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Nomogram for evaluating obvious liver inflammation in treatment-naïve HBeAg positive chronic hepatitis B virus infection patients with normal ALT
The purpose of this study was to develop an effective and non-invasive nomogram for evaluating liver obvious inflammation in untreated HBeAg positive patients with chronic hepatitis B virus (HBV) infection. A nomogram was established on a model cohort of 292 treatment-naïve HBeAg positive patients w...
Autores principales: | , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Taylor & Francis
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9828634/ https://www.ncbi.nlm.nih.gov/pubmed/36600180 http://dx.doi.org/10.1080/21505594.2022.2158710 |
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author | Zhang, Lu Yang, Liu Gao, Yuanjiao Bi, Xiaoyue Lin, Yanjie Deng, Wen Jiang, Tingting Lu, Yao Hao, Hongxiao Wan, Gang Yi, Wei Xie, Yao Li, Minghui |
author_facet | Zhang, Lu Yang, Liu Gao, Yuanjiao Bi, Xiaoyue Lin, Yanjie Deng, Wen Jiang, Tingting Lu, Yao Hao, Hongxiao Wan, Gang Yi, Wei Xie, Yao Li, Minghui |
author_sort | Zhang, Lu |
collection | PubMed |
description | The purpose of this study was to develop an effective and non-invasive nomogram for evaluating liver obvious inflammation in untreated HBeAg positive patients with chronic hepatitis B virus (HBV) infection. A nomogram was established on a model cohort of 292 treatment-naïve HBeAg positive patients with normal alanine aminotransferase (ALT ≤40 U/L) at Beijing Ditan Hospital from January 2008 to March 2018. Then the nomogram was prospectively validated in a cohort of 88 patients from July 2019 to May 2021. Calibration curves and Concordance index were used to evaluate the accuracy of prediction and identification performance of the model. In untreated HBeAg positive chronic hepatitis B virus infection patients with normal ALT, the formula for predicting liver inflammation was Logit (P) =-0.91-0.41×log(10) (qHBeAg)+0.11×AST-0.01×PLT. The nomogram had C-index of 0.751 (95% CI, 0.688–0.815), indicating a good consistency between prediction and real observation on the model cohort. The validation cohort confirmed its good performance. In this study, liver inflammation nomograms based on HBeAg, AST, and PLT were established and verified in treatment-naïve HBeAg positive chronic HBV patients with normal ALT. |
format | Online Article Text |
id | pubmed-9828634 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Taylor & Francis |
record_format | MEDLINE/PubMed |
spelling | pubmed-98286342023-01-10 Nomogram for evaluating obvious liver inflammation in treatment-naïve HBeAg positive chronic hepatitis B virus infection patients with normal ALT Zhang, Lu Yang, Liu Gao, Yuanjiao Bi, Xiaoyue Lin, Yanjie Deng, Wen Jiang, Tingting Lu, Yao Hao, Hongxiao Wan, Gang Yi, Wei Xie, Yao Li, Minghui Virulence Research Article The purpose of this study was to develop an effective and non-invasive nomogram for evaluating liver obvious inflammation in untreated HBeAg positive patients with chronic hepatitis B virus (HBV) infection. A nomogram was established on a model cohort of 292 treatment-naïve HBeAg positive patients with normal alanine aminotransferase (ALT ≤40 U/L) at Beijing Ditan Hospital from January 2008 to March 2018. Then the nomogram was prospectively validated in a cohort of 88 patients from July 2019 to May 2021. Calibration curves and Concordance index were used to evaluate the accuracy of prediction and identification performance of the model. In untreated HBeAg positive chronic hepatitis B virus infection patients with normal ALT, the formula for predicting liver inflammation was Logit (P) =-0.91-0.41×log(10) (qHBeAg)+0.11×AST-0.01×PLT. The nomogram had C-index of 0.751 (95% CI, 0.688–0.815), indicating a good consistency between prediction and real observation on the model cohort. The validation cohort confirmed its good performance. In this study, liver inflammation nomograms based on HBeAg, AST, and PLT were established and verified in treatment-naïve HBeAg positive chronic HBV patients with normal ALT. Taylor & Francis 2023-01-04 /pmc/articles/PMC9828634/ /pubmed/36600180 http://dx.doi.org/10.1080/21505594.2022.2158710 Text en © 2022 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Zhang, Lu Yang, Liu Gao, Yuanjiao Bi, Xiaoyue Lin, Yanjie Deng, Wen Jiang, Tingting Lu, Yao Hao, Hongxiao Wan, Gang Yi, Wei Xie, Yao Li, Minghui Nomogram for evaluating obvious liver inflammation in treatment-naïve HBeAg positive chronic hepatitis B virus infection patients with normal ALT |
title | Nomogram for evaluating obvious liver inflammation in treatment-naïve HBeAg positive chronic hepatitis B virus infection patients with normal ALT |
title_full | Nomogram for evaluating obvious liver inflammation in treatment-naïve HBeAg positive chronic hepatitis B virus infection patients with normal ALT |
title_fullStr | Nomogram for evaluating obvious liver inflammation in treatment-naïve HBeAg positive chronic hepatitis B virus infection patients with normal ALT |
title_full_unstemmed | Nomogram for evaluating obvious liver inflammation in treatment-naïve HBeAg positive chronic hepatitis B virus infection patients with normal ALT |
title_short | Nomogram for evaluating obvious liver inflammation in treatment-naïve HBeAg positive chronic hepatitis B virus infection patients with normal ALT |
title_sort | nomogram for evaluating obvious liver inflammation in treatment-naïve hbeag positive chronic hepatitis b virus infection patients with normal alt |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9828634/ https://www.ncbi.nlm.nih.gov/pubmed/36600180 http://dx.doi.org/10.1080/21505594.2022.2158710 |
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