基于Nomogram的NAFLD进展性纤维化预测模型研究

肝脏 ›› 2022, Vol. 27 ›› Issue (2): 160-163.

基于Nomogram的NAFLD进展性纤维化预测模型研究

杨永勤, 王晓君, 冯巩, 李嵘, 刘小瑜, 孙雪梅, 贺娜

710077 西安医学院第一附属医院(杨永勤,贺娜);陆军军医大学第一附属医院(王晓君);西安医学院(冯巩,刘小瑜,孙雪梅);西安医学院全科医学院(李嵘)

收稿日期:2021-06-06 出版日期:2022-02-28 发布日期:2022-04-19
通讯作者: 贺娜,Email:ylhena@163.com
基金资助:
佑安肝病感染病专科医疗联盟专项基金(LM202003);陕西省教育科学“十三五”规划课题(SGH20Y1330)

Research on the prediction model for progressive fibrosis in patients with NAFLD based on Nomogram

YANG Yong-qin¹, WANG Xiao-jun², FENG Gong³, LI Rong⁴, LIU Xiao-yu³, SUN Xue-mei³, HE Na¹

1. The First Affiliated Hospital of Xi'an Medical University, Shanxi 710077, China;
2. The First Affiliated Hospital of Army Military Medical University, Chongqing 400038;
3. Xi'an Medical University, Shanxi 710021, China;
4. Xi'an Medical University of General Medicine, Shanxi 710077, China

Received:2021-06-06 Online:2022-02-28 Published:2022-04-19
Contact: HE Na, Email: ylhena@163.com

摘要/Abstract

摘要： 目的开发一种新型的基于Nomogram的非侵入性模型,以准确预测非酒精性脂肪性肝病(nonalcoholic fatty liver disease, NAFLD)患者的进展性纤维化。方法共纳入380例经Fibroscan诊断的NAFLD患者,收集了人体学和纤维化相关等实验室参数。将与进展性纤维化独立相关的变量用于构建Nomogram预测模型。根据受试者工作特征曲线下面积评估预测模型的诊断效能。结果纳入Nomogram预测模型的变量包括:2型糖尿病(OR=1.135, 95%CI:1.019~1.265)、AST(OR=1.005, 95%CI:1.002~1.018)、Ⅲ型前胶原肽(OR=1.116, 95%CI:1.028~1.212)和Ⅳ型胶原(OR=1.097, 95%CI:1.032~1.166)。Nomogram预测模型ROC曲线下面积为0.851, 95％CI为0.778~0.925,灵敏度为0.900,特异度为0.826。结论 Nomogram模型对于进展性纤维化的诊断更加准确,优于APRI、NFS、FIB-4和BRAD评分,可作为NAFLD患者进展性纤维化的非侵入性筛查工具。

关键词: 纤维化, 非酒精性脂肪性肝病, Nomogram

Abstract: Objective The degree of fibrosis is considered as a determining factor of long-term prognosis for nonalcoholic fatty liver disease (NAFLD). We aimed to develop a novel non-invasive model based on Nomogram to accurately predict progressive fibrosis in patients with NAFLD. Methods A total of 380 NAFLD patients diagnosed by FibroScan were enrolled. Detailed anthropological data and fibrosis related laboratory parameters were collected. Variables independently associated with advanced fibrosis would be used to construct Nomogram prediction models. Ultimately, the diagnostic efficacy of the prediction model were evaluated by receiver operating characteristic (ROC) curve. Results Variables included in the prediction model were as followed: type 2 diabetes mellitus (OR=1.135, 95%CI 1.019-1.265), aspartate aminotransferase (OR=1.005, 95%CI 1.002-1.018), type III procollagen peptide (OR=1.116, 95%CI 1.028-1.212), and type IV collagen (OR=1.097, 95%CI 1.032-1.166). The area under the ROC curve of the Nomogram prediction model was 0.851, with the 95% CI as 0.778-0.925, the sensitivity as 0.900, and the specificity as 0.826, respectively. Conclusion The novel Nomogram model is more accurate in predicting advanced fibrosis and performs significantly better than the APRI, NFS, FIB-4 and BRAD scores reported in the literature. It might be a noninvasive screening tool for advanced fibrosis in overall NAFLD population.

Key words: Fibrosis, Nonalcoholic fatty liver disease, Nomogram

杨永勤, 王晓君, 冯巩, 李嵘, 刘小瑜, 孙雪梅, 贺娜. 基于Nomogram的NAFLD进展性纤维化预测模型研究[J]. 肝脏, 2022, 27(2): 160-163.

YANG Yong-qin, WANG Xiao-jun, FENG Gong, LI Rong, LIU Xiao-yu, SUN Xue-mei, HE Na. Research on the prediction model for progressive fibrosis in patients with NAFLD based on Nomogram[J]. Chinese Hepatolgy, 2022, 27(2): 160-163.

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