ArticleDiabetes, obesity & metabolism2023
Nomogram model and risk score to predict 5-year risk of progression from prediabetes to diabetes in Chinese adults: Development and validation of a novel model.
Article in Diabetes, obesity & metabolism, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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16 citing papers in PubMed, 15 citations in OpenAlex.
- A Prediction model for moderate-to-severe postoperative pain in patients undergoing oral and maxillofacial ambulatory surgery.BMC oral health · 2026Article
- A predictive study of glycaemic reversal in Chinese individuals with prediabetes based on machine learning: a 5-year cohort study.Frontiers in endocrinology · 2026Article
- External validation and application of a machine learning-based model for diabetes progression in prediabetes.Frontiers in endocrinology · 2026Article
- Diagnostic Model for Obesity and Type 2 Diabetes Mellitus Based on Feature Selection from Fatty Acids, Amino Acids, and Clinical Characteristics.Diabetes, metabolic syndrome and obesity : targets and therapy · 2026Article
- Artificial intelligence in prediabetes care: applications in screening, risk prediction, and lifestyle intervention.Frontiers in endocrinology · 2026Review
- Risk stratification at prediabetes onset and association with diabetes outcomes using EHR data.npj metabolic health and disease · 2025Article
- Applications of Artificial Intelligence and Machine Learning in Prediabetes: A Scoping Review.Journal of diabetes science and technology · 2025Review
- Predictive value of MetS-IR for the glucose status conversion in prediabetes: a multi-center retrospective cohort study.BMC endocrine disorders · 2025Article
- Development of 3-Year Risk Prediction Model for Type 2 Diabetes in Older Adults with Prediabetes - China, 2019-2022.China CDC weekly · 2025Article
- Machine Learning Models Integrating Dietary Indicators Improve the Prediction of Progression from Prediabetes to Type 2 Diabetes Mellitus.Nutrients · 2025Article
- Building a predictive model for depression risk in fracture patients: insights from cross-sectional NHANES 2005-2020 data and an external hospital-based dataset.BMC public health · 2024Article
- Association between high-density lipoprotein cholesterol and reversion to normoglycemia from prediabetes: an analysis based on data from a retrospective cohort study.Scientific reports · 2024Article
- Elevated triglyceride-glucose-body mass index associated with lower probability of future regression to normoglycemia in Chinese adults with prediabetes: a 5-year cohort study.Frontiers in endocrinology · 2024Article
- A nomogram model for predicting 5-year risk of prediabetes in Chinese adults.Scientific reports · 2023Article
- Article
- Nomogram model and risk score to predict 5-year risk of progression from prediabetes to diabetes in Chinese adults: Development and validation of a novel model.Diabetes, obesity & metabolism · 2023Article
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Authors and funding
5 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
aimTo develop a personalized nomogram and risk score to predict the 5-year risk of diabetes among Chinese adults with prediabetes.
methodsThere were 26 018 participants with prediabetes at baseline in this retrospective cohort study. We randomly stratified participants into two cohorts for training (n = 12 947) and validation (n = 13 071). The least absolute shrinkage and selection operator (LASSO) model was applied to select the most significant variables among candidate variables. And we further established a stepwise Cox proportional hazards model to screen out the risk factors based on the predictors chosen by the LASSO model. We presented the model with a nomogram. The model's discrimination, clinical use and calibration were assessed using the area under the receiver operating characteristic (ROC) curve, decision curve and calibration analysis. The associated risk factors were also categorized according to clinical cut-points or tertials to create the diabetes risk score model. Based on the total score, we divided it into four risk categories: low, middle, high and extremely high. We also evaluated our diabetes risk score model's performance.
resultsWe developed a simple nomogram and risk score that predicts the risk of prediabetes by using the variables age, triglyceride, fasting blood glucose, body mass index, alanine aminotransferase, high-density lipoprotein cholesterol and family history of diabetes. The area under the ROC curve of the nomogram was 0.8146 (95% CI 0.8035-0.8258) and 0.8147 (95% CI 0.8035-0.8259) for the training and validation cohort, respectively. The calibration curve showed a perfect fit between predicted and observed diabetes risks at 5 years. Decision curve analysis presented the clinical use of the nomogram, and there was a wide range of alternative threshold probability spectrums. A total risk score of 0 to 2.5, 3 to 4.5, 5 to 7.5 and 8 to 13.5 is associated with low, middle, high and extremely high diabetes risk status, respectively.
conclusionsWe developed and validated a personalized prediction nomogram and risk score for 5-year diabetes risk among Chinese adults with prediabetes, identifying individuals at a high risk of developing diabetes. Doctors and other healthcare professionals can easily and quickly use our diabetes score model to assess the diabetes risk status in patients with prediabetes. In addition, the nomogram model and risk score we developed need to be validated in a prospective cohort study.
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