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Research Paper|Volume 12, Issue 10|pp 9427—9439

Development of a nomogram that predicts the risk for coronary atherosclerotic heart disease

Shuna Huang1, Xiaoxu Xie1, Yi Sun1, Tingxing Zhang2, Yingying Cai1, Xingyan Xu1, Huangyuan Li3, Siying Wu1
  • 1Department of Epidemiology and Health Statistics, School of Public Health, Fujian Medical University, Fuzhou 350122, China
  • 2Department of Cardiology, The First Affiliated Hospital of Fujian Medical University, Fuzhou 350005, China
  • 3Department of Preventive Medicine, School of Public Health, Fujian Medical University, Fuzhou 350122, China
* Equal contribution
Received: January 19, 2020Accepted: April 17, 2020Published: May 18, 2020
https://doi.org/10.18632/aging.103216

Copyright © 2020 Huang et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Abstract

Studies seldom combine biological, behavioral and psychological factors to estimate coronary atherosclerotic heart disease (CHD) risk. Here, we evaluated the associations between these factors and CHD to develop a predictive nomogram to identify those at high risk of CHD. This case-control study included 4392 participants (1578 CHD cases and 2814 controls) in southeast China. Thirty-three biological, behavioral and psychological variables were evaluated. Following multivariate logistic regression analysis, which revealed eight risk factors associated with CHD, a predictive nomogram was developed based on a final model that included the three non-modifiable (sex, age and family history of CHD) and five modifiable (hypertension, hyperlipidemia, diabetes, recent experience of a major traumatic event, and anxiety) variables. The higher total nomogram score, the greater the CHD risk. Final model accuracy (as estimated from the area under the receiver operating characteristic curve) was 0.726 (95% confidence interval: 0.709-0.747). Validation analysis confirmed the high accuracy of the nomogram. High risk of CHD was associated with several biological, behavioral and psychological factors. We have thus developed an intuitive nomogram that could facilitate development of preliminary prevention strategies for CHD.