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A proposed predictive model for advanced fibrosis in patients with chronic hepatitis B and its validation
We created a predictive model using serum-based biomarkers for advanced fibrosis (F3 or more) in patients with chronic hepatitis B (CHB) and to confirm the accuracy in an independent cohort. A total of 249 CHB patients were analyzed. To achieve our study aim, a training group (n = 125) and a validat...
Autores principales: | , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Wolters Kluwer Health
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5008579/ https://www.ncbi.nlm.nih.gov/pubmed/27583895 http://dx.doi.org/10.1097/MD.0000000000004679 |
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author | Nishikawa, Hiroki Hasegawa, Kunihiro Ishii, Akio Takata, Ryo Enomoto, Hirayuki Yoh, Kazunori Kishino, Kyohei Shimono, Yoshihiro Iwata, Yoshinori Nakano, Chikage Nishimura, Takashi Aizawa, Nobuhiro Sakai, Yoshiyuki Ikeda, Naoto Takashima, Tomoyuki Iijima, Hiroko Nishiguchi, Shuhei |
author_facet | Nishikawa, Hiroki Hasegawa, Kunihiro Ishii, Akio Takata, Ryo Enomoto, Hirayuki Yoh, Kazunori Kishino, Kyohei Shimono, Yoshihiro Iwata, Yoshinori Nakano, Chikage Nishimura, Takashi Aizawa, Nobuhiro Sakai, Yoshiyuki Ikeda, Naoto Takashima, Tomoyuki Iijima, Hiroko Nishiguchi, Shuhei |
author_sort | Nishikawa, Hiroki |
collection | PubMed |
description | We created a predictive model using serum-based biomarkers for advanced fibrosis (F3 or more) in patients with chronic hepatitis B (CHB) and to confirm the accuracy in an independent cohort. A total of 249 CHB patients were analyzed. To achieve our study aim, a training group (n = 125) and a validation group (n = 124) were formed. In the training group, parameters related to the presence of advanced fibrosis in univariate and multivariate analyses were examined, and a formula for advanced fibrosis was created. Next, we verified the applicability of the predictive model in the validation group. Multivariate analysis identified that gamma-glutamyl transpeptidase (GGT, P = 0.0343) and platelet count (P = 0.0034) were significant predictors of the presence of advanced fibrosis, while Wisteria floribunda agglutinin-positive Mac-2-binding protein (WFA(+)-M2BP, P = 0.0741) and hyaluronic acid (P = 0.0916) tended to be significant factors. Using these 4 parameters, we created the following formula: GMPH score = −0.755 − (0.015 × GGT) − (0.268 × WFA(+)-M2BP) + (0.167 × platelet count) + (0.003 × hyaluronic acid). In 8 analyzed variables (WFA(+)-M2BP, aspartate aminotransferase-to-platelet ratio index, FIB-4 index, prothrombin time, platelet count, hyaluronic acid, Forns index, and GMPH score), GMPH score had the highest area under the receiver operating characteristic (AUROC) curve for advanced fibrosis with a value of 0.8064 in the training group and in the validation group, GMPH score also had the highest AUROC (0.7782). In all subgroup analyses of the hepatitis B virus (HBV) status (HB surface antigen quantification, HBV-DNA quantification, and HBe antigen seropositivity), GMPH score in F3 or F4 was significantly lower than that in F0 to F2. In the above mentioned 8 variables, differences between the liver fibrosis stages (F0 to F1 vs F2, F2 vs F3, F3 vs F4, F0 to F1 vs F3, F0 to F1 vs F4, and F2 vs F4) for the entire cohort (n = 249) were all significant only in GMPH score. In conclusion, the GMPH scoring system may be helpful for detecting advanced liver fibrosis in patients with CHB. |
format | Online Article Text |
id | pubmed-5008579 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Wolters Kluwer Health |
record_format | MEDLINE/PubMed |
