Development and validation of a multi-center nomogram for the presence of diabetic retinopathy in patients with type 2 diabetes: incorporating homocysteine, glycemic, lipid, and renal markers

Objective: To develop and validate a nomogram that integrates plasma homocysteine with glycemic, lipid, and renal markers for estimating the probability of prevalent diabetic retinopathy (DR) in patients with type 2 diabetes mellitus (T2DM). Methods: This multi-center retrospective study included 930 patients. A development cohort (n=651; 145 DR events, 22.3% prevalence) was recruited from Shanghai Fengxian District Central Hospital, and an independent validation cohort (n=279; 71 DR events, 25.4% prevalence) was recruited from Shanghai Xuhui District Central Hospital. The primary outcome was the presence of DR based on fundus examination. Candidate clinical variables included demographic, clinical, and laboratory data. After pre-screening for multicollinearity, Least Absolute Shrinkage and Selection Operator (LASSO) regression was used to select informative indicators. A multivariable logistic regression model was built, and a nomogram was constructed. Model performance was evaluated by discrimination (area under the curve, AUC), calibration (Brier score, calibration-in-the-large [CITL]), and clinical utility (Decision Curve Analysis, DCA). Results: Eight variables were selected for the final model: Age, T2DM Duration, Systolic Blood Pressure, HbA1c, HDL-C, estimated glomerular filtration rate (eGFR), urinary albumin-to-creatinine ratio (UACR), and Homocysteine. The nomogram demonstrated favorable discrimination with an AUC of 0.865 in the development cohort and maintained a stable performance with an AUC of 0.842 in the validation cohort. Calibration was adequate in both sets (development Brier score 0.132, CITL 0.02; validation Brier score 0.148, CITL 0.15). DCA showed a positive net benefit for clinical decision-making across a wide range of threshold probabilities (10% to 75%). Subgroup analyses confirmed consistent performance across different patient demographics. Conclusion: A nomogram combining homocysteine with traditional clinical and renal markers shows promising capability in assessing the probability of prevalent DR in T2DM patients. While demonstrating potential applicability for screening prioritization, these retrospective findings require further prospective validation before the tool can be routinely implemented to guide clinical management.

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Journal
Frontiers in Endocrinology
Published
2026-04-22
DOI
https://doi.org/10.3389/fendo.2026.1822839
Primary Topic
Folate and B Vitamins Research
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article
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article

Development and validation of a multi-center nomogram for the presence of diabetic retinopathy in patients with type 2 diabetes: incorporating homocysteine, glycemic, lipid, and renal markers

Ling Qiu, Risu Na, Liming Wu
Frontiers in Endocrinology
Folate and B Vitamins Research
article

Development and validation of a multi-center nomogram for the presence of diabetic retinopathy in patients with type 2 diabetes: incorporating homocysteine, glycemic, lipid, and renal markers

Ling Qiu, Risu Na, Liming Wu
article en

Abstract

Objective: To develop and validate a nomogram that integrates plasma homocysteine with glycemic, lipid, and renal markers for estimating the probability of prevalent diabetic retinopathy (DR) in patients with type 2 diabetes mellitus (T2DM). Methods: This multi-center retrospective study included 930 patients. A development cohort (n=651; 145 DR events, 22.3% prevalence) was recruited from Shanghai Fengxian District Central Hospital, and an independent validation cohort (n=279; 71 DR events, 25.4% prevalence) was recruited from Shanghai Xuhui District Central Hospital. The primary outcome was the presence of DR based on fundus examination. Candidate clinical variables included demographic, clinical, and laboratory data. After pre-screening for multicollinearity, Least Absolute Shrinkage and Selection Operator (LASSO) regression was used to select informative indicators. A multivariable logistic regression model was built, and a nomogram was constructed. Model performance was evaluated by discrimination (area under the curve, AUC), calibration (Brier score, calibration-in-the-large [CITL]), and clinical utility (Decision Curve Analysis, DCA). Results: Eight variables were selected for the final model: Age, T2DM Duration, Systolic Blood Pressure, HbA1c, HDL-C, estimated glomerular filtration rate (eGFR), urinary albumin-to-creatinine ratio (UACR), and Homocysteine. The nomogram demonstrated favorable discrimination with an AUC of 0.865 in the development cohort and maintained a stable performance with an AUC of 0.842 in the validation cohort. Calibration was adequate in both sets (development Brier score 0.132, CITL 0.02; validation Brier score 0.148, CITL 0.15). DCA showed a positive net benefit for clinical decision-making across a wide range of threshold probabilities (10% to 75%). Subgroup analyses confirmed consistent performance across different patient demographics. Conclusion: A nomogram combining homocysteine with traditional clinical and renal markers shows promising capability in assessing the probability of prevalent DR in T2DM patients. While demonstrating potential applicability for screening prioritization, these retrospective findings require further prospective validation before the tool can be routinely implemented to guide clinical management.

Frontiers in EndocrinologyVol. 17
Xian Central Hospital (CN), Shanghai Xuhui Central Hospital (CN)
Peace, Justice and strong institutions, Reduced inequalities
Openalex Percentile: Top 22%
Folate and B Vitamins Research
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