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Predicting medication nonadherence risk in the Chinese type 2 diabetes mellitus population – establishment of a new risk nomogram model: a retrospective study

OBJECTIVE: To investigate the risk factors of medication nonadherence in patients with type 2 diabetes mellitus (T2DM) and to establish a risk nomogram model. METHODS: This retrospective study enrolled patients with T2DM, which were divided into two groups based on their scores on the Morisky Medica...

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Autores principales: Wang, Fa-Cai, Chang, Wei, Nie, Song-Liu, Shen, Bing-Xiang, He, Chun-Yuan, Zhao, Wei-Chen, Liu, Xiao-Yan, Lu, Jing-Tao
Formato: Online Artículo Texto
Lenguaje:English
Publicado: SAGE Publications 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8485320/
https://www.ncbi.nlm.nih.gov/pubmed/34551601
http://dx.doi.org/10.1177/03000605211042502
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author Wang, Fa-Cai
Chang, Wei
Nie, Song-Liu
Shen, Bing-Xiang
He, Chun-Yuan
Zhao, Wei-Chen
Liu, Xiao-Yan
Lu, Jing-Tao
author_facet Wang, Fa-Cai
Chang, Wei
Nie, Song-Liu
Shen, Bing-Xiang
He, Chun-Yuan
Zhao, Wei-Chen
Liu, Xiao-Yan
Lu, Jing-Tao
author_sort Wang, Fa-Cai
collection PubMed
description OBJECTIVE: To investigate the risk factors of medication nonadherence in patients with type 2 diabetes mellitus (T2DM) and to establish a risk nomogram model. METHODS: This retrospective study enrolled patients with T2DM, which were divided into two groups based on their scores on the Morisky Medication Adherence scale. Univariate and multivariate logistic regression analyses were used to screen for independent risk factors for medication nonadherence. A risk model was then established using a nomogram. The accuracy of the prediction model was evaluated using centrality measurement index and receiver operating characteristic curves. Internal verification was evaluated using bootstrapping validation. RESULTS: A total of 338 patients with T2DM who included in the analysis. Logistic regression analysis showed that the educational level, monthly per capita income, drug affordability, the number of drugs used, daily doses of drugs and the time spent taking medicine were all independent risk factors for medication nonadherence. Based on these six risk factors, a nomogram model was established to predict the risk of medication nonadherence, which was shown to be very reliable. Bootstrapping validated the nonadherence nomogram model for patients with T2DM. CONCLUSIONS: This nomogram model could be used to evaluate the risks of drug nonadherence in patients with T2DM.
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spelling pubmed-84853202021-10-02 Predicting medication nonadherence risk in the Chinese type 2 diabetes mellitus population – establishment of a new risk nomogram model: a retrospective study Wang, Fa-Cai Chang, Wei Nie, Song-Liu Shen, Bing-Xiang He, Chun-Yuan Zhao, Wei-Chen Liu, Xiao-Yan Lu, Jing-Tao J Int Med Res Retrospective Clinical Research Report OBJECTIVE: To investigate the risk factors of medication nonadherence in patients with type 2 diabetes mellitus (T2DM) and to establish a risk nomogram model. METHODS: This retrospective study enrolled patients with T2DM, which were divided into two groups based on their scores on the Morisky Medication Adherence scale. Univariate and multivariate logistic regression analyses were used to screen for independent risk factors for medication nonadherence. A risk model was then established using a nomogram. The accuracy of the prediction model was evaluated using centrality measurement index and receiver operating characteristic curves. Internal verification was evaluated using bootstrapping validation. RESULTS: A total of 338 patients with T2DM who included in the analysis. Logistic regression analysis showed that the educational level, monthly per capita income, drug affordability, the number of drugs used, daily doses of drugs and the time spent taking medicine were all independent risk factors for medication nonadherence. Based on these six risk factors, a nomogram model was established to predict the risk of medication nonadherence, which was shown to be very reliable. Bootstrapping validated the nonadherence nomogram model for patients with T2DM. CONCLUSIONS: This nomogram model could be used to evaluate the risks of drug nonadherence in patients with T2DM. SAGE Publications 2021-09-22 /pmc/articles/PMC8485320/ /pubmed/34551601 http://dx.doi.org/10.1177/03000605211042502 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by-nc/4.0/Creative Commons Non Commercial CC BY-NC: 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 pages (https://us.sagepub.com/en-us/nam/open-access-at-sage).
spellingShingle Retrospective Clinical Research Report
Wang, Fa-Cai
Chang, Wei
Nie, Song-Liu
Shen, Bing-Xiang
He, Chun-Yuan
Zhao, Wei-Chen
Liu, Xiao-Yan
Lu, Jing-Tao
Predicting medication nonadherence risk in the Chinese type 2 diabetes mellitus population – establishment of a new risk nomogram model: a retrospective study
title Predicting medication nonadherence risk in the Chinese type 2 diabetes mellitus population – establishment of a new risk nomogram model: a retrospective study
title_full Predicting medication nonadherence risk in the Chinese type 2 diabetes mellitus population – establishment of a new risk nomogram model: a retrospective study
title_fullStr Predicting medication nonadherence risk in the Chinese type 2 diabetes mellitus population – establishment of a new risk nomogram model: a retrospective study
title_full_unstemmed Predicting medication nonadherence risk in the Chinese type 2 diabetes mellitus population – establishment of a new risk nomogram model: a retrospective study
title_short Predicting medication nonadherence risk in the Chinese type 2 diabetes mellitus population – establishment of a new risk nomogram model: a retrospective study
title_sort predicting medication nonadherence risk in the chinese type 2 diabetes mellitus population – establishment of a new risk nomogram model: a retrospective study
topic Retrospective Clinical Research Report
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8485320/
https://www.ncbi.nlm.nih.gov/pubmed/34551601
http://dx.doi.org/10.1177/03000605211042502
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