Abstract:

Objective To investigate the clinical factors associated with bone erosion in patients with tophi detected by ultrasound and to construct and internally validate a nomogram-based risk assessment model. Methods Clinical data of 226 gout patients who underwent musculoskeletal ultrasonography and were diagnosed with tophi at Zhengzhou Central Hospital Affiliated to Zhengzhou University from January 2022 to October 2025 were retrospectively collected. The presence of bone erosion was set as the outcome variable. General characteristics， medical history， and laboratory indicators of these patients were collected. Subsequently， the patients were randomly divided into a training set and an internal validation set at a ratio of 7∶3. Univariate analysis was carried out to screen candidate variables， and multivariate logistic regression analysis was employed to identify independent factors associated with bone erosion in patients with ultrasound-detected tophi. Based on these factors， a nomogram model was constructed. The discriminatory ability of the model was evaluated through receiver operating characteristic （ROC） curve analysis. Calibration and goodness of fit were respectively assessed by using calibration curves and the Hosmer-Lemeshow test. Decision curve analysis （DCA） was utilized to evaluate the clinical utility of the model. Results The bone erosion group was characterized by an older age， a longer disease duration， higher serum uric acid levels， a higher proportion of polyarticular involvement， and lower estimated glomerular filtration rate and albumin levels compared to the non-bone erosion group； all these differences were statistically significant （all P 0.05）. Multivariate logistic regression analysis revealed that an older age， a longer disease duration， polyarticular involvement， higher serum uric acid levels， and a lower estimated glomerular filtration rate were independently associated with bone erosion in patients with ultrasound-detected tophi. A nomogram model was constructed based on these factors. Receiver operating characteristic curve analysis demonstrated that the areas under the curve of the model were 0.950 （95%CI： 0.903 - 0.997） in the training set and 0.915 （95%CI： 0.874 - 0.957） in the internal validation set， indicating that the model had a certain discriminative ability within this cohort. The calibration curve showed an acceptable agreement between the predicted and observed probabilities. The Hosmer-Lemeshow goodness-of-fit test indicated an acceptable model fit in both the training and internal validation sets （χ2 = 5.164 and 3.353， respectively； P = 0.740 and 0.910， respectively）. Decision curve analysis showed that the model had a certain clinical net benefit within a range of threshold probabilities. Conclusions Advanced age， extended disease duration， polyarticular involvement， elevated serum uric acid levels， and reduced estimated glomerular filtration rate were independently associated with bone erosion in patients with ultrasound-detected tophi. The nomogram model constructed based on these factors exhibited a certain degree of predictive value and could offer a reference for clinical risk assessment and stratified management.

Key words: gout, tophi, bone erosion, ultrasonography, nomograms