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Role of clinical biomarkers in predicting the effectiveness of omalizumab

OBJECTIVE: To explore whether baseline clinical biomarkers and characteristics can be used to predict the responsiveness of omalizumab. METHODS: We retrospectively analyzed a cohort of patients with severe asthma who received omalizumab treatment and collected their baseline data and relevant labora...

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Autores principales: Zhang, Qing, Li, Chunxiao, Wan, Jingxuan, Zhang, Mengyuan, Nong, Ying, Lin, Jiangtao
Formato: Online Artículo Texto
Lenguaje:English
Publicado: SAGE Publications 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10164849/
https://www.ncbi.nlm.nih.gov/pubmed/37148201
http://dx.doi.org/10.1177/17534666231170821
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author Zhang, Qing
Li, Chunxiao
Wan, Jingxuan
Zhang, Mengyuan
Nong, Ying
Lin, Jiangtao
author_facet Zhang, Qing
Li, Chunxiao
Wan, Jingxuan
Zhang, Mengyuan
Nong, Ying
Lin, Jiangtao
author_sort Zhang, Qing
collection PubMed
description OBJECTIVE: To explore whether baseline clinical biomarkers and characteristics can be used to predict the responsiveness of omalizumab. METHODS: We retrospectively analyzed a cohort of patients with severe asthma who received omalizumab treatment and collected their baseline data and relevant laboratory examination results along with case records of omalizumab treatment responsiveness after 16 weeks. We compared the differences in variables between the group of patients that responded to omalizumab therapy and the non-responder group, and then performed univariate and multivariate logistic regression. Finally, we analyzed the difference in response rate for subgroups by selecting cut-off values for the variables using Fisher’s exact probability method. RESULTS: This retrospective, single-center observational study enrolled 32 patients with severe asthma who were prescribed daily high-dose inhaled corticosteroids and long-acting β2 receptor agonists on long-acting muscarinic receptor antagonists with or without OCS. Data on age, sex, BMI, bronchial thermoplasty, FeNO, serum total IgE, FEV1, blood eosinophils, induced sputum eosinophils, blood basophils, and complications were not significantly different between the responder and non-responder groups. In the univariate and multivariate logistic regression, all the variants were not significant, and we were unable to build a regression model. We used normal high values and the mean or median of variables as cut-off values to create patient subgroups for the variables and found no significant difference in the omalizumab response rate between the subgroups. CONCLUSION: The responsiveness of omalizumab is not associated with pretreatment clinical biomarkers, and these biomarkers should not be used to predict the responsiveness of omalizumab.
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spelling pubmed-101648492023-05-09 Role of clinical biomarkers in predicting the effectiveness of omalizumab Zhang, Qing Li, Chunxiao Wan, Jingxuan Zhang, Mengyuan Nong, Ying Lin, Jiangtao Ther Adv Respir Dis Original Research OBJECTIVE: To explore whether baseline clinical biomarkers and characteristics can be used to predict the responsiveness of omalizumab. METHODS: We retrospectively analyzed a cohort of patients with severe asthma who received omalizumab treatment and collected their baseline data and relevant laboratory examination results along with case records of omalizumab treatment responsiveness after 16 weeks. We compared the differences in variables between the group of patients that responded to omalizumab therapy and the non-responder group, and then performed univariate and multivariate logistic regression. Finally, we analyzed the difference in response rate for subgroups by selecting cut-off values for the variables using Fisher’s exact probability method. RESULTS: This retrospective, single-center observational study enrolled 32 patients with severe asthma who were prescribed daily high-dose inhaled corticosteroids and long-acting β2 receptor agonists on long-acting muscarinic receptor antagonists with or without OCS. Data on age, sex, BMI, bronchial thermoplasty, FeNO, serum total IgE, FEV1, blood eosinophils, induced sputum eosinophils, blood basophils, and complications were not significantly different between the responder and non-responder groups. In the univariate and multivariate logistic regression, all the variants were not significant, and we were unable to build a regression model. We used normal high values and the mean or median of variables as cut-off values to create patient subgroups for the variables and found no significant difference in the omalizumab response rate between the subgroups. CONCLUSION: The responsiveness of omalizumab is not associated with pretreatment clinical biomarkers, and these biomarkers should not be used to predict the responsiveness of omalizumab. SAGE Publications 2023-05-06 /pmc/articles/PMC10164849/ /pubmed/37148201 http://dx.doi.org/10.1177/17534666231170821 Text en © The Author(s), 2023 https://creativecommons.org/licenses/by-nc/4.0/This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (https://creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access page (https://us.sagepub.com/en-us/nam/open-access-at-sage).
spellingShingle Original Research
Zhang, Qing
Li, Chunxiao
Wan, Jingxuan
Zhang, Mengyuan
Nong, Ying
Lin, Jiangtao
Role of clinical biomarkers in predicting the effectiveness of omalizumab
title Role of clinical biomarkers in predicting the effectiveness of omalizumab
title_full Role of clinical biomarkers in predicting the effectiveness of omalizumab
title_fullStr Role of clinical biomarkers in predicting the effectiveness of omalizumab
title_full_unstemmed Role of clinical biomarkers in predicting the effectiveness of omalizumab
title_short Role of clinical biomarkers in predicting the effectiveness of omalizumab
title_sort role of clinical biomarkers in predicting the effectiveness of omalizumab
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10164849/
https://www.ncbi.nlm.nih.gov/pubmed/37148201
http://dx.doi.org/10.1177/17534666231170821
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