Development and validation of a nomogram for predicting diabetic foot ulcer risk in patients with type 2 diabetes mellitus
ObjectiveTo identify the risk factors of diabetic foot ulcer (DFU) in patients with type 2 diabetes mellitus (T2DM) and to develop and validate a nomogram prediction model for DFU occurrence in primary care setting.MethodsWe conducted a single-center retrospective study enrolling 547 T2DM patients h...
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Frontiers Media S.A.
2025-06-01
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| Series: | Frontiers in Endocrinology |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fendo.2025.1555163/full |
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| author | Xiuli Feng Renhao Zhao Teng Yang Na Wang Guofeng Wang |
| author_facet | Xiuli Feng Renhao Zhao Teng Yang Na Wang Guofeng Wang |
| author_sort | Xiuli Feng |
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| description | ObjectiveTo identify the risk factors of diabetic foot ulcer (DFU) in patients with type 2 diabetes mellitus (T2DM) and to develop and validate a nomogram prediction model for DFU occurrence in primary care setting.MethodsWe conducted a single-center retrospective study enrolling 547 T2DM patients hospitalized at The First People’s Hospital of Lianyungang from January 2019 to April 2022. Patients were randomly divided (3:1) into modeling (n = 411) and validation (n = 136) cohorts, and further stratified by DFU status. Thirty-four clinical variables were extracted for analysis. LASSO regression with tenfold cross-validation identified key features, followed by multivariate logistic regression to determine independent DFU risk factors. A nomogram model was developed using R software, and its performance was evaluated using the area under the receiver operating characteristic curve (AUC), calibration curves, the Hosmer–Lemeshow goodness-of-fit test, and decision curve analysis (DCA).ResultsAmong 547 T2DM patients, 150 (27.4%) developed DFU. Multivariate analysis identified seven independent risk factors: age (odds ratio [OR] = 1.032, 95% confidence interval [CI]: 1.005–1.062, P = 0.021), white blood cell (WBC) (OR = 1.127, 95% CI: 1.006–1.270, P = 0.043), ankle-brachial index (ABI) (OR = 5.447, 95% CI: 2.186–14.340, P < 0.001), urine albumin-to-creatinine ratio (UACR) (OR = 2.049, 95% CI: 1.062–3.936, P = 0.031), family history of diabetes (OR = 3.405, 95% CI: 1.666–7.039, P < 0.001), diabetic peripheral neuropathy (DPN) (OR = 5.084, 95% CI: 2.673–9.805, P < 0.001), and albumin (ALB) (OR = 0.850, 95% CI: 0.786–0.915, P < 0.001). The developed nomogram demonstrated excellent discrimination (AUC = 0.917 and 0.956 for modeling and validation cohorts). Internal validation confirmed good model reliability (C-index = 0.917). Calibration curves showed strong agreement between predicted and observed outcomes (Hosmer–Lemeshow P = 0.649 and 0.345). DCA indicated a consistently higher net benefit across threshold probabilities of 0 to 0.8, underscoring the model’s potential clinical utility.ConclusionsThe nomogram prediction model developed in this study demonstrates excellent performance and strong clinical applicability. It provides an effective tool to identify high-risk T2DM patients for DFU and guide early preventive interventions. |
| format | Article |
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| institution | Kabale University |
| issn | 1664-2392 |
| language | English |
| publishDate | 2025-06-01 |
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| spelling | doaj-art-92b0aec4bbe14bba83eaa0b50750dee42025-08-20T03:27:33ZengFrontiers Media S.A.Frontiers in Endocrinology1664-23922025-06-011610.3389/fendo.2025.15551631555163Development and validation of a nomogram for predicting diabetic foot ulcer risk in patients with type 2 diabetes mellitusXiuli Feng0Renhao Zhao1Teng Yang2Na Wang3Guofeng Wang4Department of Endocrinology, Lianyungang Clinical College of Nanjing Medical University/The First People’s Hospital of Lianyungang, Lianyungang, ChinaDepartment of Endocrinology, The First People’s Hospital of Yancheng, Yancheng, ChinaDepartment of Endocrinology, Postgraduate Training Base of Lianyungang First