AUTHOR=Liu Hanying , Li Xiao , Han Xiaodong , Zhang Yan , Gu Yanting , Sun Lianjie , Han Junfeng , Tu Yinfang , Bao Yuqian , Bai Wenkun , Yu Haoyong 

TITLE=Simple surrogate equations to predict controlled attenuation parameter values for screening non-alcoholic fatty liver disease in a Chinese population

JOURNAL=Frontiers in Medicine

VOLUME=Volume 9 - 2022

YEAR=2022

URL=https://www.frontiersin.org/journals/medicine/articles/10.3389/fmed.2022.894895

DOI=10.3389/fmed.2022.894895

ISSN=2296-858X

ABSTRACT=Objective: Non-alcoholic fatty liver disease (NAFLD) is one of the most common causes of chronic liver disease. The controlled attenuation parameter (CAP) obtained by FibroScan reflects the level of liver steatosis in patients with obesity. Our study aimed to develop a simple model to predict the CAP, to facilitate the screening, diagnosis and monitoring of patients at high risk for NAFLD.
Methods: 272 subjects were randomly divided into derivation and validation cohorts at a ratio of 1:2. The derivation set was used for constructing a multiple linear regression model; the validation set was used to verify the effectiveness of the model.
Results: Several variables strongly correlated with the CAP were used to construct the following equation for predicting CAP values: CAP1 = 2.4×BMI + 10.5×TG+ 3.6×NC + 10.2×CP +31.0, where BMI is body mass index, TG is triglyceride, NC is neck circumference and CP is C-peptide. The CAP1 model had an R2 of 0.764 and adjusted R2 of 0.753. It was then simplified to derive CAP2 included only simple anthropometric parameters: CAP2 = 3.5 × BMI + 4.2 × NC + 20.3 (R2=0.696, adjusted R2=0.689). The data were well fitted by both models. In the verification group, we compared the actual CAP values to the predicted (CAP1 and CAP2) values. For the CAP1 equation, R2 =0.653, adjusted R2=0.651. For the CAP2 equation, R2=0.625, adjusted R2=0.623. Both of the equations showed a significant correlation with the actual CAP value.
Conclusions: The equations for predicting the CAP value comprise easily accessible variables, and showed good stability and predictive power. Thus, they can be used as simple surrogate tools for early screening, diagnosis, and follow-up of NAFLD.