国普通人群肝纤维化检测中的表现

F. Åberg, Mitja Lääperi, V. Männistö
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摘要

脂肪肝(SLD)是全球日益关注的问题。慢性肝病(CLivD)风险评分利用易于获取的变量,通过或不通过实验室检测(CLivDlab 和 CLivDnon-lab)预测普通人群中与肝脏相关的结果。我们评估了CLivD与肝脏脂肪变性、肝纤维化的关联,以及其与纤维化-4(FIB-4)联合检测晚期肝纤维化的性能。利用美国国家健康与营养调查数据(2017-2020年),纳入了3603名年龄在40-70岁之间、具有有效肝脏硬度测量值(LSM)的参与者。晚期肝纤维化的定义为 LSM ≥12 kPa,SLD 为受控衰减参数 ≥288 dB/m.研究发现 CLivD 和 SLD 与晚期肝纤维化之间存在显著关联。CLivDlab的晚期纤维化曲线下面积(AUC)为0.72(95% CI 0.68至0.77),而CLivDnon-lab的AUC为0.68(95% CI 0.64至0.72),均略高于FIB-4(AUC 0.66,95% CI 0.60至0.72)。在无肥胖症的参与者中,CLivDlab的AUC为0.82(95% CI 0.76至0.88),CLivDnon-lab的AUC为0.72(95% CI 0.65至0.79)。CLivD评分提高了FIB-4的晚期纤维化检测AUC,CLivD高分时AUC为0.8。CLivD→FIB-4连续检测策略优于FIB-4全面检测,特异性从72%提高到83%,灵敏度为51%-53%。CLivD评分是为预测肝脏相关结果而设计的,能有效识别普通人群中的肝脏脂肪变性和晚期纤维化。将CLivD与FIB-4结合可提高晚期肝纤维化检测的准确性。CLivD评分可加强基于人群的肝纤维化筛查,优化资源分配。
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CLivD score modifies FIB-4 performance in liver fibrosis detection in the US general population
Steatotic liver disease (SLD) is a growing global concern. The Chronic Liver Disease (CLivD) risk score predicts liver-related outcomes in the general population using easily accessible variables with or without laboratory tests (CLivDlaband CLivDnon-lab). We assessed CLivD’s associations with liver steatosis, fibrosis and its combined performance with fibrosis-4 (FIB-4) for advanced fibrosis detection.Using the National Health and Nutrition Examination Survey data (2017–2020), 3603 participants aged 40–70 years with valid liver stiffness measurements (LSMs) were included. Advanced fibrosis was defined as LSM ≥12 kPa, and SLD as controlled attenuation parameter ≥288 dB/m.Significant associations were found between CLivD and SLD and advanced fibrosis. CLivDlabhad an area under the curve (AUC) for advanced fibrosis of 0.72 (95% CI 0.68 to 0.77), while CLivDnon-labhad an AUC of 0.68 (95% CI 0.64 to 0.72), both slightly higher than FIB-4 (AUC 0.66, 95% CI 0.60 to 0.72). Among participants without obesity, AUC of CLivDlabwas 0.82 (95% CI 0.76 to 0.88) and AUC of CLivDnon-labwas 0.72 (95% CI 0.65 to 0.79). The CLivD score improved FIB-4’s AUC for advanced fibrosis detection from <0.5 at minimal CLivD scores to >0.8 at high CLivD scores. A sequential CLivD→FIB-4 strategy outperformed universal FIB-4 testing, enhancing specificity from 72% to 83%, with sensitivity at 51%–53%. This strategy identified a subgroup with a 55% prevalence of advanced fibrosis, while 47% had minimal-risk CLivD scores, eliminating the need for FIB-4 testing.The CLivD score, designed for predicting liver-related outcomes, effectively identifies liver steatosis and advanced fibrosis in the general population. Combining CLivD with FIB-4 enhances advanced fibrosis detection accuracy. The CLivD score could enhance population-based liver fibrosis screening, optimising resource allocation.
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