Development and Validation of a Nomogram-Based Risk Prediction Model for Diabetic Retinopathy in Elderly Adults with Type 2 Diabetes Mellitus
Meitong Chen,1,2 Tongtong Niu,2 Yan Sun,2 Meisong Chang,2 Shanshan Liu,2 Tiantian Xu,2 Huixia Cui3 1School of Nursing, Jinzhou Medical University, Jinzhou, Liaoning Province, 121001, People’s Republic of China; 2Department of Ophthalmology, Shenyang Fourth People’s Hospital, Shenyang, Liaoning Provi...
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Dove Medical Press
2025-07-01
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| author | Chen M Niu T Sun Y Chang M Liu S Xu T Cui H |
| author_facet | Chen M Niu T Sun Y Chang M Liu S Xu T Cui H |
| author_sort | Chen M |
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| description | Meitong Chen,1,2 Tongtong Niu,2 Yan Sun,2 Meisong Chang,2 Shanshan Liu,2 Tiantian Xu,2 Huixia Cui3 1School of Nursing, Jinzhou Medical University, Jinzhou, Liaoning Province, 121001, People’s Republic of China; 2Department of Ophthalmology, Shenyang Fourth People’s Hospital, Shenyang, Liaoning Province, 11000, People’s Republic of China; 3School of Nursing, Wannan Medical College, Wuhu City, Anhui Province, 241002, People’s Republic of ChinaCorrespondence: Huixia Cui, School of Nursing, Wannan Medical College, No. 22 Wenchang West Road, Higher Education Park, Wuhu City, Anhui Province, 241002, People’s Republic of China, Email cnurs@ldy.edu.rsPurpose: Diabetic retinopathy (DR) is a significant comorbidity with Type 2 Diabetes Mellitus (T2DM), however, risk prediction for DR remains understudied in the elderly population. This study aimed to develop and validate a nomogram for identifying individuals at high risk of DR among elderly T2DM patients to guide early clinical intervention.Patients and Methods: A retrospective cohort of 1912 T2DM patients (aged ≥ 60 years) was enrolled from 2018 to 2024. Sociodemographic, biochemical, and health-related variables were extracted. The cohort was randomly stratified into derivation (70%) and validation (30%) sets. Least Absolute Shrinkage and Selection Operator (LASSO) regression was applied to identify key predictors, followed by multivariate logistic regression to construct the nomogram. Model performance was evaluated via Receiver Operating Characteristic-Area Under the Curve (ROC-AUC), calibration plots, Hosmer–Lemeshow (H-L) tests, and decision curve analysis (DCA). External validation was performed using an independent cohort (n = 476).Results: Among 1912 patients, 655 (34.3%) were diagnosed with DR. Independent predictors included T2DM duration, glycosylated hemoglobin (HbA1c), platelet-to-lymphocyte ratio (PLR), estimated glomerular filtration rate (eGFR), and neutrophil percentage to albumin ratio (NPAR) (all p < 0.05). The nomogram demonstrated robust discrimination, with AUCs of 0.823 (95% CI: 0.805– 0.851) and 0.808 (95% CI: 0.770– 0.846) in the derivation and internal validation sets, respectively. Calibration plots demonstrated strong agreement between predicted and observed risks (H-L test: p = 0.807 [derivation], p = 0.374 [validation]). DCA indicated favorable clinical utility across threshold probabilities, and external validation confirmed generalizability (AUC=0.788) and readiness for clinical deployment.Conclusion: This rigorously validated nomogram, integrating clinical accessible variables, provided a pragmatic tool for early DR risk stratification in elderly T2DM patients. Implementation of this model in clinical practice may enable personalized risk mitigation strategies to reduce DR incidence in this vulnerable population.Keywords: nomogram, predictive model, diabetic retinopathy, elderly adults, T2DM |
| format | Article |
| id | doaj-art-7e3a293000104bb491e267ada750c4ef |
| institution | DOAJ |
| issn | 1178-7007 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | Dove Medical Press |
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| series | Diabetes, Metabolic Syndrome and Obesity |
