Research Paper|Volume 13, Issue 6|pp 8369—8379

A dynamic nomogram for predicting diabetic macular edema in type 2 diabetes patients based on plasma cytokines

Ning Zhang^1,², Jing Ke^1,², Dawei Zhang³, Yuanyuan Zhang^1,², Ying Fu^1,², Bin Cao^1,², Dong Zhao^1,²

¹Center for Endocrine Metabolism and Immune Diseases, Beijing Luhe Hospital, Capital Medical University, Beijing 101149, China
²Beijing Key Laboratory of Diabetes Research and Care, Beijing 101149, China
³Department of Ophthalmology, Beijing Luhe Hospital, Capital Medical University, Beijing 101149, China

Received: November 13, 2020Accepted: January 22, 2021Published: March 3, 2021

https://doi.org/10.18632/aging.202647

Copyright: © 2021 Zhang et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Abstract

Objective: This study investigated changes of plasma cytokines and aimed to build a dynamic nomogram for diabetic macular edema (DME) in type 2 diabetes mellitus (T2DM).

Methods: In a pilot cohort, plasma samples were selected from 9 T2DM patients and 9 DME patients to screen for cytokine differences. The screening cytokines were then validated by enzyme-linked immunoassay in a cohort, which contained 100 DME (DME group) and 100 T2DM patients without DME (T2DM group). A dynamic nomogram for predicting DME was developed, based on the plasma cytokines.

Results: In the pilot cohort, 11 plasma cytokines were significantly increased in the DME group. In the validation cohort, platelet-derived growth factor (PDGF)-BB, tissue inhibitors of metalloproteinase (TIMP)-1, angiopoietin (ANG-1), and vascular endothelial cell growth factor receptor (VEGFR)-2 were confirmed to be significantly elevated in the DME group. The dynamic nomogram demonstrated good calibration and discrimination, with an area under the receiver operating characteristic curve (AUC) of 0.88. In the test set, sensitivity, specificity, and AUC were 73.3%, 80.0%, and 0.84, respectively.

Conclusion: Plasma cytokines were closely associated with DME. A novel dynamic monogram including ANG-1, PDGF-BB, TIMP-1, and VEGFR2 was a novel tool for predicting DME.