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已发表论文
一种用于预测中国高脂血症人群药物依从性风险的新列线图的开发与验证
Authors Guo J, Ning F, Xiao J, Pu P, Zhao Y, Zhang W, Wu M
Received 10 July 2025
Accepted for publication 20 December 2025
Published 30 December 2025 Volume 2025:19 Pages 4321—4334
DOI https://doi.org/10.2147/PPA.S547265
Checked for plagiarism Yes
Review by Single anonymous peer review
Peer reviewer comments 3
Editor who approved publication: Dr Ramón Morillo-Verdugo
Jingyue Guo,1,* Feng Ning,2,* Jianbiao Xiao,2,* Peipei Pu,2 Yuesong Zhao,3 Wei Zhang,4 Mingfen Wu5
1Medical Department, Dahongmen Community Health Service Center, Beijing, 100075, People’s Republic of China; 2Executive Office, Dahongmen Community Health Service Center, Beijing, 100075, People’s Republic of China; 3Executive Office, Heyi Community Health Service Center, Beijing, 100076, People’s Republic of China; 4Fengtai District Community Health Service Management Center, Beijing, 100071, People’s Republic of China; 5Department of Pharmacy, Beijing Tiantan Hospital, Capital Medical University, Beijing, 100070, People’s Republic of China
*These authors contributed equally to this work
Correspondence: Mingfen Wu, Email wmfling@163.com
Purpose: This study aimed to explore the factors influencing medication adherence and develop a medication nonadherence risk nomogram in a Chinese population with hyperlipidemia.
Methods: This prospective intervention study was conducted in Beijing from November 2020 to October 2021. Medication adherence was determined according to the 9-question scale and nonadherence patients were intervened by pharmacists and followed up for 3 months. Multivariate logistic regression was used to analyze the risk factors of medication nonadherence, and then a nomogram model was established. The concordance index (C-index), area under the curve (AUC) was used to evaluate the accuracy of the prediction model. The decision curve analysis (DCA) and clinical impact plot analysis were employed to further evaluate the clinical effectiveness of the nomogram.
Results: A total of 685 patients were included for analysis. The rate of medication nonadherence was 238 patients (34.75%). Post-intervention, the average score of medication adherence increased from 20.75± 8.01 to 29.90± 6.93 (p < 0.001). And the number of patients with TC, TG, LDL-C, and HDL-C reaching the standard was 264 (62.86%), 201 (47.43%), 318 (78.52%), and 377 (96.71%), respectively. Five predictors including the course of hyperlipidemia (OR=2.957, 95% CI 1.168– 7.488), following the doctor’s advice to visit (OR=2.757, 95% CI 1.389– 5.472), use of medications empirically (OR=1.189, 95% CI 1.188– 2.786), physical exercise (OR=0.399, 95% CI 0.205– 0.776) and lifestyle compliance (OR=0.910, 95% CI 0.839– 0.988) were identified to build the nomogram model. The AUC was 0.927 and C-index was 0.87.
Conclusion: Patients with hyperlipidemia displayed low medication adherence which pharmaceutical interventions can improve. We developed and validated a nomogram model to facilitate the individual medication nonadherence risk prediction in hyperlipidemia patients.
Limitation: First, using the cut-off value of 27 for adherence assessment in the adherence questionnaire, criterion validity was not enough good to validly screen a patient with nonadherence to medication. Second, our study may have unmeasured confounding variables, which could bias the results. Third, owing to the lack of external validation in this study, it may have some limitations in extrapolation. Fourth, the questionnaire was assessed by self-report measures.
Keywords: hyperlipidemia, medication non adherence, risk factor, intervention, nomogram
1Medical Department, Dahongmen Community Health Service Center, Beijing, 100075, People’s Republic of China; 2Executive Office, Dahongmen Community Health Service Center, Beijing, 100075, People’s Republic of China; 3Executive Office, Heyi Community Health Service Center, Beijing, 100076, People’s Republic of China; 4Fengtai District Community Health Service Management Center, Beijing, 100071, People’s Republic of China; 5Department of Pharmacy, Beijing Tiantan Hospital, Capital Medical University, Beijing, 100070, People’s Republic of China
*These authors contributed equally to this work
Correspondence: Mingfen Wu, Email wmfling@163.com
Purpose: This study aimed to explore the factors influencing medication adherence and develop a medication nonadherence risk nomogram in a Chinese population with hyperlipidemia.
Methods: This prospective intervention study was conducted in Beijing from November 2020 to October 2021. Medication adherence was determined according to the 9-question scale and nonadherence patients were intervened by pharmacists and followed up for 3 months. Multivariate logistic regression was used to analyze the risk factors of medication nonadherence, and then a nomogram model was established. The concordance index (C-index), area under the curve (AUC) was used to evaluate the accuracy of the prediction model. The decision curve analysis (DCA) and clinical impact plot analysis were employed to further evaluate the clinical effectiveness of the nomogram.
Results: A total of 685 patients were included for analysis. The rate of medication nonadherence was 238 patients (34.75%). Post-intervention, the average score of medication adherence increased from 20.75± 8.01 to 29.90± 6.93 (p < 0.001). And the number of patients with TC, TG, LDL-C, and HDL-C reaching the standard was 264 (62.86%), 201 (47.43%), 318 (78.52%), and 377 (96.71%), respectively. Five predictors including the course of hyperlipidemia (OR=2.957, 95% CI 1.168– 7.488), following the doctor’s advice to visit (OR=2.757, 95% CI 1.389– 5.472), use of medications empirically (OR=1.189, 95% CI 1.188– 2.786), physical exercise (OR=0.399, 95% CI 0.205– 0.776) and lifestyle compliance (OR=0.910, 95% CI 0.839– 0.988) were identified to build the nomogram model. The AUC was 0.927 and C-index was 0.87.
Conclusion: Patients with hyperlipidemia displayed low medication adherence which pharmaceutical interventions can improve. We developed and validated a nomogram model to facilitate the individual medication nonadherence risk prediction in hyperlipidemia patients.
Limitation: First, using the cut-off value of 27 for adherence assessment in the adherence questionnaire, criterion validity was not enough good to validly screen a patient with nonadherence to medication. Second, our study may have unmeasured confounding variables, which could bias the results. Third, owing to the lack of external validation in this study, it may have some limitations in extrapolation. Fourth, the questionnaire was assessed by self-report measures.
Keywords: hyperlipidemia, medication non adherence, risk factor, intervention, nomogram