Development and Validation of a Score for Fibrotic Nonalcoholic Steatohepatitis
Development and Validation of a Score for Fibrotic Nonalcoholic Steatohepatitis
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DOI：
10.1016/j.cgh.2022.03.044
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发表时间：
2023-05-23
影响因子：
12.6
通讯作者：
Mancina, Rosellina Margherita
中科院分区：
文献类型：
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作者：
Tavaglione, Federica;Jamialahmadi, Oveis;Mancina, Rosellina Margherita
背景与目的：非酒精性脂肪性肝病（NAFLD）的组织学特征的非侵入性评估在过去十年中一直是一个深入的研究领域。在此，我们的目的是通过常规的实验室检查开发一种简单的非侵入性评分，以确定在NAFLD高危人群中，患有纤维化非酒精性脂肪性肝炎（NASH）的人群，NASH定义为NASH，NAFLD活动性评分≥4，纤维化分期≥ 2。方法：推导队列包括264名在罗马，意大利接受术中肝活检的病态肥胖患者。开发了最佳预测模型，并使用自举逐步逻辑回归分析（2000个自举样本）进行内部验证。通过受试者工作特征曲线下面积（AUROC）评估性能。在3个独立的欧洲队列（芬兰，n = 370;意大利，n = 947;英格兰，n = 5368）中评估了NAFLD高风险个体的外部验证。研究结果：最终的预测模型，命名为纤维化NASH指数（FNI），结合天冬氨酸转氨酶，高密度脂蛋白胆固醇和血红蛋白A1 c。FNI用于纤维化NASH的性能在推导和外部验证队列中均令人满意（AUROC = 0.78和AUROC = 0.80-0.95）。在推导队列中，排除和纳入截止值分别为0.10，敏感性和GE;0.89（阴性预测值，0.93）和0.33，特异性和GE;0.90（阳性预测值，0.57）。在外部验证队列中，灵敏度范围为0.87至1（阴性预测值，0.99-1），特异性为0.73 - 0.94（阳性预测值，0.12-0.49）。结论：FNI是一种准确、简单且经济实惠的非侵入性评分，可用于在初级卫生保健中筛查代谢异常个体的纤维化NASH。
BACKGROUND & AIMS: Noninvasive assessment of histological features of nonalcoholic fatty liver disease (NAFLD) has been an intensive research area over the last decade. Herein, we aimed to develop a simple noninvasive score using routine laboratory tests to identify, among individuals at high risk for NAFLD, those with fibrotic nonalcoholic steatohepatitis (NASH) defined as NASH, NAFLD activity score & GE;4, and fibrosis stage & GE;2.METHODS: The derivation cohort included 264 morbidly obese individuals undergoing intraoperative liver biopsy in Rome, Italy. The best predictive model was developed and internally validated using a bootstrapping stepwise logistic regression analysis (2000 bootstrap samples). Performance was estimated by the area under the receiver operating characteristic curve (AUROC). External validation was assessed in 3 independent European cohorts (Finland, n = 370; Italy, n = 947; England, n = 5368) of individuals at high risk for NAFLD. RESULTS: The final predictive model, designated as Fibrotic NASH Index (FNI), combined aspartate aminotransferase, high-density lipoprotein cholesterol, and hemoglobin A1c. The performance of FNI for fibrotic NASH was satisfactory in both derivation and external validation cohorts (AUROC = 0.78 and AUROC = 0.80-0.95, respectively). In the derivation cohort, rule-out and rule-in cutoffs were 0.10 for sensitivity & GE;0.89 (negative predictive value, 0.93) and 0.33 for specificity & GE;0.90 (positive predictive value, 0.57), respectively. In the external validation co-horts, sensitivity ranged from 0.87 to 1 (negative predictive value, 0.99-1) and specificity from 0.73 to 0.94 (positive predictive value, 0.12-0.49) for rule-out and rule-in cutoff, respectively.CONCLUSION: FNI is an accurate, simple, and affordable noninvasive score which can be used to screen for fibrotic NASH in individuals with dysmetabolism in primary health care.