A Novel Nomogram for predicting coronary vulnerable plaques risk in patients with coronary artery disease - Supplementary Figure 1
Objective: To develop and validate a nomogram for predicting coronary vulnerable plaques (VPs) in
coronary artery disease (CAD) patients. Methods: One hundred seventy-seven CAD patients were enrolled
in the training group. Another 60 patients were included for validation. Based on the identified
independent risk factors, a nomogram model was developed and then validated. Results: Type 2 diabetes,
hypertension, neutrophil-to-lymphocyte ratio, low-density lipoprotein cholesterol, MCP-1 and MMP-9
were found to be independent risk factors for coronary VPs. Both internal and external validation showed
this nomogram had satisfactory discrimination via receiver operating characteristic curves, calibration
via calibration plots and clinical application values via decision curve analysis. Conclusion: The authors
established a nomogram model predicting coronary VP risk in CAD patients with promising clinical
application value.
Plain language summary: Vulnerability to coronary atherosclerotic plaques is the important initiating
cause of major adverse cardiovascular events in coronary artery disease (CAD) patients. Early detection
of high-risk CAD patients with vulnerable plaques (VPs) could prevent the occurrence of major adverse
cardiovascular events and improve patients’ clinical outcomes. The present study aimed to investigate
the risk factors for coronary VPs and then develop a model for predicting VP risk in CAD patients. The
authors found that Type 2 diabetes, hypertension, neutrophil-to-lymphocyte ratio, low-density lipoprotein
cholesterol, MCP-1 and MMP-9 were independently associated with coronary VPs in CAD patients. Based
on these variables, the authors constructed a nomogram to estimate the individualized risk of VPs
and validated the nomogram internally and externally with good accuracy and discrimination. These
demonstrated that this nomogram model could achieve individualized prediction of coronary VP risk and
would aid physicians in identifying high-risk patients and optimizing a timely treatment strategy with
potential clinical application value.
