Related Experiment Video
Updated: May 7, 2025
04:57
Establishing a Competing Risk Regression Nomogram Model for Survival Data
Published on: October 23, 2020
10.0K
Construction and validation of a nomogram model for predicting diabetic peripheral neuropathy
Hanying Liu1, Qiao Liu1, Mengdie Chen1
1Department of Endocrinology, Taizhou Central Hospital (Taizhou University Hospital), Taizhou, China.
Frontiers in Endocrinology
|December 31, 2024
Summary
This study developed a predictive nomogram to assess diabetic peripheral neuropathy (DPN) risk in diabetic patients. The model aids early DPN detection and intervention, potentially preventing severe complications.
Area of Science:
- Endocrinology and Metabolism
- Neurology
- Biostatistics
Background:
- Diabetic peripheral neuropathy (DPN) is a serious diabetes complication.
- DPN can lead to severe outcomes like ulceration and amputation.
- Early identification of high-risk individuals is crucial for timely intervention.
Purpose of the Study:
- To develop and validate a predictive nomogram model for DPN risk assessment.
- To facilitate early identification of diabetic patients at high risk for DPN.
- To mitigate the incidence of severe DPN-related outcomes.
Main Methods:
- A cohort of 1185 diabetic patients was analyzed.
- Least Absolute Shrinkage and Selection Operator (LASSO) logistic regression identified risk factors.
- A nomogram was constructed and validated using ROC curves, calibration curves, and DCA.
Main Results:
- A 7-factor nomogram model was established: age, hip circumference, fasting plasma glucose, fasting C-peptide, 2-hour postprandial C-peptide, albumin, and blood urea nitrogen.
- The nomogram demonstrated good predictive performance with AUCs of 0.703 (training) and 0.704 (validation).
- Calibration curves and DCA confirmed the nomogram's clinical utility and accuracy.
Conclusions:
- The developed DPN nomogram model shows excellent predictive performance.
- The model can aid in the early detection of DPN in diabetic patients.
- Clinical application of this nomogram can support prompt intervention for high-risk individuals.
