ORIGINAL RESEARCH article
Front. Endocrinol.
Sec. Clinical Diabetes
Volume 16 - 2025 | doi: 10.3389/fendo.2025.1557166
This article is part of the Research TopicPrevention and Treatment Advancements in Diabetic RetinopathyView all 7 articles
Universal Nomogram for Predicting Referable Diabetic Retinopathy: A Validated Model for Community and Ophthalmic Outpatient Populations Using Easily Accessible Indicators
Provisionally accepted
- 1Clinical Laboratory Center, Xi'an People's Hospital (Xi'an Fourth Hospital), Affiliated People's Hospital of Northwest University, xi'an, China
- 2Shaanxi Eye Hospital, Xi'an People's Hospital (Xi'an Fourth Hospital), Affiliated People's Hospital of Northwest University, xi'an, China
- 3Department of Nephrology, Xi'an People's Hospital (Xi'an Fourth Hospital), Affiliated People's Hospital of Northwest University, xi'an, China
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Purpose: This study aimed to develop and validate a universal nomogram for predicting referable diabetic retinopathy (RDR) in type 2 diabetes mellitus (T2DM) patients, using easily accessible clinical indicators for both community and ophthalmic outpatient populations.Methods: A cross-sectional study was conducted with 1,830 T2DM patients from 14 communities in Xi'an, Shaanxi, China. Participants completed questionnaires, underwent physical exams, and ophthalmic assessments. Univariate analysis and least absolute shrinkage and selection operator (LASSO) regression identified key predictors for RDR. A nomogram was developed using multivariable logistic regression. Model performance was evaluated through area under the curve (AUC), accuracy, precision, recall, F1 score, Youden index, calibration curves, and decision curve analysis (DCA). The dataset was split into training (80%) and test (20%) sets, with external validation using 123 T2DM outpatients from Shaanxi Eye Hospital.Results: Seven key predictors were identified: serum creatinine, urea nitrogen, urine glucose, HbA1c, urinary microalbumin, diabetes duration, and systolic blood pressure. The nomogram exhibited moderate predictive accuracy, with AUCs of 0.730 (95% CI: 0.691–0.759), 0.767 (95% CI: 0.704–0.831), and 0.723 (95% CI: 0.610–0.835) for the training, test, and external validation sets, respectively. DCA showed that using the model is beneficial for threshold probabilities between 8% and 72%, supporting its broad clinical utility.Conclusion: This nomogram, based on readily available clinical indicators, provides a reliable and scalable tool for predicting RDR risk in both community and ophthalmic settings. It offers a practical solution for early detection and personalized management of RDR, with broad applicability and clinical potential.
Keywords: Referable Diabetic Retinopathy, Nomogram Construction, Community screening, risk stratification, Easily Accessible Indicators
Received: 08 Jan 2025; Accepted: 09 May 2025.
Copyright: © 2025 Dongling, Ziwei, Juanling, Li, Chang, Ting, Hongli and Yanchun. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence:
Liu Hongli, Clinical Laboratory Center, Xi'an People's Hospital (Xi'an Fourth Hospital), Affiliated People's Hospital of Northwest University, xi'an, China
Zhang Yanchun, Shaanxi Eye Hospital, Xi'an People's Hospital (Xi'an Fourth Hospital), Affiliated People's Hospital of Northwest University, xi'an, China
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