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

• Main Authors: Fa-Cai Wang, Wei Chang, Song-Liu Nie, Bing-Xiang Shen, Chun-Yuan He, Wei-Chen Zhao, Xiao-Yan Liu, Jing-Tao Lu
• Format: Article
• Language: English
• Published: SAGE Publishing 2021-09-01
• Series: Journal of International Medical Research
• Online Access: https://doi.org/10.1177/03000605211042502

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.