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Simple surrogate equations to predict controlled attenuation parameter values for screening non-alcoholic fatty liver disease in a Chinese population
OBJECTIVE: Non-alcoholic fatty liver disease (NAFLD) is one of the leading 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 construct a simple equation to predict the C...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9355088/ https://www.ncbi.nlm.nih.gov/pubmed/35935792 http://dx.doi.org/10.3389/fmed.2022.894895 |
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author | Liu, Hanying Li, Xiao Han, Xiaodong Zhang, Yan Gu, Yanting Sun, Lianjie Han, Junfeng Tu, Yinfang Bao, Yuqian Bai, Wenkun Yu, Haoyong |
author_facet | Liu, Hanying Li, Xiao Han, Xiaodong Zhang, Yan Gu, Yanting Sun, Lianjie Han, Junfeng Tu, Yinfang Bao, Yuqian Bai, Wenkun Yu, Haoyong |
author_sort | Liu, Hanying |
collection | PubMed |
description | OBJECTIVE: Non-alcoholic fatty liver disease (NAFLD) is one of the leading 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 construct a simple equation to predict the CAP, to facilitate the screening and monitoring of patients at high risk for NAFLD. METHODS: A total of 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 validity 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 + 10.3 × 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 R(2) of 0.764 and adjusted R(2) of 0.753. It was then simplified to derive CAP2 included only simple anthropometric parameters: CAP2 = 3.5 × BMI + 4.2 × NC + 20.3 (R(2) = 0.696, adjusted R(2) = 0.689). The data were well fitted by both models. In the verification group, the predicted (CAP1 and CAP2) values were compared to the actual CAP values. For the CAP1 equation, R(2) = 0.653, adjusted R(2) = 0.651. For the CAP2 equation, R(2) = 0.625, adjusted R(2) = 0.623. The intra-class correlation coefficient (ICC) values were 0.781 for CAP1 and 0.716 for CAP2 (p < 0.001). The actual CAP and the predicted CAP also showed good agreement in Bland-Altman plot. CONCLUSION: 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 and follow-up of NAFLD in the Chinese population. |
format | Online Article Text |
id | pubmed-9355088 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-93550882022-08-06 Simple surrogate equations to predict controlled attenuation parameter values for screening non-alcoholic fatty liver disease in a Chinese population Liu, Hanying Li, Xiao Han, Xiaodong Zhang, Yan Gu, Yanting Sun, Lianjie Han, Junfeng Tu, Yinfang Bao, Yuqian Bai, Wenkun Yu, Haoyong Front Med (Lausanne) Medicine OBJECTIVE: Non-alcoholic fatty liver disease (NAFLD) is one of the leading 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 construct a simple equation to predict the CAP, to facilitate the screening and monitoring of patients at high risk for NAFLD. METHODS: A total of 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 validity 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 + 10.3 × 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 R(2) of 0.764 and adjusted R(2) of 0.753. It was then simplified to derive CAP2 included only simple anthropometric parameters: CAP2 = 3.5 × BMI + 4.2 × NC + 20.3 (R(2) = 0.696, adjusted R(2) = 0.689). The data were well fitted by both models. In the verification group, the predicted (CAP1 and CAP2) values were compared to the actual CAP values. For the CAP1 equation, R(2) = 0.653, adjusted R(2) = 0.651. For the CAP2 equation, R(2) = 0.625, adjusted R(2) = 0.623. The intra-class correlation coefficient (ICC) values were 0.781 for CAP1 and 0.716 for CAP2 (p < 0.001). The actual CAP and the predicted CAP also showed good agreement in Bland-Altman plot. CONCLUSION: 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 and follow-up of NAFLD in the Chinese population. Frontiers Media S.A. 2022-07-22 /pmc/articles/PMC9355088/ /pubmed/35935792 http://dx.doi.org/10.3389/fmed.2022.894895 Text en Copyright © 2022 Liu, Li, Han, Zhang, Gu, Sun, Han, Tu, Bao, Bai and Yu. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Medicine Liu, Hanying Li, Xiao Han, Xiaodong Zhang, Yan Gu, Yanting Sun, Lianjie Han, Junfeng Tu, Yinfang Bao, Yuqian Bai, Wenkun Yu, Haoyong Simple surrogate equations to predict controlled attenuation parameter values for screening non-alcoholic fatty liver disease in a Chinese population |
title | Simple surrogate equations to predict controlled attenuation parameter values for screening non-alcoholic fatty liver disease in a Chinese population |
title_full | Simple surrogate equations to predict controlled attenuation parameter values for screening non-alcoholic fatty liver disease in a Chinese population |
title_fullStr | Simple surrogate equations to predict controlled attenuation parameter values for screening non-alcoholic fatty liver disease in a Chinese population |
title_full_unstemmed | Simple surrogate equations to predict controlled attenuation parameter values for screening non-alcoholic fatty liver disease in a Chinese population |
title_short | Simple surrogate equations to predict controlled attenuation parameter values for screening non-alcoholic fatty liver disease in a Chinese population |
title_sort | simple surrogate equations to predict controlled attenuation parameter values for screening non-alcoholic fatty liver disease in a chinese population |
topic | Medicine |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9355088/ https://www.ncbi.nlm.nih.gov/pubmed/35935792 http://dx.doi.org/10.3389/fmed.2022.894895 |
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