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A diagnostic model for predicting type 2 nasal polyps using biomarkers in nasal secretion
BACKGROUND: Predicting type 2 chronic rhinosinusitis with nasal polyps (CRSwNP) may help for selection of appropriate surgical procedures or pharmacotherapies in advance. However, an accurate non-invasive method for diagnosis of type 2 CRSwNP is presently unavailable. METHODS: To optimize the techni...
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/PMC9811186/ https://www.ncbi.nlm.nih.gov/pubmed/36618395 http://dx.doi.org/10.3389/fimmu.2022.1054201 |
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author | Wang, Zaichuan Wang, Qiqi Duan, Su Zhang, Yuling Zhao, Limin Zhang, Shujian Hao, Liusiqi Li, Yan Wang, Xiangdong Wang, Chenshuo Zhang, Nan Bachert, Claus Zhang, Luo Lan, Feng |
author_facet | Wang, Zaichuan Wang, Qiqi Duan, Su Zhang, Yuling Zhao, Limin Zhang, Shujian Hao, Liusiqi Li, Yan Wang, Xiangdong Wang, Chenshuo Zhang, Nan Bachert, Claus Zhang, Luo Lan, Feng |
author_sort | Wang, Zaichuan |
collection | PubMed |
description | BACKGROUND: Predicting type 2 chronic rhinosinusitis with nasal polyps (CRSwNP) may help for selection of appropriate surgical procedures or pharmacotherapies in advance. However, an accurate non-invasive method for diagnosis of type 2 CRSwNP is presently unavailable. METHODS: To optimize the technique for collecting nasal secretion (NasSec), 89 CRSwNP patients were tested using nasal packs made with four types of materials. Further, Th2(low) and Th2(high)CRSwNP defined by clustering analysis in another 142 CRSwNP patients using tissue biomarkers, in the meanwhile, inflammatory biomarkers were detected in NasSec of the same patients collected by the selected nasal pack. A diagnostic model was established by machine learning algorithms to predict Th2(high)CRSwNP using NasSecs biomarkers. RESULTS: Considering the area under receiver operating characteristic curve (AUC) for IL-5 in NasSec, nasal pack in polyvinyl alcohol (PVA) was superior to other materials for NasSec collection. When Th2(low) and Th2(high)CRSwNP clusters were defined, logistic regression and decision tree model for prediction of Th2(high)CRSwNP demonstrated high AUCs values of 0.92 and 0.90 respectively using biomarkers of NasSecs. Consequently, the pre-pruned decision tree model; based on the levels of IL-5 in NasSec (≤ 15.04 pg/mL), blood eosinophil count (≤ 0.475*10(9)/L) and absence of comorbid asthma; was chosen to define Th2(low)CRSwNP from Th2(high)CRSwNP for routine clinical use. CONCLUSIONS: Taken together, a decision tree model based on a combination of NasSec biomarkers and clinical features can accurately define type 2 CRSwNP patients and therefore may be of benefit to patients in receiving appropriate therapies in daily clinical practice. |
format | Online Article Text |
id | pubmed-9811186 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-98111862023-01-05 A diagnostic model for predicting type 2 nasal polyps using biomarkers in nasal secretion Wang, Zaichuan Wang, Qiqi Duan, Su Zhang, Yuling Zhao, Limin Zhang, Shujian Hao, Liusiqi Li, Yan Wang, Xiangdong Wang, Chenshuo Zhang, Nan Bachert, Claus Zhang, Luo Lan, Feng Front Immunol Immunology BACKGROUND: Predicting type 2 chronic rhinosinusitis with nasal polyps (CRSwNP) may help for selection of appropriate surgical procedures or pharmacotherapies in advance. However, an accurate non-invasive method for diagnosis of type 2 CRSwNP is presently unavailable. METHODS: To optimize the technique for collecting nasal secretion (NasSec), 89 CRSwNP patients were tested using nasal packs made with four types of materials. Further, Th2(low) and Th2(high)CRSwNP defined by clustering analysis in another 142 CRSwNP patients using tissue biomarkers, in the meanwhile, inflammatory biomarkers were detected in NasSec of the same patients collected by the selected nasal pack. A diagnostic model was established by machine learning algorithms to predict Th2(high)CRSwNP using NasSecs biomarkers. RESULTS: Considering the area under receiver operating characteristic curve (AUC) for IL-5 in NasSec, nasal pack in polyvinyl alcohol (PVA) was superior to other materials for NasSec collection. When Th2(low) and Th2(high)CRSwNP clusters were defined, logistic regression and decision tree model for prediction of Th2(high)CRSwNP demonstrated high AUCs values of 0.92 and 0.90 respectively using biomarkers of NasSecs. Consequently, the pre-pruned decision tree model; based on the levels of IL-5 in NasSec (≤ 15.04 pg/mL), blood eosinophil count (≤ 0.475*10(9)/L) and absence of comorbid asthma; was chosen to define Th2(low)CRSwNP from Th2(high)CRSwNP for routine clinical use. CONCLUSIONS: Taken together, a decision tree model based on a combination of NasSec biomarkers and clinical features can accurately define type 2 CRSwNP patients and therefore may be of benefit to patients in receiving appropriate therapies in daily clinical practice. Frontiers Media S.A. 2022-12-21 /pmc/articles/PMC9811186/ /pubmed/36618395 http://dx.doi.org/10.3389/fimmu.2022.1054201 Text en Copyright © 2022 Wang, Wang, Duan, Zhang, Zhao, Zhang, Hao, Li, Wang, Wang, Zhang, Bachert, Zhang and Lan 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 | Immunology Wang, Zaichuan Wang, Qiqi Duan, Su Zhang, Yuling Zhao, Limin Zhang, Shujian Hao, Liusiqi Li, Yan Wang, Xiangdong Wang, Chenshuo Zhang, Nan Bachert, Claus Zhang, Luo Lan, Feng A diagnostic model for predicting type 2 nasal polyps using biomarkers in nasal secretion |
title | A diagnostic model for predicting type 2 nasal polyps using biomarkers in nasal secretion |
title_full | A diagnostic model for predicting type 2 nasal polyps using biomarkers in nasal secretion |
title_fullStr | A diagnostic model for predicting type 2 nasal polyps using biomarkers in nasal secretion |
title_full_unstemmed | A diagnostic model for predicting type 2 nasal polyps using biomarkers in nasal secretion |
title_short | A diagnostic model for predicting type 2 nasal polyps using biomarkers in nasal secretion |
title_sort | diagnostic model for predicting type 2 nasal polyps using biomarkers in nasal secretion |
topic | Immunology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9811186/ https://www.ncbi.nlm.nih.gov/pubmed/36618395 http://dx.doi.org/10.3389/fimmu.2022.1054201 |
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