TY - JOUR
T1 - Diagnosis of Fibrosis Using Blood Markers and Logistic Regression in Southeast Asian Patients With Non-alcoholic Fatty Liver Disease
AU - Sang, Chao
AU - Yan, Hongmei
AU - Chan, Wah Kheong
AU - Zhu, Xiaopeng
AU - Sun, Tao
AU - Chang, Xinxia
AU - Xia, Mingfeng
AU - Sun, Xiaoyang
AU - Hu, Xiqi
AU - Gao, Xin
AU - Jia, Wei
AU - Bian, Hua
AU - Chen, Tianlu
AU - Xie, Guoxiang
N1 - Funding Information:
This study was funded by the National Key Research and Development Program of China (2019YFA0802300 and 2017YFC0906800), the National Natural Science Foundation of China (31972935), the Shenzhen Science, Technology and Innovation Commission [2020(82)], and the Shanghai Municipal Science and Technology Major Project (2017SHZDZX01).
Publisher Copyright:
© 2021 Sang, Yan, Chan, Zhu, Sun, Chang, Xia, Sun, Hu, Gao, Jia, Bian, Chen and Xie.
PY - 2021/2/23
Y1 - 2021/2/23
N2 - Non-alcoholic fatty liver disease (NAFLD) is one of the main causes of fibrosis. Liver biopsy remains the gold standard for the confirmation of fibrosis in NAFLD patients. Effective and non-invasive diagnosis of advanced fibrosis is essential to disease surveillance and treatment decisions. Herein we used routine medical test markers and logistic regression to differentiate early and advanced fibrosis in NAFLD patients from China, Malaysia, and India (n1 = 540, n2 = 147, and n3 = 97) who were confirmed by liver biopsy. Nine parameters, including age, body mass index, fasting blood glucose, presence of diabetes or impaired fasting glycemia, alanine aminotransferase, γ-glutamyl transferase, triglyceride, and aspartate transaminase/platelet count ratio, were selected by stepwise logistic regression, receiver operating characteristic curve (ROC), and hypothesis testing and were used for model construction. The area under the ROC curve (auROC) of the model was 0.82 for differentiating early and advanced fibrosis (sensitivity = 0.69, when specificity = 0.80) in the discovery set. Its diagnostic ability remained good in the two independent validation sets (auROC = 0.89 and 0.71) and was consistently superior to existing panels such as the FIB-4 and NAFLD fibrosis score. A web-based tool, LiveFbr, was developed for fast access to our model. The new model may serve as an attractive tool for fibrosis classification in NAFLD patients.
AB - Non-alcoholic fatty liver disease (NAFLD) is one of the main causes of fibrosis. Liver biopsy remains the gold standard for the confirmation of fibrosis in NAFLD patients. Effective and non-invasive diagnosis of advanced fibrosis is essential to disease surveillance and treatment decisions. Herein we used routine medical test markers and logistic regression to differentiate early and advanced fibrosis in NAFLD patients from China, Malaysia, and India (n1 = 540, n2 = 147, and n3 = 97) who were confirmed by liver biopsy. Nine parameters, including age, body mass index, fasting blood glucose, presence of diabetes or impaired fasting glycemia, alanine aminotransferase, γ-glutamyl transferase, triglyceride, and aspartate transaminase/platelet count ratio, were selected by stepwise logistic regression, receiver operating characteristic curve (ROC), and hypothesis testing and were used for model construction. The area under the ROC curve (auROC) of the model was 0.82 for differentiating early and advanced fibrosis (sensitivity = 0.69, when specificity = 0.80) in the discovery set. Its diagnostic ability remained good in the two independent validation sets (auROC = 0.89 and 0.71) and was consistently superior to existing panels such as the FIB-4 and NAFLD fibrosis score. A web-based tool, LiveFbr, was developed for fast access to our model. The new model may serve as an attractive tool for fibrosis classification in NAFLD patients.
KW - advanced fibrosis
KW - FIB-4
KW - hepatic fibrosis
KW - logistic regression
KW - NAFLD
KW - NFS
UR - http://www.scopus.com/inward/record.url?scp=85102350567&partnerID=8YFLogxK
U2 - 10.3389/fmed.2021.637652
DO - 10.3389/fmed.2021.637652
M3 - Journal article
AN - SCOPUS:85102350567
SN - 2296-858X
VL - 8
JO - Frontiers in Medicine
JF - Frontiers in Medicine
M1 - 637652
ER -