British journal of hospital medicine (London, England : 2005) · 2026
Influencing Factors and a Predictive Model for Cardiovascular Events in Patients With Hyperuricemia Treated With Febuxostat.
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Chen Xiaojun, Chen Yuqun, Xu Wenxian, Lv Ying, Chen Yunxian
Аннотация
AIMS/BACKGROUND: The incidence of hyperuricemia is increasing globally, and febuxostat is a commonly used therapeutic agent. Investigating the relationship between febuxostat therapy and cardiovascular events in patients with hyperuricemia is of significant clinical value. This study aimed to construct a cardiovascular event prediction model for patients with hyperuricemia treated with febuxostat and to analyze factors associated with cardiovascular events, to provide a basis for clinical risk management.
METHODS: This single-center retrospective cohort study enrolled patients with hyperuricemia who were treated with febuxostat at Quzhou Municipal People's Hospital between January 2021 and January 2024 and were followed up at 3, 6, and 12 months after treatment. Baseline information, including age, body mass index, and medical history, was collected. Univariate and multivariate analyses were performed using binary logistic regression to identify influencing and predictive factors, and a cardiovascular event risk prediction model was established. The predictive performance and clinical applicability of the model were evaluated using nomograms, receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA).
RESULTS: A total of 700 patients with hyperuricemia receiving febuxostat were included, and the incidence of cardiovascular events during follow-up was 19.0%. Multivariate logistic regression analysis identified age (odds ratio [OR] = 1.05), prior hypertension (OR = 5.10), and body mass index (BMI, OR = 1.22) as independent predictors of cardiovascular events. Based on these variables, the established prediction model demonstrated good discriminatory ability, with a high area under the curve (AUC). The AUC of the nomogram model was 0.80 (0.74-0.85) in the training set and 0.78 (0.69-0.87) in the validation set. The calibration curve showed good agreement (Hosmer-Lemeshow test, p > 0.05). Decision curve analysis indicated a significant net clinical benefit.
CONCLUSION: The cardiovascular event prediction model developed in this study demonstrates good predictive performance and may serve as a useful clinical tool for cardiovascular risk assessment in patients with hyperuricemia. Age, BMI, and prior hypertension are important independent risk factors for cardiovascular events in patients with hyperuricemia. Future multicenter, long-term prospective studies are warranted to further validate the generalizability of this model and the cardiovascular safety of febuxostat treatment.
METHODS: This single-center retrospective cohort study enrolled patients with hyperuricemia who were treated with febuxostat at Quzhou Municipal People's Hospital between January 2021 and January 2024 and were followed up at 3, 6, and 12 months after treatment. Baseline information, including age, body mass index, and medical history, was collected. Univariate and multivariate analyses were performed using binary logistic regression to identify influencing and predictive factors, and a cardiovascular event risk prediction model was established. The predictive performance and clinical applicability of the model were evaluated using nomograms, receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA).
RESULTS: A total of 700 patients with hyperuricemia receiving febuxostat were included, and the incidence of cardiovascular events during follow-up was 19.0%. Multivariate logistic regression analysis identified age (odds ratio [OR] = 1.05), prior hypertension (OR = 5.10), and body mass index (BMI, OR = 1.22) as independent predictors of cardiovascular events. Based on these variables, the established prediction model demonstrated good discriminatory ability, with a high area under the curve (AUC). The AUC of the nomogram model was 0.80 (0.74-0.85) in the training set and 0.78 (0.69-0.87) in the validation set. The calibration curve showed good agreement (Hosmer-Lemeshow test, p > 0.05). Decision curve analysis indicated a significant net clinical benefit.
CONCLUSION: The cardiovascular event prediction model developed in this study demonstrates good predictive performance and may serve as a useful clinical tool for cardiovascular risk assessment in patients with hyperuricemia. Age, BMI, and prior hypertension are important independent risk factors for cardiovascular events in patients with hyperuricemia. Future multicenter, long-term prospective studies are warranted to further validate the generalizability of this model and the cardiovascular safety of febuxostat treatment.