Development and External Validation of Nomogram to Identify Risk Factors for CHD in T2DM in the Population of Northwestern China

Qi Meng; Jing Yang; Fei Wang; Cheng Li; Guoyao Sang; Hua Liu; Di Shen; Jinxia Zhang; Sheng Jiang; Aibibai Yusufu; Guoli Du

doi:10.2147/DMSO.S404683

Development and External Validation of Nomogram to Identify Risk Factors for CHD in T2DM in the Population of Northwestern China

Diabetes Metab Syndr Obes. 2023 May 4:16:1271-1282. doi: 10.2147/DMSO.S404683. eCollection 2023.

Authors

Qi Meng^#^{1

2}, Jing Yang^{1

2}, Fei Wang^{1

2}, Cheng Li³, Guoyao Sang⁴, Hua Liu^{1

2}, Di Shen^{1

2}, Jinxia Zhang^{1

2}, Sheng Jiang^#^{1

2}, Aibibai Yusufu^#^{1

2}, Guoli Du^#^{1

2}

Affiliations

¹ State Key Laboratory of Pathogenesis, Prevention and Treatment of High Incidence Diseases in Central Asia, Urumqi, People's Republic of China.
² Department of Endocrinology, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, People's Republic of China.
³ Laboratory Medicine Diagnostic Center, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, People's Republic of China.
⁴ Data Statistics and Analysis Center of Operation Management Department, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, People's Republic of China.

^# Contributed equally.

Abstract

Purpose: Cardiovascular disease is the leading cause of mortality in patients with type 2 diabetes mellitus (T2DM). This study aimed to develop and validate a nomogram for predicting the risk factors for coronary heart disease (CHD) in T2DM in the population of northwestern China.

Patients and methods: The records of 2357 T2DM patients who were treated in the First Affiliated Hospital of Xinjiang Medical University from July 2021 to July 2022 were reviewed. After some data (n =239) were excluded, 2118 participants were included in the study and randomly divided into a training set (n =1483) and a validation set (n = 635) at a ratio of 3:1. Univariate and stepwise regression analysis was performed to screen risk factors and develop predictive models. The results of logistic regression are presented through a nomogram. The C-index, receiver operating characteristic (ROC) curve, calibration plot, and decision curve analysis (DCA) were employed to verify the distinction, calibration, and clinical practicality of the model.

Results: The stepwise logistic regression analysis suggested that independent factors in patients with T2DM combined with CHD were age, gender, hypertension (HTN), glycated hemoglobin (HbA1c), high density lipoprotein cholesterol (HDL-C), low density lipoprotein cholesterol (LDL-C), and Uygur, which were associated with the occurrence of CHD. The nomogram demonstrated good discrimination with a C-index of 0.771 (95% CI, 0.741, 0.800) in the training set and 0.785 (95% CI, 0.743, 0.828) in the validation set. The area under curve (AUC) of the ROC curves were 0.771 (95% CI, 0.741, 0.800) and 0.785 (95% CI, 0.743, 0.828) in the training and validation sets, respectively. The nomogram was well-calibrated. The DCA revealed that the nomogram was clinically valuable.

Conclusion: A nomogram based on 7 clinical characteristics was developed to predict CHD in patients with T2DM.

Keywords: coronary heart disease; ethnicity; nomogram; risk factor; type 2 diabetes mellitus.

Grants and funding

The survey was funded by the National Natural Science Foundation of China (81660155), State Key Laboratory of Pathogenesis, Prevention and Treatment of High Incidence Diseases in Central Asia, Xinjiang Medical University (SKL-HIDCA-2019-15 and SKL-HIDCA-2021-2), Natural Science Foundation of Xinjiang Uygur Autonomous Region, Outstanding Youth Science Foundation Project (2021D01E28) and Xinjiang Young Scientific and Technical Talents Training Project (2019Q040).