Establishment and validation of a risk prediction model for adverse drug reactions in patients with coronary heart disease after taking statins: a retrospective study
Objective This study aims to develop and validate a nomogram-based predictive model for estimating the risk of adverse drug reactions (ADR) to statins in patients with coronary heart disease (CHD). Methods A retrospective cohort study was conducted using clinical data from 351 patients with CHD who...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
PeerJ Inc.
2025-07-01
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| Series: | PeerJ |
| Subjects: | |
| Online Access: | https://peerj.com/articles/19630.pdf |
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| Summary: | Objective This study aims to develop and validate a nomogram-based predictive model for estimating the risk of adverse drug reactions (ADR) to statins in patients with coronary heart disease (CHD). Methods A retrospective cohort study was conducted using clinical data from 351 patients with CHD who received statin therapy in the cardiology department of a tertiary hospital in Anhui Province, China, between February 2021 and January 2022. The dataset was randomly divided into a development cohort (n = 283) and a validation cohort (n = 68) in an 8:2 ratio. Logistic regression analysis was applied in the development cohort to identify independent risk factors for statin-induced ADR. A nomogram was subsequently constructed in R based on the selected predictors, and its clinical utility, discriminative performance, and calibration were evaluated. Results The overall incidence of statin-associated ADR among the 351 subjects was 24.22%, classified into three categories according to the affected system: musculoskeletal toxicity, hepatic/renal dysfunction, and gastrointestinal reactions. Univariate and multivariate logistic regression analyses in the development cohort identified the following as significant independent risk factors (P < 0.05): age ≥60 years, body mass index ≥23 kg/m2, disease duration ≥5 years, presence of ≥3 comorbid conditions, dyslipidemia, history of cerebral infarction, high-dose statin use, and concomitant use of multiple medications. A nomogram model was constructed based on these predictors. The model demonstrated strong discriminative performance, with an area under the receiver operating characteristic (ROC) curve of 0.808 (95% CI [0.751–0.865]) in the development cohort and 0.852 (95% CI [0.752–0.951]) in the validation cohort. Conclusion A nomogram-based risk prediction model was successfully developed to estimate the probability of statin-induced ADR in patients with CHD, based on a set of statistically significant clinical risk factors. The model exhibited favorable predictive accuracy and discrimination. It offers a practical tool for clinicians to identify high-risk individuals and implement early preventive or interventional strategies accordingly. |
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| ISSN: | 2167-8359 |