spelling | pubmed-50085792016-09-10 A proposed predictive model for advanced fibrosis in patients with chronic hepatitis B and its validation Nishikawa, Hiroki Hasegawa, Kunihiro Ishii, Akio Takata, Ryo Enomoto, Hirayuki Yoh, Kazunori Kishino, Kyohei Shimono, Yoshihiro Iwata, Yoshinori Nakano, Chikage Nishimura, Takashi Aizawa, Nobuhiro Sakai, Yoshiyuki Ikeda, Naoto Takashima, Tomoyuki Iijima, Hiroko Nishiguchi, Shuhei Medicine (Baltimore) 4500 We created a predictive model using serum-based biomarkers for advanced fibrosis (F3 or more) in patients with chronic hepatitis B (CHB) and to confirm the accuracy in an independent cohort. A total of 249 CHB patients were analyzed. To achieve our study aim, a training group (n = 125) and a validation group (n = 124) were formed. In the training group, parameters related to the presence of advanced fibrosis in univariate and multivariate analyses were examined, and a formula for advanced fibrosis was created. Next, we verified the applicability of the predictive model in the validation group. Multivariate analysis identified that gamma-glutamyl transpeptidase (GGT, P = 0.0343) and platelet count (P = 0.0034) were significant predictors of the presence of advanced fibrosis, while Wisteria floribunda agglutinin-positive Mac-2-binding protein (WFA(+)-M2BP, P = 0.0741) and hyaluronic acid (P = 0.0916) tended to be significant factors. Using these 4 parameters, we created the following formula: GMPH score = −0.755 − (0.015 × GGT) − (0.268 × WFA(+)-M2BP) + (0.167 × platelet count) + (0.003 × hyaluronic acid). In 8 analyzed variables (WFA(+)-M2BP, aspartate aminotransferase-to-platelet ratio index, FIB-4 index, prothrombin time, platelet count, hyaluronic acid, Forns index, and GMPH score), GMPH score had the highest area under the receiver operating characteristic (AUROC) curve for advanced fibrosis with a value of 0.8064 in the training group and in the validation group, GMPH score also had the highest AUROC (0.7782). In all subgroup analyses of the hepatitis B virus (HBV) status (HB surface antigen quantification, HBV-DNA quantification, and HBe antigen seropositivity), GMPH score in F3 or F4 was significantly lower than that in F0 to F2. In the above mentioned 8 variables, differences between the liver fibrosis stages (F0 to F1 vs F2, F2 vs F3, F3 vs F4, F0 to F1 vs F3, F0 to F1 vs F4, and F2 vs F4) for the entire cohort (n = 249) were all significant only in GMPH score. In conclusion, the GMPH scoring system may be helpful for detecting advanced liver fibrosis in patients with CHB. Wolters Kluwer Health 2016-09-02 /pmc/articles/PMC5008579/ /pubmed/27583895 http://dx.doi.org/10.1097/MD.0000000000004679 Text en Copyright © 2016 the Author(s). Published by Wolters Kluwer Health, Inc. All rights reserved. http://creativecommons.org/licenses/by-nd/4.0 This is an open access article distributed under the Creative Commons Attribution-NoDerivatives License 4.0, which allows for redistribution, commercial and non-commercial, as long as it is passed along unchanged and in whole, with credit to the author. http://creativecommons.org/licenses/by-nd/4.0 |
spellingShingle | 4500 Nishikawa, Hiroki Hasegawa, Kunihiro Ishii, Akio Takata, Ryo Enomoto, Hirayuki Yoh, Kazunori Kishino, Kyohei Shimono, Yoshihiro Iwata, Yoshinori Nakano, Chikage Nishimura, Takashi Aizawa, Nobuhiro Sakai, Yoshiyuki Ikeda, Naoto Takashima, Tomoyuki Iijima, Hiroko Nishiguchi, Shuhei A proposed predictive model for advanced fibrosis in patients with chronic hepatitis B and its validation |
title | A proposed predictive model for advanced fibrosis in patients with chronic hepatitis B and its validation |
title_full | A proposed predictive model for advanced fibrosis in patients with chronic hepatitis B and its validation |
title_fullStr | A proposed predictive model for advanced fibrosis in patients with chronic hepatitis B and its validation |
title_full_unstemmed | A proposed predictive model for advanced fibrosis in patients with chronic hepatitis B and its validation |
title_short | A proposed predictive model for advanced fibrosis in patients with chronic hepatitis B and its validation |
title_sort | proposed predictive model for advanced fibrosis in patients with chronic hepatitis b and its validation |
topic | 4500 |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5008579/ https://www.ncbi.nlm.nih.gov/pubmed/27583895 http://dx.doi.org/10.1097/MD.0000000000004679 |
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