Association of non-high-density lipoprotein cholesterol to high-density lipoprotein cholesterol ratio with coronary heart disease: Establishment and validation of a clinical nomogram model.

The purpose of this study is to investigate the non-high-density lipoprotein cholesterol (non-HDL-C) to high-density lipoprotein cholesterol (HDL-C) ratio (NHHR) as a novel compound lipid index for atherosclerosis and explore its relationship with coronary heart disease (CHD). This study also aims to establish NHHR as a sensitive indicator for early prevention of CHD and to construct a clinical prediction model to further predict the occurrence of CHD. This study selected 707 patients who visited the First People's Hospital of Mengcheng County from January 2020 to May 2024, including 466 patients with CHD and a control group. Logistic regression analysis was used to analyze the correlation between NHHR and CHD. Patients were randomly divided into a training set and validation set in a 7:3 ratio. Multivariable logistic regression was used to screen for risk factors, and a nomogram model was constructed and validated. After adjusting for confounding factors, the results showed that for each increase of 1 standard deviation in NHHR, the risk of CHD increased by 42%, with a P-value of .003. In model 3, the risk of CHD for the highest quartile increased by 144%, with a P-value of .01. The smoothed curve fitting showed a nonlinear relationship between NHHR and CHD. Multivariable logistic analysis indicated that age, body mass index, smoke, hypertension, white blood cells, fasting plasma glucose, uric acid, and NHHR were independent risk factors for predicting the occurrence of CHD (P < .05), and a risk prediction nomogram model was constructed. The receiver operating characteristic curve analysis of the training set showed an AUC of 0.922 (95% CI: 0.900-0.945), and the AUC of the validation set was 0.902 (95% CI: 0.856-0.948), indicating good model accuracy. Calibration curve analysis showed that the calibration curves of the nomogram model were very close for predicting the occurrence of CHD in the training set and validation set, and the decision curve analysis also showed a good clinical net benefit of the nomogram model. The study results indicated a strong and nonlinear correlation between NHHR and CHD. Our constructed nomogram model has a certain predictive ability for the occurrence of CHD.