开发并验证基于循环成纤维细胞活化蛋白的新型预测模型,改善代谢性肝病人群的纤维化风险分层

Ziqi Vincent Wang, Badwi B Boumelhem, Torsten Pennell, William W Bachovchin, Geraldine Ooi, Jacob George, Mohammed Eslam, Leon A Adams, Pieter van der Veken, Jack Hung-Sen Lai, Sarah Poplawski, Kate Brewer, Hui Emma Zhang, Geoffrey W McCaughan, Avik Majumdar, Mark D Gorrell
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摘要

目的:代谢性脂肪肝会造成慢性肝损伤,导致肝纤维化。本研究旨在建立一种利用血清循环成纤维细胞活化蛋白(cFAP)诊断脂肪肝患者晚期肝纤维化的模型。设计:研究了两个从三级肝病诊所招募的回顾性队列,分别作为训练队列(n=160)和外部验证队列(n=342),其组织学晚期肝纤维化(F3/F4)发生率分别为20%和11%。活化间质纤维化细胞的标志物 cFAP 是用我们的单步酶测定法测量的。利用逻辑回归建立了一个预测模型,即 FAP 指数,其中包含年龄、2 型糖尿病、丙氨酸转氨酶和 cFAP 的序数。结果:FAP 指数的 AUROC 在训练队列中为 0.875(95% CI 0.813-0.938),在验证队列中为 0.841(95% CI 0.776-0.906)。低临界值-1.68(灵敏度 80.0%,阴性预测值 95.5%)和高临界值+0.953(特异性 97.7%,阳性预测值 88.9%)分别排除和诊断了晚期纤维化。在验证队列中,与单独使用 FIB-4 相比,先使用 FAP 指数再使用 FIB-4 可将不确定结果减少三分之一。而 FAP 指数和 NFS(非酒精性脂肪肝纤维化评分)可将不确定结果减少 70%。结论:FAP 指数是一种新颖、快速、可靠、廉价的代谢性脂肪肝晚期纤维化诊断工具。与单独使用 FIB-4 或 NFS 相比,使用 FAP 指数和 FIB-4 或 NFS 可大大减少不确定结果的出现频率,从而有助于对患者进行准确的风险分层,而不会影响阴性预测值。
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Development and validation of a novel circulating fibroblast activation protein - based predictive model to improve fibrosis risk stratification in metabolic liver disease population
Objective: Metabolic fatty liver disease drives chronic liver injury leading to fibrosis. This study aimed to establish a model utilising serum circulating fibroblast activation protein (cFAP) to diagnose advanced fibrosis in patients with fatty liver disease. Design: Two retrospective cohorts recruited from tertiary hepatology clinics were studied as training (n=160) and external validation cohorts (n=342), with prevalence of histologic advanced fibrosis (F3/F4) of 20% and 11%, respectively. A marker of activated mesenchymal fibrogenic cells, cFAP, was measured using our single-step enzyme assay. A predictive model, FAP Index, containing age, type 2 diabetes, alanine transaminase and ordinal cFAP was developed using logistic regression. Diagnostic accuracy of FAP Index was assessed on a single and then sequential basis. Results: FAP Index AUROC was 0.875 (95% CI 0.813-0.938) in the training cohort and 0.841 (95% CI 0.776-0.906) in the validation cohort. Low cut-off -1.68 (Sensitivity 80.0%, negative predictive value 95.5%) and high cut-off +0.953 values (Specificity 97.7%, positive predictive value 88.9%) excluded and diagnosed advanced fibrosis, respectively. In the validation cohort, FAP Index then FIB-4 reduced indeterminate results by one-third compared to FIB-4 alone. Whereas FAP-Index followed by NFS (NAFLD Fibrosis Score) resulted in a reduction of indeterminate results by 70% compared to NFS alone. Conclusion: FAP Index is a novel, rapid, robust, inexpensive diagnostic tool for advanced fibrosis in metabolic fatty liver disease. Applying FAP Index followed by FIB-4 or NFS facilitates accurate risk-stratification of patients by greatly reducing the frequency of indeterminate results compared to FIB-4 or NFS alone, without compromising negative predictive value.
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