Nomogram for Prediction of Diabetic Retinopathy Among Type 2 Diabetes Population in Xinjiang, China

Abstract

Purpose

To establish an accurate risk prediction model of diabetic retinopathy (DR) using cost effective and easily available patients’ characteristics and clinical biomarkers.

Patients and Methods

Totally 18,904 cases diagnosed type 2 diabetes mellitus (T2DM) were collected, among which 13,980 cases were selected after quality screening. The least absolute shrinkage and selection operator (LASSO) regression models were used for univariate analysis and factors selection, and the multi-factor logistic regression analysis was used to establish the prediction model. Discrimination, calibration, and clinical usefulness of the prediction model were assessed using AUC/ Harrell’s C statistic, calibration plot, and decision curve analysis. Both the development group and validation group were assessed.

Results

Candidate variables were selected by Lasso regression and multivariate logistic regression analysis. Finally, the candidate predictive variables were included diabetic peripheral neuropathy (DPN), age, neutrophilic granulocyte (NE), high-density lipoprotein (HDL), hemoglobin A1c (HbA1C), duration of T2DM, and glycosylated serum protein (GSP) were used to establish a nomogram model for predicting the risk of DR. In the development group, the area under the receiver operating characteristic curve (AUC) was 0.882 (95% CI, 0.875–0.888). In the validation group, the AUC was 0.870 (95% CI, 0.856–0.881). Meanwhile, the optimism-corrected Harrell’s C statistic were 0.878 and 0.867 in the development group and the validation group, respectively. Decision curve analysis demonstrated that the nomogram was clinically useful.

Conclusion

We constructed and verified nomograms that could accurately predict the risk of DR in T2DM patients, which could be used to predict the personalized risk of DR patients in Xinjiang, China.

Keywords:

• diabetic peripheral neuropathy
• risk factors
• prediction model
• nomogram

Ethics Statement

The study was approved by the Medical Ethics Committee of the First Affiliated Hospital of Xinjiang Medical University (approval number, k202105-05) and followed the principles of the Declaration of Helsinki.

Author Contributions

All authors made a significant contribution to the work reported, whether that is in the conception, study design, execution, acquisition of data, analysis and interpretation, or in all these areas; took part in drafting, revising or critically reviewing the article; gave final approval of the version to be published; have agreed on the journal to which the article has been submitted; and agree to be accountable for all aspects of the work.

Disclosure

The authors report no conflicts of interest in this work.

Additional information

Funding

This study was also supported by the Natural Science Foundation of Xinjiang Uygur Autonomous Region (Grant Number, 2019D01C215).