A nomogram for predicting cerebral white matter lesions in elderly men

Abstract

Objective: This study aimed to develop a nomogram tool to predict cerebral white matter lesions (WMLs) in elderly men.

Methods: Based on a retrospective cohort from January 2017 to December 2019, a multivariate logistic analysis was performed to construct a nomogram for predicting WMLs. The nomogram was further validated using a follow-up cohort between January 2020 and December 2022. The calibration curve, receiver operating characteristics (ROC) curves, and the decision curves analysis (DCA) were used to evaluate discrimination and calibration of this nomogram.

Result: A total of 436 male patients were enrolled in this study, and all 436 patients were used as the training cohort and 163 follow-up patients as the validation cohort. A multivariate logistic analysis showed that age, cystatin C, uric acid, total cholesterol, platelet, and the use of antiplatelet drugs were independently associated with WMLs. Based on these variables, a nomogram was developed. The nomogram displayed excellent predictive power with the area under the ROC curve of 0.951 [95% confidence interval (CI), 0.929-0.972] in the training cohort and 0.915 (95% CI, 0.864-0.966) in the validation cohort. The calibration of the nomogram was also good, as indicated by the Hosmer-Lemeshow test with p-value of 0.594 in the training cohort and 0.178 in the validation cohort. The DCA showed that the nomogram holds good clinical application value.

Conclusion: We have developed and validated a novel nomogram tool for identifying elderly men at high risk of WMLs, which exhibits excellent predictive power, discrimination, and calibration.

Keywords: cerebral white matter lesions; elderly; male; nomogram; prediction model.