Abstract
We developed and validated a nomogram to predict coronary heart disease (CHD) in patients with rheumatoid arthritis (RA) in northern China. We analyzed a cohort of RA patients admitted to the Department of Rheumatology and Immunology of the First Affiliated Hospital of China Medical University from 2011 to 2017. To select a high-performance model for clinical data prediction, we evaluated the F1-scores of six machine learning models. Based on the results, we selected multivariable logistic regression analysis for the development of a prediction model. We then generated an individualized prediction nomogram that included age, sex, hypertension, anti-cyclic citrullinated peptide antibody positivity, the erythrocyte sedimentation rate, and serum LDL-cholesterol, triglyceride and HDL-cholesterol levels. The prediction model exhibited better discrimination than the Framingham Risk Score in predicting CHD in RA patients. The area under the curve of the prediction model was 0.77, with a sensitivity of 63.9% and a specificity of 77.2%. The nomogram exhibited good calibration and clinical usefulness. In conclusion, our prediction model was more accurate than the Framingham Risk Score in predicting CHD in RA patients. Our nomogram combining various risk factors can be used for the individualized preoperative prediction of CHD in patients with RA.
Highlights
Rheumatoid arthritis (RA) is the prototype of chronic inflammatory rheumatic disease, and is associated with accelerated atherosclerosis and an increased risk of cardiovascular disease (CVD) [1,2,3]
We analyzed a cohort of RA patients with and without coronary heart disease (CHD) who were admitted to the Department of Rheumatology and Immunology of the First Affiliated Hospital of China Medical University from 2011 to 2017
The age distribution, hypertension, anti-CCP antibody positivity, rheumatoid factor positivity, erythrocyte sedimentation rate (ESR), and dyslipidemia of low-density lipoprotein cholesterol (LDL-c), total cholesterol (TC), triglycerides and high-density lipoprotein cholesterol (HDL-c) differed significantly between the RA and RA+CHD groups, while C-reactive protein (CRP) levels did not differ between the two groups in this cohort
Summary
Rheumatoid arthritis (RA) is the prototype of chronic inflammatory rheumatic disease, and is associated with accelerated atherosclerosis and an increased risk of cardiovascular disease (CVD) [1,2,3]. Patients with RA are at greater risk for coronary heart disease (CHD) than those without RA [4]. It is important to be able to predict whether patients with RA are at high risk for cardiovascular events so that preventive measures can be taken. While some traditional CHD risk factors (e.g., hypertension [7], disease activity [8], smoking [9] and dyslipidemia [10]). Are more prevalent among RA patients than among those without RA, these factors explain only a portion of the observed excess of CHD risk in RA patients. The incidence of atherosclerosis is two to three times higher in RA patients than in the general population after adjustment for traditional risk factors of atherosclerosis [11,12,13]. The predictors of CHD in RA have not been fully elucidated
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