People’s Hospital of Jinzhou Medical University, Lianyungang, ChinaDepartment of Endocrinology, Lianyungang Clinical College of Nanjing Medical University/The First People’s Hospital of Lianyungang, Lianyungang, ChinaDepartment of Endocrinology, Lianyungang Clinical College of Nanjing Medical University/The First People’s Hospital of Lianyungang, Lianyungang, ChinaObjectiveTo identify the risk factors of diabetic foot ulcer (DFU) in patients with type 2 diabetes mellitus (T2DM) and to develop and validate a nomogram prediction model for DFU occurrence in primary care setting.MethodsWe conducted a single-center retrospective study enrolling 547 T2DM patients hospitalized at The First People’s Hospital of Lianyungang from January 2019 to April 2022. Patients were randomly divided (3:1) into modeling (n = 411) and validation (n = 136) cohorts, and further stratified by DFU status. Thirty-four clinical variables were extracted for analysis. LASSO regression with tenfold cross-validation identified key features, followed by multivariate logistic regression to determine independent DFU risk factors. A nomogram model was developed using R software, and its performance was evaluated using the area under the receiver operating characteristic curve (AUC), calibration curves, the Hosmer–Lemeshow goodness-of-fit test, and decision curve analysis (DCA).ResultsAmong 547 T2DM patients, 150 (27.4%) developed DFU. Multivariate analysis identified seven independent risk factors: age (odds ratio [OR] = 1.032, 95% confidence interval [CI]: 1.005–1.062, P = 0.021), white blood cell (WBC) (OR = 1.127, 95% CI: 1.006–1.270, P = 0.043), ankle-brachial index (ABI) (OR = 5.447, 95% CI: 2.186–14.340, P < 0.001), urine albumin-to-creatinine ratio (UACR) (OR = 2.049, 95% CI: 1.062–3.936, P = 0.031), family history of diabetes (OR = 3.405, 95% CI: 1.666–7.039, P < 0.001), diabetic peripheral neuropathy (DPN) (OR = 5.084, 95% CI: 2.673–9.805, P < 0.001), and albumin (ALB) (OR = 0.850, 95% CI: 0.786–0.915, P < 0.001). The developed nomogram demonstrated excellent discrimination (AUC = 0.917 and 0.956 for modeling and validation cohorts). Internal validation confirmed good model reliability (C-index = 0.917). Calibration curves showed strong agreement between predicted and observed outcomes (Hosmer–Lemeshow P = 0.649 and 0.345). DCA indicated a consistently higher net benefit across threshold probabilities of 0 to 0.8, underscoring the model’s potential clinical utility.ConclusionsThe nomogram prediction model developed in this study demonstrates excellent performance and strong clinical applicability. It provides an effective tool to identify high-risk T2DM patients for DFU and guide early preventive interventions.https://www.frontiersin.org/articles/10.3389/fendo.2025.1555163/fulltype 2 diabetes mellitusdiabetic foot ulcernomogramrisk factorsprediction |
| spellingShingle | Xiuli Feng Renhao Zhao Teng Yang Na Wang Guofeng Wang Development and validation of a nomogram for predicting diabetic foot ulcer risk in patients with type 2 diabetes mellitus Frontiers in Endocrinology type 2 diabetes mellitus diabetic foot ulcer nomogram risk factors prediction |
| title | Development and validation of a nomogram for predicting diabetic foot ulcer risk in patients with type 2 diabetes mellitus |
| title_full | Development and validation of a nomogram for predicting diabetic foot ulcer risk in patients with type 2 diabetes mellitus |
| title_fullStr | Development and validation of a nomogram for predicting diabetic foot ulcer risk in patients with type 2 diabetes mellitus |
| title_full_unstemmed | Development and validation of a nomogram for predicting diabetic foot ulcer risk in patients with type 2 diabetes mellitus |
| title_short | Development and validation of a nomogram for predicting diabetic foot ulcer risk in patients with type 2 diabetes mellitus |
| title_sort | development and validation of a nomogram for predicting diabetic foot ulcer risk in patients with type 2 diabetes mellitus |
| topic | type 2 diabetes mellitus diabetic foot ulcer nomogram risk factors prediction |
| url | https://www.frontiersin.org/articles/10.3389/fendo.2025.1555163/full |
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