| spelling | doaj-art-7e3a293000104bb491e267ada750c4ef2025-08-20T03:15:27ZengDove Medical PressDiabetes, Metabolic Syndrome and Obesity1178-70072025-07-01Volume 18Issue 125092523105137Development and Validation of a Nomogram-Based Risk Prediction Model for Diabetic Retinopathy in Elderly Adults with Type 2 Diabetes MellitusChen MNiu TSun YChang MLiu SXu TCui HMeitong Chen,1,2 Tongtong Niu,2 Yan Sun,2 Meisong Chang,2 Shanshan Liu,2 Tiantian Xu,2 Huixia Cui3 1School of Nursing, Jinzhou Medical University, Jinzhou, Liaoning Province, 121001, People’s Republic of China; 2Department of Ophthalmology, Shenyang Fourth People’s Hospital, Shenyang, Liaoning Province, 11000, People’s Republic of China; 3School of Nursing, Wannan Medical College, Wuhu City, Anhui Province, 241002, People’s Republic of ChinaCorrespondence: Huixia Cui, School of Nursing, Wannan Medical College, No. 22 Wenchang West Road, Higher Education Park, Wuhu City, Anhui Province, 241002, People’s Republic of China, Email cnurs@ldy.edu.rsPurpose: Diabetic retinopathy (DR) is a significant comorbidity with Type 2 Diabetes Mellitus (T2DM), however, risk prediction for DR remains understudied in the elderly population. This study aimed to develop and validate a nomogram for identifying individuals at high risk of DR among elderly T2DM patients to guide early clinical intervention.Patients and Methods: A retrospective cohort of 1912 T2DM patients (aged ≥ 60 years) was enrolled from 2018 to 2024. Sociodemographic, biochemical, and health-related variables were extracted. The cohort was randomly stratified into derivation (70%) and validation (30%) sets. Least Absolute Shrinkage and Selection Operator (LASSO) regression was applied to identify key predictors, followed by multivariate logistic regression to construct the nomogram. Model performance was evaluated via Receiver Operating Characteristic-Area Under the Curve (ROC-AUC), calibration plots, Hosmer–Lemeshow (H-L) tests, and decision curve analysis (DCA). External validation was performed using an independent cohort (n = 476).Results: Among 1912 patients, 655 (34.3%) were diagnosed with DR. Independent predictors included T2DM duration, glycosylated hemoglobin (HbA1c), platelet-to-lymphocyte ratio (PLR), estimated glomerular filtration rate (eGFR), and neutrophil percentage to albumin ratio (NPAR) (all p < 0.05). The nomogram demonstrated robust discrimination, with AUCs of 0.823 (95% CI: 0.805– 0.851) and 0.808 (95% CI: 0.770– 0.846) in the derivation and internal validation sets, respectively. Calibration plots demonstrated strong agreement between predicted and observed risks (H-L test: p = 0.807 [derivation], p = 0.374 [validation]). DCA indicated favorable clinical utility across threshold probabilities, and external validation confirmed generalizability (AUC=0.788) and readiness for clinical deployment.Conclusion: This rigorously validated nomogram, integrating clinical accessible variables, provided a pragmatic tool for early DR risk stratification in elderly T2DM patients. Implementation of this model in clinical practice may enable personalized risk mitigation strategies to reduce DR incidence in this vulnerable population.Keywords: nomogram, predictive model, diabetic retinopathy, elderly adults, T2DMhttps://www.dovepress.com/development-and-validation-of-a-nomogram-based-risk-prediction-model-f-peer-reviewed-fulltext-article-DMSONomogramPredictive modelDiabetic retinopathyElderly adultsT2DM |
| spellingShingle | Chen M Niu T Sun Y Chang M Liu S Xu T Cui H Development and Validation of a Nomogram-Based Risk Prediction Model for Diabetic Retinopathy in Elderly Adults with Type 2 Diabetes Mellitus Diabetes, Metabolic Syndrome and Obesity Nomogram Predictive model Diabetic retinopathy Elderly adults T2DM |
| title | Development and Validation of a Nomogram-Based Risk Prediction Model for Diabetic Retinopathy in Elderly Adults with Type 2 Diabetes Mellitus |
| title_full | Development and Validation of a Nomogram-Based Risk Prediction Model for Diabetic Retinopathy in Elderly Adults with Type 2 Diabetes Mellitus |
| title_fullStr | Development and Validation of a Nomogram-Based Risk Prediction Model for Diabetic Retinopathy in Elderly Adults with Type 2 Diabetes Mellitus |
| title_full_unstemmed | Development and Validation of a Nomogram-Based Risk Prediction Model for Diabetic Retinopathy in Elderly Adults with Type 2 Diabetes Mellitus |
| title_short | Development and Validation of a Nomogram-Based Risk Prediction Model for Diabetic Retinopathy in Elderly Adults with Type 2 Diabetes Mellitus |
| title_sort | development and validation of a nomogram based risk prediction model for diabetic retinopathy in elderly adults with type 2 diabetes mellitus |
| topic | Nomogram Predictive model Diabetic retinopathy Elderly adults T2DM |
| url | https://www.dovepress.com/development-and-validation-of-a-nomogram-based-risk-prediction-model-f-peer-reviewed-fulltext-article-DMSO |
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