Objectives
Hyperuricaemia (HUA) is a major contributing factor to the development of gout and is linked to an increased risk of cardiometabolic disease, particularly in men. Despite this, there is a lack of simple tools for predicting HUA in male patients. This study aims to develop and validate a nomogram model to estimate the risk of HUA in male subjects.
Methods
A total of 21,953 eligible male participants, aged 18 years and older, were consecutively recruited during routine medical examinations at Northern Jiangsu People’s Hospital from July 2014 to August 2023. To identify factors related to HUA in male subjects, the least absolute shrinkage and selection operator (LASSO) regression and logistic regression methods were used. A nomogram was subsequently constructed to predict the likelihood of HUA in men.The performance of the proposed nomogram was evaluated based on a calibration plot, ROC curve and Harrell’s concordance index (C-index).
Results
Patients with hyperuricemia exhibited significantly elevated levels of BMI, red blood cell count, hemoglobin, hematocrit, blood glucose, serum urea, creatinine, total cholesterol, LDL-c, and triglyceride levels compared to those without hyperuricemia (P < 0.001). Conversely, the age and HDL-c levels of patients with hyperuricemia were notably lower than those without hyperuricemia (P < 0.001). Predictors used in the prediction nomogram included LDL-c, TG, HDL-c and serum Creatinine and RBC. Then, a nomogram model for predicting HUA was established based on the above indicators. Our model achieved well-fitted calibration curves and the C-indices of this model were 0.700 (95% CI: 0.692–0.708) and 0.705 (95% CI: 0.691–0.720) in the development and validation groups, respectively.
Conclusions
With excellent predictive abilities, the nomogram serves as a straightforward and dependable tool for estimating the risk of HUA among male participants.
