Construction and validation of prediction model for diabetic retinopathy
10.3980/j.issn.1672-5123.2024.8.22
- VernacularTitle:糖尿病视网膜病变预测模型的构建与验证
- Author:
Xingyue CHEN
1
;
Weiqin CAI
1
;
Suzhen WANG
1
;
Hongqing AN
1
;
Leitao QI
1
Author Information
1. School of Public Health,Shandong Second Medical University, Weifang 261053, Shandong Province, China
- Publication Type:Journal Article
- Keywords:
diabetic retinopathy;
LASSO;
nomogram;
ROC curve;
calibration curve;
DCA curve
- From:
International Eye Science
2024;24(8):1297-1302
- CountryChina
- Language:Chinese
-
Abstract:
AIM: To analyze and screen influencing factors of diabetic patients complicated with retinopathy, and establish and validate prediction model of nomogram.METHODS: A total of 1 252 patients from the Diabetes Complications Early Warning Dataset of the National Population Health Data Archive(PHDA)between January 2013 to January 2021 were selected and randomly divided into a modeling group(n=941)and a validation group(n=311). Univariate analysis, LASSO regression and Logistic regression analysis were used to screen out the influencing factors of diabetic retinopathy, and a nomogram prediction model was established. The receiver operating characteristic curve, Hosmer-Lemeshow test and calibration curve were used to evaluate the model. The clinical benefit was evaluated by the decision curve analysis(DCA).RESULTS: Age, hypertension, nephropathy, systolic blood pressure(SBP), glycated hemoglobin(HbA1c), high-density lipoprotein cholesterol(HDL-C), and blood urea(BU)were the influencing factors of diabetic retinopathy. The area under the curve(AUC)of the modeling group was 0.792(95%CI: 0.763-0.821), and the AUC of the validation group was 0.769(95%CI: 0.716-0.822). The Hosmer-Lemeshow goodness of fit test and calibration curve suggested that the theoretical value of the model was in good agreement(modeling group: χ2=14.520, P=0.069; validation group: χ2=14.400, P=0.072). The DCA results showed that the threshold probabilities range was 0.09-0.89 for modeling group and 0.07-0.84 for the validation group, which suggested the clinical net benefit was higher.CONCLUSION: This study constructed a risk prediction model including age, hypertension, nephropathy, SBP, HbA1c, HDL-C, and BU. The model has a high discrimination and consistency, and can be used to predict the risk of diabetic retinopathy in patients with diabetes.
