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Prediction and associated factors of non-steroidal anti-inflammatory drugs efficacy in migraine treatment

Background: The selection strategy of non-steroidal anti-inflammatory drugs (NSAIDs) for migraine is hard to judge whether it is effective, leading to unnecessary exposure to insufficient or lengthy treatment trials. The goal of the study was to investigate potential predictors of NSAIDs efficacy in...

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Autores principales: Lu, Zhao-Xuan, Dong, Bing-Qing, Wei, Heng-Le, Chen, Liang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9754055/
https://www.ncbi.nlm.nih.gov/pubmed/36532762
http://dx.doi.org/10.3389/fphar.2022.1002080
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author Lu, Zhao-Xuan
Dong, Bing-Qing
Wei, Heng-Le
Chen, Liang
author_facet Lu, Zhao-Xuan
Dong, Bing-Qing
Wei, Heng-Le
Chen, Liang
author_sort Lu, Zhao-Xuan
collection PubMed
description Background: The selection strategy of non-steroidal anti-inflammatory drugs (NSAIDs) for migraine is hard to judge whether it is effective, leading to unnecessary exposure to insufficient or lengthy treatment trials. The goal of the study was to investigate potential predictors of NSAIDs efficacy in migraine therapy and to explore their influence on efficacy. Methods: 610 migraine patients were recruited and assigned into responders and non-responders. Potential predictors among demographic and clinical characteristics for NSAIDs efficacy were extracted using multivariable logistic regression (LR) analysis, and were applied to construct prediction models via machine learning (ML) algorithms. Finally, Cochran-Mantel-Haenszel tests were used to examine the impact of each predictor on drug efficacy. Results: Multivariate LR analysis revealed migraine-related (disease duration, headache intensity and frequency) and psychiatric (anxiety, depression and sleep disorder) characteristics were predictive of NSAIDs efficacy. The accuracies of ML models using support vector machine, decision tree and multilayer perceptron were 0.712, 0.741, and 0.715, respectively. Cochran-Mantel-Haenszel test showed that, for variables with homogeneity of odds ratio, disease duration, frequency, anxiety, and depression and sleep disorder were associated with decreased likelihood of response to all NSAIDs. However, the variabilities in the efficacy of acetaminophen and celecoxib between patients with mild and severe headache intensity were not confirmed. Conclusion: Migraine-related and psychiatric parameters play a critical role in predicting the outcomes of acute migraine treatment. These models based on predictors could optimize drug selection and improve benefits from the start of treatment.
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spelling pubmed-97540552022-12-16 Prediction and associated factors of non-steroidal anti-inflammatory drugs efficacy in migraine treatment Lu, Zhao-Xuan Dong, Bing-Qing Wei, Heng-Le Chen, Liang Front Pharmacol Pharmacology Background: The selection strategy of non-steroidal anti-inflammatory drugs (NSAIDs) for migraine is hard to judge whether it is effective, leading to unnecessary exposure to insufficient or lengthy treatment trials. The goal of the study was to investigate potential predictors of NSAIDs efficacy in migraine therapy and to explore their influence on efficacy. Methods: 610 migraine patients were recruited and assigned into responders and non-responders. Potential predictors among demographic and clinical characteristics for NSAIDs efficacy were extracted using multivariable logistic regression (LR) analysis, and were applied to construct prediction models via machine learning (ML) algorithms. Finally, Cochran-Mantel-Haenszel tests were used to examine the impact of each predictor on drug efficacy. Results: Multivariate LR analysis revealed migraine-related (disease duration, headache intensity and frequency) and psychiatric (anxiety, depression and sleep disorder) characteristics were predictive of NSAIDs efficacy. The accuracies of ML models using support vector machine, decision tree and multilayer perceptron were 0.712, 0.741, and 0.715, respectively. Cochran-Mantel-Haenszel test showed that, for variables with homogeneity of odds ratio, disease duration, frequency, anxiety, and depression and sleep disorder were associated with decreased likelihood of response to all NSAIDs. However, the variabilities in the efficacy of acetaminophen and celecoxib between patients with mild and severe headache intensity were not confirmed. Conclusion: Migraine-related and psychiatric parameters play a critical role in predicting the outcomes of acute migraine treatment. These models based on predictors could optimize drug selection and improve benefits from the start of treatment. Frontiers Media S.A. 2022-11-18 /pmc/articles/PMC9754055/ /pubmed/36532762 http://dx.doi.org/10.3389/fphar.2022.1002080 Text en Copyright © 2022 Lu, Dong, Wei and Chen. 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 Pharmacology
Lu, Zhao-Xuan
Dong, Bing-Qing
Wei, Heng-Le
Chen, Liang
Prediction and associated factors of non-steroidal anti-inflammatory drugs efficacy in migraine treatment
title Prediction and associated factors of non-steroidal anti-inflammatory drugs efficacy in migraine treatment
title_full Prediction and associated factors of non-steroidal anti-inflammatory drugs efficacy in migraine treatment
title_fullStr Prediction and associated factors of non-steroidal anti-inflammatory drugs efficacy in migraine treatment
title_full_unstemmed Prediction and associated factors of non-steroidal anti-inflammatory drugs efficacy in migraine treatment
title_short Prediction and associated factors of non-steroidal anti-inflammatory drugs efficacy in migraine treatment
title_sort prediction and associated factors of non-steroidal anti-inflammatory drugs efficacy in migraine treatment
topic Pharmacology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9754055/
https://www.ncbi.nlm.nih.gov/pubmed/36532762
http://dx.doi.org/10.3389/fphar.2022.1002080
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