Division of Gastroenterology, Hepatology and Nutrition, Cincinnati Children's Hospital Medical Center, Cincinnati, OH.
Department of Clinical Research and Quality Management, University of the Ryukyus Graduate School of Medicine.
J Pediatr Gastroenterol Nutr. 2022 Apr 1;74(4):495-502. doi: 10.1097/MPG.0000000000003371. Epub 2021 Dec 14.
To develop pediatric-specific models that predict liver stiffness and hepatic steatosis in non-alcoholic fatty liver disease (NAFLD), based on clinical and laboratory data.
Children with NAFLD, who had undergone magnetic resonance imaging with proton density fat fraction (MRI-PDFF) for steatosis quantification and/or magnetic resonance elastography (MRE) for liver stiffness assessment were included. We used data from patients imaged between April 2009 to July 2018 to develop a predictive model for fat fraction and stiffness. We validated the performance of the models using data from a second cohort, imaged between 2018 and 2019.
The first cohort (n = 344) consisted of predominantly non-Hispanic (80%), male (67%) adolescents. MRE data were available for 343 children, while PDFF data were available for 130. In multivariable regression, ethnicity, insulin levels, platelet count, and aspartate aminotransferase independently predicted liver stiffness and these variables were used to develop the predictive model. Similarly, sex, ethnicity, alanine aminotransferase, and triglycerides levels independently predicted liver PDFF and were used in the PDFF model. The AUC of the optimal cutoff for the model that predicted a stiffness of >2.71 kPa was 0.70 and for the model that predicted PDFF >5% was 0.78. The validation group (n = 110) had similar characteristics. The correlation coefficient of the model with the measured liver stiffness was 0.30 and with the measured liver PDFF was 0.26.
Pediatric-specific models perform poorly at predicting exact liver stiffness and steatosis; however, in the absence of magnetic resonance imaging can be used to predict the presence of significant steatosis (>5%) and/or significant stiffness (>2.71). Thus, imaging remains an invaluable adjunct to laboratory investigations in determining disease severity.
基于临床和实验室数据，开发专门用于预测非酒精性脂肪性肝病（NAFLD）患者肝硬度和肝脂肪变性的儿科专用模型。
纳入接受磁共振成像质子密度脂肪分数（MRI-PDFF）定量评估脂肪变性和/或磁共振弹性成像（MRE）评估肝硬度的 NAFLD 患儿。我们使用 2009 年 4 月至 2018 年 7 月间成像患者的数据来开发脂肪分数和硬度的预测模型。我们使用 2018 年至 2019 年间成像的第二队列的数据来验证模型的性能。
第一队列（n = 344）主要由非西班牙裔（80%）、男性（67%）青少年组成。343 名儿童有 MRE 数据，130 名儿童有 PDFF 数据。多元回归分析显示，种族、胰岛素水平、血小板计数和天冬氨酸转氨酶独立预测肝硬度，这些变量用于开发预测模型。同样，性别、种族、丙氨酸转氨酶和甘油三酯水平独立预测肝 PDFF，并用于 PDFF 模型。预测肝硬度>2.71 kPa 的最佳截断值模型的 AUC 为 0.70，预测 PDFF >5%的模型的 AUC 为 0.78。验证组（n = 110）具有相似的特征。模型与测量肝硬度的相关系数为 0.30，与测量肝 PDFF 的相关系数为 0.26。
专门针对儿科患者的模型在预测肝硬度和脂肪变性的具体数值时表现不佳；然而，在没有磁共振成像的情况下，模型可以用于预测存在明显的脂肪变性（>5%）和/或明显的肝硬度（>2.71）。因此，成像仍然是确定疾病严重程度的实验室检查的宝贵辅助手段。
