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. 2020 May 18;12(10):9427-9439.
doi: 10.18632/aging.103216. Epub 2020 May 18.

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

Shuna Huang  1 , Xiaoxu Xie  1 , Yi Sun  1 , Tingxing Zhang  2 , Yingying Cai  1 , Xingyan Xu  1 , Huangyuan Li  3 , Siying Wu  1
Affiliations

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

Shuna Huang et al. Aging (Albany NY). .

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.

Keywords: behavioral; biological; coronary atherosclerotic heart disease; nomogram; psychological.

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Conflict of interest statement

CONFLICTS OF INTEREST: The authors declare no potential conflicts of interest.

Figures

Figure 1
Figure 1
Estimated odds ratios determined in a logistic regression model (Backwald: Wald). Abbreviations: OR, odds ratio; CI, confidence interval.
Figure 2
Figure 2
Nomogram for predicting CHD risk. The value of each variable was scored on a point scale from 0 to 100, after which the scores for each variable were added together. That sum is located on the total points axis, which enables us to predict the probability of CHD risk. For age categories, 1= 10 to 20, 2 = 21 to 30, 3 = 31 to 40, 4 = 41 to 50, 5 = 51 to 60, 6 = 61 to 70, 7 = 71 to 80, 8 = 81 to 90, 9 = 91 to 100, 10 = 101 to 110 year. For other variables, 0 = no and 1 = yes.
Figure 3
Figure 3
Association between the total points of the nomogram and CHD. Abbreviations: OR, odds ratio; CI, confidence interval.
Figure 4
Figure 4
Evaluation of the nomogram model. (A) Receiver operating characteristic curve for the nomogram generated using bootstrap resampling (500 times). (B) Nomogram calibration plot. When the solid line (performance nomogram) was closer to the dotted line (ideal model), the prediction accuracy of the nomogram was better. (C) Decision curve analysis for the prediction model. The red solid line is from the prediction model, the gray line is for all patients with CHD, and the solid horizontal line indicates no patients have CHD. The graph depicts the expected net benefit per patient relative to the nomogram prediction of CHD risk. The net benefit increases as the model curve is extended.
Figure 5
Figure 5
Hypothesized association between CHD and potential predictors in our study.
See this image and copyright information in PMC

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